R version 3.0.2 (2013-09-25) -- "Frisbee Sailing" Copyright (C) 2013 The R Foundation for Statistical Computing Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1 + ,119.992 + ,157.302 + ,74.997 + ,0.00784 + ,0.00007 + ,0.0037 + ,0.00554 + ,0.01109 + ,0.04374 + ,0.426 + ,0.02182 + ,0.0313 + ,0.06545 + ,0.02211 + ,21.033 + ,0.414783 + ,0.815285 + ,-4.813031 + ,0.266482 + ,2.301442 + ,0.284654 + ,1 + ,122.4 + ,148.65 + ,113.819 + ,0.00968 + ,0.00008 + ,0.00465 + ,0.00696 + ,0.01394 + ,0.06134 + ,0.626 + ,0.03134 + ,0.04518 + ,0.09403 + ,0.01929 + ,19.085 + ,0.458359 + ,0.819521 + ,-4.075192 + ,0.33559 + ,2.486855 + ,0.368674 + ,1 + ,116.682 + ,131.111 + ,111.555 + ,0.0105 + ,0.00009 + ,0.00544 + ,0.00781 + ,0.01633 + ,0.05233 + ,0.482 + ,0.02757 + ,0.03858 + ,0.0827 + ,0.01309 + ,20.651 + ,0.429895 + ,0.825288 + ,-4.443179 + ,0.311173 + ,2.342259 + ,0.332634 + ,1 + ,116.676 + ,137.871 + ,111.366 + ,0.00997 + ,0.00009 + ,0.00502 + ,0.00698 + ,0.01505 + ,0.05492 + ,0.517 + ,0.02924 + ,0.04005 + ,0.08771 + ,0.01353 + ,20.644 + ,0.434969 + ,0.819235 + ,-4.117501 + ,0.334147 + ,2.405554 + ,0.368975 + ,1 + 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,0.0051 + ,0.01484 + ,0.133 + ,0.00754 + ,0.0095 + ,0.02261 + ,0.0043 + ,26.55 + ,0.36909 + ,0.776158 + ,-6.085567 + ,0.192375 + ,1.889002 + ,0.174152 + ,0 + ,113.715 + ,116.443 + ,96.913 + ,0.00349 + ,0.00003 + ,0.00171 + ,0.00203 + ,0.00514 + ,0.01472 + ,0.133 + ,0.00748 + ,0.00905 + ,0.02245 + ,0.00478 + ,26.547 + ,0.380253 + ,0.7667 + ,-5.943501 + ,0.19215 + ,1.852542 + ,0.179677 + ,0 + ,117.004 + ,144.466 + ,99.923 + ,0.00353 + ,0.00003 + ,0.00176 + ,0.00218 + ,0.00528 + ,0.01657 + ,0.145 + ,0.00881 + ,0.01062 + ,0.02643 + ,0.0059 + ,25.445 + ,0.387482 + ,0.756482 + ,-6.012559 + ,0.229298 + ,1.872946 + ,0.163118 + ,0 + ,115.38 + ,123.109 + ,108.634 + ,0.00332 + ,0.00003 + ,0.0016 + ,0.00199 + ,0.0048 + ,0.01503 + ,0.137 + ,0.00812 + ,0.00933 + ,0.02436 + ,0.00401 + ,26.005 + ,0.405991 + ,0.761255 + ,-5.966779 + ,0.197938 + ,1.974857 + ,0.184067 + ,0 + ,116.388 + ,129.038 + ,108.97 + ,0.00346 + ,0.00003 + ,0.00169 + ,0.00213 + ,0.00507 + ,0.01725 + ,0.155 + ,0.00874 + ,0.01021 + ,0.02623 + ,0.00415 + ,26.143 + ,0.361232 + ,0.763242 + ,-6.016891 + ,0.109256 + ,2.004719 + ,0.174429 + ,1 + ,151.737 + ,190.204 + ,129.859 + ,0.00314 + ,0.00002 + ,0.00135 + ,0.00162 + ,0.00406 + ,0.01469 + ,0.132 + ,0.00728 + ,0.00886 + ,0.02184 + ,0.0057 + ,24.151 + ,0.39661 + ,0.745957 + ,-6.486822 + ,0.197919 + ,2.449763 + ,0.132703 + ,1 + ,148.79 + ,158.359 + ,138.99 + ,0.00309 + ,0.00002 + ,0.00152 + ,0.00186 + ,0.00456 + ,0.01574 + ,0.142 + ,0.00839 + ,0.00956 + ,0.02518 + ,0.00488 + ,24.412 + ,0.402591 + ,0.762508 + ,-6.311987 + ,0.182459 + ,2.251553 + ,0.160306 + ,1 + ,148.143 + ,155.982 + ,135.041 + ,0.00392 + ,0.00003 + ,0.00204 + ,0.00231 + ,0.00612 + ,0.0145 + ,0.131 + ,0.00725 + ,0.00876 + ,0.02175 + ,0.0054 + ,23.683 + ,0.398499 + ,0.778349 + ,-5.711205 + ,0.240875 + ,2.845109 + ,0.19273 + ,1 + ,150.44 + ,163.441 + ,144.736 + ,0.00396 + ,0.00003 + ,0.00206 + ,0.00233 + ,0.00619 + ,0.02551 + ,0.237 + ,0.01321 + ,0.01574 + ,0.03964 + ,0.00611 + ,23.133 + ,0.352396 + ,0.75932 + ,-6.261446 + ,0.183218 + ,2.264226 + ,0.144105 + ,1 + ,148.462 + ,161.078 + ,141.998 + ,0.00397 + ,0.00003 + ,0.00202 + ,0.00235 + ,0.00605 + ,0.01831 + ,0.163 + ,0.0095 + ,0.01103 + ,0.02849 + ,0.00639 + ,22.866 + ,0.408598 + ,0.768845 + ,-5.704053 + ,0.216204 + ,2.679185 + ,0.19771 + ,1 + ,149.818 + ,163.417 + ,144.786 + ,0.00336 + ,0.00002 + ,0.00174 + ,0.00198 + ,0.00521 + ,0.02145 + ,0.198 + ,0.01155 + ,0.01341 + ,0.03464 + ,0.00595 + ,23.008 + ,0.329577 + ,0.75718 + ,-6.27717 + ,0.109397 + ,2.209021 + ,0.156368 + ,0 + ,117.226 + ,123.925 + ,106.656 + ,0.00417 + ,0.00004 + ,0.00186 + ,0.0027 + ,0.00558 + ,0.01909 + ,0.171 + ,0.00864 + ,0.01223 + ,0.02592 + ,0.00955 + ,23.079 + ,0.603515 + ,0.669565 + ,-5.61907 + ,0.191576 + ,2.027228 + ,0.215724 + ,0 + ,116.848 + ,217.552 + ,99.503 + ,0.00531 + ,0.00005 + ,0.0026 + ,0.00346 + ,0.0078 + ,0.01795 + ,0.163 + ,0.0081 + ,0.01144 + ,0.02429 + ,0.01179 + ,22.085 + ,0.663842 + ,0.656516 + ,-5.198864 + ,0.206768 + ,2.120412 + ,0.252404 + ,0 + ,116.286 + ,177.291 + ,96.983 + ,0.00314 + ,0.00003 + ,0.00134 + ,0.00192 + ,0.00403 + ,0.01564 + ,0.136 + ,0.00667 + ,0.0099 + ,0.02001 + ,0.00737 + ,24.199 + ,0.598515 + ,0.654331 + ,-5.592584 + ,0.133917 + ,2.058658 + ,0.214346 + ,0 + ,116.556 + ,592.03 + ,86.228 + ,0.00496 + ,0.00004 + ,0.00254 + ,0.00263 + ,0.00762 + ,0.0166 + ,0.154 + ,0.0082 + ,0.00972 + ,0.0246 + ,0.01397 + ,23.958 + ,0.566424 + ,0.667654 + ,-6.431119 + ,0.15331 + ,2.161936 + ,0.120605 + ,0 + ,116.342 + ,581.289 + ,94.246 + ,0.00267 + ,0.00002 + ,0.00115 + ,0.00148 + ,0.00345 + ,0.013 + ,0.117 + ,0.00631 + ,0.00789 + ,0.01892 + ,0.0068 + ,25.023 + ,0.528485 + ,0.663884 + ,-6.359018 + ,0.116636 + ,2.152083 + ,0.138868 + ,0 + ,114.563 + ,119.167 + ,86.647 + ,0.00327 + ,0.00003 + ,0.00146 + ,0.00184 + ,0.00439 + ,0.01185 + ,0.106 + ,0.00557 + ,0.00721 + ,0.01672 + ,0.00703 + ,24.775 + ,0.555303 + ,0.659132 + ,-6.710219 + ,0.149694 + ,1.91399 + ,0.121777 + ,0 + ,201.774 + ,262.707 + ,78.228 + ,0.00694 + ,0.00003 + ,0.00412 + ,0.00396 + ,0.01235 + ,0.02574 + ,0.255 + ,0.01454 + ,0.01582 + ,0.04363 + ,0.04441 + ,19.368 + ,0.508479 + ,0.683761 + ,-6.934474 + ,0.15989 + ,2.316346 + ,0.112838 + ,0 + ,174.188 + ,230.978 + ,94.261 + ,0.00459 + ,0.00003 + ,0.00263 + ,0.00259 + ,0.0079 + ,0.04087 + ,0.405 + ,0.02336 + ,0.02498 + ,0.07008 + ,0.02764 + ,19.517 + ,0.448439 + ,0.657899 + ,-6.538586 + ,0.121952 + ,2.657476 + ,0.13305 + ,0 + ,209.516 + ,253.017 + ,89.488 + ,0.00564 + ,0.00003 + ,0.00331 + ,0.00292 + ,0.00994 + ,0.02751 + ,0.263 + ,0.01604 + ,0.01657 + ,0.04812 + ,0.0181 + ,19.147 + ,0.431674 + ,0.683244 + ,-6.195325 + ,0.129303 + ,2.784312 + ,0.168895 + ,0 + ,174.688 + ,240.005 + ,74.287 + ,0.0136 + ,0.00008 + ,0.00624 + ,0.00564 + ,0.01873 + ,0.02308 + ,0.256 + ,0.01268 + ,0.01365 + ,0.03804 + ,0.10715 + ,17.883 + ,0.407567 + ,0.655683 + ,-6.787197 + ,0.158453 + ,2.679772 + ,0.131728 + ,0 + ,198.764 + ,396.961 + ,74.904 + ,0.0074 + ,0.00004 + ,0.0037 + ,0.0039 + ,0.01109 + ,0.02296 + ,0.241 + ,0.01265 + ,0.01321 + ,0.03794 + ,0.07223 + ,19.02 + ,0.451221 + ,0.643956 + ,-6.744577 + ,0.207454 + ,2.138608 + ,0.123306 + ,0 + ,214.289 + ,260.277 + ,77.973 + ,0.00567 + ,0.00003 + ,0.00295 + ,0.00317 + ,0.00885 + ,0.01884 + ,0.19 + ,0.01026 + ,0.01161 + ,0.03078 + ,0.04398 + ,21.209 + ,0.462803 + ,0.664357 + ,-5.724056 + ,0.190667 + ,2.555477 + ,0.148569) + ,dim=c(22 + ,195) + ,dimnames=list(c('status' + ,'MDVP:Fo(Hz)' + ,'MDVP:Fhi(Hz)' + ,'MDVP:Flo(Hz)' + ,'MDVP:Jitter(%)' + ,'MDVP:Jitter(Abs)' + ,'MDVP:RAP' + ,'MDVP:PPQ' + ,'Jitter:DDP' + ,'MDVP:Shimmer' + ,'MDVP:Shimmer(dB)' + ,'Shimmer:APQ3' + ,'Shimmer:APQ5' + ,'Shimmer:DDA' + ,'NHR' + ,'HNR' + ,'RPDE' + ,'DFA' + ,'spread1' + ,'spread2' + ,'D2' + ,'PPE') + ,1:195)) > y <- array(NA,dim=c(22,195),dimnames=list(c('status','MDVP:Fo(Hz)','MDVP:Fhi(Hz)','MDVP:Flo(Hz)','MDVP:Jitter(%)','MDVP:Jitter(Abs)','MDVP:RAP','MDVP:PPQ','Jitter:DDP','MDVP:Shimmer','MDVP:Shimmer(dB)','Shimmer:APQ3','Shimmer:APQ5','Shimmer:DDA','NHR','HNR','RPDE','DFA','spread1','spread2','D2','PPE'),1:195)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 () > #Author: root > #To cite this work: Wessa P., (2013), Multiple Regression (v1.0.29) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x status MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) 1 1 119.992 157.302 74.997 0.00784 2 1 122.400 148.650 113.819 0.00968 3 1 116.682 131.111 111.555 0.01050 4 1 116.676 137.871 111.366 0.00997 5 1 116.014 141.781 110.655 0.01284 6 1 120.552 131.162 113.787 0.00968 7 1 120.267 137.244 114.820 0.00333 8 1 107.332 113.840 104.315 0.00290 9 1 95.730 132.068 91.754 0.00551 10 1 95.056 120.103 91.226 0.00532 11 1 88.333 112.240 84.072 0.00505 12 1 91.904 115.871 86.292 0.00540 13 1 136.926 159.866 131.276 0.00293 14 1 139.173 179.139 76.556 0.00390 15 1 152.845 163.305 75.836 0.00294 16 1 142.167 217.455 83.159 0.00369 17 1 144.188 349.259 82.764 0.00544 18 1 168.778 232.181 75.603 0.00718 19 1 153.046 175.829 68.623 0.00742 20 1 156.405 189.398 142.822 0.00768 21 1 153.848 165.738 65.782 0.00840 22 1 153.880 172.860 78.128 0.00480 23 1 167.930 193.221 79.068 0.00442 24 1 173.917 192.735 86.180 0.00476 25 1 163.656 200.841 76.779 0.00742 26 1 104.400 206.002 77.968 0.00633 27 1 171.041 208.313 75.501 0.00455 28 1 146.845 208.701 81.737 0.00496 29 1 155.358 227.383 80.055 0.00310 30 1 162.568 198.346 77.630 0.00502 31 0 197.076 206.896 192.055 0.00289 32 0 199.228 209.512 192.091 0.00241 33 0 198.383 215.203 193.104 0.00212 34 0 202.266 211.604 197.079 0.00180 35 0 203.184 211.526 196.160 0.00178 36 0 201.464 210.565 195.708 0.00198 37 1 177.876 192.921 168.013 0.00411 38 1 176.170 185.604 163.564 0.00369 39 1 180.198 201.249 175.456 0.00284 40 1 187.733 202.324 173.015 0.00316 41 1 186.163 197.724 177.584 0.00298 42 1 184.055 196.537 166.977 0.00258 43 0 237.226 247.326 225.227 0.00298 44 0 241.404 248.834 232.483 0.00281 45 0 243.439 250.912 232.435 0.00210 46 0 242.852 255.034 227.911 0.00225 47 0 245.510 262.090 231.848 0.00235 48 0 252.455 261.487 182.786 0.00185 49 0 122.188 128.611 115.765 0.00524 50 0 122.964 130.049 114.676 0.00428 51 0 124.445 135.069 117.495 0.00431 52 0 126.344 134.231 112.773 0.00448 53 0 128.001 138.052 122.080 0.00436 54 0 129.336 139.867 118.604 0.00490 55 1 108.807 134.656 102.874 0.00761 56 1 109.860 126.358 104.437 0.00874 57 1 110.417 131.067 103.370 0.00784 58 1 117.274 129.916 110.402 0.00752 59 1 116.879 131.897 108.153 0.00788 60 1 114.847 271.314 104.680 0.00867 61 0 209.144 237.494 109.379 0.00282 62 0 223.365 238.987 98.664 0.00264 63 0 222.236 231.345 205.495 0.00266 64 0 228.832 234.619 223.634 0.00296 65 0 229.401 252.221 221.156 0.00205 66 0 228.969 239.541 113.201 0.00238 67 1 140.341 159.774 67.021 0.00817 68 1 136.969 166.607 66.004 0.00923 69 1 143.533 162.215 65.809 0.01101 70 1 148.090 162.824 67.343 0.00762 71 1 142.729 162.408 65.476 0.00831 72 1 136.358 176.595 65.750 0.00971 73 1 120.080 139.710 111.208 0.00405 74 1 112.014 588.518 107.024 0.00533 75 1 110.793 128.101 107.316 0.00494 76 1 110.707 122.611 105.007 0.00516 77 1 112.876 148.826 106.981 0.00500 78 1 110.568 125.394 106.821 0.00462 79 1 95.385 102.145 90.264 0.00608 80 1 100.770 115.697 85.545 0.01038 81 1 96.106 108.664 84.510 0.00694 82 1 95.605 107.715 87.549 0.00702 83 1 100.960 110.019 95.628 0.00606 84 1 98.804 102.305 87.804 0.00432 85 1 176.858 205.560 75.344 0.00747 86 1 180.978 200.125 155.495 0.00406 87 1 178.222 202.450 141.047 0.00321 88 1 176.281 227.381 125.610 0.00520 89 1 173.898 211.350 74.677 0.00448 90 1 179.711 225.930 144.878 0.00709 91 1 166.605 206.008 78.032 0.00742 92 1 151.955 163.335 147.226 0.00419 93 1 148.272 164.989 142.299 0.00459 94 1 152.125 161.469 76.596 0.00382 95 1 157.821 172.975 68.401 0.00358 96 1 157.447 163.267 149.605 0.00369 97 1 159.116 168.913 144.811 0.00342 98 1 125.036 143.946 116.187 0.01280 99 1 125.791 140.557 96.206 0.01378 100 1 126.512 141.756 99.770 0.01936 101 1 125.641 141.068 116.346 0.03316 102 1 128.451 150.449 75.632 0.01551 103 1 139.224 586.567 66.157 0.03011 104 1 150.258 154.609 75.349 0.00248 105 1 154.003 160.267 128.621 0.00183 106 1 149.689 160.368 133.608 0.00257 107 1 155.078 163.736 144.148 0.00168 108 1 151.884 157.765 133.751 0.00258 109 1 151.989 157.339 132.857 0.00174 110 1 193.030 208.900 80.297 0.00766 111 1 200.714 223.982 89.686 0.00621 112 1 208.519 220.315 199.020 0.00609 113 1 204.664 221.300 189.621 0.00841 114 1 210.141 232.706 185.258 0.00534 115 1 206.327 226.355 92.020 0.00495 116 1 151.872 492.892 69.085 0.00856 117 1 158.219 442.557 71.948 0.00476 118 1 170.756 450.247 79.032 0.00555 119 1 178.285 442.824 82.063 0.00462 120 1 217.116 233.481 93.978 0.00404 121 1 128.940 479.697 88.251 0.00581 122 1 176.824 215.293 83.961 0.00460 123 1 138.190 203.522 83.340 0.00704 124 1 182.018 197.173 79.187 0.00842 125 1 156.239 195.107 79.820 0.00694 126 1 145.174 198.109 80.637 0.00733 127 1 138.145 197.238 81.114 0.00544 128 1 166.888 198.966 79.512 0.00638 129 1 119.031 127.533 109.216 0.00440 130 1 120.078 126.632 105.667 0.00270 131 1 120.289 128.143 100.209 0.00492 132 1 120.256 125.306 104.773 0.00407 133 1 119.056 125.213 86.795 0.00346 134 1 118.747 123.723 109.836 0.00331 135 1 106.516 112.777 93.105 0.00589 136 1 110.453 127.611 105.554 0.00494 137 1 113.400 133.344 107.816 0.00451 138 1 113.166 130.270 100.673 0.00502 139 1 112.239 126.609 104.095 0.00472 140 1 116.150 131.731 109.815 0.00381 141 1 170.368 268.796 79.543 0.00571 142 1 208.083 253.792 91.802 0.00757 143 1 198.458 219.290 148.691 0.00376 144 1 202.805 231.508 86.232 0.00370 145 1 202.544 241.350 164.168 0.00254 146 1 223.361 263.872 87.638 0.00352 147 1 169.774 191.759 151.451 0.01568 148 1 183.520 216.814 161.340 0.01466 149 1 188.620 216.302 165.982 0.01719 150 1 202.632 565.740 177.258 0.01627 151 1 186.695 211.961 149.442 0.01872 152 1 192.818 224.429 168.793 0.03107 153 1 198.116 233.099 174.478 0.02714 154 1 121.345 139.644 98.250 0.00684 155 1 119.100 128.442 88.833 0.00692 156 1 117.870 127.349 95.654 0.00647 157 1 122.336 142.369 94.794 0.00727 158 1 117.963 134.209 100.757 0.01813 159 1 126.144 154.284 97.543 0.00975 160 1 127.930 138.752 112.173 0.00605 161 1 114.238 124.393 77.022 0.00581 162 1 115.322 135.738 107.802 0.00619 163 1 114.554 126.778 91.121 0.00651 164 1 112.150 131.669 97.527 0.00519 165 1 102.273 142.830 85.902 0.00907 166 0 236.200 244.663 102.137 0.00277 167 0 237.323 243.709 229.256 0.00303 168 0 260.105 264.919 237.303 0.00339 169 0 197.569 217.627 90.794 0.00803 170 0 240.301 245.135 219.783 0.00517 171 0 244.990 272.210 239.170 0.00451 172 0 112.547 133.374 105.715 0.00355 173 0 110.739 113.597 100.139 0.00356 174 0 113.715 116.443 96.913 0.00349 175 0 117.004 144.466 99.923 0.00353 176 0 115.380 123.109 108.634 0.00332 177 0 116.388 129.038 108.970 0.00346 178 1 151.737 190.204 129.859 0.00314 179 1 148.790 158.359 138.990 0.00309 180 1 148.143 155.982 135.041 0.00392 181 1 150.440 163.441 144.736 0.00396 182 1 148.462 161.078 141.998 0.00397 183 1 149.818 163.417 144.786 0.00336 184 0 117.226 123.925 106.656 0.00417 185 0 116.848 217.552 99.503 0.00531 186 0 116.286 177.291 96.983 0.00314 187 0 116.556 592.030 86.228 0.00496 188 0 116.342 581.289 94.246 0.00267 189 0 114.563 119.167 86.647 0.00327 190 0 201.774 262.707 78.228 0.00694 191 0 174.188 230.978 94.261 0.00459 192 0 209.516 253.017 89.488 0.00564 193 0 174.688 240.005 74.287 0.01360 194 0 198.764 396.961 74.904 0.00740 195 0 214.289 260.277 77.973 0.00567 MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer MDVP:Shimmer(dB) 1 7.0e-05 0.00370 0.00554 0.01109 0.04374 0.426 2 8.0e-05 0.00465 0.00696 0.01394 0.06134 0.626 3 9.0e-05 0.00544 0.00781 0.01633 0.05233 0.482 4 9.0e-05 0.00502 0.00698 0.01505 0.05492 0.517 5 1.1e-04 0.00655 0.00908 0.01966 0.06425 0.584 6 8.0e-05 0.00463 0.00750 0.01388 0.04701 0.456 7 3.0e-05 0.00155 0.00202 0.00466 0.01608 0.140 8 3.0e-05 0.00144 0.00182 0.00431 0.01567 0.134 9 6.0e-05 0.00293 0.00332 0.00880 0.02093 0.191 10 6.0e-05 0.00268 0.00332 0.00803 0.02838 0.255 11 6.0e-05 0.00254 0.00330 0.00763 0.02143 0.197 12 6.0e-05 0.00281 0.00336 0.00844 0.02752 0.249 13 2.0e-05 0.00118 0.00153 0.00355 0.01259 0.112 14 3.0e-05 0.00165 0.00208 0.00496 0.01642 0.154 15 2.0e-05 0.00121 0.00149 0.00364 0.01828 0.158 16 3.0e-05 0.00157 0.00203 0.00471 0.01503 0.126 17 4.0e-05 0.00211 0.00292 0.00632 0.02047 0.192 18 4.0e-05 0.00284 0.00387 0.00853 0.03327 0.348 19 5.0e-05 0.00364 0.00432 0.01092 0.05517 0.542 20 5.0e-05 0.00372 0.00399 0.01116 0.03995 0.348 21 5.0e-05 0.00428 0.00450 0.01285 0.03810 0.328 22 3.0e-05 0.00232 0.00267 0.00696 0.04137 0.370 23 3.0e-05 0.00220 0.00247 0.00661 0.04351 0.377 24 3.0e-05 0.00221 0.00258 0.00663 0.04192 0.364 25 5.0e-05 0.00380 0.00390 0.01140 0.01659 0.164 26 6.0e-05 0.00316 0.00375 0.00948 0.03767 0.381 27 3.0e-05 0.00250 0.00234 0.00750 0.01966 0.186 28 3.0e-05 0.00250 0.00275 0.00749 0.01919 0.198 29 2.0e-05 0.00159 0.00176 0.00476 0.01718 0.161 30 3.0e-05 0.00280 0.00253 0.00841 0.01791 0.168 31 1.0e-05 0.00166 0.00168 0.00498 0.01098 0.097 32 1.0e-05 0.00134 0.00138 0.00402 0.01015 0.089 33 1.0e-05 0.00113 0.00135 0.00339 0.01263 0.111 34 9.0e-06 0.00093 0.00107 0.00278 0.00954 0.085 35 9.0e-06 0.00094 0.00106 0.00283 0.00958 0.085 36 1.0e-05 0.00105 0.00115 0.00314 0.01194 0.107 37 2.0e-05 0.00233 0.00241 0.00700 0.02126 0.189 38 2.0e-05 0.00205 0.00218 0.00616 0.01851 0.168 39 2.0e-05 0.00153 0.00166 0.00459 0.01444 0.131 40 2.0e-05 0.00168 0.00182 0.00504 0.01663 0.151 41 2.0e-05 0.00165 0.00175 0.00496 0.01495 0.135 42 1.0e-05 0.00134 0.00147 0.00403 0.01463 0.132 43 1.0e-05 0.00169 0.00182 0.00507 0.01752 0.164 44 1.0e-05 0.00157 0.00173 0.00470 0.01760 0.154 45 9.0e-06 0.00109 0.00137 0.00327 0.01419 0.126 46 9.0e-06 0.00117 0.00139 0.00350 0.01494 0.134 47 1.0e-05 0.00127 0.00148 0.00380 0.01608 0.141 48 7.0e-06 0.00092 0.00113 0.00276 0.01152 0.103 49 4.0e-05 0.00169 0.00203 0.00507 0.01613 0.143 50 3.0e-05 0.00124 0.00155 0.00373 0.01681 0.154 51 3.0e-05 0.00141 0.00167 0.00422 0.02184 0.197 52 4.0e-05 0.00131 0.00169 0.00393 0.02033 0.185 53 3.0e-05 0.00137 0.00166 0.00411 0.02297 0.210 54 4.0e-05 0.00165 0.00183 0.00495 0.02498 0.228 55 7.0e-05 0.00349 0.00486 0.01046 0.02719 0.255 56 8.0e-05 0.00398 0.00539 0.01193 0.03209 0.307 57 7.0e-05 0.00352 0.00514 0.01056 0.03715 0.334 58 6.0e-05 0.00299 0.00469 0.00898 0.02293 0.221 59 7.0e-05 0.00334 0.00493 0.01003 0.02645 0.265 60 8.0e-05 0.00373 0.00520 0.01120 0.03225 0.350 61 1.0e-05 0.00147 0.00152 0.00442 0.01861 0.170 62 1.0e-05 0.00154 0.00151 0.00461 0.01906 0.165 63 1.0e-05 0.00152 0.00144 0.00457 0.01643 0.145 64 1.0e-05 0.00175 0.00155 0.00526 0.01644 0.145 65 9.0e-06 0.00114 0.00113 0.00342 0.01457 0.129 66 1.0e-05 0.00136 0.00140 0.00408 0.01745 0.154 67 6.0e-05 0.00430 0.00440 0.01289 0.03198 0.313 68 7.0e-05 0.00507 0.00463 0.01520 0.03111 0.308 69 8.0e-05 0.00647 0.00467 0.01941 0.05384 0.478 70 5.0e-05 0.00467 0.00354 0.01400 0.05428 0.497 71 6.0e-05 0.00469 0.00419 0.01407 0.03485 0.365 72 7.0e-05 0.00534 0.00478 0.01601 0.04978 0.483 73 3.0e-05 0.00180 0.00220 0.00540 0.01706 0.152 74 5.0e-05 0.00268 0.00329 0.00805 0.02448 0.226 75 4.0e-05 0.00260 0.00283 0.00780 0.02442 0.216 76 5.0e-05 0.00277 0.00289 0.00831 0.02215 0.206 77 4.0e-05 0.00270 0.00289 0.00810 0.03999 0.350 78 4.0e-05 0.00226 0.00280 0.00677 0.02199 0.197 79 6.0e-05 0.00331 0.00332 0.00994 0.03202 0.263 80 1.0e-04 0.00622 0.00576 0.01865 0.03121 0.361 81 7.0e-05 0.00389 0.00415 0.01168 0.04024 0.364 82 7.0e-05 0.00428 0.00371 0.01283 0.03156 0.296 83 6.0e-05 0.00351 0.00348 0.01053 0.02427 0.216 84 4.0e-05 0.00247 0.00258 0.00742 0.02223 0.202 85 4.0e-05 0.00418 0.00420 0.01254 0.04795 0.435 86 2.0e-05 0.00220 0.00244 0.00659 0.03852 0.331 87 2.0e-05 0.00163 0.00194 0.00488 0.03759 0.327 88 3.0e-05 0.00287 0.00312 0.00862 0.06511 0.580 89 3.0e-05 0.00237 0.00254 0.00710 0.06727 0.650 90 4.0e-05 0.00391 0.00419 0.01172 0.04313 0.442 91 4.0e-05 0.00387 0.00453 0.01161 0.06640 0.634 92 3.0e-05 0.00224 0.00227 0.00672 0.07959 0.772 93 3.0e-05 0.00250 0.00256 0.00750 0.04190 0.383 94 3.0e-05 0.00191 0.00226 0.00574 0.05925 0.637 95 2.0e-05 0.00196 0.00196 0.00587 0.03716 0.307 96 2.0e-05 0.00201 0.00197 0.00602 0.03272 0.283 97 2.0e-05 0.00178 0.00184 0.00535 0.03381 0.307 98 1.0e-04 0.00743 0.00623 0.02228 0.03886 0.342 99 1.1e-04 0.00826 0.00655 0.02478 0.04689 0.422 100 1.5e-04 0.01159 0.00990 0.03476 0.06734 0.659 101 2.6e-04 0.02144 0.01522 0.06433 0.09178 0.891 102 1.2e-04 0.00905 0.00909 0.02716 0.06170 0.584 103 2.2e-04 0.01854 0.01628 0.05563 0.09419 0.930 104 2.0e-05 0.00105 0.00136 0.00315 0.01131 0.107 105 1.0e-05 0.00076 0.00100 0.00229 0.01030 0.094 106 2.0e-05 0.00116 0.00134 0.00349 0.01346 0.126 107 1.0e-05 0.00068 0.00092 0.00204 0.01064 0.097 108 2.0e-05 0.00115 0.00122 0.00346 0.01450 0.137 109 1.0e-05 0.00075 0.00096 0.00225 0.01024 0.093 110 4.0e-05 0.00450 0.00389 0.01351 0.03044 0.275 111 3.0e-05 0.00371 0.00337 0.01112 0.02286 0.207 112 3.0e-05 0.00368 0.00339 0.01105 0.01761 0.155 113 4.0e-05 0.00502 0.00485 0.01506 0.02378 0.210 114 3.0e-05 0.00321 0.00280 0.00964 0.01680 0.149 115 2.0e-05 0.00302 0.00246 0.00905 0.02105 0.209 116 6.0e-05 0.00404 0.00385 0.01211 0.01843 0.235 117 3.0e-05 0.00214 0.00207 0.00642 0.01458 0.148 118 3.0e-05 0.00244 0.00261 0.00731 0.01725 0.175 119 3.0e-05 0.00157 0.00194 0.00472 0.01279 0.129 120 2.0e-05 0.00127 0.00128 0.00381 0.01299 0.124 121 5.0e-05 0.00241 0.00314 0.00723 0.02008 0.221 122 3.0e-05 0.00209 0.00221 0.00628 0.01169 0.117 123 5.0e-05 0.00406 0.00398 0.01218 0.04479 0.441 124 5.0e-05 0.00506 0.00449 0.01517 0.02503 0.231 125 4.0e-05 0.00403 0.00395 0.01209 0.02343 0.224 126 5.0e-05 0.00414 0.00422 0.01242 0.02362 0.233 127 4.0e-05 0.00294 0.00327 0.00883 0.02791 0.246 128 4.0e-05 0.00368 0.00351 0.01104 0.02857 0.257 129 4.0e-05 0.00214 0.00192 0.00641 0.01033 0.098 130 2.0e-05 0.00116 0.00135 0.00349 0.01022 0.090 131 4.0e-05 0.00269 0.00238 0.00808 0.01412 0.125 132 3.0e-05 0.00224 0.00205 0.00671 0.01516 0.138 133 3.0e-05 0.00169 0.00170 0.00508 0.01201 0.106 134 3.0e-05 0.00168 0.00171 0.00504 0.01043 0.099 135 6.0e-05 0.00291 0.00319 0.00873 0.04932 0.441 136 4.0e-05 0.00244 0.00315 0.00731 0.04128 0.379 137 4.0e-05 0.00219 0.00283 0.00658 0.04879 0.431 138 4.0e-05 0.00257 0.00312 0.00772 0.05279 0.476 139 4.0e-05 0.00238 0.00290 0.00715 0.05643 0.517 140 3.0e-05 0.00181 0.00232 0.00542 0.03026 0.267 141 3.0e-05 0.00232 0.00269 0.00696 0.03273 0.281 142 4.0e-05 0.00428 0.00428 0.01285 0.06725 0.571 143 2.0e-05 0.00182 0.00215 0.00546 0.03527 0.297 144 2.0e-05 0.00189 0.00211 0.00568 0.01997 0.180 145 1.0e-05 0.00100 0.00133 0.00301 0.02662 0.228 146 2.0e-05 0.00169 0.00188 0.00506 0.02536 0.225 147 9.0e-05 0.00863 0.00946 0.02589 0.08143 0.821 148 8.0e-05 0.00849 0.00819 0.02546 0.06050 0.618 149 9.0e-05 0.00996 0.01027 0.02987 0.07118 0.722 150 8.0e-05 0.00919 0.00963 0.02756 0.07170 0.833 151 1.0e-04 0.01075 0.01154 0.03225 0.05830 0.784 152 1.6e-04 0.01800 0.01958 0.05401 0.11908 1.302 153 1.4e-04 0.01568 0.01699 0.04705 0.08684 1.018 154 6.0e-05 0.00388 0.00332 0.01164 0.02534 0.241 155 6.0e-05 0.00393 0.00300 0.01179 0.02682 0.236 156 5.0e-05 0.00356 0.00300 0.01067 0.03087 0.276 157 6.0e-05 0.00415 0.00339 0.01246 0.02293 0.223 158 1.5e-04 0.01117 0.00718 0.03351 0.04912 0.438 159 8.0e-05 0.00593 0.00454 0.01778 0.02852 0.266 160 5.0e-05 0.00321 0.00318 0.00962 0.03235 0.339 161 5.0e-05 0.00299 0.00316 0.00896 0.04009 0.406 162 5.0e-05 0.00352 0.00329 0.01057 0.03273 0.325 163 6.0e-05 0.00366 0.00340 0.01097 0.03658 0.369 164 5.0e-05 0.00291 0.00284 0.00873 0.01756 0.155 165 9.0e-05 0.00493 0.00461 0.01480 0.02814 0.272 166 1.0e-05 0.00154 0.00153 0.00462 0.02448 0.217 167 1.0e-05 0.00173 0.00159 0.00519 0.01242 0.116 168 1.0e-05 0.00205 0.00186 0.00616 0.02030 0.197 169 4.0e-05 0.00490 0.00448 0.01470 0.02177 0.189 170 2.0e-05 0.00316 0.00283 0.00949 0.02018 0.212 171 2.0e-05 0.00279 0.00237 0.00837 0.01897 0.181 172 3.0e-05 0.00166 0.00190 0.00499 0.01358 0.129 173 3.0e-05 0.00170 0.00200 0.00510 0.01484 0.133 174 3.0e-05 0.00171 0.00203 0.00514 0.01472 0.133 175 3.0e-05 0.00176 0.00218 0.00528 0.01657 0.145 176 3.0e-05 0.00160 0.00199 0.00480 0.01503 0.137 177 3.0e-05 0.00169 0.00213 0.00507 0.01725 0.155 178 2.0e-05 0.00135 0.00162 0.00406 0.01469 0.132 179 2.0e-05 0.00152 0.00186 0.00456 0.01574 0.142 180 3.0e-05 0.00204 0.00231 0.00612 0.01450 0.131 181 3.0e-05 0.00206 0.00233 0.00619 0.02551 0.237 182 3.0e-05 0.00202 0.00235 0.00605 0.01831 0.163 183 2.0e-05 0.00174 0.00198 0.00521 0.02145 0.198 184 4.0e-05 0.00186 0.00270 0.00558 0.01909 0.171 185 5.0e-05 0.00260 0.00346 0.00780 0.01795 0.163 186 3.0e-05 0.00134 0.00192 0.00403 0.01564 0.136 187 4.0e-05 0.00254 0.00263 0.00762 0.01660 0.154 188 2.0e-05 0.00115 0.00148 0.00345 0.01300 0.117 189 3.0e-05 0.00146 0.00184 0.00439 0.01185 0.106 190 3.0e-05 0.00412 0.00396 0.01235 0.02574 0.255 191 3.0e-05 0.00263 0.00259 0.00790 0.04087 0.405 192 3.0e-05 0.00331 0.00292 0.00994 0.02751 0.263 193 8.0e-05 0.00624 0.00564 0.01873 0.02308 0.256 194 4.0e-05 0.00370 0.00390 0.01109 0.02296 0.241 195 3.0e-05 0.00295 0.00317 0.00885 0.01884 0.190 Shimmer:APQ3 Shimmer:APQ5 Shimmer:DDA NHR HNR RPDE DFA 1 0.02182 0.03130 0.06545 0.02211 21.033 0.414783 0.815285 2 0.03134 0.04518 0.09403 0.01929 19.085 0.458359 0.819521 3 0.02757 0.03858 0.08270 0.01309 20.651 0.429895 0.825288 4 0.02924 0.04005 0.08771 0.01353 20.644 0.434969 0.819235 5 0.03490 0.04825 0.10470 0.01767 19.649 0.417356 0.823484 6 0.02328 0.03526 0.06985 0.01222 21.378 0.415564 0.825069 7 0.00779 0.00937 0.02337 0.00607 24.886 0.596040 0.764112 8 0.00829 0.00946 0.02487 0.00344 26.892 0.637420 0.763262 9 0.01073 0.01277 0.03218 0.01070 21.812 0.615551 0.773587 10 0.01441 0.01725 0.04324 0.01022 21.862 0.547037 0.798463 11 0.01079 0.01342 0.03237 0.01166 21.118 0.611137 0.776156 12 0.01424 0.01641 0.04272 0.01141 21.414 0.583390 0.792520 13 0.00656 0.00717 0.01968 0.00581 25.703 0.460600 0.646846 14 0.00728 0.00932 0.02184 0.01041 24.889 0.430166 0.665833 15 0.01064 0.00972 0.03191 0.00609 24.922 0.474791 0.654027 16 0.00772 0.00888 0.02316 0.00839 25.175 0.565924 0.658245 17 0.00969 0.01200 0.02908 0.01859 22.333 0.567380 0.644692 18 0.01441 0.01893 0.04322 0.02919 20.376 0.631099 0.605417 19 0.02471 0.03572 0.07413 0.03160 17.280 0.665318 0.719467 20 0.01721 0.02374 0.05164 0.03365 17.153 0.649554 0.686080 21 0.01667 0.02383 0.05000 0.03871 17.536 0.660125 0.704087 22 0.02021 0.02591 0.06062 0.01849 19.493 0.629017 0.698951 23 0.02228 0.02540 0.06685 0.01280 22.468 0.619060 0.679834 24 0.02187 0.02470 0.06562 0.01840 20.422 0.537264 0.686894 25 0.00738 0.00948 0.02214 0.01778 23.831 0.397937 0.732479 26 0.01732 0.02245 0.05197 0.02887 22.066 0.522746 0.737948 27 0.00889 0.01169 0.02666 0.01095 25.908 0.418622 0.720916 28 0.00883 0.01144 0.02650 0.01328 25.119 0.358773 0.726652 29 0.00769 0.01012 0.02307 0.00677 25.970 0.470478 0.676258 30 0.00793 0.01057 0.02380 0.01170 25.678 0.427785 0.723797 31 0.00563 0.00680 0.01689 0.00339 26.775 0.422229 0.741367 32 0.00504 0.00641 0.01513 0.00167 30.940 0.432439 0.742055 33 0.00640 0.00825 0.01919 0.00119 30.775 0.465946 0.738703 34 0.00469 0.00606 0.01407 0.00072 32.684 0.368535 0.742133 35 0.00468 0.00610 0.01403 0.00065 33.047 0.340068 0.741899 36 0.00586 0.00760 0.01758 0.00135 31.732 0.344252 0.742737 37 0.01154 0.01347 0.03463 0.00586 23.216 0.360148 0.778834 38 0.00938 0.01160 0.02814 0.00340 24.951 0.341435 0.783626 39 0.00726 0.00885 0.02177 0.00231 26.738 0.403884 0.766209 40 0.00829 0.01003 0.02488 0.00265 26.310 0.396793 0.758324 41 0.00774 0.00941 0.02321 0.00231 26.822 0.326480 0.765623 42 0.00742 0.00901 0.02226 0.00257 26.453 0.306443 0.759203 43 0.01035 0.01024 0.03104 0.00740 22.736 0.305062 0.654172 44 0.01006 0.01038 0.03017 0.00675 23.145 0.457702 0.634267 45 0.00777 0.00898 0.02330 0.00454 25.368 0.438296 0.635285 46 0.00847 0.00879 0.02542 0.00476 25.032 0.431285 0.638928 47 0.00906 0.00977 0.02719 0.00476 24.602 0.467489 0.631653 48 0.00614 0.00730 0.01841 0.00432 26.805 0.610367 0.635204 49 0.00855 0.00776 0.02566 0.00839 23.162 0.579597 0.733659 50 0.00930 0.00802 0.02789 0.00462 24.971 0.538688 0.754073 51 0.01241 0.01024 0.03724 0.00479 25.135 0.553134 0.775933 52 0.01143 0.00959 0.03429 0.00474 25.030 0.507504 0.760361 53 0.01323 0.01072 0.03969 0.00481 24.692 0.459766 0.766204 54 0.01396 0.01219 0.04188 0.00484 25.429 0.420383 0.785714 55 0.01483 0.01609 0.04450 0.01036 21.028 0.536009 0.819032 56 0.01789 0.01992 0.05368 0.01180 20.767 0.558586 0.811843 57 0.02032 0.02302 0.06097 0.00969 21.422 0.541781 0.821364 58 0.01189 0.01459 0.03568 0.00681 22.817 0.530529 0.817756 59 0.01394 0.01625 0.04183 0.00786 22.603 0.540049 0.813432 60 0.01805 0.01974 0.05414 0.01143 21.660 0.547975 0.817396 61 0.00975 0.01258 0.02925 0.00871 25.554 0.341788 0.678874 62 0.01013 0.01296 0.03039 0.00301 26.138 0.447979 0.686264 63 0.00867 0.01108 0.02602 0.00340 25.856 0.364867 0.694399 64 0.00882 0.01075 0.02647 0.00351 25.964 0.256570 0.683296 65 0.00769 0.00957 0.02308 0.00300 26.415 0.276850 0.673636 66 0.00942 0.01160 0.02827 0.00420 24.547 0.305429 0.681811 67 0.01830 0.01810 0.05490 0.02183 19.560 0.460139 0.720908 68 0.01638 0.01759 0.04914 0.02659 19.979 0.498133 0.729067 69 0.03152 0.02422 0.09455 0.04882 20.338 0.513237 0.731444 70 0.03357 0.02494 0.10070 0.02431 21.718 0.487407 0.727313 71 0.01868 0.01906 0.05605 0.02599 20.264 0.489345 0.730387 72 0.02749 0.02466 0.08247 0.03361 18.570 0.543299 0.733232 73 0.00974 0.00925 0.02921 0.00442 25.742 0.495954 0.762959 74 0.01373 0.01375 0.04120 0.00623 24.178 0.509127 0.789532 75 0.01432 0.01325 0.04295 0.00479 25.438 0.437031 0.815908 76 0.01284 0.01219 0.03851 0.00472 25.197 0.463514 0.807217 77 0.02413 0.02231 0.07238 0.00905 23.370 0.489538 0.789977 78 0.01284 0.01199 0.03852 0.00420 25.820 0.429484 0.816340 79 0.01803 0.01886 0.05408 0.01062 21.875 0.644954 0.779612 80 0.01773 0.01783 0.05320 0.02220 19.200 0.594387 0.790117 81 0.02266 0.02451 0.06799 0.01823 19.055 0.544805 0.770466 82 0.01792 0.01841 0.05377 0.01825 19.659 0.576084 0.778747 83 0.01371 0.01421 0.04114 0.01237 20.536 0.554610 0.787896 84 0.01277 0.01343 0.03831 0.00882 22.244 0.576644 0.772416 85 0.02679 0.03022 0.08037 0.05470 13.893 0.556494 0.729586 86 0.02107 0.02493 0.06321 0.02782 16.176 0.583574 0.727747 87 0.02073 0.02415 0.06219 0.03151 15.924 0.598714 0.712199 88 0.03671 0.04159 0.11012 0.04824 13.922 0.602874 0.740837 89 0.03788 0.04254 0.11363 0.04214 14.739 0.599371 0.743937 90 0.02297 0.02768 0.06892 0.07223 11.866 0.590951 0.745526 91 0.03650 0.04282 0.10949 0.08725 11.744 0.653410 0.733165 92 0.04421 0.04962 0.13262 0.01658 19.664 0.501037 0.714360 93 0.02383 0.02521 0.07150 0.01914 18.780 0.454444 0.734504 94 0.03341 0.03794 0.10024 0.01211 20.969 0.447456 0.697790 95 0.02062 0.02321 0.06185 0.00850 22.219 0.502380 0.712170 96 0.01813 0.01909 0.05439 0.01018 21.693 0.447285 0.705658 97 0.01806 0.02024 0.05417 0.00852 22.663 0.366329 0.693429 98 0.02135 0.02174 0.06406 0.08151 15.338 0.629574 0.714485 99 0.02542 0.02630 0.07625 0.10323 15.433 0.571010 0.690892 100 0.03611 0.03963 0.10833 0.16744 12.435 0.638545 0.674953 101 0.05358 0.04791 0.16074 0.31482 8.867 0.671299 0.656846 102 0.03223 0.03672 0.09669 0.11843 15.060 0.639808 0.643327 103 0.05551 0.05005 0.16654 0.25930 10.489 0.596362 0.641418 104 0.00522 0.00659 0.01567 0.00495 26.759 0.296888 0.722356 105 0.00469 0.00582 0.01406 0.00243 28.409 0.263654 0.691483 106 0.00660 0.00818 0.01979 0.00578 27.421 0.365488 0.719974 107 0.00522 0.00632 0.01567 0.00233 29.746 0.334171 0.677930 108 0.00633 0.00788 0.01898 0.00659 26.833 0.393563 0.700246 109 0.00455 0.00576 0.01364 0.00238 29.928 0.311369 0.676066 110 0.01771 0.01815 0.05312 0.00947 21.934 0.497554 0.740539 111 0.01192 0.01439 0.03576 0.00704 23.239 0.436084 0.727863 112 0.00952 0.01058 0.02855 0.00830 22.407 0.338097 0.712466 113 0.01277 0.01483 0.03831 0.01316 21.305 0.498877 0.722085 114 0.00861 0.01017 0.02583 0.00620 23.671 0.441097 0.722254 115 0.01107 0.01284 0.03320 0.01048 21.864 0.331508 0.715121 116 0.00796 0.00832 0.02389 0.06051 23.693 0.407701 0.662668 117 0.00606 0.00747 0.01818 0.01554 26.356 0.450798 0.653823 118 0.00757 0.00971 0.02270 0.01802 25.690 0.486738 0.676023 119 0.00617 0.00744 0.01851 0.00856 25.020 0.470422 0.655239 120 0.00679 0.00631 0.02038 0.00681 24.581 0.462516 0.582710 121 0.00849 0.01117 0.02548 0.02350 24.743 0.487756 0.684130 122 0.00534 0.00630 0.01603 0.01161 27.166 0.400088 0.656182 123 0.02587 0.02567 0.07761 0.01968 18.305 0.538016 0.741480 124 0.01372 0.01580 0.04115 0.01813 18.784 0.589956 0.732903 125 0.01289 0.01420 0.03867 0.02020 19.196 0.618663 0.728421 126 0.01235 0.01495 0.03706 0.01874 18.857 0.637518 0.735546 127 0.01484 0.01805 0.04451 0.01794 18.178 0.623209 0.738245 128 0.01547 0.01859 0.04641 0.01796 18.330 0.585169 0.736964 129 0.00538 0.00570 0.01614 0.01724 26.842 0.457541 0.699787 130 0.00476 0.00588 0.01428 0.00487 26.369 0.491345 0.718839 131 0.00703 0.00820 0.02110 0.01610 23.949 0.467160 0.724045 132 0.00721 0.00815 0.02164 0.01015 26.017 0.468621 0.735136 133 0.00633 0.00701 0.01898 0.00903 23.389 0.470972 0.721308 134 0.00490 0.00621 0.01471 0.00504 25.619 0.482296 0.723096 135 0.02683 0.03112 0.08050 0.03031 17.060 0.637814 0.744064 136 0.02229 0.02592 0.06688 0.02529 17.707 0.653427 0.706687 137 0.02385 0.02973 0.07154 0.02278 19.013 0.647900 0.708144 138 0.02896 0.03347 0.08689 0.03690 16.747 0.625362 0.708617 139 0.03070 0.03530 0.09211 0.02629 17.366 0.640945 0.701404 140 0.01514 0.01812 0.04543 0.01827 18.801 0.624811 0.696049 141 0.01713 0.01964 0.05139 0.02485 18.540 0.677131 0.685057 142 0.04016 0.04003 0.12047 0.04238 15.648 0.606344 0.665945 143 0.02055 0.02076 0.06165 0.01728 18.702 0.606273 0.661735 144 0.01117 0.01177 0.03350 0.02010 18.687 0.536102 0.632631 145 0.01475 0.01558 0.04426 0.01049 20.680 0.497480 0.630409 146 0.01379 0.01478 0.04137 0.01493 20.366 0.566849 0.574282 147 0.03804 0.05426 0.11411 0.07530 12.359 0.561610 0.793509 148 0.02865 0.04101 0.08595 0.06057 14.367 0.478024 0.768974 149 0.03474 0.04580 0.10422 0.08069 12.298 0.552870 0.764036 150 0.03515 0.04265 0.10546 0.07889 14.989 0.427627 0.775708 151 0.02699 0.03714 0.08096 0.10952 12.529 0.507826 0.762726 152 0.05647 0.07940 0.16942 0.21713 8.441 0.625866 0.768320 153 0.04284 0.05556 0.12851 0.16265 9.449 0.584164 0.754449 154 0.01340 0.01399 0.04019 0.04179 21.520 0.566867 0.670475 155 0.01484 0.01405 0.04451 0.04611 21.824 0.651680 0.659333 156 0.01659 0.01804 0.04977 0.02631 22.431 0.628300 0.652025 157 0.01205 0.01289 0.03615 0.03191 22.953 0.611679 0.623731 158 0.02610 0.02161 0.07830 0.10748 19.075 0.630547 0.646786 159 0.01500 0.01581 0.04499 0.03828 21.534 0.635015 0.627337 160 0.01360 0.01650 0.04079 0.02663 19.651 0.654945 0.675865 161 0.01579 0.01994 0.04736 0.02073 20.437 0.653139 0.694571 162 0.01644 0.01722 0.04933 0.02810 19.388 0.577802 0.684373 163 0.01864 0.01940 0.05592 0.02707 18.954 0.685151 0.719576 164 0.00967 0.01033 0.02902 0.01435 21.219 0.557045 0.673086 165 0.01579 0.01553 0.04736 0.03882 18.447 0.671378 0.674562 166 0.01410 0.01426 0.04231 0.00620 24.078 0.469928 0.628232 167 0.00696 0.00747 0.02089 0.00533 24.679 0.384868 0.626710 168 0.01186 0.01230 0.03557 0.00910 21.083 0.440988 0.628058 169 0.01279 0.01272 0.03836 0.01337 19.269 0.372222 0.725216 170 0.01176 0.01191 0.03529 0.00965 21.020 0.371837 0.646167 171 0.01084 0.01121 0.03253 0.01049 21.528 0.522812 0.646818 172 0.00664 0.00786 0.01992 0.00435 26.436 0.413295 0.756700 173 0.00754 0.00950 0.02261 0.00430 26.550 0.369090 0.776158 174 0.00748 0.00905 0.02245 0.00478 26.547 0.380253 0.766700 175 0.00881 0.01062 0.02643 0.00590 25.445 0.387482 0.756482 176 0.00812 0.00933 0.02436 0.00401 26.005 0.405991 0.761255 177 0.00874 0.01021 0.02623 0.00415 26.143 0.361232 0.763242 178 0.00728 0.00886 0.02184 0.00570 24.151 0.396610 0.745957 179 0.00839 0.00956 0.02518 0.00488 24.412 0.402591 0.762508 180 0.00725 0.00876 0.02175 0.00540 23.683 0.398499 0.778349 181 0.01321 0.01574 0.03964 0.00611 23.133 0.352396 0.759320 182 0.00950 0.01103 0.02849 0.00639 22.866 0.408598 0.768845 183 0.01155 0.01341 0.03464 0.00595 23.008 0.329577 0.757180 184 0.00864 0.01223 0.02592 0.00955 23.079 0.603515 0.669565 185 0.00810 0.01144 0.02429 0.01179 22.085 0.663842 0.656516 186 0.00667 0.00990 0.02001 0.00737 24.199 0.598515 0.654331 187 0.00820 0.00972 0.02460 0.01397 23.958 0.566424 0.667654 188 0.00631 0.00789 0.01892 0.00680 25.023 0.528485 0.663884 189 0.00557 0.00721 0.01672 0.00703 24.775 0.555303 0.659132 190 0.01454 0.01582 0.04363 0.04441 19.368 0.508479 0.683761 191 0.02336 0.02498 0.07008 0.02764 19.517 0.448439 0.657899 192 0.01604 0.01657 0.04812 0.01810 19.147 0.431674 0.683244 193 0.01268 0.01365 0.03804 0.10715 17.883 0.407567 0.655683 194 0.01265 0.01321 0.03794 0.07223 19.020 0.451221 0.643956 195 0.01026 0.01161 0.03078 0.04398 21.209 0.462803 0.664357 spread1 spread2 D2 PPE 1 -4.813031 0.266482 2.301442 0.284654 2 -4.075192 0.335590 2.486855 0.368674 3 -4.443179 0.311173 2.342259 0.332634 4 -4.117501 0.334147 2.405554 0.368975 5 -3.747787 0.234513 2.332180 0.410335 6 -4.242867 0.299111 2.187560 0.357775 7 -5.634322 0.257682 1.854785 0.211756 8 -6.167603 0.183721 2.064693 0.163755 9 -5.498678 0.327769 2.322511 0.231571 10 -5.011879 0.325996 2.432792 0.271362 11 -5.249770 0.391002 2.407313 0.249740 12 -4.960234 0.363566 2.642476 0.275931 13 -6.547148 0.152813 2.041277 0.138512 14 -5.660217 0.254989 2.519422 0.199889 15 -6.105098 0.203653 2.125618 0.170100 16 -5.340115 0.210185 2.205546 0.234589 17 -5.440040 0.239764 2.264501 0.218164 18 -2.931070 0.434326 3.007463 0.430788 19 -3.949079 0.357870 3.109010 0.377429 20 -4.554466 0.340176 2.856676 0.322111 21 -4.095442 0.262564 2.739710 0.365391 22 -5.186960 0.237622 2.557536 0.259765 23 -4.330956 0.262384 2.916777 0.285695 24 -5.248776 0.210279 2.547508 0.253556 25 -5.557447 0.220890 2.692176 0.215961 26 -5.571843 0.236853 2.846369 0.219514 27 -6.183590 0.226278 2.589702 0.147403 28 -6.271690 0.196102 2.314209 0.162999 29 -7.120925 0.279789 2.241742 0.108514 30 -6.635729 0.209866 1.957961 0.135242 31 -7.348300 0.177551 1.743867 0.085569 32 -7.682587 0.173319 2.103106 0.068501 33 -7.067931 0.175181 1.512275 0.096320 34 -7.695734 0.178540 1.544609 0.056141 35 -7.964984 0.163519 1.423287 0.044539 36 -7.777685 0.170183 2.447064 0.057610 37 -6.149653 0.218037 2.477082 0.165827 38 -6.006414 0.196371 2.536527 0.173218 39 -6.452058 0.212294 2.269398 0.141929 40 -6.006647 0.266892 2.382544 0.160691 41 -6.647379 0.201095 2.374073 0.130554 42 -7.044105 0.063412 2.361532 0.115730 43 -7.310550 0.098648 2.416838 0.095032 44 -6.793547 0.158266 2.256699 0.117399 45 -7.057869 0.091608 2.330716 0.091470 46 -6.995820 0.102083 2.365800 0.102706 47 -7.156076 0.127642 2.392122 0.097336 48 -7.319510 0.200873 2.028612 0.086398 49 -6.439398 0.266392 2.079922 0.133867 50 -6.482096 0.264967 2.054419 0.128872 51 -6.650471 0.254498 1.840198 0.103561 52 -6.689151 0.291954 2.431854 0.105993 53 -7.072419 0.220434 1.972297 0.119308 54 -6.836811 0.269866 2.223719 0.147491 55 -4.649573 0.205558 1.986899 0.316700 56 -4.333543 0.221727 2.014606 0.344834 57 -4.438453 0.238298 1.922940 0.335041 58 -4.608260 0.290024 2.021591 0.314464 59 -4.476755 0.262633 1.827012 0.326197 60 -4.609161 0.221711 1.831691 0.316395 61 -7.040508 0.066994 2.460791 0.101516 62 -7.293801 0.086372 2.321560 0.098555 63 -6.966321 0.095882 2.278687 0.103224 64 -7.245620 0.018689 2.498224 0.093534 65 -7.496264 0.056844 2.003032 0.073581 66 -7.314237 0.006274 2.118596 0.091546 67 -5.409423 0.226850 2.359973 0.226156 68 -5.324574 0.205660 2.291558 0.226247 69 -5.869750 0.151814 2.118496 0.185580 70 -6.261141 0.120956 2.137075 0.141958 71 -5.720868 0.158830 2.277927 0.180828 72 -5.207985 0.224852 2.642276 0.242981 73 -5.791820 0.329066 2.205024 0.188180 74 -5.389129 0.306636 1.928708 0.225461 75 -5.313360 0.201861 2.225815 0.244512 76 -5.477592 0.315074 1.862092 0.228624 77 -5.775966 0.341169 2.007923 0.193918 78 -5.391029 0.250572 1.777901 0.232744 79 -5.115212 0.249494 2.017753 0.260015 80 -4.913885 0.265699 2.398422 0.277948 81 -4.441519 0.155097 2.645959 0.327978 82 -5.132032 0.210458 2.232576 0.260633 83 -5.022288 0.146948 2.428306 0.264666 84 -6.025367 0.078202 2.053601 0.177275 85 -5.288912 0.343073 3.099301 0.242119 86 -5.657899 0.315903 3.098256 0.200423 87 -6.366916 0.335753 2.654271 0.144614 88 -5.515071 0.299549 3.136550 0.220968 89 -5.783272 0.299793 3.007096 0.194052 90 -4.379411 0.375531 3.671155 0.332086 91 -4.508984 0.389232 3.317586 0.301952 92 -6.411497 0.207156 2.344876 0.134120 93 -5.952058 0.087840 2.344336 0.186489 94 -6.152551 0.173520 2.080121 0.160809 95 -6.251425 0.188056 2.143851 0.160812 96 -6.247076 0.180528 2.344348 0.164916 97 -6.417440 0.194627 2.473239 0.151709 98 -4.020042 0.265315 2.671825 0.340623 99 -5.159169 0.202146 2.441612 0.260375 100 -3.760348 0.242861 2.634633 0.378483 101 -3.700544 0.260481 2.991063 0.370961 102 -4.202730 0.310163 2.638279 0.356881 103 -3.269487 0.270641 2.690917 0.444774 104 -6.878393 0.089267 2.004055 0.113942 105 -7.111576 0.144780 2.065477 0.093193 106 -6.997403 0.210279 1.994387 0.112878 107 -6.981201 0.184550 2.129924 0.106802 108 -6.600023 0.249172 2.499148 0.105306 109 -6.739151 0.160686 2.296873 0.115130 110 -5.845099 0.278679 2.608749 0.185668 111 -5.258320 0.256454 2.550961 0.232520 112 -6.471427 0.184378 2.502336 0.136390 113 -4.876336 0.212054 2.376749 0.268144 114 -5.963040 0.250283 2.489191 0.177807 115 -6.729713 0.181701 2.938114 0.115515 116 -4.673241 0.261549 2.702355 0.274407 117 -6.051233 0.273280 2.640798 0.170106 118 -4.597834 0.372114 2.975889 0.282780 119 -4.913137 0.393056 2.816781 0.251972 120 -5.517173 0.389295 2.925862 0.220657 121 -6.186128 0.279933 2.686240 0.152428 122 -4.711007 0.281618 2.655744 0.234809 123 -5.418787 0.160267 2.090438 0.229892 124 -5.445140 0.142466 2.174306 0.215558 125 -5.944191 0.143359 1.929715 0.181988 126 -5.594275 0.127950 1.765957 0.222716 127 -5.540351 0.087165 1.821297 0.214075 128 -5.825257 0.115697 1.996146 0.196535 129 -6.890021 0.152941 2.328513 0.112856 130 -5.892061 0.195976 2.108873 0.183572 131 -6.135296 0.203630 2.539724 0.169923 132 -6.112667 0.217013 2.527742 0.170633 133 -5.436135 0.254909 2.516320 0.232209 134 -6.448134 0.178713 2.034827 0.141422 135 -5.301321 0.320385 2.375138 0.243080 136 -5.333619 0.322044 2.631793 0.228319 137 -4.378916 0.300067 2.445502 0.259451 138 -4.654894 0.304107 2.672362 0.274387 139 -5.634576 0.306014 2.419253 0.209191 140 -5.866357 0.233070 2.445646 0.184985 141 -4.796845 0.397749 2.963799 0.277227 142 -5.410336 0.288917 2.665133 0.231723 143 -5.585259 0.310746 2.465528 0.209863 144 -5.898673 0.213353 2.470746 0.189032 145 -6.132663 0.220617 2.576563 0.159777 146 -5.456811 0.345238 2.840556 0.232861 147 -3.297668 0.414758 3.413649 0.457533 148 -4.276605 0.355736 3.142364 0.336085 149 -3.377325 0.335357 3.274865 0.418646 150 -4.892495 0.262281 2.910213 0.270173 151 -4.484303 0.340256 2.958815 0.301487 152 -2.434031 0.450493 3.079221 0.527367 153 -2.839756 0.356224 3.184027 0.454721 154 -4.865194 0.246404 2.013530 0.168581 155 -4.239028 0.175691 2.451130 0.247455 156 -3.583722 0.207914 2.439597 0.206256 157 -5.435100 0.230532 2.699645 0.220546 158 -3.444478 0.303214 2.964568 0.261305 159 -5.070096 0.280091 2.892300 0.249703 160 -5.498456 0.234196 2.103014 0.216638 161 -5.185987 0.259229 2.151121 0.244948 162 -5.283009 0.226528 2.442906 0.238281 163 -5.529833 0.242750 2.408689 0.220520 164 -5.617124 0.184896 1.871871 0.212386 165 -2.929379 0.396746 2.560422 0.367233 166 -6.816086 0.172270 2.235197 0.119652 167 -7.018057 0.176316 1.852402 0.091604 168 -7.517934 0.160414 1.881767 0.075587 169 -5.736781 0.164529 2.882450 0.202879 170 -7.169701 0.073298 2.266432 0.100881 171 -7.304500 0.171088 2.095237 0.096220 172 -6.323531 0.218885 2.193412 0.160376 173 -6.085567 0.192375 1.889002 0.174152 174 -5.943501 0.192150 1.852542 0.179677 175 -6.012559 0.229298 1.872946 0.163118 176 -5.966779 0.197938 1.974857 0.184067 177 -6.016891 0.109256 2.004719 0.174429 178 -6.486822 0.197919 2.449763 0.132703 179 -6.311987 0.182459 2.251553 0.160306 180 -5.711205 0.240875 2.845109 0.192730 181 -6.261446 0.183218 2.264226 0.144105 182 -5.704053 0.216204 2.679185 0.197710 183 -6.277170 0.109397 2.209021 0.156368 184 -5.619070 0.191576 2.027228 0.215724 185 -5.198864 0.206768 2.120412 0.252404 186 -5.592584 0.133917 2.058658 0.214346 187 -6.431119 0.153310 2.161936 0.120605 188 -6.359018 0.116636 2.152083 0.138868 189 -6.710219 0.149694 1.913990 0.121777 190 -6.934474 0.159890 2.316346 0.112838 191 -6.538586 0.121952 2.657476 0.133050 192 -6.195325 0.129303 2.784312 0.168895 193 -6.787197 0.158453 2.679772 0.131728 194 -6.744577 0.207454 2.138608 0.123306 195 -5.724056 0.190667 2.555477 0.148569 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `MDVP:Fo(Hz)` `MDVP:Fhi(Hz)` `MDVP:Flo(Hz)` 2.270e+00 -2.286e-03 -9.960e-05 -1.558e-03 `MDVP:Jitter(%)` `MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ` -1.807e+02 -2.632e+03 -4.068e+02 -3.516e+01 `Jitter:DDP` `MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3` 2.426e+02 2.118e+01 5.449e-01 -6.739e+02 `Shimmer:APQ5` `Shimmer:DDA` NHR HNR -2.603e+01 2.204e+02 -2.586e+00 -1.602e-02 RPDE DFA spread1 spread2 -1.043e+00 3.505e-01 1.318e-01 1.267e+00 D2 PPE 5.130e-02 1.180e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.94281 -0.15029 0.04766 0.20812 0.58217 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.270e+00 1.144e+00 1.984 0.04887 * `MDVP:Fo(Hz)` -2.286e-03 1.465e-03 -1.560 0.12057 `MDVP:Fhi(Hz)` -9.960e-05 3.154e-04 -0.316 0.75255 `MDVP:Flo(Hz)` -1.558e-03 7.960e-04 -1.958 0.05188 . `MDVP:Jitter(%)` -1.807e+02 6.548e+01 -2.760 0.00640 ** `MDVP:Jitter(Abs)` -2.632e+03 3.917e+03 -0.672 0.50256 `MDVP:RAP` -4.068e+02 9.223e+03 -0.044 0.96487 `MDVP:PPQ` -3.516e+01 8.808e+01 -0.399 0.69029 `Jitter:DDP` 2.426e+02 3.075e+03 0.079 0.93720 `MDVP:Shimmer` 2.118e+01 2.605e+01 0.813 0.41733 `MDVP:Shimmer(dB)` 5.449e-01 1.193e+00 0.457 0.64832 `Shimmer:APQ3` -6.739e+02 8.921e+03 -0.076 0.93987 `Shimmer:APQ5` -2.603e+01 2.003e+01 -1.300 0.19547 `Shimmer:DDA` 2.204e+02 2.974e+03 0.074 0.94101 NHR -2.586e+00 1.964e+00 -1.317 0.18957 HNR -1.602e-02 1.426e-02 -1.123 0.26288 RPDE -1.043e+00 4.266e-01 -2.445 0.01550 * DFA 3.505e-01 7.372e-01 0.475 0.63509 spread1 1.318e-01 9.632e-02 1.369 0.17286 spread2 1.267e+00 4.767e-01 2.657 0.00862 ** D2 5.130e-02 1.138e-01 0.451 0.65277 PPE 1.180e+00 1.347e+00 0.875 0.38258 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.3258 on 173 degrees of freedom Multiple R-squared: 0.4925, Adjusted R-squared: 0.4309 F-statistic: 7.995 on 21 and 173 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 2.542585e-49 5.085170e-49 1.00000000 [2,] 3.200967e-70 6.401933e-70 1.00000000 [3,] 3.243071e-80 6.486142e-80 1.00000000 [4,] 7.678565e-92 1.535713e-91 1.00000000 [5,] 8.363704e-110 1.672741e-109 1.00000000 [6,] 3.065328e-121 6.130656e-121 1.00000000 [7,] 3.312769e-04 6.625538e-04 0.99966872 [8,] 9.476026e-05 1.895205e-04 0.99990524 [9,] 2.761903e-05 5.523807e-05 0.99997238 [10,] 7.249990e-06 1.449998e-05 0.99999275 [11,] 2.318831e-06 4.637662e-06 0.99999768 [12,] 6.510161e-07 1.302032e-06 0.99999935 [13,] 4.263066e-05 8.526131e-05 0.99995737 [14,] 3.296660e-05 6.593319e-05 0.99996703 [15,] 5.381629e-04 1.076326e-03 0.99946184 [16,] 7.382982e-04 1.476596e-03 0.99926170 [17,] 8.945070e-04 1.789014e-03 0.99910549 [18,] 5.581095e-04 1.116219e-03 0.99944189 [19,] 3.304338e-04 6.608677e-04 0.99966957 [20,] 1.889292e-04 3.778584e-04 0.99981107 [21,] 9.039295e-05 1.807859e-04 0.99990961 [22,] 4.601249e-05 9.202498e-05 0.99995399 [23,] 2.880337e-05 5.760673e-05 0.99997120 [24,] 3.684783e-05 7.369567e-05 0.99996315 [25,] 1.959926e-04 3.919851e-04 0.99980401 [26,] 1.553175e-04 3.106350e-04 0.99984468 [27,] 1.040494e-04 2.080988e-04 0.99989595 [28,] 7.090766e-05 1.418153e-04 0.99992909 [29,] 5.333506e-05 1.066701e-04 0.99994666 [30,] 5.529667e-05 1.105933e-04 0.99994470 [31,] 4.333263e-05 8.666527e-05 0.99995667 [32,] 4.398262e-05 8.796524e-05 0.99995602 [33,] 2.468572e-05 4.937145e-05 0.99997531 [34,] 1.585459e-05 3.170918e-05 0.99998415 [35,] 8.854622e-06 1.770924e-05 0.99999115 [36,] 5.045770e-06 1.009154e-05 0.99999495 [37,] 2.508399e-04 5.016798e-04 0.99974916 [38,] 3.823141e-04 7.646283e-04 0.99961769 [39,] 6.260249e-04 1.252050e-03 0.99937398 [40,] 7.443919e-04 1.488784e-03 0.99925561 [41,] 5.327956e-04 1.065591e-03 0.99946720 [42,] 5.347926e-04 1.069585e-03 0.99946521 [43,] 4.117990e-04 8.235979e-04 0.99958820 [44,] 2.641959e-04 5.283917e-04 0.99973580 [45,] 2.066948e-04 4.133895e-04 0.99979331 [46,] 1.499057e-04 2.998114e-04 0.99985009 [47,] 9.286552e-05 1.857310e-04 0.99990713 [48,] 6.392835e-05 1.278567e-04 0.99993607 [49,] 3.712688e-05 7.425377e-05 0.99996287 [50,] 1.296265e-04 2.592530e-04 0.99987037 [51,] 1.583747e-04 3.167494e-04 0.99984163 [52,] 1.092359e-04 2.184718e-04 0.99989076 [53,] 6.974057e-05 1.394811e-04 0.99993026 [54,] 5.093130e-05 1.018626e-04 0.99994907 [55,] 3.063298e-05 6.126596e-05 0.99996937 [56,] 2.228956e-05 4.457912e-05 0.99997771 [57,] 1.816548e-05 3.633096e-05 0.99998183 [58,] 1.091103e-05 2.182207e-05 0.99998909 [59,] 7.687149e-06 1.537430e-05 0.99999231 [60,] 5.026557e-06 1.005311e-05 0.99999497 [61,] 3.624360e-06 7.248719e-06 0.99999638 [62,] 3.741303e-06 7.482606e-06 0.99999626 [63,] 6.099887e-06 1.219977e-05 0.99999390 [64,] 3.891708e-06 7.783415e-06 0.99999611 [65,] 2.913975e-06 5.827950e-06 0.99999709 [66,] 3.105474e-06 6.210948e-06 0.99999689 [67,] 2.861832e-06 5.723664e-06 0.99999714 [68,] 3.334987e-06 6.669974e-06 0.99999667 [69,] 2.137840e-06 4.275681e-06 0.99999786 [70,] 1.437111e-06 2.874223e-06 0.99999856 [71,] 9.098060e-07 1.819612e-06 0.99999909 [72,] 5.759366e-07 1.151873e-06 0.99999942 [73,] 3.681128e-07 7.362255e-07 0.99999963 [74,] 2.137790e-07 4.275581e-07 0.99999979 [75,] 1.473809e-07 2.947619e-07 0.99999985 [76,] 8.484970e-08 1.696994e-07 0.99999992 [77,] 6.184009e-08 1.236802e-07 0.99999994 [78,] 5.590367e-08 1.118073e-07 0.99999994 [79,] 6.760528e-08 1.352106e-07 0.99999993 [80,] 1.336403e-07 2.672805e-07 0.99999987 [81,] 2.015059e-07 4.030118e-07 0.99999980 [82,] 3.427429e-07 6.854858e-07 0.99999966 [83,] 7.951648e-07 1.590330e-06 0.99999920 [84,] 5.585143e-07 1.117029e-06 0.99999944 [85,] 1.236067e-06 2.472134e-06 0.99999876 [86,] 1.030757e-06 2.061514e-06 0.99999897 [87,] 6.038895e-07 1.207779e-06 0.99999940 [88,] 1.265273e-06 2.530545e-06 0.99999873 [89,] 7.780694e-07 1.556139e-06 0.99999922 [90,] 8.479460e-07 1.695892e-06 0.99999915 [91,] 8.390880e-07 1.678176e-06 0.99999916 [92,] 4.968462e-07 9.936924e-07 0.99999950 [93,] 6.171099e-07 1.234220e-06 0.99999938 [94,] 3.508326e-07 7.016652e-07 0.99999965 [95,] 2.479412e-07 4.958824e-07 0.99999975 [96,] 6.227586e-07 1.245517e-06 0.99999938 [97,] 3.223712e-06 6.447424e-06 0.99999678 [98,] 8.056822e-06 1.611364e-05 0.99999194 [99,] 5.471975e-06 1.094395e-05 0.99999453 [100,] 3.857092e-06 7.714184e-06 0.99999614 [101,] 2.666566e-06 5.333131e-06 0.99999733 [102,] 2.710302e-06 5.420604e-06 0.99999729 [103,] 4.720534e-06 9.441068e-06 0.99999528 [104,] 5.733389e-05 1.146678e-04 0.99994267 [105,] 1.971389e-04 3.942778e-04 0.99980286 [106,] 2.078994e-04 4.157989e-04 0.99979210 [107,] 2.017614e-04 4.035228e-04 0.99979824 [108,] 1.335066e-04 2.670133e-04 0.99986649 [109,] 1.112461e-04 2.224922e-04 0.99988875 [110,] 4.202961e-04 8.405922e-04 0.99957970 [111,] 3.318479e-04 6.636957e-04 0.99966815 [112,] 3.431238e-04 6.862476e-04 0.99965688 [113,] 4.378250e-04 8.756500e-04 0.99956218 [114,] 8.020040e-04 1.604008e-03 0.99919800 [115,] 6.701368e-04 1.340274e-03 0.99932986 [116,] 8.895838e-04 1.779168e-03 0.99911042 [117,] 7.378485e-04 1.475697e-03 0.99926215 [118,] 9.630031e-04 1.926006e-03 0.99903700 [119,] 7.922516e-04 1.584503e-03 0.99920775 [120,] 2.702960e-03 5.405921e-03 0.99729704 [121,] 2.354841e-03 4.709682e-03 0.99764516 [122,] 1.863254e-03 3.726508e-03 0.99813675 [123,] 1.376988e-03 2.753975e-03 0.99862301 [124,] 9.343288e-04 1.868658e-03 0.99906567 [125,] 1.778761e-03 3.557521e-03 0.99822124 [126,] 1.189494e-03 2.378988e-03 0.99881051 [127,] 1.012757e-03 2.025514e-03 0.99898724 [128,] 1.011031e-03 2.022062e-03 0.99898897 [129,] 2.255904e-02 4.511807e-02 0.97744096 [130,] 2.897953e-02 5.795906e-02 0.97102047 [131,] 3.085113e-02 6.170225e-02 0.96914887 [132,] 2.355814e-02 4.711628e-02 0.97644186 [133,] 1.063476e-01 2.126953e-01 0.89365237 [134,] 1.086464e-01 2.172928e-01 0.89135361 [135,] 3.460340e-01 6.920681e-01 0.65396597 [136,] 2.806283e-01 5.612567e-01 0.71937166 [137,] 2.168288e-01 4.336575e-01 0.78317125 [138,] 1.677847e-01 3.355693e-01 0.83221533 [139,] 1.911700e-01 3.823401e-01 0.80882997 [140,] 3.783363e-01 7.566727e-01 0.62166367 [141,] 5.020622e-01 9.958756e-01 0.49793781 [142,] 6.209635e-01 7.580730e-01 0.37903650 [143,] 9.263567e-01 1.472866e-01 0.07364328 [144,] 9.065595e-01 1.868810e-01 0.09344048 [145,] 9.551134e-01 8.977311e-02 0.04488656 [146,] 9.151082e-01 1.697837e-01 0.08489183 > postscript(file="/var/fisher/rcomp/tmp/1dbzz1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2n8bl1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/317sp1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4mbtb1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5473e1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 195 Frequency = 1 1 2 3 4 5 0.0701258623 -0.0514529296 0.0362719818 -0.0725332996 0.1315158840 6 7 8 9 10 0.0706676596 0.2160464438 0.4225534430 0.0227766828 -0.1583029451 11 12 13 14 15 -0.1179025351 -0.2393499326 0.5433445603 0.1135752305 0.2961330853 16 17 18 19 20 0.2951712703 0.4475557243 -0.3109197352 -0.2935133450 0.0374387511 21 22 23 24 25 -0.0584070862 0.0910770005 -0.1171105862 0.1271901579 0.1803200855 26 27 28 29 30 0.0734406974 0.1923698917 0.2040232674 0.3384398352 0.3031297454 31 32 33 34 35 -0.2892991187 -0.1528163535 -0.1870295956 -0.1267568588 -0.0854029670 36 37 38 39 40 -0.2048818481 0.1923074378 0.1791320195 0.4018848174 0.2465487868 41 42 43 44 45 0.3825606085 0.5648101997 -0.2495419163 -0.2085917433 -0.0187574361 46 47 48 49 50 -0.0926866683 -0.0557239090 0.0451515782 -0.3393060640 -0.4292672534 51 52 53 54 55 -0.4109190090 -0.4349002979 -0.4096176794 -0.5524029928 0.1698969863 56 57 58 59 60 0.2015264323 0.1324084202 0.2421741366 0.2206706319 0.3384044733 61 62 63 64 65 -0.3690941287 -0.2734134993 -0.2624328769 -0.2136757077 -0.1308833071 66 67 68 69 70 -0.2867052798 0.0755973788 0.1037763756 0.0859517697 0.0476560691 71 72 73 74 75 0.1417965024 -0.0918238408 0.1113384846 0.0645111014 -0.0458090661 76 77 78 79 80 -0.0873647303 -0.1024155043 -0.0048980470 0.0359645542 -0.1473980021 81 82 83 84 85 -0.1813392122 -0.1370282150 -0.0160901256 0.3076263989 -0.0817867276 86 87 88 89 90 0.1327567692 0.2968729647 0.0603967527 0.0107407408 -0.2171890472 91 92 93 94 95 -0.1366057668 0.2098975616 0.2671478485 0.1433173936 0.2118478480 96 97 98 99 100 0.2409902950 0.1932511329 -0.0299143810 0.1893785791 0.0902200984 101 102 103 104 105 0.0380810421 0.0260995536 0.0214677351 0.4108419344 0.4210545774 106 107 108 109 110 0.4356404043 0.4653584524 0.3123733418 0.3815574820 0.1040295318 111 112 113 114 115 -0.0338821476 0.4097161158 0.2099593094 0.3038102705 0.1955950307 116 117 118 119 120 0.1292696340 0.2745232910 -0.0499362452 0.1089664039 0.2360458305 121 122 123 124 125 0.4496455531 0.0237243230 0.0264153346 0.2897285114 0.3905362482 126 127 128 129 130 0.3809525355 0.3893559944 0.3722594451 0.5821732248 0.2430294327 131 132 133 134 135 0.1992634392 0.1309263925 -0.0499954721 0.3559000408 0.0384285430 136 137 138 139 140 0.0394350255 -0.1440930690 -0.1477572853 0.0425783478 0.2184198005 141 142 143 144 145 0.0927353453 0.1426011132 0.2696295275 0.3148098810 0.4510685199 146 147 148 149 150 0.1368546881 -0.3680690359 -0.1640555410 -0.2386483982 0.1173537192 151 152 153 154 155 0.0642281920 0.0082886324 0.0571992474 0.1462046260 0.1038403026 156 157 158 159 160 0.0003592216 0.2063450760 -0.2493911304 0.0310806775 0.1509187768 161 162 163 164 165 -0.1126607571 -0.0553105168 0.0703788753 0.2030341446 -0.3912657849 166 167 168 169 170 -0.4505415003 -0.2265153348 -0.0946885232 -0.9428134891 -0.2281599826 171 172 173 174 175 -0.1105664221 -0.7954817912 -0.8374265143 -0.8738884760 -0.8686731218 176 177 178 179 180 -0.8342017850 -0.7736445551 0.3565946892 0.2873994732 0.0616521112 181 182 183 184 185 0.2313055231 0.1213822982 0.2786509081 -0.6061113367 -0.6494359886 186 187 188 189 190 -0.6052159039 -0.4315454219 -0.4783835049 -0.4330765767 -0.4207740756 191 192 193 194 195 -0.6495521784 -0.7039654166 0.1798504075 -0.2664820661 -0.5231375976 > postscript(file="/var/fisher/rcomp/tmp/6qfjn1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 195 Frequency = 1 lag(myerror, k = 1) myerror 0 0.0701258623 NA 1 -0.0514529296 0.0701258623 2 0.0362719818 -0.0514529296 3 -0.0725332996 0.0362719818 4 0.1315158840 -0.0725332996 5 0.0706676596 0.1315158840 6 0.2160464438 0.0706676596 7 0.4225534430 0.2160464438 8 0.0227766828 0.4225534430 9 -0.1583029451 0.0227766828 10 -0.1179025351 -0.1583029451 11 -0.2393499326 -0.1179025351 12 0.5433445603 -0.2393499326 13 0.1135752305 0.5433445603 14 0.2961330853 0.1135752305 15 0.2951712703 0.2961330853 16 0.4475557243 0.2951712703 17 -0.3109197352 0.4475557243 18 -0.2935133450 -0.3109197352 19 0.0374387511 -0.2935133450 20 -0.0584070862 0.0374387511 21 0.0910770005 -0.0584070862 22 -0.1171105862 0.0910770005 23 0.1271901579 -0.1171105862 24 0.1803200855 0.1271901579 25 0.0734406974 0.1803200855 26 0.1923698917 0.0734406974 27 0.2040232674 0.1923698917 28 0.3384398352 0.2040232674 29 0.3031297454 0.3384398352 30 -0.2892991187 0.3031297454 31 -0.1528163535 -0.2892991187 32 -0.1870295956 -0.1528163535 33 -0.1267568588 -0.1870295956 34 -0.0854029670 -0.1267568588 35 -0.2048818481 -0.0854029670 36 0.1923074378 -0.2048818481 37 0.1791320195 0.1923074378 38 0.4018848174 0.1791320195 39 0.2465487868 0.4018848174 40 0.3825606085 0.2465487868 41 0.5648101997 0.3825606085 42 -0.2495419163 0.5648101997 43 -0.2085917433 -0.2495419163 44 -0.0187574361 -0.2085917433 45 -0.0926866683 -0.0187574361 46 -0.0557239090 -0.0926866683 47 0.0451515782 -0.0557239090 48 -0.3393060640 0.0451515782 49 -0.4292672534 -0.3393060640 50 -0.4109190090 -0.4292672534 51 -0.4349002979 -0.4109190090 52 -0.4096176794 -0.4349002979 53 -0.5524029928 -0.4096176794 54 0.1698969863 -0.5524029928 55 0.2015264323 0.1698969863 56 0.1324084202 0.2015264323 57 0.2421741366 0.1324084202 58 0.2206706319 0.2421741366 59 0.3384044733 0.2206706319 60 -0.3690941287 0.3384044733 61 -0.2734134993 -0.3690941287 62 -0.2624328769 -0.2734134993 63 -0.2136757077 -0.2624328769 64 -0.1308833071 -0.2136757077 65 -0.2867052798 -0.1308833071 66 0.0755973788 -0.2867052798 67 0.1037763756 0.0755973788 68 0.0859517697 0.1037763756 69 0.0476560691 0.0859517697 70 0.1417965024 0.0476560691 71 -0.0918238408 0.1417965024 72 0.1113384846 -0.0918238408 73 0.0645111014 0.1113384846 74 -0.0458090661 0.0645111014 75 -0.0873647303 -0.0458090661 76 -0.1024155043 -0.0873647303 77 -0.0048980470 -0.1024155043 78 0.0359645542 -0.0048980470 79 -0.1473980021 0.0359645542 80 -0.1813392122 -0.1473980021 81 -0.1370282150 -0.1813392122 82 -0.0160901256 -0.1370282150 83 0.3076263989 -0.0160901256 84 -0.0817867276 0.3076263989 85 0.1327567692 -0.0817867276 86 0.2968729647 0.1327567692 87 0.0603967527 0.2968729647 88 0.0107407408 0.0603967527 89 -0.2171890472 0.0107407408 90 -0.1366057668 -0.2171890472 91 0.2098975616 -0.1366057668 92 0.2671478485 0.2098975616 93 0.1433173936 0.2671478485 94 0.2118478480 0.1433173936 95 0.2409902950 0.2118478480 96 0.1932511329 0.2409902950 97 -0.0299143810 0.1932511329 98 0.1893785791 -0.0299143810 99 0.0902200984 0.1893785791 100 0.0380810421 0.0902200984 101 0.0260995536 0.0380810421 102 0.0214677351 0.0260995536 103 0.4108419344 0.0214677351 104 0.4210545774 0.4108419344 105 0.4356404043 0.4210545774 106 0.4653584524 0.4356404043 107 0.3123733418 0.4653584524 108 0.3815574820 0.3123733418 109 0.1040295318 0.3815574820 110 -0.0338821476 0.1040295318 111 0.4097161158 -0.0338821476 112 0.2099593094 0.4097161158 113 0.3038102705 0.2099593094 114 0.1955950307 0.3038102705 115 0.1292696340 0.1955950307 116 0.2745232910 0.1292696340 117 -0.0499362452 0.2745232910 118 0.1089664039 -0.0499362452 119 0.2360458305 0.1089664039 120 0.4496455531 0.2360458305 121 0.0237243230 0.4496455531 122 0.0264153346 0.0237243230 123 0.2897285114 0.0264153346 124 0.3905362482 0.2897285114 125 0.3809525355 0.3905362482 126 0.3893559944 0.3809525355 127 0.3722594451 0.3893559944 128 0.5821732248 0.3722594451 129 0.2430294327 0.5821732248 130 0.1992634392 0.2430294327 131 0.1309263925 0.1992634392 132 -0.0499954721 0.1309263925 133 0.3559000408 -0.0499954721 134 0.0384285430 0.3559000408 135 0.0394350255 0.0384285430 136 -0.1440930690 0.0394350255 137 -0.1477572853 -0.1440930690 138 0.0425783478 -0.1477572853 139 0.2184198005 0.0425783478 140 0.0927353453 0.2184198005 141 0.1426011132 0.0927353453 142 0.2696295275 0.1426011132 143 0.3148098810 0.2696295275 144 0.4510685199 0.3148098810 145 0.1368546881 0.4510685199 146 -0.3680690359 0.1368546881 147 -0.1640555410 -0.3680690359 148 -0.2386483982 -0.1640555410 149 0.1173537192 -0.2386483982 150 0.0642281920 0.1173537192 151 0.0082886324 0.0642281920 152 0.0571992474 0.0082886324 153 0.1462046260 0.0571992474 154 0.1038403026 0.1462046260 155 0.0003592216 0.1038403026 156 0.2063450760 0.0003592216 157 -0.2493911304 0.2063450760 158 0.0310806775 -0.2493911304 159 0.1509187768 0.0310806775 160 -0.1126607571 0.1509187768 161 -0.0553105168 -0.1126607571 162 0.0703788753 -0.0553105168 163 0.2030341446 0.0703788753 164 -0.3912657849 0.2030341446 165 -0.4505415003 -0.3912657849 166 -0.2265153348 -0.4505415003 167 -0.0946885232 -0.2265153348 168 -0.9428134891 -0.0946885232 169 -0.2281599826 -0.9428134891 170 -0.1105664221 -0.2281599826 171 -0.7954817912 -0.1105664221 172 -0.8374265143 -0.7954817912 173 -0.8738884760 -0.8374265143 174 -0.8686731218 -0.8738884760 175 -0.8342017850 -0.8686731218 176 -0.7736445551 -0.8342017850 177 0.3565946892 -0.7736445551 178 0.2873994732 0.3565946892 179 0.0616521112 0.2873994732 180 0.2313055231 0.0616521112 181 0.1213822982 0.2313055231 182 0.2786509081 0.1213822982 183 -0.6061113367 0.2786509081 184 -0.6494359886 -0.6061113367 185 -0.6052159039 -0.6494359886 186 -0.4315454219 -0.6052159039 187 -0.4783835049 -0.4315454219 188 -0.4330765767 -0.4783835049 189 -0.4207740756 -0.4330765767 190 -0.6495521784 -0.4207740756 191 -0.7039654166 -0.6495521784 192 0.1798504075 -0.7039654166 193 -0.2664820661 0.1798504075 194 -0.5231375976 -0.2664820661 195 NA -0.5231375976 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.0514529296 0.0701258623 [2,] 0.0362719818 -0.0514529296 [3,] -0.0725332996 0.0362719818 [4,] 0.1315158840 -0.0725332996 [5,] 0.0706676596 0.1315158840 [6,] 0.2160464438 0.0706676596 [7,] 0.4225534430 0.2160464438 [8,] 0.0227766828 0.4225534430 [9,] -0.1583029451 0.0227766828 [10,] -0.1179025351 -0.1583029451 [11,] -0.2393499326 -0.1179025351 [12,] 0.5433445603 -0.2393499326 [13,] 0.1135752305 0.5433445603 [14,] 0.2961330853 0.1135752305 [15,] 0.2951712703 0.2961330853 [16,] 0.4475557243 0.2951712703 [17,] -0.3109197352 0.4475557243 [18,] -0.2935133450 -0.3109197352 [19,] 0.0374387511 -0.2935133450 [20,] -0.0584070862 0.0374387511 [21,] 0.0910770005 -0.0584070862 [22,] -0.1171105862 0.0910770005 [23,] 0.1271901579 -0.1171105862 [24,] 0.1803200855 0.1271901579 [25,] 0.0734406974 0.1803200855 [26,] 0.1923698917 0.0734406974 [27,] 0.2040232674 0.1923698917 [28,] 0.3384398352 0.2040232674 [29,] 0.3031297454 0.3384398352 [30,] -0.2892991187 0.3031297454 [31,] -0.1528163535 -0.2892991187 [32,] -0.1870295956 -0.1528163535 [33,] -0.1267568588 -0.1870295956 [34,] -0.0854029670 -0.1267568588 [35,] -0.2048818481 -0.0854029670 [36,] 0.1923074378 -0.2048818481 [37,] 0.1791320195 0.1923074378 [38,] 0.4018848174 0.1791320195 [39,] 0.2465487868 0.4018848174 [40,] 0.3825606085 0.2465487868 [41,] 0.5648101997 0.3825606085 [42,] -0.2495419163 0.5648101997 [43,] -0.2085917433 -0.2495419163 [44,] -0.0187574361 -0.2085917433 [45,] -0.0926866683 -0.0187574361 [46,] -0.0557239090 -0.0926866683 [47,] 0.0451515782 -0.0557239090 [48,] -0.3393060640 0.0451515782 [49,] -0.4292672534 -0.3393060640 [50,] -0.4109190090 -0.4292672534 [51,] -0.4349002979 -0.4109190090 [52,] -0.4096176794 -0.4349002979 [53,] -0.5524029928 -0.4096176794 [54,] 0.1698969863 -0.5524029928 [55,] 0.2015264323 0.1698969863 [56,] 0.1324084202 0.2015264323 [57,] 0.2421741366 0.1324084202 [58,] 0.2206706319 0.2421741366 [59,] 0.3384044733 0.2206706319 [60,] -0.3690941287 0.3384044733 [61,] -0.2734134993 -0.3690941287 [62,] -0.2624328769 -0.2734134993 [63,] -0.2136757077 -0.2624328769 [64,] -0.1308833071 -0.2136757077 [65,] -0.2867052798 -0.1308833071 [66,] 0.0755973788 -0.2867052798 [67,] 0.1037763756 0.0755973788 [68,] 0.0859517697 0.1037763756 [69,] 0.0476560691 0.0859517697 [70,] 0.1417965024 0.0476560691 [71,] -0.0918238408 0.1417965024 [72,] 0.1113384846 -0.0918238408 [73,] 0.0645111014 0.1113384846 [74,] -0.0458090661 0.0645111014 [75,] -0.0873647303 -0.0458090661 [76,] -0.1024155043 -0.0873647303 [77,] -0.0048980470 -0.1024155043 [78,] 0.0359645542 -0.0048980470 [79,] -0.1473980021 0.0359645542 [80,] -0.1813392122 -0.1473980021 [81,] -0.1370282150 -0.1813392122 [82,] -0.0160901256 -0.1370282150 [83,] 0.3076263989 -0.0160901256 [84,] -0.0817867276 0.3076263989 [85,] 0.1327567692 -0.0817867276 [86,] 0.2968729647 0.1327567692 [87,] 0.0603967527 0.2968729647 [88,] 0.0107407408 0.0603967527 [89,] -0.2171890472 0.0107407408 [90,] -0.1366057668 -0.2171890472 [91,] 0.2098975616 -0.1366057668 [92,] 0.2671478485 0.2098975616 [93,] 0.1433173936 0.2671478485 [94,] 0.2118478480 0.1433173936 [95,] 0.2409902950 0.2118478480 [96,] 0.1932511329 0.2409902950 [97,] -0.0299143810 0.1932511329 [98,] 0.1893785791 -0.0299143810 [99,] 0.0902200984 0.1893785791 [100,] 0.0380810421 0.0902200984 [101,] 0.0260995536 0.0380810421 [102,] 0.0214677351 0.0260995536 [103,] 0.4108419344 0.0214677351 [104,] 0.4210545774 0.4108419344 [105,] 0.4356404043 0.4210545774 [106,] 0.4653584524 0.4356404043 [107,] 0.3123733418 0.4653584524 [108,] 0.3815574820 0.3123733418 [109,] 0.1040295318 0.3815574820 [110,] -0.0338821476 0.1040295318 [111,] 0.4097161158 -0.0338821476 [112,] 0.2099593094 0.4097161158 [113,] 0.3038102705 0.2099593094 [114,] 0.1955950307 0.3038102705 [115,] 0.1292696340 0.1955950307 [116,] 0.2745232910 0.1292696340 [117,] -0.0499362452 0.2745232910 [118,] 0.1089664039 -0.0499362452 [119,] 0.2360458305 0.1089664039 [120,] 0.4496455531 0.2360458305 [121,] 0.0237243230 0.4496455531 [122,] 0.0264153346 0.0237243230 [123,] 0.2897285114 0.0264153346 [124,] 0.3905362482 0.2897285114 [125,] 0.3809525355 0.3905362482 [126,] 0.3893559944 0.3809525355 [127,] 0.3722594451 0.3893559944 [128,] 0.5821732248 0.3722594451 [129,] 0.2430294327 0.5821732248 [130,] 0.1992634392 0.2430294327 [131,] 0.1309263925 0.1992634392 [132,] -0.0499954721 0.1309263925 [133,] 0.3559000408 -0.0499954721 [134,] 0.0384285430 0.3559000408 [135,] 0.0394350255 0.0384285430 [136,] -0.1440930690 0.0394350255 [137,] -0.1477572853 -0.1440930690 [138,] 0.0425783478 -0.1477572853 [139,] 0.2184198005 0.0425783478 [140,] 0.0927353453 0.2184198005 [141,] 0.1426011132 0.0927353453 [142,] 0.2696295275 0.1426011132 [143,] 0.3148098810 0.2696295275 [144,] 0.4510685199 0.3148098810 [145,] 0.1368546881 0.4510685199 [146,] -0.3680690359 0.1368546881 [147,] -0.1640555410 -0.3680690359 [148,] -0.2386483982 -0.1640555410 [149,] 0.1173537192 -0.2386483982 [150,] 0.0642281920 0.1173537192 [151,] 0.0082886324 0.0642281920 [152,] 0.0571992474 0.0082886324 [153,] 0.1462046260 0.0571992474 [154,] 0.1038403026 0.1462046260 [155,] 0.0003592216 0.1038403026 [156,] 0.2063450760 0.0003592216 [157,] -0.2493911304 0.2063450760 [158,] 0.0310806775 -0.2493911304 [159,] 0.1509187768 0.0310806775 [160,] -0.1126607571 0.1509187768 [161,] -0.0553105168 -0.1126607571 [162,] 0.0703788753 -0.0553105168 [163,] 0.2030341446 0.0703788753 [164,] -0.3912657849 0.2030341446 [165,] -0.4505415003 -0.3912657849 [166,] -0.2265153348 -0.4505415003 [167,] -0.0946885232 -0.2265153348 [168,] -0.9428134891 -0.0946885232 [169,] -0.2281599826 -0.9428134891 [170,] -0.1105664221 -0.2281599826 [171,] -0.7954817912 -0.1105664221 [172,] -0.8374265143 -0.7954817912 [173,] -0.8738884760 -0.8374265143 [174,] -0.8686731218 -0.8738884760 [175,] -0.8342017850 -0.8686731218 [176,] -0.7736445551 -0.8342017850 [177,] 0.3565946892 -0.7736445551 [178,] 0.2873994732 0.3565946892 [179,] 0.0616521112 0.2873994732 [180,] 0.2313055231 0.0616521112 [181,] 0.1213822982 0.2313055231 [182,] 0.2786509081 0.1213822982 [183,] -0.6061113367 0.2786509081 [184,] -0.6494359886 -0.6061113367 [185,] -0.6052159039 -0.6494359886 [186,] -0.4315454219 -0.6052159039 [187,] -0.4783835049 -0.4315454219 [188,] -0.4330765767 -0.4783835049 [189,] -0.4207740756 -0.4330765767 [190,] -0.6495521784 -0.4207740756 [191,] -0.7039654166 -0.6495521784 [192,] 0.1798504075 -0.7039654166 [193,] -0.2664820661 0.1798504075 [194,] -0.5231375976 -0.2664820661 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.0514529296 0.0701258623 2 0.0362719818 -0.0514529296 3 -0.0725332996 0.0362719818 4 0.1315158840 -0.0725332996 5 0.0706676596 0.1315158840 6 0.2160464438 0.0706676596 7 0.4225534430 0.2160464438 8 0.0227766828 0.4225534430 9 -0.1583029451 0.0227766828 10 -0.1179025351 -0.1583029451 11 -0.2393499326 -0.1179025351 12 0.5433445603 -0.2393499326 13 0.1135752305 0.5433445603 14 0.2961330853 0.1135752305 15 0.2951712703 0.2961330853 16 0.4475557243 0.2951712703 17 -0.3109197352 0.4475557243 18 -0.2935133450 -0.3109197352 19 0.0374387511 -0.2935133450 20 -0.0584070862 0.0374387511 21 0.0910770005 -0.0584070862 22 -0.1171105862 0.0910770005 23 0.1271901579 -0.1171105862 24 0.1803200855 0.1271901579 25 0.0734406974 0.1803200855 26 0.1923698917 0.0734406974 27 0.2040232674 0.1923698917 28 0.3384398352 0.2040232674 29 0.3031297454 0.3384398352 30 -0.2892991187 0.3031297454 31 -0.1528163535 -0.2892991187 32 -0.1870295956 -0.1528163535 33 -0.1267568588 -0.1870295956 34 -0.0854029670 -0.1267568588 35 -0.2048818481 -0.0854029670 36 0.1923074378 -0.2048818481 37 0.1791320195 0.1923074378 38 0.4018848174 0.1791320195 39 0.2465487868 0.4018848174 40 0.3825606085 0.2465487868 41 0.5648101997 0.3825606085 42 -0.2495419163 0.5648101997 43 -0.2085917433 -0.2495419163 44 -0.0187574361 -0.2085917433 45 -0.0926866683 -0.0187574361 46 -0.0557239090 -0.0926866683 47 0.0451515782 -0.0557239090 48 -0.3393060640 0.0451515782 49 -0.4292672534 -0.3393060640 50 -0.4109190090 -0.4292672534 51 -0.4349002979 -0.4109190090 52 -0.4096176794 -0.4349002979 53 -0.5524029928 -0.4096176794 54 0.1698969863 -0.5524029928 55 0.2015264323 0.1698969863 56 0.1324084202 0.2015264323 57 0.2421741366 0.1324084202 58 0.2206706319 0.2421741366 59 0.3384044733 0.2206706319 60 -0.3690941287 0.3384044733 61 -0.2734134993 -0.3690941287 62 -0.2624328769 -0.2734134993 63 -0.2136757077 -0.2624328769 64 -0.1308833071 -0.2136757077 65 -0.2867052798 -0.1308833071 66 0.0755973788 -0.2867052798 67 0.1037763756 0.0755973788 68 0.0859517697 0.1037763756 69 0.0476560691 0.0859517697 70 0.1417965024 0.0476560691 71 -0.0918238408 0.1417965024 72 0.1113384846 -0.0918238408 73 0.0645111014 0.1113384846 74 -0.0458090661 0.0645111014 75 -0.0873647303 -0.0458090661 76 -0.1024155043 -0.0873647303 77 -0.0048980470 -0.1024155043 78 0.0359645542 -0.0048980470 79 -0.1473980021 0.0359645542 80 -0.1813392122 -0.1473980021 81 -0.1370282150 -0.1813392122 82 -0.0160901256 -0.1370282150 83 0.3076263989 -0.0160901256 84 -0.0817867276 0.3076263989 85 0.1327567692 -0.0817867276 86 0.2968729647 0.1327567692 87 0.0603967527 0.2968729647 88 0.0107407408 0.0603967527 89 -0.2171890472 0.0107407408 90 -0.1366057668 -0.2171890472 91 0.2098975616 -0.1366057668 92 0.2671478485 0.2098975616 93 0.1433173936 0.2671478485 94 0.2118478480 0.1433173936 95 0.2409902950 0.2118478480 96 0.1932511329 0.2409902950 97 -0.0299143810 0.1932511329 98 0.1893785791 -0.0299143810 99 0.0902200984 0.1893785791 100 0.0380810421 0.0902200984 101 0.0260995536 0.0380810421 102 0.0214677351 0.0260995536 103 0.4108419344 0.0214677351 104 0.4210545774 0.4108419344 105 0.4356404043 0.4210545774 106 0.4653584524 0.4356404043 107 0.3123733418 0.4653584524 108 0.3815574820 0.3123733418 109 0.1040295318 0.3815574820 110 -0.0338821476 0.1040295318 111 0.4097161158 -0.0338821476 112 0.2099593094 0.4097161158 113 0.3038102705 0.2099593094 114 0.1955950307 0.3038102705 115 0.1292696340 0.1955950307 116 0.2745232910 0.1292696340 117 -0.0499362452 0.2745232910 118 0.1089664039 -0.0499362452 119 0.2360458305 0.1089664039 120 0.4496455531 0.2360458305 121 0.0237243230 0.4496455531 122 0.0264153346 0.0237243230 123 0.2897285114 0.0264153346 124 0.3905362482 0.2897285114 125 0.3809525355 0.3905362482 126 0.3893559944 0.3809525355 127 0.3722594451 0.3893559944 128 0.5821732248 0.3722594451 129 0.2430294327 0.5821732248 130 0.1992634392 0.2430294327 131 0.1309263925 0.1992634392 132 -0.0499954721 0.1309263925 133 0.3559000408 -0.0499954721 134 0.0384285430 0.3559000408 135 0.0394350255 0.0384285430 136 -0.1440930690 0.0394350255 137 -0.1477572853 -0.1440930690 138 0.0425783478 -0.1477572853 139 0.2184198005 0.0425783478 140 0.0927353453 0.2184198005 141 0.1426011132 0.0927353453 142 0.2696295275 0.1426011132 143 0.3148098810 0.2696295275 144 0.4510685199 0.3148098810 145 0.1368546881 0.4510685199 146 -0.3680690359 0.1368546881 147 -0.1640555410 -0.3680690359 148 -0.2386483982 -0.1640555410 149 0.1173537192 -0.2386483982 150 0.0642281920 0.1173537192 151 0.0082886324 0.0642281920 152 0.0571992474 0.0082886324 153 0.1462046260 0.0571992474 154 0.1038403026 0.1462046260 155 0.0003592216 0.1038403026 156 0.2063450760 0.0003592216 157 -0.2493911304 0.2063450760 158 0.0310806775 -0.2493911304 159 0.1509187768 0.0310806775 160 -0.1126607571 0.1509187768 161 -0.0553105168 -0.1126607571 162 0.0703788753 -0.0553105168 163 0.2030341446 0.0703788753 164 -0.3912657849 0.2030341446 165 -0.4505415003 -0.3912657849 166 -0.2265153348 -0.4505415003 167 -0.0946885232 -0.2265153348 168 -0.9428134891 -0.0946885232 169 -0.2281599826 -0.9428134891 170 -0.1105664221 -0.2281599826 171 -0.7954817912 -0.1105664221 172 -0.8374265143 -0.7954817912 173 -0.8738884760 -0.8374265143 174 -0.8686731218 -0.8738884760 175 -0.8342017850 -0.8686731218 176 -0.7736445551 -0.8342017850 177 0.3565946892 -0.7736445551 178 0.2873994732 0.3565946892 179 0.0616521112 0.2873994732 180 0.2313055231 0.0616521112 181 0.1213822982 0.2313055231 182 0.2786509081 0.1213822982 183 -0.6061113367 0.2786509081 184 -0.6494359886 -0.6061113367 185 -0.6052159039 -0.6494359886 186 -0.4315454219 -0.6052159039 187 -0.4783835049 -0.4315454219 188 -0.4330765767 -0.4783835049 189 -0.4207740756 -0.4330765767 190 -0.6495521784 -0.4207740756 191 -0.7039654166 -0.6495521784 192 0.1798504075 -0.7039654166 193 -0.2664820661 0.1798504075 194 -0.5231375976 -0.2664820661 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/726tc1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/81t131386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9ey271386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/101q7g1386423751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/11f7191386423751.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,signif(mysum$coefficients[i,1],6)) + a<-table.element(a, signif(mysum$coefficients[i,2],6)) + a<-table.element(a, signif(mysum$coefficients[i,3],4)) + a<-table.element(a, signif(mysum$coefficients[i,4],6)) + a<-table.element(a, signif(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/12fo5r1386423751.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, signif(sqrt(mysum$r.squared),6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, signif(mysum$r.squared,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, signif(mysum$adj.r.squared,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[1],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[2],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[3],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, signif(mysum$sigma,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, signif(sum(myerror*myerror),6)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/13p5tv1386423751.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,signif(x[i],6)) + a<-table.element(a,signif(x[i]-mysum$resid[i],6)) + a<-table.element(a,signif(mysum$resid[i],6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/140mpt1386423751.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6)) + a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6)) + a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6)) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/fisher/rcomp/tmp/155x9s1386423751.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,signif(numsignificant1,6)) + a<-table.element(a,signif(numsignificant1/numgqtests,6)) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,signif(numsignificant5,6)) + a<-table.element(a,signif(numsignificant5/numgqtests,6)) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,signif(numsignificant10,6)) + a<-table.element(a,signif(numsignificant10/numgqtests,6)) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/fisher/rcomp/tmp/16xxsq1386423751.tab") + } > > try(system("convert tmp/1dbzz1386423751.ps tmp/1dbzz1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/2n8bl1386423751.ps tmp/2n8bl1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/317sp1386423751.ps tmp/317sp1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/4mbtb1386423751.ps tmp/4mbtb1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/5473e1386423751.ps tmp/5473e1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/6qfjn1386423751.ps tmp/6qfjn1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/726tc1386423751.ps tmp/726tc1386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/81t131386423751.ps tmp/81t131386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/9ey271386423751.ps tmp/9ey271386423751.png",intern=TRUE)) character(0) > try(system("convert tmp/101q7g1386423751.ps tmp/101q7g1386423751.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 36.044 5.652 41.768