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(119.992 + ,157.302 + ,74.997 + ,0.00784 + ,0.00007 + ,0.0037 + ,0.00554 + ,0.01109 + ,0.04374 + ,0.426 + ,0.02182 + ,0.0313 + ,0.02971 + ,0.06545 + ,0.02211 + ,21.033 + ,1 + ,0.414783 + ,0.815285 + ,-4.813031 + ,0.266482 + ,2.301442 + ,122.4 + ,148.65 + ,113.819 + ,0.00968 + ,0.00008 + ,0.00465 + ,0.00696 + ,0.01394 + ,0.06134 + ,0.626 + ,0.03134 + ,0.04518 + ,0.04368 + ,0.09403 + ,0.01929 + ,19.085 + ,1 + ,0.458359 + ,0.819521 + ,-4.075192 + ,0.33559 + ,2.486855 + ,116.682 + ,131.111 + ,111.555 + ,0.0105 + ,0.00009 + ,0.00544 + ,0.00781 + ,0.01633 + ,0.05233 + ,0.482 + ,0.02757 + ,0.03858 + ,0.0359 + ,0.0827 + ,0.01309 + ,20.651 + ,1 + ,0.429895 + ,0.825288 + ,-4.443179 + ,0.311173 + ,2.342259 + ,116.676 + ,137.871 + ,111.366 + ,0.00997 + ,0.00009 + ,0.00502 + ,0.00698 + ,0.01505 + ,0.05492 + ,0.517 + ,0.02924 + ,0.04005 + ,0.03772 + ,0.08771 + ,0.01353 + ,20.644 + ,1 + ,0.434969 + ,0.819235 + ,-4.117501 + ,0.334147 + ,2.405554 + ,116.014 + 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+ ,230.978 + ,94.261 + ,0.00459 + ,0.00003 + ,0.00263 + ,0.00259 + ,0.0079 + ,0.04087 + ,0.405 + ,0.02336 + ,0.02498 + ,0.02745 + ,0.07008 + ,0.02764 + ,19.517 + ,0 + ,0.448439 + ,0.657899 + ,-6.538586 + ,0.121952 + ,2.657476 + ,209.516 + ,253.017 + ,89.488 + ,0.00564 + ,0.00003 + ,0.00331 + ,0.00292 + ,0.00994 + ,0.02751 + ,0.263 + ,0.01604 + ,0.01657 + ,0.01879 + ,0.04812 + ,0.0181 + ,19.147 + ,0 + ,0.431674 + ,0.683244 + ,-6.195325 + ,0.129303 + ,2.784312 + ,174.688 + ,240.005 + ,74.287 + ,0.0136 + ,0.00008 + ,0.00624 + ,0.00564 + ,0.01873 + ,0.02308 + ,0.256 + ,0.01268 + ,0.01365 + ,0.01667 + ,0.03804 + ,0.10715 + ,17.883 + ,0 + ,0.407567 + ,0.655683 + ,-6.787197 + ,0.158453 + ,2.679772 + ,198.764 + ,396.961 + ,74.904 + ,0.0074 + ,0.00004 + ,0.0037 + ,0.0039 + ,0.01109 + ,0.02296 + ,0.241 + ,0.01265 + ,0.01321 + ,0.01588 + ,0.03794 + ,0.07223 + ,19.02 + ,0 + ,0.451221 + ,0.643956 + ,-6.744577 + ,0.207454 + ,2.138608 + ,214.289 + ,260.277 + ,77.973 + ,0.00567 + ,0.00003 + ,0.00295 + ,0.00317 + ,0.00885 + ,0.01884 + ,0.19 + ,0.01026 + ,0.01161 + ,0.01373 + ,0.03078 + ,0.04398 + ,21.209 + ,0 + ,0.462803 + ,0.664357 + ,-5.724056 + ,0.190667 + ,2.555477) + ,dim=c(22 + ,195) + ,dimnames=list(c('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' + ,'MDVP:APQ' + ,'Shimmer:DDA' + ,'NHR' + ,'HNR' + ,'status' + ,'RPDE' + ,'DFA' + ,'spread1' + ,'spread2' + ,'D2') + ,1:195)) > y <- array(NA,dim=c(22,195),dimnames=list(c('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','MDVP:APQ','Shimmer:DDA','NHR','HNR','status','RPDE','DFA','spread1','spread2','D2'),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 MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) MDVP:Jitter(Abs) 1 119.992 157.302 74.997 0.00784 7.0e-05 2 122.400 148.650 113.819 0.00968 8.0e-05 3 116.682 131.111 111.555 0.01050 9.0e-05 4 116.676 137.871 111.366 0.00997 9.0e-05 5 116.014 141.781 110.655 0.01284 1.1e-04 6 120.552 131.162 113.787 0.00968 8.0e-05 7 120.267 137.244 114.820 0.00333 3.0e-05 8 107.332 113.840 104.315 0.00290 3.0e-05 9 95.730 132.068 91.754 0.00551 6.0e-05 10 95.056 120.103 91.226 0.00532 6.0e-05 11 88.333 112.240 84.072 0.00505 6.0e-05 12 91.904 115.871 86.292 0.00540 6.0e-05 13 136.926 159.866 131.276 0.00293 2.0e-05 14 139.173 179.139 76.556 0.00390 3.0e-05 15 152.845 163.305 75.836 0.00294 2.0e-05 16 142.167 217.455 83.159 0.00369 3.0e-05 17 144.188 349.259 82.764 0.00544 4.0e-05 18 168.778 232.181 75.603 0.00718 4.0e-05 19 153.046 175.829 68.623 0.00742 5.0e-05 20 156.405 189.398 142.822 0.00768 5.0e-05 21 153.848 165.738 65.782 0.00840 5.0e-05 22 153.880 172.860 78.128 0.00480 3.0e-05 23 167.930 193.221 79.068 0.00442 3.0e-05 24 173.917 192.735 86.180 0.00476 3.0e-05 25 163.656 200.841 76.779 0.00742 5.0e-05 26 104.400 206.002 77.968 0.00633 6.0e-05 27 171.041 208.313 75.501 0.00455 3.0e-05 28 146.845 208.701 81.737 0.00496 3.0e-05 29 155.358 227.383 80.055 0.00310 2.0e-05 30 162.568 198.346 77.630 0.00502 3.0e-05 31 197.076 206.896 192.055 0.00289 1.0e-05 32 199.228 209.512 192.091 0.00241 1.0e-05 33 198.383 215.203 193.104 0.00212 1.0e-05 34 202.266 211.604 197.079 0.00180 9.0e-06 35 203.184 211.526 196.160 0.00178 9.0e-06 36 201.464 210.565 195.708 0.00198 1.0e-05 37 177.876 192.921 168.013 0.00411 2.0e-05 38 176.170 185.604 163.564 0.00369 2.0e-05 39 180.198 201.249 175.456 0.00284 2.0e-05 40 187.733 202.324 173.015 0.00316 2.0e-05 41 186.163 197.724 177.584 0.00298 2.0e-05 42 184.055 196.537 166.977 0.00258 1.0e-05 43 237.226 247.326 225.227 0.00298 1.0e-05 44 241.404 248.834 232.483 0.00281 1.0e-05 45 243.439 250.912 232.435 0.00210 9.0e-06 46 242.852 255.034 227.911 0.00225 9.0e-06 47 245.510 262.090 231.848 0.00235 1.0e-05 48 252.455 261.487 182.786 0.00185 7.0e-06 49 122.188 128.611 115.765 0.00524 4.0e-05 50 122.964 130.049 114.676 0.00428 3.0e-05 51 124.445 135.069 117.495 0.00431 3.0e-05 52 126.344 134.231 112.773 0.00448 4.0e-05 53 128.001 138.052 122.080 0.00436 3.0e-05 54 129.336 139.867 118.604 0.00490 4.0e-05 55 108.807 134.656 102.874 0.00761 7.0e-05 56 109.860 126.358 104.437 0.00874 8.0e-05 57 110.417 131.067 103.370 0.00784 7.0e-05 58 117.274 129.916 110.402 0.00752 6.0e-05 59 116.879 131.897 108.153 0.00788 7.0e-05 60 114.847 271.314 104.680 0.00867 8.0e-05 61 209.144 237.494 109.379 0.00282 1.0e-05 62 223.365 238.987 98.664 0.00264 1.0e-05 63 222.236 231.345 205.495 0.00266 1.0e-05 64 228.832 234.619 223.634 0.00296 1.0e-05 65 229.401 252.221 221.156 0.00205 9.0e-06 66 228.969 239.541 113.201 0.00238 1.0e-05 67 140.341 159.774 67.021 0.00817 6.0e-05 68 136.969 166.607 66.004 0.00923 7.0e-05 69 143.533 162.215 65.809 0.01101 8.0e-05 70 148.090 162.824 67.343 0.00762 5.0e-05 71 142.729 162.408 65.476 0.00831 6.0e-05 72 136.358 176.595 65.750 0.00971 7.0e-05 73 120.080 139.710 111.208 0.00405 3.0e-05 74 112.014 588.518 107.024 0.00533 5.0e-05 75 110.793 128.101 107.316 0.00494 4.0e-05 76 110.707 122.611 105.007 0.00516 5.0e-05 77 112.876 148.826 106.981 0.00500 4.0e-05 78 110.568 125.394 106.821 0.00462 4.0e-05 79 95.385 102.145 90.264 0.00608 6.0e-05 80 100.770 115.697 85.545 0.01038 1.0e-04 81 96.106 108.664 84.510 0.00694 7.0e-05 82 95.605 107.715 87.549 0.00702 7.0e-05 83 100.960 110.019 95.628 0.00606 6.0e-05 84 98.804 102.305 87.804 0.00432 4.0e-05 85 176.858 205.560 75.344 0.00747 4.0e-05 86 180.978 200.125 155.495 0.00406 2.0e-05 87 178.222 202.450 141.047 0.00321 2.0e-05 88 176.281 227.381 125.610 0.00520 3.0e-05 89 173.898 211.350 74.677 0.00448 3.0e-05 90 179.711 225.930 144.878 0.00709 4.0e-05 91 166.605 206.008 78.032 0.00742 4.0e-05 92 151.955 163.335 147.226 0.00419 3.0e-05 93 148.272 164.989 142.299 0.00459 3.0e-05 94 152.125 161.469 76.596 0.00382 3.0e-05 95 157.821 172.975 68.401 0.00358 2.0e-05 96 157.447 163.267 149.605 0.00369 2.0e-05 97 159.116 168.913 144.811 0.00342 2.0e-05 98 125.036 143.946 116.187 0.01280 1.0e-04 99 125.791 140.557 96.206 0.01378 1.1e-04 100 126.512 141.756 99.770 0.01936 1.5e-04 101 125.641 141.068 116.346 0.03316 2.6e-04 102 128.451 150.449 75.632 0.01551 1.2e-04 103 139.224 586.567 66.157 0.03011 2.2e-04 104 150.258 154.609 75.349 0.00248 2.0e-05 105 154.003 160.267 128.621 0.00183 1.0e-05 106 149.689 160.368 133.608 0.00257 2.0e-05 107 155.078 163.736 144.148 0.00168 1.0e-05 108 151.884 157.765 133.751 0.00258 2.0e-05 109 151.989 157.339 132.857 0.00174 1.0e-05 110 193.030 208.900 80.297 0.00766 4.0e-05 111 200.714 223.982 89.686 0.00621 3.0e-05 112 208.519 220.315 199.020 0.00609 3.0e-05 113 204.664 221.300 189.621 0.00841 4.0e-05 114 210.141 232.706 185.258 0.00534 3.0e-05 115 206.327 226.355 92.020 0.00495 2.0e-05 116 151.872 492.892 69.085 0.00856 6.0e-05 117 158.219 442.557 71.948 0.00476 3.0e-05 118 170.756 450.247 79.032 0.00555 3.0e-05 119 178.285 442.824 82.063 0.00462 3.0e-05 120 217.116 233.481 93.978 0.00404 2.0e-05 121 128.940 479.697 88.251 0.00581 5.0e-05 122 176.824 215.293 83.961 0.00460 3.0e-05 123 138.190 203.522 83.340 0.00704 5.0e-05 124 182.018 197.173 79.187 0.00842 5.0e-05 125 156.239 195.107 79.820 0.00694 4.0e-05 126 145.174 198.109 80.637 0.00733 5.0e-05 127 138.145 197.238 81.114 0.00544 4.0e-05 128 166.888 198.966 79.512 0.00638 4.0e-05 129 119.031 127.533 109.216 0.00440 4.0e-05 130 120.078 126.632 105.667 0.00270 2.0e-05 131 120.289 128.143 100.209 0.00492 4.0e-05 132 120.256 125.306 104.773 0.00407 3.0e-05 133 119.056 125.213 86.795 0.00346 3.0e-05 134 118.747 123.723 109.836 0.00331 3.0e-05 135 106.516 112.777 93.105 0.00589 6.0e-05 136 110.453 127.611 105.554 0.00494 4.0e-05 137 113.400 133.344 107.816 0.00451 4.0e-05 138 113.166 130.270 100.673 0.00502 4.0e-05 139 112.239 126.609 104.095 0.00472 4.0e-05 140 116.150 131.731 109.815 0.00381 3.0e-05 141 170.368 268.796 79.543 0.00571 3.0e-05 142 208.083 253.792 91.802 0.00757 4.0e-05 143 198.458 219.290 148.691 0.00376 2.0e-05 144 202.805 231.508 86.232 0.00370 2.0e-05 145 202.544 241.350 164.168 0.00254 1.0e-05 146 223.361 263.872 87.638 0.00352 2.0e-05 147 169.774 191.759 151.451 0.01568 9.0e-05 148 183.520 216.814 161.340 0.01466 8.0e-05 149 188.620 216.302 165.982 0.01719 9.0e-05 150 202.632 565.740 177.258 0.01627 8.0e-05 151 186.695 211.961 149.442 0.01872 1.0e-04 152 192.818 224.429 168.793 0.03107 1.6e-04 153 198.116 233.099 174.478 0.02714 1.4e-04 154 121.345 139.644 98.250 0.00684 6.0e-05 155 119.100 128.442 88.833 0.00692 6.0e-05 156 117.870 127.349 95.654 0.00647 5.0e-05 157 122.336 142.369 94.794 0.00727 6.0e-05 158 117.963 134.209 100.757 0.01813 1.5e-04 159 126.144 154.284 97.543 0.00975 8.0e-05 160 127.930 138.752 112.173 0.00605 5.0e-05 161 114.238 124.393 77.022 0.00581 5.0e-05 162 115.322 135.738 107.802 0.00619 5.0e-05 163 114.554 126.778 91.121 0.00651 6.0e-05 164 112.150 131.669 97.527 0.00519 5.0e-05 165 102.273 142.830 85.902 0.00907 9.0e-05 166 236.200 244.663 102.137 0.00277 1.0e-05 167 237.323 243.709 229.256 0.00303 1.0e-05 168 260.105 264.919 237.303 0.00339 1.0e-05 169 197.569 217.627 90.794 0.00803 4.0e-05 170 240.301 245.135 219.783 0.00517 2.0e-05 171 244.990 272.210 239.170 0.00451 2.0e-05 172 112.547 133.374 105.715 0.00355 3.0e-05 173 110.739 113.597 100.139 0.00356 3.0e-05 174 113.715 116.443 96.913 0.00349 3.0e-05 175 117.004 144.466 99.923 0.00353 3.0e-05 176 115.380 123.109 108.634 0.00332 3.0e-05 177 116.388 129.038 108.970 0.00346 3.0e-05 178 151.737 190.204 129.859 0.00314 2.0e-05 179 148.790 158.359 138.990 0.00309 2.0e-05 180 148.143 155.982 135.041 0.00392 3.0e-05 181 150.440 163.441 144.736 0.00396 3.0e-05 182 148.462 161.078 141.998 0.00397 3.0e-05 183 149.818 163.417 144.786 0.00336 2.0e-05 184 117.226 123.925 106.656 0.00417 4.0e-05 185 116.848 217.552 99.503 0.00531 5.0e-05 186 116.286 177.291 96.983 0.00314 3.0e-05 187 116.556 592.030 86.228 0.00496 4.0e-05 188 116.342 581.289 94.246 0.00267 2.0e-05 189 114.563 119.167 86.647 0.00327 3.0e-05 190 201.774 262.707 78.228 0.00694 3.0e-05 191 174.188 230.978 94.261 0.00459 3.0e-05 192 209.516 253.017 89.488 0.00564 3.0e-05 193 174.688 240.005 74.287 0.01360 8.0e-05 194 198.764 396.961 74.904 0.00740 4.0e-05 195 214.289 260.277 77.973 0.00567 3.0e-05 MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer MDVP:Shimmer(dB) Shimmer:APQ3 1 0.00370 0.00554 0.01109 0.04374 0.426 0.02182 2 0.00465 0.00696 0.01394 0.06134 0.626 0.03134 3 0.00544 0.00781 0.01633 0.05233 0.482 0.02757 4 0.00502 0.00698 0.01505 0.05492 0.517 0.02924 5 0.00655 0.00908 0.01966 0.06425 0.584 0.03490 6 0.00463 0.00750 0.01388 0.04701 0.456 0.02328 7 0.00155 0.00202 0.00466 0.01608 0.140 0.00779 8 0.00144 0.00182 0.00431 0.01567 0.134 0.00829 9 0.00293 0.00332 0.00880 0.02093 0.191 0.01073 10 0.00268 0.00332 0.00803 0.02838 0.255 0.01441 11 0.00254 0.00330 0.00763 0.02143 0.197 0.01079 12 0.00281 0.00336 0.00844 0.02752 0.249 0.01424 13 0.00118 0.00153 0.00355 0.01259 0.112 0.00656 14 0.00165 0.00208 0.00496 0.01642 0.154 0.00728 15 0.00121 0.00149 0.00364 0.01828 0.158 0.01064 16 0.00157 0.00203 0.00471 0.01503 0.126 0.00772 17 0.00211 0.00292 0.00632 0.02047 0.192 0.00969 18 0.00284 0.00387 0.00853 0.03327 0.348 0.01441 19 0.00364 0.00432 0.01092 0.05517 0.542 0.02471 20 0.00372 0.00399 0.01116 0.03995 0.348 0.01721 21 0.00428 0.00450 0.01285 0.03810 0.328 0.01667 22 0.00232 0.00267 0.00696 0.04137 0.370 0.02021 23 0.00220 0.00247 0.00661 0.04351 0.377 0.02228 24 0.00221 0.00258 0.00663 0.04192 0.364 0.02187 25 0.00380 0.00390 0.01140 0.01659 0.164 0.00738 26 0.00316 0.00375 0.00948 0.03767 0.381 0.01732 27 0.00250 0.00234 0.00750 0.01966 0.186 0.00889 28 0.00250 0.00275 0.00749 0.01919 0.198 0.00883 29 0.00159 0.00176 0.00476 0.01718 0.161 0.00769 30 0.00280 0.00253 0.00841 0.01791 0.168 0.00793 31 0.00166 0.00168 0.00498 0.01098 0.097 0.00563 32 0.00134 0.00138 0.00402 0.01015 0.089 0.00504 33 0.00113 0.00135 0.00339 0.01263 0.111 0.00640 34 0.00093 0.00107 0.00278 0.00954 0.085 0.00469 35 0.00094 0.00106 0.00283 0.00958 0.085 0.00468 36 0.00105 0.00115 0.00314 0.01194 0.107 0.00586 37 0.00233 0.00241 0.00700 0.02126 0.189 0.01154 38 0.00205 0.00218 0.00616 0.01851 0.168 0.00938 39 0.00153 0.00166 0.00459 0.01444 0.131 0.00726 40 0.00168 0.00182 0.00504 0.01663 0.151 0.00829 41 0.00165 0.00175 0.00496 0.01495 0.135 0.00774 42 0.00134 0.00147 0.00403 0.01463 0.132 0.00742 43 0.00169 0.00182 0.00507 0.01752 0.164 0.01035 44 0.00157 0.00173 0.00470 0.01760 0.154 0.01006 45 0.00109 0.00137 0.00327 0.01419 0.126 0.00777 46 0.00117 0.00139 0.00350 0.01494 0.134 0.00847 47 0.00127 0.00148 0.00380 0.01608 0.141 0.00906 48 0.00092 0.00113 0.00276 0.01152 0.103 0.00614 49 0.00169 0.00203 0.00507 0.01613 0.143 0.00855 50 0.00124 0.00155 0.00373 0.01681 0.154 0.00930 51 0.00141 0.00167 0.00422 0.02184 0.197 0.01241 52 0.00131 0.00169 0.00393 0.02033 0.185 0.01143 53 0.00137 0.00166 0.00411 0.02297 0.210 0.01323 54 0.00165 0.00183 0.00495 0.02498 0.228 0.01396 55 0.00349 0.00486 0.01046 0.02719 0.255 0.01483 56 0.00398 0.00539 0.01193 0.03209 0.307 0.01789 57 0.00352 0.00514 0.01056 0.03715 0.334 0.02032 58 0.00299 0.00469 0.00898 0.02293 0.221 0.01189 59 0.00334 0.00493 0.01003 0.02645 0.265 0.01394 60 0.00373 0.00520 0.01120 0.03225 0.350 0.01805 61 0.00147 0.00152 0.00442 0.01861 0.170 0.00975 62 0.00154 0.00151 0.00461 0.01906 0.165 0.01013 63 0.00152 0.00144 0.00457 0.01643 0.145 0.00867 64 0.00175 0.00155 0.00526 0.01644 0.145 0.00882 65 0.00114 0.00113 0.00342 0.01457 0.129 0.00769 66 0.00136 0.00140 0.00408 0.01745 0.154 0.00942 67 0.00430 0.00440 0.01289 0.03198 0.313 0.01830 68 0.00507 0.00463 0.01520 0.03111 0.308 0.01638 69 0.00647 0.00467 0.01941 0.05384 0.478 0.03152 70 0.00467 0.00354 0.01400 0.05428 0.497 0.03357 71 0.00469 0.00419 0.01407 0.03485 0.365 0.01868 72 0.00534 0.00478 0.01601 0.04978 0.483 0.02749 73 0.00180 0.00220 0.00540 0.01706 0.152 0.00974 74 0.00268 0.00329 0.00805 0.02448 0.226 0.01373 75 0.00260 0.00283 0.00780 0.02442 0.216 0.01432 76 0.00277 0.00289 0.00831 0.02215 0.206 0.01284 77 0.00270 0.00289 0.00810 0.03999 0.350 0.02413 78 0.00226 0.00280 0.00677 0.02199 0.197 0.01284 79 0.00331 0.00332 0.00994 0.03202 0.263 0.01803 80 0.00622 0.00576 0.01865 0.03121 0.361 0.01773 81 0.00389 0.00415 0.01168 0.04024 0.364 0.02266 82 0.00428 0.00371 0.01283 0.03156 0.296 0.01792 83 0.00351 0.00348 0.01053 0.02427 0.216 0.01371 84 0.00247 0.00258 0.00742 0.02223 0.202 0.01277 85 0.00418 0.00420 0.01254 0.04795 0.435 0.02679 86 0.00220 0.00244 0.00659 0.03852 0.331 0.02107 87 0.00163 0.00194 0.00488 0.03759 0.327 0.02073 88 0.00287 0.00312 0.00862 0.06511 0.580 0.03671 89 0.00237 0.00254 0.00710 0.06727 0.650 0.03788 90 0.00391 0.00419 0.01172 0.04313 0.442 0.02297 91 0.00387 0.00453 0.01161 0.06640 0.634 0.03650 92 0.00224 0.00227 0.00672 0.07959 0.772 0.04421 93 0.00250 0.00256 0.00750 0.04190 0.383 0.02383 94 0.00191 0.00226 0.00574 0.05925 0.637 0.03341 95 0.00196 0.00196 0.00587 0.03716 0.307 0.02062 96 0.00201 0.00197 0.00602 0.03272 0.283 0.01813 97 0.00178 0.00184 0.00535 0.03381 0.307 0.01806 98 0.00743 0.00623 0.02228 0.03886 0.342 0.02135 99 0.00826 0.00655 0.02478 0.04689 0.422 0.02542 100 0.01159 0.00990 0.03476 0.06734 0.659 0.03611 101 0.02144 0.01522 0.06433 0.09178 0.891 0.05358 102 0.00905 0.00909 0.02716 0.06170 0.584 0.03223 103 0.01854 0.01628 0.05563 0.09419 0.930 0.05551 104 0.00105 0.00136 0.00315 0.01131 0.107 0.00522 105 0.00076 0.00100 0.00229 0.01030 0.094 0.00469 106 0.00116 0.00134 0.00349 0.01346 0.126 0.00660 107 0.00068 0.00092 0.00204 0.01064 0.097 0.00522 108 0.00115 0.00122 0.00346 0.01450 0.137 0.00633 109 0.00075 0.00096 0.00225 0.01024 0.093 0.00455 110 0.00450 0.00389 0.01351 0.03044 0.275 0.01771 111 0.00371 0.00337 0.01112 0.02286 0.207 0.01192 112 0.00368 0.00339 0.01105 0.01761 0.155 0.00952 113 0.00502 0.00485 0.01506 0.02378 0.210 0.01277 114 0.00321 0.00280 0.00964 0.01680 0.149 0.00861 115 0.00302 0.00246 0.00905 0.02105 0.209 0.01107 116 0.00404 0.00385 0.01211 0.01843 0.235 0.00796 117 0.00214 0.00207 0.00642 0.01458 0.148 0.00606 118 0.00244 0.00261 0.00731 0.01725 0.175 0.00757 119 0.00157 0.00194 0.00472 0.01279 0.129 0.00617 120 0.00127 0.00128 0.00381 0.01299 0.124 0.00679 121 0.00241 0.00314 0.00723 0.02008 0.221 0.00849 122 0.00209 0.00221 0.00628 0.01169 0.117 0.00534 123 0.00406 0.00398 0.01218 0.04479 0.441 0.02587 124 0.00506 0.00449 0.01517 0.02503 0.231 0.01372 125 0.00403 0.00395 0.01209 0.02343 0.224 0.01289 126 0.00414 0.00422 0.01242 0.02362 0.233 0.01235 127 0.00294 0.00327 0.00883 0.02791 0.246 0.01484 128 0.00368 0.00351 0.01104 0.02857 0.257 0.01547 129 0.00214 0.00192 0.00641 0.01033 0.098 0.00538 130 0.00116 0.00135 0.00349 0.01022 0.090 0.00476 131 0.00269 0.00238 0.00808 0.01412 0.125 0.00703 132 0.00224 0.00205 0.00671 0.01516 0.138 0.00721 133 0.00169 0.00170 0.00508 0.01201 0.106 0.00633 134 0.00168 0.00171 0.00504 0.01043 0.099 0.00490 135 0.00291 0.00319 0.00873 0.04932 0.441 0.02683 136 0.00244 0.00315 0.00731 0.04128 0.379 0.02229 137 0.00219 0.00283 0.00658 0.04879 0.431 0.02385 138 0.00257 0.00312 0.00772 0.05279 0.476 0.02896 139 0.00238 0.00290 0.00715 0.05643 0.517 0.03070 140 0.00181 0.00232 0.00542 0.03026 0.267 0.01514 141 0.00232 0.00269 0.00696 0.03273 0.281 0.01713 142 0.00428 0.00428 0.01285 0.06725 0.571 0.04016 143 0.00182 0.00215 0.00546 0.03527 0.297 0.02055 144 0.00189 0.00211 0.00568 0.01997 0.180 0.01117 145 0.00100 0.00133 0.00301 0.02662 0.228 0.01475 146 0.00169 0.00188 0.00506 0.02536 0.225 0.01379 147 0.00863 0.00946 0.02589 0.08143 0.821 0.03804 148 0.00849 0.00819 0.02546 0.06050 0.618 0.02865 149 0.00996 0.01027 0.02987 0.07118 0.722 0.03474 150 0.00919 0.00963 0.02756 0.07170 0.833 0.03515 151 0.01075 0.01154 0.03225 0.05830 0.784 0.02699 152 0.01800 0.01958 0.05401 0.11908 1.302 0.05647 153 0.01568 0.01699 0.04705 0.08684 1.018 0.04284 154 0.00388 0.00332 0.01164 0.02534 0.241 0.01340 155 0.00393 0.00300 0.01179 0.02682 0.236 0.01484 156 0.00356 0.00300 0.01067 0.03087 0.276 0.01659 157 0.00415 0.00339 0.01246 0.02293 0.223 0.01205 158 0.01117 0.00718 0.03351 0.04912 0.438 0.02610 159 0.00593 0.00454 0.01778 0.02852 0.266 0.01500 160 0.00321 0.00318 0.00962 0.03235 0.339 0.01360 161 0.00299 0.00316 0.00896 0.04009 0.406 0.01579 162 0.00352 0.00329 0.01057 0.03273 0.325 0.01644 163 0.00366 0.00340 0.01097 0.03658 0.369 0.01864 164 0.00291 0.00284 0.00873 0.01756 0.155 0.00967 165 0.00493 0.00461 0.01480 0.02814 0.272 0.01579 166 0.00154 0.00153 0.00462 0.02448 0.217 0.01410 167 0.00173 0.00159 0.00519 0.01242 0.116 0.00696 168 0.00205 0.00186 0.00616 0.02030 0.197 0.01186 169 0.00490 0.00448 0.01470 0.02177 0.189 0.01279 170 0.00316 0.00283 0.00949 0.02018 0.212 0.01176 171 0.00279 0.00237 0.00837 0.01897 0.181 0.01084 172 0.00166 0.00190 0.00499 0.01358 0.129 0.00664 173 0.00170 0.00200 0.00510 0.01484 0.133 0.00754 174 0.00171 0.00203 0.00514 0.01472 0.133 0.00748 175 0.00176 0.00218 0.00528 0.01657 0.145 0.00881 176 0.00160 0.00199 0.00480 0.01503 0.137 0.00812 177 0.00169 0.00213 0.00507 0.01725 0.155 0.00874 178 0.00135 0.00162 0.00406 0.01469 0.132 0.00728 179 0.00152 0.00186 0.00456 0.01574 0.142 0.00839 180 0.00204 0.00231 0.00612 0.01450 0.131 0.00725 181 0.00206 0.00233 0.00619 0.02551 0.237 0.01321 182 0.00202 0.00235 0.00605 0.01831 0.163 0.00950 183 0.00174 0.00198 0.00521 0.02145 0.198 0.01155 184 0.00186 0.00270 0.00558 0.01909 0.171 0.00864 185 0.00260 0.00346 0.00780 0.01795 0.163 0.00810 186 0.00134 0.00192 0.00403 0.01564 0.136 0.00667 187 0.00254 0.00263 0.00762 0.01660 0.154 0.00820 188 0.00115 0.00148 0.00345 0.01300 0.117 0.00631 189 0.00146 0.00184 0.00439 0.01185 0.106 0.00557 190 0.00412 0.00396 0.01235 0.02574 0.255 0.01454 191 0.00263 0.00259 0.00790 0.04087 0.405 0.02336 192 0.00331 0.00292 0.00994 0.02751 0.263 0.01604 193 0.00624 0.00564 0.01873 0.02308 0.256 0.01268 194 0.00370 0.00390 0.01109 0.02296 0.241 0.01265 195 0.00295 0.00317 0.00885 0.01884 0.190 0.01026 Shimmer:APQ5 MDVP:APQ Shimmer:DDA NHR HNR status RPDE DFA 1 0.03130 0.02971 0.06545 0.02211 21.033 1 0.414783 0.815285 2 0.04518 0.04368 0.09403 0.01929 19.085 1 0.458359 0.819521 3 0.03858 0.03590 0.08270 0.01309 20.651 1 0.429895 0.825288 4 0.04005 0.03772 0.08771 0.01353 20.644 1 0.434969 0.819235 5 0.04825 0.04465 0.10470 0.01767 19.649 1 0.417356 0.823484 6 0.03526 0.03243 0.06985 0.01222 21.378 1 0.415564 0.825069 7 0.00937 0.01351 0.02337 0.00607 24.886 1 0.596040 0.764112 8 0.00946 0.01256 0.02487 0.00344 26.892 1 0.637420 0.763262 9 0.01277 0.01717 0.03218 0.01070 21.812 1 0.615551 0.773587 10 0.01725 0.02444 0.04324 0.01022 21.862 1 0.547037 0.798463 11 0.01342 0.01892 0.03237 0.01166 21.118 1 0.611137 0.776156 12 0.01641 0.02214 0.04272 0.01141 21.414 1 0.583390 0.792520 13 0.00717 0.01140 0.01968 0.00581 25.703 1 0.460600 0.646846 14 0.00932 0.01797 0.02184 0.01041 24.889 1 0.430166 0.665833 15 0.00972 0.01246 0.03191 0.00609 24.922 1 0.474791 0.654027 16 0.00888 0.01359 0.02316 0.00839 25.175 1 0.565924 0.658245 17 0.01200 0.02074 0.02908 0.01859 22.333 1 0.567380 0.644692 18 0.01893 0.03430 0.04322 0.02919 20.376 1 0.631099 0.605417 19 0.03572 0.05767 0.07413 0.03160 17.280 1 0.665318 0.719467 20 0.02374 0.04310 0.05164 0.03365 17.153 1 0.649554 0.686080 21 0.02383 0.04055 0.05000 0.03871 17.536 1 0.660125 0.704087 22 0.02591 0.04525 0.06062 0.01849 19.493 1 0.629017 0.698951 23 0.02540 0.04246 0.06685 0.01280 22.468 1 0.619060 0.679834 24 0.02470 0.03772 0.06562 0.01840 20.422 1 0.537264 0.686894 25 0.00948 0.01497 0.02214 0.01778 23.831 1 0.397937 0.732479 26 0.02245 0.03780 0.05197 0.02887 22.066 1 0.522746 0.737948 27 0.01169 0.01872 0.02666 0.01095 25.908 1 0.418622 0.720916 28 0.01144 0.01826 0.02650 0.01328 25.119 1 0.358773 0.726652 29 0.01012 0.01661 0.02307 0.00677 25.970 1 0.470478 0.676258 30 0.01057 0.01799 0.02380 0.01170 25.678 1 0.427785 0.723797 31 0.00680 0.00802 0.01689 0.00339 26.775 0 0.422229 0.741367 32 0.00641 0.00762 0.01513 0.00167 30.940 0 0.432439 0.742055 33 0.00825 0.00951 0.01919 0.00119 30.775 0 0.465946 0.738703 34 0.00606 0.00719 0.01407 0.00072 32.684 0 0.368535 0.742133 35 0.00610 0.00726 0.01403 0.00065 33.047 0 0.340068 0.741899 36 0.00760 0.00957 0.01758 0.00135 31.732 0 0.344252 0.742737 37 0.01347 0.01612 0.03463 0.00586 23.216 1 0.360148 0.778834 38 0.01160 0.01491 0.02814 0.00340 24.951 1 0.341435 0.783626 39 0.00885 0.01190 0.02177 0.00231 26.738 1 0.403884 0.766209 40 0.01003 0.01366 0.02488 0.00265 26.310 1 0.396793 0.758324 41 0.00941 0.01233 0.02321 0.00231 26.822 1 0.326480 0.765623 42 0.00901 0.01234 0.02226 0.00257 26.453 1 0.306443 0.759203 43 0.01024 0.01133 0.03104 0.00740 22.736 0 0.305062 0.654172 44 0.01038 0.01251 0.03017 0.00675 23.145 0 0.457702 0.634267 45 0.00898 0.01033 0.02330 0.00454 25.368 0 0.438296 0.635285 46 0.00879 0.01014 0.02542 0.00476 25.032 0 0.431285 0.638928 47 0.00977 0.01149 0.02719 0.00476 24.602 0 0.467489 0.631653 48 0.00730 0.00860 0.01841 0.00432 26.805 0 0.610367 0.635204 49 0.00776 0.01433 0.02566 0.00839 23.162 0 0.579597 0.733659 50 0.00802 0.01400 0.02789 0.00462 24.971 0 0.538688 0.754073 51 0.01024 0.01685 0.03724 0.00479 25.135 0 0.553134 0.775933 52 0.00959 0.01614 0.03429 0.00474 25.030 0 0.507504 0.760361 53 0.01072 0.01677 0.03969 0.00481 24.692 0 0.459766 0.766204 54 0.01219 0.01947 0.04188 0.00484 25.429 0 0.420383 0.785714 55 0.01609 0.02067 0.04450 0.01036 21.028 1 0.536009 0.819032 56 0.01992 0.02454 0.05368 0.01180 20.767 1 0.558586 0.811843 57 0.02302 0.02802 0.06097 0.00969 21.422 1 0.541781 0.821364 58 0.01459 0.01948 0.03568 0.00681 22.817 1 0.530529 0.817756 59 0.01625 0.02137 0.04183 0.00786 22.603 1 0.540049 0.813432 60 0.01974 0.02519 0.05414 0.01143 21.660 1 0.547975 0.817396 61 0.01258 0.01382 0.02925 0.00871 25.554 0 0.341788 0.678874 62 0.01296 0.01340 0.03039 0.00301 26.138 0 0.447979 0.686264 63 0.01108 0.01200 0.02602 0.00340 25.856 0 0.364867 0.694399 64 0.01075 0.01179 0.02647 0.00351 25.964 0 0.256570 0.683296 65 0.00957 0.01016 0.02308 0.00300 26.415 0 0.276850 0.673636 66 0.01160 0.01234 0.02827 0.00420 24.547 0 0.305429 0.681811 67 0.01810 0.02428 0.05490 0.02183 19.560 1 0.460139 0.720908 68 0.01759 0.02603 0.04914 0.02659 19.979 1 0.498133 0.729067 69 0.02422 0.03392 0.09455 0.04882 20.338 1 0.513237 0.731444 70 0.02494 0.03635 0.10070 0.02431 21.718 1 0.487407 0.727313 71 0.01906 0.02949 0.05605 0.02599 20.264 1 0.489345 0.730387 72 0.02466 0.03736 0.08247 0.03361 18.570 1 0.543299 0.733232 73 0.00925 0.01345 0.02921 0.00442 25.742 1 0.495954 0.762959 74 0.01375 0.01956 0.04120 0.00623 24.178 1 0.509127 0.789532 75 0.01325 0.01831 0.04295 0.00479 25.438 1 0.437031 0.815908 76 0.01219 0.01715 0.03851 0.00472 25.197 1 0.463514 0.807217 77 0.02231 0.02704 0.07238 0.00905 23.370 1 0.489538 0.789977 78 0.01199 0.01636 0.03852 0.00420 25.820 1 0.429484 0.816340 79 0.01886 0.02455 0.05408 0.01062 21.875 1 0.644954 0.779612 80 0.01783 0.02139 0.05320 0.02220 19.200 1 0.594387 0.790117 81 0.02451 0.02876 0.06799 0.01823 19.055 1 0.544805 0.770466 82 0.01841 0.02190 0.05377 0.01825 19.659 1 0.576084 0.778747 83 0.01421 0.01751 0.04114 0.01237 20.536 1 0.554610 0.787896 84 0.01343 0.01552 0.03831 0.00882 22.244 1 0.576644 0.772416 85 0.03022 0.03510 0.08037 0.05470 13.893 1 0.556494 0.729586 86 0.02493 0.02877 0.06321 0.02782 16.176 1 0.583574 0.727747 87 0.02415 0.02784 0.06219 0.03151 15.924 1 0.598714 0.712199 88 0.04159 0.04683 0.11012 0.04824 13.922 1 0.602874 0.740837 89 0.04254 0.04802 0.11363 0.04214 14.739 1 0.599371 0.743937 90 0.02768 0.03455 0.06892 0.07223 11.866 1 0.590951 0.745526 91 0.04282 0.05114 0.10949 0.08725 11.744 1 0.653410 0.733165 92 0.04962 0.05690 0.13262 0.01658 19.664 1 0.501037 0.714360 93 0.02521 0.03051 0.07150 0.01914 18.780 1 0.454444 0.734504 94 0.03794 0.04398 0.10024 0.01211 20.969 1 0.447456 0.697790 95 0.02321 0.02764 0.06185 0.00850 22.219 1 0.502380 0.712170 96 0.01909 0.02571 0.05439 0.01018 21.693 1 0.447285 0.705658 97 0.02024 0.02809 0.05417 0.00852 22.663 1 0.366329 0.693429 98 0.02174 0.03088 0.06406 0.08151 15.338 1 0.629574 0.714485 99 0.02630 0.03908 0.07625 0.10323 15.433 1 0.571010 0.690892 100 0.03963 0.05783 0.10833 0.16744 12.435 1 0.638545 0.674953 101 0.04791 0.06196 0.16074 0.31482 8.867 1 0.671299 0.656846 102 0.03672 0.05174 0.09669 0.11843 15.060 1 0.639808 0.643327 103 0.05005 0.06023 0.16654 0.25930 10.489 1 0.596362 0.641418 104 0.00659 0.01009 0.01567 0.00495 26.759 1 0.296888 0.722356 105 0.00582 0.00871 0.01406 0.00243 28.409 1 0.263654 0.691483 106 0.00818 0.01059 0.01979 0.00578 27.421 1 0.365488 0.719974 107 0.00632 0.00928 0.01567 0.00233 29.746 1 0.334171 0.677930 108 0.00788 0.01267 0.01898 0.00659 26.833 1 0.393563 0.700246 109 0.00576 0.00993 0.01364 0.00238 29.928 1 0.311369 0.676066 110 0.01815 0.02084 0.05312 0.00947 21.934 1 0.497554 0.740539 111 0.01439 0.01852 0.03576 0.00704 23.239 1 0.436084 0.727863 112 0.01058 0.01307 0.02855 0.00830 22.407 1 0.338097 0.712466 113 0.01483 0.01767 0.03831 0.01316 21.305 1 0.498877 0.722085 114 0.01017 0.01301 0.02583 0.00620 23.671 1 0.441097 0.722254 115 0.01284 0.01604 0.03320 0.01048 21.864 1 0.331508 0.715121 116 0.00832 0.01271 0.02389 0.06051 23.693 1 0.407701 0.662668 117 0.00747 0.01312 0.01818 0.01554 26.356 1 0.450798 0.653823 118 0.00971 0.01652 0.02270 0.01802 25.690 1 0.486738 0.676023 119 0.00744 0.01151 0.01851 0.00856 25.020 1 0.470422 0.655239 120 0.00631 0.01075 0.02038 0.00681 24.581 1 0.462516 0.582710 121 0.01117 0.01734 0.02548 0.02350 24.743 1 0.487756 0.684130 122 0.00630 0.01104 0.01603 0.01161 27.166 1 0.400088 0.656182 123 0.02567 0.03220 0.07761 0.01968 18.305 1 0.538016 0.741480 124 0.01580 0.01931 0.04115 0.01813 18.784 1 0.589956 0.732903 125 0.01420 0.01720 0.03867 0.02020 19.196 1 0.618663 0.728421 126 0.01495 0.01944 0.03706 0.01874 18.857 1 0.637518 0.735546 127 0.01805 0.02259 0.04451 0.01794 18.178 1 0.623209 0.738245 128 0.01859 0.02301 0.04641 0.01796 18.330 1 0.585169 0.736964 129 0.00570 0.00811 0.01614 0.01724 26.842 1 0.457541 0.699787 130 0.00588 0.00903 0.01428 0.00487 26.369 1 0.491345 0.718839 131 0.00820 0.01194 0.02110 0.01610 23.949 1 0.467160 0.724045 132 0.00815 0.01310 0.02164 0.01015 26.017 1 0.468621 0.735136 133 0.00701 0.00915 0.01898 0.00903 23.389 1 0.470972 0.721308 134 0.00621 0.00903 0.01471 0.00504 25.619 1 0.482296 0.723096 135 0.03112 0.03651 0.08050 0.03031 17.060 1 0.637814 0.744064 136 0.02592 0.03316 0.06688 0.02529 17.707 1 0.653427 0.706687 137 0.02973 0.04370 0.07154 0.02278 19.013 1 0.647900 0.708144 138 0.03347 0.04134 0.08689 0.03690 16.747 1 0.625362 0.708617 139 0.03530 0.04451 0.09211 0.02629 17.366 1 0.640945 0.701404 140 0.01812 0.02770 0.04543 0.01827 18.801 1 0.624811 0.696049 141 0.01964 0.02824 0.05139 0.02485 18.540 1 0.677131 0.685057 142 0.04003 0.04464 0.12047 0.04238 15.648 1 0.606344 0.665945 143 0.02076 0.02530 0.06165 0.01728 18.702 1 0.606273 0.661735 144 0.01177 0.01506 0.03350 0.02010 18.687 1 0.536102 0.632631 145 0.01558 0.02006 0.04426 0.01049 20.680 1 0.497480 0.630409 146 0.01478 0.01909 0.04137 0.01493 20.366 1 0.566849 0.574282 147 0.05426 0.08808 0.11411 0.07530 12.359 1 0.561610 0.793509 148 0.04101 0.06359 0.08595 0.06057 14.367 1 0.478024 0.768974 149 0.04580 0.06824 0.10422 0.08069 12.298 1 0.552870 0.764036 150 0.04265 0.06460 0.10546 0.07889 14.989 1 0.427627 0.775708 151 0.03714 0.06259 0.08096 0.10952 12.529 1 0.507826 0.762726 152 0.07940 0.13778 0.16942 0.21713 8.441 1 0.625866 0.768320 153 0.05556 0.08318 0.12851 0.16265 9.449 1 0.584164 0.754449 154 0.01399 0.02056 0.04019 0.04179 21.520 1 0.566867 0.670475 155 0.01405 0.02018 0.04451 0.04611 21.824 1 0.651680 0.659333 156 0.01804 0.02402 0.04977 0.02631 22.431 1 0.628300 0.652025 157 0.01289 0.01771 0.03615 0.03191 22.953 1 0.611679 0.623731 158 0.02161 0.02916 0.07830 0.10748 19.075 1 0.630547 0.646786 159 0.01581 0.02157 0.04499 0.03828 21.534 1 0.635015 0.627337 160 0.01650 0.03105 0.04079 0.02663 19.651 1 0.654945 0.675865 161 0.01994 0.04114 0.04736 0.02073 20.437 1 0.653139 0.694571 162 0.01722 0.02931 0.04933 0.02810 19.388 1 0.577802 0.684373 163 0.01940 0.03091 0.05592 0.02707 18.954 1 0.685151 0.719576 164 0.01033 0.01363 0.02902 0.01435 21.219 1 0.557045 0.673086 165 0.01553 0.02073 0.04736 0.03882 18.447 1 0.671378 0.674562 166 0.01426 0.01621 0.04231 0.00620 24.078 0 0.469928 0.628232 167 0.00747 0.00882 0.02089 0.00533 24.679 0 0.384868 0.626710 168 0.01230 0.01367 0.03557 0.00910 21.083 0 0.440988 0.628058 169 0.01272 0.01439 0.03836 0.01337 19.269 0 0.372222 0.725216 170 0.01191 0.01344 0.03529 0.00965 21.020 0 0.371837 0.646167 171 0.01121 0.01255 0.03253 0.01049 21.528 0 0.522812 0.646818 172 0.00786 0.01140 0.01992 0.00435 26.436 0 0.413295 0.756700 173 0.00950 0.01285 0.02261 0.00430 26.550 0 0.369090 0.776158 174 0.00905 0.01148 0.02245 0.00478 26.547 0 0.380253 0.766700 175 0.01062 0.01318 0.02643 0.00590 25.445 0 0.387482 0.756482 176 0.00933 0.01133 0.02436 0.00401 26.005 0 0.405991 0.761255 177 0.01021 0.01331 0.02623 0.00415 26.143 0 0.361232 0.763242 178 0.00886 0.01230 0.02184 0.00570 24.151 1 0.396610 0.745957 179 0.00956 0.01309 0.02518 0.00488 24.412 1 0.402591 0.762508 180 0.00876 0.01263 0.02175 0.00540 23.683 1 0.398499 0.778349 181 0.01574 0.02148 0.03964 0.00611 23.133 1 0.352396 0.759320 182 0.01103 0.01559 0.02849 0.00639 22.866 1 0.408598 0.768845 183 0.01341 0.01666 0.03464 0.00595 23.008 1 0.329577 0.757180 184 0.01223 0.01949 0.02592 0.00955 23.079 0 0.603515 0.669565 185 0.01144 0.01756 0.02429 0.01179 22.085 0 0.663842 0.656516 186 0.00990 0.01691 0.02001 0.00737 24.199 0 0.598515 0.654331 187 0.00972 0.01491 0.02460 0.01397 23.958 0 0.566424 0.667654 188 0.00789 0.01144 0.01892 0.00680 25.023 0 0.528485 0.663884 189 0.00721 0.01095 0.01672 0.00703 24.775 0 0.555303 0.659132 190 0.01582 0.01758 0.04363 0.04441 19.368 0 0.508479 0.683761 191 0.02498 0.02745 0.07008 0.02764 19.517 0 0.448439 0.657899 192 0.01657 0.01879 0.04812 0.01810 19.147 0 0.431674 0.683244 193 0.01365 0.01667 0.03804 0.10715 17.883 0 0.407567 0.655683 194 0.01321 0.01588 0.03794 0.07223 19.020 0 0.451221 0.643956 195 0.01161 0.01373 0.03078 0.04398 21.209 0 0.462803 0.664357 spread1 spread2 D2 1 -4.813031 0.266482 2.301442 2 -4.075192 0.335590 2.486855 3 -4.443179 0.311173 2.342259 4 -4.117501 0.334147 2.405554 5 -3.747787 0.234513 2.332180 6 -4.242867 0.299111 2.187560 7 -5.634322 0.257682 1.854785 8 -6.167603 0.183721 2.064693 9 -5.498678 0.327769 2.322511 10 -5.011879 0.325996 2.432792 11 -5.249770 0.391002 2.407313 12 -4.960234 0.363566 2.642476 13 -6.547148 0.152813 2.041277 14 -5.660217 0.254989 2.519422 15 -6.105098 0.203653 2.125618 16 -5.340115 0.210185 2.205546 17 -5.440040 0.239764 2.264501 18 -2.931070 0.434326 3.007463 19 -3.949079 0.357870 3.109010 20 -4.554466 0.340176 2.856676 21 -4.095442 0.262564 2.739710 22 -5.186960 0.237622 2.557536 23 -4.330956 0.262384 2.916777 24 -5.248776 0.210279 2.547508 25 -5.557447 0.220890 2.692176 26 -5.571843 0.236853 2.846369 27 -6.183590 0.226278 2.589702 28 -6.271690 0.196102 2.314209 29 -7.120925 0.279789 2.241742 30 -6.635729 0.209866 1.957961 31 -7.348300 0.177551 1.743867 32 -7.682587 0.173319 2.103106 33 -7.067931 0.175181 1.512275 34 -7.695734 0.178540 1.544609 35 -7.964984 0.163519 1.423287 36 -7.777685 0.170183 2.447064 37 -6.149653 0.218037 2.477082 38 -6.006414 0.196371 2.536527 39 -6.452058 0.212294 2.269398 40 -6.006647 0.266892 2.382544 41 -6.647379 0.201095 2.374073 42 -7.044105 0.063412 2.361532 43 -7.310550 0.098648 2.416838 44 -6.793547 0.158266 2.256699 45 -7.057869 0.091608 2.330716 46 -6.995820 0.102083 2.365800 47 -7.156076 0.127642 2.392122 48 -7.319510 0.200873 2.028612 49 -6.439398 0.266392 2.079922 50 -6.482096 0.264967 2.054419 51 -6.650471 0.254498 1.840198 52 -6.689151 0.291954 2.431854 53 -7.072419 0.220434 1.972297 54 -6.836811 0.269866 2.223719 55 -4.649573 0.205558 1.986899 56 -4.333543 0.221727 2.014606 57 -4.438453 0.238298 1.922940 58 -4.608260 0.290024 2.021591 59 -4.476755 0.262633 1.827012 60 -4.609161 0.221711 1.831691 61 -7.040508 0.066994 2.460791 62 -7.293801 0.086372 2.321560 63 -6.966321 0.095882 2.278687 64 -7.245620 0.018689 2.498224 65 -7.496264 0.056844 2.003032 66 -7.314237 0.006274 2.118596 67 -5.409423 0.226850 2.359973 68 -5.324574 0.205660 2.291558 69 -5.869750 0.151814 2.118496 70 -6.261141 0.120956 2.137075 71 -5.720868 0.158830 2.277927 72 -5.207985 0.224852 2.642276 73 -5.791820 0.329066 2.205024 74 -5.389129 0.306636 1.928708 75 -5.313360 0.201861 2.225815 76 -5.477592 0.315074 1.862092 77 -5.775966 0.341169 2.007923 78 -5.391029 0.250572 1.777901 79 -5.115212 0.249494 2.017753 80 -4.913885 0.265699 2.398422 81 -4.441519 0.155097 2.645959 82 -5.132032 0.210458 2.232576 83 -5.022288 0.146948 2.428306 84 -6.025367 0.078202 2.053601 85 -5.288912 0.343073 3.099301 86 -5.657899 0.315903 3.098256 87 -6.366916 0.335753 2.654271 88 -5.515071 0.299549 3.136550 89 -5.783272 0.299793 3.007096 90 -4.379411 0.375531 3.671155 91 -4.508984 0.389232 3.317586 92 -6.411497 0.207156 2.344876 93 -5.952058 0.087840 2.344336 94 -6.152551 0.173520 2.080121 95 -6.251425 0.188056 2.143851 96 -6.247076 0.180528 2.344348 97 -6.417440 0.194627 2.473239 98 -4.020042 0.265315 2.671825 99 -5.159169 0.202146 2.441612 100 -3.760348 0.242861 2.634633 101 -3.700544 0.260481 2.991063 102 -4.202730 0.310163 2.638279 103 -3.269487 0.270641 2.690917 104 -6.878393 0.089267 2.004055 105 -7.111576 0.144780 2.065477 106 -6.997403 0.210279 1.994387 107 -6.981201 0.184550 2.129924 108 -6.600023 0.249172 2.499148 109 -6.739151 0.160686 2.296873 110 -5.845099 0.278679 2.608749 111 -5.258320 0.256454 2.550961 112 -6.471427 0.184378 2.502336 113 -4.876336 0.212054 2.376749 114 -5.963040 0.250283 2.489191 115 -6.729713 0.181701 2.938114 116 -4.673241 0.261549 2.702355 117 -6.051233 0.273280 2.640798 118 -4.597834 0.372114 2.975889 119 -4.913137 0.393056 2.816781 120 -5.517173 0.389295 2.925862 121 -6.186128 0.279933 2.686240 122 -4.711007 0.281618 2.655744 123 -5.418787 0.160267 2.090438 124 -5.445140 0.142466 2.174306 125 -5.944191 0.143359 1.929715 126 -5.594275 0.127950 1.765957 127 -5.540351 0.087165 1.821297 128 -5.825257 0.115697 1.996146 129 -6.890021 0.152941 2.328513 130 -5.892061 0.195976 2.108873 131 -6.135296 0.203630 2.539724 132 -6.112667 0.217013 2.527742 133 -5.436135 0.254909 2.516320 134 -6.448134 0.178713 2.034827 135 -5.301321 0.320385 2.375138 136 -5.333619 0.322044 2.631793 137 -4.378916 0.300067 2.445502 138 -4.654894 0.304107 2.672362 139 -5.634576 0.306014 2.419253 140 -5.866357 0.233070 2.445646 141 -4.796845 0.397749 2.963799 142 -5.410336 0.288917 2.665133 143 -5.585259 0.310746 2.465528 144 -5.898673 0.213353 2.470746 145 -6.132663 0.220617 2.576563 146 -5.456811 0.345238 2.840556 147 -3.297668 0.414758 3.413649 148 -4.276605 0.355736 3.142364 149 -3.377325 0.335357 3.274865 150 -4.892495 0.262281 2.910213 151 -4.484303 0.340256 2.958815 152 -2.434031 0.450493 3.079221 153 -2.839756 0.356224 3.184027 154 -4.865194 0.246404 2.013530 155 -4.239028 0.175691 2.451130 156 -3.583722 0.207914 2.439597 157 -5.435100 0.230532 2.699645 158 -3.444478 0.303214 2.964568 159 -5.070096 0.280091 2.892300 160 -5.498456 0.234196 2.103014 161 -5.185987 0.259229 2.151121 162 -5.283009 0.226528 2.442906 163 -5.529833 0.242750 2.408689 164 -5.617124 0.184896 1.871871 165 -2.929379 0.396746 2.560422 166 -6.816086 0.172270 2.235197 167 -7.018057 0.176316 1.852402 168 -7.517934 0.160414 1.881767 169 -5.736781 0.164529 2.882450 170 -7.169701 0.073298 2.266432 171 -7.304500 0.171088 2.095237 172 -6.323531 0.218885 2.193412 173 -6.085567 0.192375 1.889002 174 -5.943501 0.192150 1.852542 175 -6.012559 0.229298 1.872946 176 -5.966779 0.197938 1.974857 177 -6.016891 0.109256 2.004719 178 -6.486822 0.197919 2.449763 179 -6.311987 0.182459 2.251553 180 -5.711205 0.240875 2.845109 181 -6.261446 0.183218 2.264226 182 -5.704053 0.216204 2.679185 183 -6.277170 0.109397 2.209021 184 -5.619070 0.191576 2.027228 185 -5.198864 0.206768 2.120412 186 -5.592584 0.133917 2.058658 187 -6.431119 0.153310 2.161936 188 -6.359018 0.116636 2.152083 189 -6.710219 0.149694 1.913990 190 -6.934474 0.159890 2.316346 191 -6.538586 0.121952 2.657476 192 -6.195325 0.129303 2.784312 193 -6.787197 0.158453 2.679772 194 -6.744577 0.207454 2.138608 195 -5.724056 0.190667 2.555477 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `MDVP:Fhi(Hz)` `MDVP:Flo(Hz)` `MDVP:Jitter(%)` 2.731e+02 3.208e-02 2.536e-01 1.079e+04 `MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ` `Jitter:DDP` -1.909e+06 6.347e+05 -1.415e+03 -2.087e+05 `MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3` `Shimmer:APQ5` 2.969e+01 -7.588e+01 8.307e+04 2.153e+03 `MDVP:APQ` `Shimmer:DDA` NHR HNR -1.354e+03 -2.743e+04 -2.433e+02 -4.896e-01 status RPDE DFA spread1 -5.457e+00 -3.635e+01 -2.260e+02 -3.095e+00 spread2 D2 2.469e+01 8.161e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -52.862 -11.013 -0.665 10.531 45.809 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.731e+02 4.887e+01 5.590 8.72e-08 *** `MDVP:Fhi(Hz)` 3.208e-02 1.644e-02 1.952 0.05257 . `MDVP:Flo(Hz)` 2.536e-01 3.695e-02 6.863 1.15e-10 *** `MDVP:Jitter(%)` 1.079e+04 3.410e+03 3.164 0.00184 ** `MDVP:Jitter(Abs)` -1.909e+06 1.761e+05 -10.839 < 2e-16 *** `MDVP:RAP` 6.347e+05 4.796e+05 1.323 0.18745 `MDVP:PPQ` -1.415e+03 4.215e+03 -0.336 0.73750 `Jitter:DDP` -2.087e+05 1.600e+05 -1.305 0.19364 `MDVP:Shimmer` 2.969e+01 1.775e+03 0.017 0.98668 `MDVP:Shimmer(dB)` -7.588e+01 5.939e+01 -1.278 0.20309 `Shimmer:APQ3` 8.307e+04 4.628e+05 0.180 0.85775 `Shimmer:APQ5` 2.153e+03 1.030e+03 2.090 0.03810 * `MDVP:APQ` -1.354e+03 5.406e+02 -2.505 0.01319 * `Shimmer:DDA` -2.743e+04 1.542e+05 -0.178 0.85904 NHR -2.433e+02 1.012e+02 -2.403 0.01733 * HNR -4.896e-01 7.383e-01 -0.663 0.50812 status -5.457e+00 3.913e+00 -1.395 0.16492 RPDE -3.635e+01 2.292e+01 -1.586 0.11459 DFA -2.260e+02 3.347e+01 -6.751 2.13e-10 *** spread1 -3.095e+00 2.890e+00 -1.071 0.28572 spread2 2.469e+01 2.515e+01 0.982 0.32766 D2 8.161e+00 5.859e+00 1.393 0.16547 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 16.9 on 173 degrees of freedom Multiple R-squared: 0.8513, Adjusted R-squared: 0.8333 F-statistic: 47.17 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,] 1.826280e-01 3.652560e-01 0.8173720 [2,] 8.711639e-02 1.742328e-01 0.9128836 [3,] 3.895557e-02 7.791114e-02 0.9610444 [4,] 4.024470e-02 8.048939e-02 0.9597553 [5,] 1.751879e-02 3.503758e-02 0.9824812 [6,] 8.486019e-03 1.697204e-02 0.9915140 [7,] 3.351956e-03 6.703912e-03 0.9966480 [8,] 1.501731e-03 3.003463e-03 0.9984983 [9,] 1.019137e-03 2.038274e-03 0.9989809 [10,] 6.937780e-04 1.387556e-03 0.9993062 [11,] 2.932588e-04 5.865175e-04 0.9997067 [12,] 1.173654e-04 2.347308e-04 0.9998826 [13,] 6.549233e-05 1.309847e-04 0.9999345 [14,] 2.438001e-05 4.876002e-05 0.9999756 [15,] 1.035496e-04 2.070993e-04 0.9998965 [16,] 1.491025e-04 2.982050e-04 0.9998509 [17,] 1.053419e-04 2.106838e-04 0.9998947 [18,] 4.924561e-05 9.849123e-05 0.9999508 [19,] 6.092988e-05 1.218598e-04 0.9999391 [20,] 4.777886e-05 9.555773e-05 0.9999522 [21,] 8.520432e-05 1.704086e-04 0.9999148 [22,] 9.500188e-05 1.900038e-04 0.9999050 [23,] 9.864357e-05 1.972871e-04 0.9999014 [24,] 6.653523e-03 1.330705e-02 0.9933465 [25,] 4.549915e-03 9.099830e-03 0.9954501 [26,] 3.462511e-03 6.925021e-03 0.9965375 [27,] 2.108898e-03 4.217797e-03 0.9978911 [28,] 1.567931e-03 3.135862e-03 0.9984321 [29,] 1.016291e-03 2.032582e-03 0.9989837 [30,] 6.002934e-04 1.200587e-03 0.9993997 [31,] 3.459197e-03 6.918394e-03 0.9965408 [32,] 6.799305e-03 1.359861e-02 0.9932007 [33,] 5.940496e-03 1.188099e-02 0.9940595 [34,] 8.331230e-03 1.666246e-02 0.9916688 [35,] 1.418706e-02 2.837413e-02 0.9858129 [36,] 2.996023e-02 5.992047e-02 0.9700398 [37,] 2.429034e-02 4.858069e-02 0.9757097 [38,] 4.012102e-02 8.024203e-02 0.9598790 [39,] 4.088711e-02 8.177421e-02 0.9591129 [40,] 4.296187e-02 8.592375e-02 0.9570381 [41,] 4.506423e-02 9.012847e-02 0.9549358 [42,] 1.022712e-01 2.045424e-01 0.8977288 [43,] 8.595385e-02 1.719077e-01 0.9140461 [44,] 6.759592e-02 1.351918e-01 0.9324041 [45,] 5.410067e-02 1.082013e-01 0.9458993 [46,] 6.809114e-02 1.361823e-01 0.9319089 [47,] 5.411564e-02 1.082313e-01 0.9458844 [48,] 4.455113e-02 8.910225e-02 0.9554489 [49,] 4.042443e-02 8.084886e-02 0.9595756 [50,] 1.852665e-01 3.705329e-01 0.8147335 [51,] 2.427338e-01 4.854676e-01 0.7572662 [52,] 2.123280e-01 4.246559e-01 0.7876720 [53,] 2.002643e-01 4.005285e-01 0.7997357 [54,] 1.749019e-01 3.498039e-01 0.8250981 [55,] 1.749328e-01 3.498656e-01 0.8250672 [56,] 1.828381e-01 3.656763e-01 0.8171619 [57,] 2.121796e-01 4.243591e-01 0.7878204 [58,] 1.955382e-01 3.910765e-01 0.8044618 [59,] 2.231487e-01 4.462973e-01 0.7768513 [60,] 2.720714e-01 5.441429e-01 0.7279286 [61,] 3.345620e-01 6.691240e-01 0.6654380 [62,] 2.969961e-01 5.939923e-01 0.7030039 [63,] 3.021263e-01 6.042526e-01 0.6978737 [64,] 2.654732e-01 5.309463e-01 0.7345268 [65,] 3.111544e-01 6.223087e-01 0.6888456 [66,] 2.896077e-01 5.792154e-01 0.7103923 [67,] 2.545371e-01 5.090742e-01 0.7454629 [68,] 2.647196e-01 5.294391e-01 0.7352804 [69,] 2.617193e-01 5.234386e-01 0.7382807 [70,] 2.608931e-01 5.217863e-01 0.7391069 [71,] 2.247193e-01 4.494387e-01 0.7752807 [72,] 2.606996e-01 5.213992e-01 0.7393004 [73,] 2.801946e-01 5.603893e-01 0.7198054 [74,] 2.492188e-01 4.984377e-01 0.7507812 [75,] 2.174467e-01 4.348934e-01 0.7825533 [76,] 2.113721e-01 4.227442e-01 0.7886279 [77,] 2.059593e-01 4.119186e-01 0.7940407 [78,] 2.012019e-01 4.024037e-01 0.7987981 [79,] 2.576274e-01 5.152547e-01 0.7423726 [80,] 2.744493e-01 5.488986e-01 0.7255507 [81,] 2.715722e-01 5.431444e-01 0.7284278 [82,] 2.355411e-01 4.710822e-01 0.7644589 [83,] 2.119744e-01 4.239488e-01 0.7880256 [84,] 1.803484e-01 3.606968e-01 0.8196516 [85,] 1.796686e-01 3.593372e-01 0.8203314 [86,] 1.586556e-01 3.173111e-01 0.8413444 [87,] 1.410488e-01 2.820975e-01 0.8589512 [88,] 1.266473e-01 2.532946e-01 0.8733527 [89,] 1.325182e-01 2.650363e-01 0.8674818 [90,] 1.542600e-01 3.085201e-01 0.8457400 [91,] 1.287901e-01 2.575802e-01 0.8712099 [92,] 1.116882e-01 2.233764e-01 0.8883118 [93,] 9.961448e-02 1.992290e-01 0.9003855 [94,] 8.482241e-02 1.696448e-01 0.9151776 [95,] 8.373236e-02 1.674647e-01 0.9162676 [96,] 1.293958e-01 2.587915e-01 0.8706042 [97,] 1.617486e-01 3.234972e-01 0.8382514 [98,] 2.004746e-01 4.009492e-01 0.7995254 [99,] 1.769885e-01 3.539769e-01 0.8230115 [100,] 1.630743e-01 3.261486e-01 0.8369257 [101,] 1.403375e-01 2.806750e-01 0.8596625 [102,] 1.399798e-01 2.799596e-01 0.8600202 [103,] 1.522004e-01 3.044008e-01 0.8477996 [104,] 3.152494e-01 6.304987e-01 0.6847506 [105,] 3.015847e-01 6.031693e-01 0.6984153 [106,] 2.931178e-01 5.862356e-01 0.7068822 [107,] 2.744944e-01 5.489887e-01 0.7255056 [108,] 2.841665e-01 5.683329e-01 0.7158335 [109,] 2.914839e-01 5.829678e-01 0.7085161 [110,] 2.752826e-01 5.505652e-01 0.7247174 [111,] 4.337877e-01 8.675755e-01 0.5662123 [112,] 5.048569e-01 9.902862e-01 0.4951431 [113,] 4.633630e-01 9.267260e-01 0.5366370 [114,] 5.161522e-01 9.676957e-01 0.4838478 [115,] 5.521470e-01 8.957060e-01 0.4478530 [116,] 7.510591e-01 4.978817e-01 0.2489409 [117,] 7.151158e-01 5.697683e-01 0.2848842 [118,] 6.914704e-01 6.170592e-01 0.3085296 [119,] 6.973522e-01 6.052957e-01 0.3026478 [120,] 7.145913e-01 5.708173e-01 0.2854087 [121,] 7.612198e-01 4.775603e-01 0.2387802 [122,] 7.645170e-01 4.709660e-01 0.2354830 [123,] 7.519138e-01 4.961725e-01 0.2480862 [124,] 7.368290e-01 5.263421e-01 0.2631710 [125,] 7.691266e-01 4.617468e-01 0.2308734 [126,] 7.225045e-01 5.549910e-01 0.2774955 [127,] 7.540178e-01 4.919643e-01 0.2459822 [128,] 7.244500e-01 5.511000e-01 0.2755500 [129,] 7.180076e-01 5.639847e-01 0.2819924 [130,] 7.056179e-01 5.887643e-01 0.2943821 [131,] 7.299402e-01 5.401196e-01 0.2700598 [132,] 8.402021e-01 3.195959e-01 0.1597979 [133,] 8.049079e-01 3.901843e-01 0.1950921 [134,] 7.577030e-01 4.845940e-01 0.2422970 [135,] 7.302020e-01 5.395960e-01 0.2697980 [136,] 6.658555e-01 6.682890e-01 0.3341445 [137,] 5.876684e-01 8.246632e-01 0.4123316 [138,] 7.809775e-01 4.380450e-01 0.2190225 [139,] 7.100172e-01 5.799655e-01 0.2899828 [140,] 6.545472e-01 6.909056e-01 0.3454528 [141,] 6.535730e-01 6.928539e-01 0.3464270 [142,] 8.498228e-01 3.003544e-01 0.1501772 [143,] 7.624901e-01 4.750198e-01 0.2375099 [144,] 7.228798e-01 5.542405e-01 0.2771202 [145,] 7.104527e-01 5.790945e-01 0.2895473 [146,] 7.594741e-01 4.810518e-01 0.2405259 > postscript(file="/var/wessaorg/rcomp/tmp/1x5cm1386521634.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2zrh51386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3x9m71386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4na2v1386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5d8a21386521634.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 6 12.7687615 -4.5114159 -4.5707673 -1.4044689 -3.2491734 -2.9294619 7 8 9 10 11 12 3.3986656 -7.2058960 4.8599607 10.8726355 8.7604526 7.0660784 13 14 15 16 17 18 -29.1836515 -1.2708514 -2.7084181 -0.2794616 -4.5004017 8.7972063 19 20 21 22 23 24 30.6199516 1.6985483 14.6550240 18.6127687 29.8962235 23.3266525 25 26 27 28 29 30 16.0789304 9.6026967 21.8580665 -6.4045001 -4.8751505 14.5331422 31 32 33 34 35 36 -0.9158338 7.3541339 16.4525285 17.2801993 22.0669047 8.0324724 37 38 39 40 41 42 -4.0598163 5.6301031 16.8083339 18.4008060 17.2319201 6.4753258 43 44 45 46 47 48 -1.9235606 4.2945049 17.8214016 14.7312680 14.1427584 45.8086554 49 50 51 52 53 54 -12.7060630 -13.3276264 -11.1302293 1.1670536 -15.4158281 -0.1079679 55 56 57 58 59 60 19.5923006 22.1562503 18.4773238 15.1286808 30.6076954 34.9223023 61 62 63 64 65 66 14.3205441 30.5943145 8.6895046 -1.2611558 10.8169025 37.1920657 67 68 69 70 71 72 -0.2170814 8.4485464 9.5028594 -1.6505872 14.2154370 5.0398267 73 74 75 76 77 78 -17.4152922 -6.6954738 -8.5416369 7.2044127 -21.1797186 -2.1230075 79 80 81 82 83 84 0.7890234 16.8144353 0.7287899 -3.6269212 0.3312369 -11.9780972 85 86 87 88 89 90 -2.2751505 -13.0619793 0.2350693 -2.6681951 18.9974270 0.7373603 91 92 93 94 95 96 2.3216851 -21.4984173 -17.6458362 10.2310665 -5.3574489 -25.5649742 97 98 99 100 101 102 -19.2520917 -6.1339783 4.9498384 15.9313262 18.9723554 7.3298523 103 104 105 106 107 108 -7.0357777 14.8629761 -14.9997758 -4.3100704 -18.8065006 -5.1607171 109 110 111 112 113 114 -19.4117723 8.4926805 14.3034267 -9.8159066 -15.9376725 13.6238043 115 116 117 118 119 120 6.5203638 0.6124355 -9.7196546 -5.4092093 10.2445042 20.2838774 121 122 123 124 125 126 -8.3848291 17.7938374 -3.3248231 14.2443004 -2.4842041 7.8447609 127 128 129 130 131 132 9.1802576 15.4959726 -19.4752720 -18.7922931 -17.1944221 -24.5785537 133 134 135 136 137 138 -14.7181582 -14.8255021 -0.6649599 -31.6898310 -5.8302941 -25.0924831 139 140 141 142 143 144 -24.6022805 -25.6150686 2.1758853 4.0333080 5.9693771 24.9722282 145 146 147 148 149 150 -0.7843086 26.3019874 8.1618809 -14.4643459 -21.8179543 -16.1378030 151 152 153 154 155 156 6.4886904 -1.4821137 -27.8413139 -3.5549840 -5.1170363 -28.4965954 157 158 159 160 161 162 -25.5748679 -7.1099855 -28.7949980 5.6626398 18.2245278 -14.7904266 163 164 165 166 167 168 8.5865902 -16.5939691 6.2175268 32.5295276 -0.9069044 12.8013955 169 170 171 172 173 174 -10.8965828 -6.0231023 3.7686143 -22.1989935 -19.9273667 -14.5847619 175 176 177 178 179 180 -20.8450755 -18.7326375 -17.4900030 -5.0745130 -5.8502082 0.6352480 181 182 183 184 185 186 0.3867237 -3.9398184 -17.5925710 -13.6636600 -15.5166903 -18.2756277 187 188 189 190 191 192 -43.1735949 -52.8618501 -24.3019666 -2.5643379 -8.2634604 15.1663115 193 194 195 -8.9493191 8.2292599 32.7038786 > postscript(file="/var/wessaorg/rcomp/tmp/6ohhv1386521634.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 12.7687615 NA 1 -4.5114159 12.7687615 2 -4.5707673 -4.5114159 3 -1.4044689 -4.5707673 4 -3.2491734 -1.4044689 5 -2.9294619 -3.2491734 6 3.3986656 -2.9294619 7 -7.2058960 3.3986656 8 4.8599607 -7.2058960 9 10.8726355 4.8599607 10 8.7604526 10.8726355 11 7.0660784 8.7604526 12 -29.1836515 7.0660784 13 -1.2708514 -29.1836515 14 -2.7084181 -1.2708514 15 -0.2794616 -2.7084181 16 -4.5004017 -0.2794616 17 8.7972063 -4.5004017 18 30.6199516 8.7972063 19 1.6985483 30.6199516 20 14.6550240 1.6985483 21 18.6127687 14.6550240 22 29.8962235 18.6127687 23 23.3266525 29.8962235 24 16.0789304 23.3266525 25 9.6026967 16.0789304 26 21.8580665 9.6026967 27 -6.4045001 21.8580665 28 -4.8751505 -6.4045001 29 14.5331422 -4.8751505 30 -0.9158338 14.5331422 31 7.3541339 -0.9158338 32 16.4525285 7.3541339 33 17.2801993 16.4525285 34 22.0669047 17.2801993 35 8.0324724 22.0669047 36 -4.0598163 8.0324724 37 5.6301031 -4.0598163 38 16.8083339 5.6301031 39 18.4008060 16.8083339 40 17.2319201 18.4008060 41 6.4753258 17.2319201 42 -1.9235606 6.4753258 43 4.2945049 -1.9235606 44 17.8214016 4.2945049 45 14.7312680 17.8214016 46 14.1427584 14.7312680 47 45.8086554 14.1427584 48 -12.7060630 45.8086554 49 -13.3276264 -12.7060630 50 -11.1302293 -13.3276264 51 1.1670536 -11.1302293 52 -15.4158281 1.1670536 53 -0.1079679 -15.4158281 54 19.5923006 -0.1079679 55 22.1562503 19.5923006 56 18.4773238 22.1562503 57 15.1286808 18.4773238 58 30.6076954 15.1286808 59 34.9223023 30.6076954 60 14.3205441 34.9223023 61 30.5943145 14.3205441 62 8.6895046 30.5943145 63 -1.2611558 8.6895046 64 10.8169025 -1.2611558 65 37.1920657 10.8169025 66 -0.2170814 37.1920657 67 8.4485464 -0.2170814 68 9.5028594 8.4485464 69 -1.6505872 9.5028594 70 14.2154370 -1.6505872 71 5.0398267 14.2154370 72 -17.4152922 5.0398267 73 -6.6954738 -17.4152922 74 -8.5416369 -6.6954738 75 7.2044127 -8.5416369 76 -21.1797186 7.2044127 77 -2.1230075 -21.1797186 78 0.7890234 -2.1230075 79 16.8144353 0.7890234 80 0.7287899 16.8144353 81 -3.6269212 0.7287899 82 0.3312369 -3.6269212 83 -11.9780972 0.3312369 84 -2.2751505 -11.9780972 85 -13.0619793 -2.2751505 86 0.2350693 -13.0619793 87 -2.6681951 0.2350693 88 18.9974270 -2.6681951 89 0.7373603 18.9974270 90 2.3216851 0.7373603 91 -21.4984173 2.3216851 92 -17.6458362 -21.4984173 93 10.2310665 -17.6458362 94 -5.3574489 10.2310665 95 -25.5649742 -5.3574489 96 -19.2520917 -25.5649742 97 -6.1339783 -19.2520917 98 4.9498384 -6.1339783 99 15.9313262 4.9498384 100 18.9723554 15.9313262 101 7.3298523 18.9723554 102 -7.0357777 7.3298523 103 14.8629761 -7.0357777 104 -14.9997758 14.8629761 105 -4.3100704 -14.9997758 106 -18.8065006 -4.3100704 107 -5.1607171 -18.8065006 108 -19.4117723 -5.1607171 109 8.4926805 -19.4117723 110 14.3034267 8.4926805 111 -9.8159066 14.3034267 112 -15.9376725 -9.8159066 113 13.6238043 -15.9376725 114 6.5203638 13.6238043 115 0.6124355 6.5203638 116 -9.7196546 0.6124355 117 -5.4092093 -9.7196546 118 10.2445042 -5.4092093 119 20.2838774 10.2445042 120 -8.3848291 20.2838774 121 17.7938374 -8.3848291 122 -3.3248231 17.7938374 123 14.2443004 -3.3248231 124 -2.4842041 14.2443004 125 7.8447609 -2.4842041 126 9.1802576 7.8447609 127 15.4959726 9.1802576 128 -19.4752720 15.4959726 129 -18.7922931 -19.4752720 130 -17.1944221 -18.7922931 131 -24.5785537 -17.1944221 132 -14.7181582 -24.5785537 133 -14.8255021 -14.7181582 134 -0.6649599 -14.8255021 135 -31.6898310 -0.6649599 136 -5.8302941 -31.6898310 137 -25.0924831 -5.8302941 138 -24.6022805 -25.0924831 139 -25.6150686 -24.6022805 140 2.1758853 -25.6150686 141 4.0333080 2.1758853 142 5.9693771 4.0333080 143 24.9722282 5.9693771 144 -0.7843086 24.9722282 145 26.3019874 -0.7843086 146 8.1618809 26.3019874 147 -14.4643459 8.1618809 148 -21.8179543 -14.4643459 149 -16.1378030 -21.8179543 150 6.4886904 -16.1378030 151 -1.4821137 6.4886904 152 -27.8413139 -1.4821137 153 -3.5549840 -27.8413139 154 -5.1170363 -3.5549840 155 -28.4965954 -5.1170363 156 -25.5748679 -28.4965954 157 -7.1099855 -25.5748679 158 -28.7949980 -7.1099855 159 5.6626398 -28.7949980 160 18.2245278 5.6626398 161 -14.7904266 18.2245278 162 8.5865902 -14.7904266 163 -16.5939691 8.5865902 164 6.2175268 -16.5939691 165 32.5295276 6.2175268 166 -0.9069044 32.5295276 167 12.8013955 -0.9069044 168 -10.8965828 12.8013955 169 -6.0231023 -10.8965828 170 3.7686143 -6.0231023 171 -22.1989935 3.7686143 172 -19.9273667 -22.1989935 173 -14.5847619 -19.9273667 174 -20.8450755 -14.5847619 175 -18.7326375 -20.8450755 176 -17.4900030 -18.7326375 177 -5.0745130 -17.4900030 178 -5.8502082 -5.0745130 179 0.6352480 -5.8502082 180 0.3867237 0.6352480 181 -3.9398184 0.3867237 182 -17.5925710 -3.9398184 183 -13.6636600 -17.5925710 184 -15.5166903 -13.6636600 185 -18.2756277 -15.5166903 186 -43.1735949 -18.2756277 187 -52.8618501 -43.1735949 188 -24.3019666 -52.8618501 189 -2.5643379 -24.3019666 190 -8.2634604 -2.5643379 191 15.1663115 -8.2634604 192 -8.9493191 15.1663115 193 8.2292599 -8.9493191 194 32.7038786 8.2292599 195 NA 32.7038786 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -4.5114159 12.7687615 [2,] -4.5707673 -4.5114159 [3,] -1.4044689 -4.5707673 [4,] -3.2491734 -1.4044689 [5,] -2.9294619 -3.2491734 [6,] 3.3986656 -2.9294619 [7,] -7.2058960 3.3986656 [8,] 4.8599607 -7.2058960 [9,] 10.8726355 4.8599607 [10,] 8.7604526 10.8726355 [11,] 7.0660784 8.7604526 [12,] -29.1836515 7.0660784 [13,] -1.2708514 -29.1836515 [14,] -2.7084181 -1.2708514 [15,] -0.2794616 -2.7084181 [16,] -4.5004017 -0.2794616 [17,] 8.7972063 -4.5004017 [18,] 30.6199516 8.7972063 [19,] 1.6985483 30.6199516 [20,] 14.6550240 1.6985483 [21,] 18.6127687 14.6550240 [22,] 29.8962235 18.6127687 [23,] 23.3266525 29.8962235 [24,] 16.0789304 23.3266525 [25,] 9.6026967 16.0789304 [26,] 21.8580665 9.6026967 [27,] -6.4045001 21.8580665 [28,] -4.8751505 -6.4045001 [29,] 14.5331422 -4.8751505 [30,] -0.9158338 14.5331422 [31,] 7.3541339 -0.9158338 [32,] 16.4525285 7.3541339 [33,] 17.2801993 16.4525285 [34,] 22.0669047 17.2801993 [35,] 8.0324724 22.0669047 [36,] -4.0598163 8.0324724 [37,] 5.6301031 -4.0598163 [38,] 16.8083339 5.6301031 [39,] 18.4008060 16.8083339 [40,] 17.2319201 18.4008060 [41,] 6.4753258 17.2319201 [42,] -1.9235606 6.4753258 [43,] 4.2945049 -1.9235606 [44,] 17.8214016 4.2945049 [45,] 14.7312680 17.8214016 [46,] 14.1427584 14.7312680 [47,] 45.8086554 14.1427584 [48,] -12.7060630 45.8086554 [49,] -13.3276264 -12.7060630 [50,] -11.1302293 -13.3276264 [51,] 1.1670536 -11.1302293 [52,] -15.4158281 1.1670536 [53,] -0.1079679 -15.4158281 [54,] 19.5923006 -0.1079679 [55,] 22.1562503 19.5923006 [56,] 18.4773238 22.1562503 [57,] 15.1286808 18.4773238 [58,] 30.6076954 15.1286808 [59,] 34.9223023 30.6076954 [60,] 14.3205441 34.9223023 [61,] 30.5943145 14.3205441 [62,] 8.6895046 30.5943145 [63,] -1.2611558 8.6895046 [64,] 10.8169025 -1.2611558 [65,] 37.1920657 10.8169025 [66,] -0.2170814 37.1920657 [67,] 8.4485464 -0.2170814 [68,] 9.5028594 8.4485464 [69,] -1.6505872 9.5028594 [70,] 14.2154370 -1.6505872 [71,] 5.0398267 14.2154370 [72,] -17.4152922 5.0398267 [73,] -6.6954738 -17.4152922 [74,] -8.5416369 -6.6954738 [75,] 7.2044127 -8.5416369 [76,] -21.1797186 7.2044127 [77,] -2.1230075 -21.1797186 [78,] 0.7890234 -2.1230075 [79,] 16.8144353 0.7890234 [80,] 0.7287899 16.8144353 [81,] -3.6269212 0.7287899 [82,] 0.3312369 -3.6269212 [83,] -11.9780972 0.3312369 [84,] -2.2751505 -11.9780972 [85,] -13.0619793 -2.2751505 [86,] 0.2350693 -13.0619793 [87,] -2.6681951 0.2350693 [88,] 18.9974270 -2.6681951 [89,] 0.7373603 18.9974270 [90,] 2.3216851 0.7373603 [91,] -21.4984173 2.3216851 [92,] -17.6458362 -21.4984173 [93,] 10.2310665 -17.6458362 [94,] -5.3574489 10.2310665 [95,] -25.5649742 -5.3574489 [96,] -19.2520917 -25.5649742 [97,] -6.1339783 -19.2520917 [98,] 4.9498384 -6.1339783 [99,] 15.9313262 4.9498384 [100,] 18.9723554 15.9313262 [101,] 7.3298523 18.9723554 [102,] -7.0357777 7.3298523 [103,] 14.8629761 -7.0357777 [104,] -14.9997758 14.8629761 [105,] -4.3100704 -14.9997758 [106,] -18.8065006 -4.3100704 [107,] -5.1607171 -18.8065006 [108,] -19.4117723 -5.1607171 [109,] 8.4926805 -19.4117723 [110,] 14.3034267 8.4926805 [111,] -9.8159066 14.3034267 [112,] -15.9376725 -9.8159066 [113,] 13.6238043 -15.9376725 [114,] 6.5203638 13.6238043 [115,] 0.6124355 6.5203638 [116,] -9.7196546 0.6124355 [117,] -5.4092093 -9.7196546 [118,] 10.2445042 -5.4092093 [119,] 20.2838774 10.2445042 [120,] -8.3848291 20.2838774 [121,] 17.7938374 -8.3848291 [122,] -3.3248231 17.7938374 [123,] 14.2443004 -3.3248231 [124,] -2.4842041 14.2443004 [125,] 7.8447609 -2.4842041 [126,] 9.1802576 7.8447609 [127,] 15.4959726 9.1802576 [128,] -19.4752720 15.4959726 [129,] -18.7922931 -19.4752720 [130,] -17.1944221 -18.7922931 [131,] -24.5785537 -17.1944221 [132,] -14.7181582 -24.5785537 [133,] -14.8255021 -14.7181582 [134,] -0.6649599 -14.8255021 [135,] -31.6898310 -0.6649599 [136,] -5.8302941 -31.6898310 [137,] -25.0924831 -5.8302941 [138,] -24.6022805 -25.0924831 [139,] -25.6150686 -24.6022805 [140,] 2.1758853 -25.6150686 [141,] 4.0333080 2.1758853 [142,] 5.9693771 4.0333080 [143,] 24.9722282 5.9693771 [144,] -0.7843086 24.9722282 [145,] 26.3019874 -0.7843086 [146,] 8.1618809 26.3019874 [147,] -14.4643459 8.1618809 [148,] -21.8179543 -14.4643459 [149,] -16.1378030 -21.8179543 [150,] 6.4886904 -16.1378030 [151,] -1.4821137 6.4886904 [152,] -27.8413139 -1.4821137 [153,] -3.5549840 -27.8413139 [154,] -5.1170363 -3.5549840 [155,] -28.4965954 -5.1170363 [156,] -25.5748679 -28.4965954 [157,] -7.1099855 -25.5748679 [158,] -28.7949980 -7.1099855 [159,] 5.6626398 -28.7949980 [160,] 18.2245278 5.6626398 [161,] -14.7904266 18.2245278 [162,] 8.5865902 -14.7904266 [163,] -16.5939691 8.5865902 [164,] 6.2175268 -16.5939691 [165,] 32.5295276 6.2175268 [166,] -0.9069044 32.5295276 [167,] 12.8013955 -0.9069044 [168,] -10.8965828 12.8013955 [169,] -6.0231023 -10.8965828 [170,] 3.7686143 -6.0231023 [171,] -22.1989935 3.7686143 [172,] -19.9273667 -22.1989935 [173,] -14.5847619 -19.9273667 [174,] -20.8450755 -14.5847619 [175,] -18.7326375 -20.8450755 [176,] -17.4900030 -18.7326375 [177,] -5.0745130 -17.4900030 [178,] -5.8502082 -5.0745130 [179,] 0.6352480 -5.8502082 [180,] 0.3867237 0.6352480 [181,] -3.9398184 0.3867237 [182,] -17.5925710 -3.9398184 [183,] -13.6636600 -17.5925710 [184,] -15.5166903 -13.6636600 [185,] -18.2756277 -15.5166903 [186,] -43.1735949 -18.2756277 [187,] -52.8618501 -43.1735949 [188,] -24.3019666 -52.8618501 [189,] -2.5643379 -24.3019666 [190,] -8.2634604 -2.5643379 [191,] 15.1663115 -8.2634604 [192,] -8.9493191 15.1663115 [193,] 8.2292599 -8.9493191 [194,] 32.7038786 8.2292599 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -4.5114159 12.7687615 2 -4.5707673 -4.5114159 3 -1.4044689 -4.5707673 4 -3.2491734 -1.4044689 5 -2.9294619 -3.2491734 6 3.3986656 -2.9294619 7 -7.2058960 3.3986656 8 4.8599607 -7.2058960 9 10.8726355 4.8599607 10 8.7604526 10.8726355 11 7.0660784 8.7604526 12 -29.1836515 7.0660784 13 -1.2708514 -29.1836515 14 -2.7084181 -1.2708514 15 -0.2794616 -2.7084181 16 -4.5004017 -0.2794616 17 8.7972063 -4.5004017 18 30.6199516 8.7972063 19 1.6985483 30.6199516 20 14.6550240 1.6985483 21 18.6127687 14.6550240 22 29.8962235 18.6127687 23 23.3266525 29.8962235 24 16.0789304 23.3266525 25 9.6026967 16.0789304 26 21.8580665 9.6026967 27 -6.4045001 21.8580665 28 -4.8751505 -6.4045001 29 14.5331422 -4.8751505 30 -0.9158338 14.5331422 31 7.3541339 -0.9158338 32 16.4525285 7.3541339 33 17.2801993 16.4525285 34 22.0669047 17.2801993 35 8.0324724 22.0669047 36 -4.0598163 8.0324724 37 5.6301031 -4.0598163 38 16.8083339 5.6301031 39 18.4008060 16.8083339 40 17.2319201 18.4008060 41 6.4753258 17.2319201 42 -1.9235606 6.4753258 43 4.2945049 -1.9235606 44 17.8214016 4.2945049 45 14.7312680 17.8214016 46 14.1427584 14.7312680 47 45.8086554 14.1427584 48 -12.7060630 45.8086554 49 -13.3276264 -12.7060630 50 -11.1302293 -13.3276264 51 1.1670536 -11.1302293 52 -15.4158281 1.1670536 53 -0.1079679 -15.4158281 54 19.5923006 -0.1079679 55 22.1562503 19.5923006 56 18.4773238 22.1562503 57 15.1286808 18.4773238 58 30.6076954 15.1286808 59 34.9223023 30.6076954 60 14.3205441 34.9223023 61 30.5943145 14.3205441 62 8.6895046 30.5943145 63 -1.2611558 8.6895046 64 10.8169025 -1.2611558 65 37.1920657 10.8169025 66 -0.2170814 37.1920657 67 8.4485464 -0.2170814 68 9.5028594 8.4485464 69 -1.6505872 9.5028594 70 14.2154370 -1.6505872 71 5.0398267 14.2154370 72 -17.4152922 5.0398267 73 -6.6954738 -17.4152922 74 -8.5416369 -6.6954738 75 7.2044127 -8.5416369 76 -21.1797186 7.2044127 77 -2.1230075 -21.1797186 78 0.7890234 -2.1230075 79 16.8144353 0.7890234 80 0.7287899 16.8144353 81 -3.6269212 0.7287899 82 0.3312369 -3.6269212 83 -11.9780972 0.3312369 84 -2.2751505 -11.9780972 85 -13.0619793 -2.2751505 86 0.2350693 -13.0619793 87 -2.6681951 0.2350693 88 18.9974270 -2.6681951 89 0.7373603 18.9974270 90 2.3216851 0.7373603 91 -21.4984173 2.3216851 92 -17.6458362 -21.4984173 93 10.2310665 -17.6458362 94 -5.3574489 10.2310665 95 -25.5649742 -5.3574489 96 -19.2520917 -25.5649742 97 -6.1339783 -19.2520917 98 4.9498384 -6.1339783 99 15.9313262 4.9498384 100 18.9723554 15.9313262 101 7.3298523 18.9723554 102 -7.0357777 7.3298523 103 14.8629761 -7.0357777 104 -14.9997758 14.8629761 105 -4.3100704 -14.9997758 106 -18.8065006 -4.3100704 107 -5.1607171 -18.8065006 108 -19.4117723 -5.1607171 109 8.4926805 -19.4117723 110 14.3034267 8.4926805 111 -9.8159066 14.3034267 112 -15.9376725 -9.8159066 113 13.6238043 -15.9376725 114 6.5203638 13.6238043 115 0.6124355 6.5203638 116 -9.7196546 0.6124355 117 -5.4092093 -9.7196546 118 10.2445042 -5.4092093 119 20.2838774 10.2445042 120 -8.3848291 20.2838774 121 17.7938374 -8.3848291 122 -3.3248231 17.7938374 123 14.2443004 -3.3248231 124 -2.4842041 14.2443004 125 7.8447609 -2.4842041 126 9.1802576 7.8447609 127 15.4959726 9.1802576 128 -19.4752720 15.4959726 129 -18.7922931 -19.4752720 130 -17.1944221 -18.7922931 131 -24.5785537 -17.1944221 132 -14.7181582 -24.5785537 133 -14.8255021 -14.7181582 134 -0.6649599 -14.8255021 135 -31.6898310 -0.6649599 136 -5.8302941 -31.6898310 137 -25.0924831 -5.8302941 138 -24.6022805 -25.0924831 139 -25.6150686 -24.6022805 140 2.1758853 -25.6150686 141 4.0333080 2.1758853 142 5.9693771 4.0333080 143 24.9722282 5.9693771 144 -0.7843086 24.9722282 145 26.3019874 -0.7843086 146 8.1618809 26.3019874 147 -14.4643459 8.1618809 148 -21.8179543 -14.4643459 149 -16.1378030 -21.8179543 150 6.4886904 -16.1378030 151 -1.4821137 6.4886904 152 -27.8413139 -1.4821137 153 -3.5549840 -27.8413139 154 -5.1170363 -3.5549840 155 -28.4965954 -5.1170363 156 -25.5748679 -28.4965954 157 -7.1099855 -25.5748679 158 -28.7949980 -7.1099855 159 5.6626398 -28.7949980 160 18.2245278 5.6626398 161 -14.7904266 18.2245278 162 8.5865902 -14.7904266 163 -16.5939691 8.5865902 164 6.2175268 -16.5939691 165 32.5295276 6.2175268 166 -0.9069044 32.5295276 167 12.8013955 -0.9069044 168 -10.8965828 12.8013955 169 -6.0231023 -10.8965828 170 3.7686143 -6.0231023 171 -22.1989935 3.7686143 172 -19.9273667 -22.1989935 173 -14.5847619 -19.9273667 174 -20.8450755 -14.5847619 175 -18.7326375 -20.8450755 176 -17.4900030 -18.7326375 177 -5.0745130 -17.4900030 178 -5.8502082 -5.0745130 179 0.6352480 -5.8502082 180 0.3867237 0.6352480 181 -3.9398184 0.3867237 182 -17.5925710 -3.9398184 183 -13.6636600 -17.5925710 184 -15.5166903 -13.6636600 185 -18.2756277 -15.5166903 186 -43.1735949 -18.2756277 187 -52.8618501 -43.1735949 188 -24.3019666 -52.8618501 189 -2.5643379 -24.3019666 190 -8.2634604 -2.5643379 191 15.1663115 -8.2634604 192 -8.9493191 15.1663115 193 8.2292599 -8.9493191 194 32.7038786 8.2292599 > 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/wessaorg/rcomp/tmp/79chx1386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/85ux51386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/90ns81386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10ug881386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/wessaorg/rcomp/tmp/11im6b1386521634.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/wessaorg/rcomp/tmp/1270mr1386521634.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/wessaorg/rcomp/tmp/13l85j1386521634.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/wessaorg/rcomp/tmp/14i7kw1386521634.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/wessaorg/rcomp/tmp/151vy21386521634.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/wessaorg/rcomp/tmp/168a3a1386521634.tab") + } > > try(system("convert tmp/1x5cm1386521634.ps tmp/1x5cm1386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/2zrh51386521634.ps tmp/2zrh51386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/3x9m71386521634.ps tmp/3x9m71386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/4na2v1386521634.ps tmp/4na2v1386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/5d8a21386521634.ps tmp/5d8a21386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/6ohhv1386521634.ps tmp/6ohhv1386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/79chx1386521634.ps tmp/79chx1386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/85ux51386521634.ps tmp/85ux51386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/90ns81386521634.ps tmp/90ns81386521634.png",intern=TRUE)) character(0) > try(system("convert tmp/10ug881386521634.ps tmp/10ug881386521634.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 33.088 5.919 39.374