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 + ,0.284654 + ,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 + ,0.368674 + ,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 + ,0.332634 + ,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 + 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+ ,0.659132 + ,-6.710219 + ,0.149694 + ,1.91399 + ,0.121777 + ,201.774 + ,262.707 + ,78.228 + ,0.00694 + ,0.00003 + ,0.00412 + ,0.00396 + ,0.01235 + ,0.02574 + ,0.255 + ,0.01454 + ,0.01582 + ,0.01758 + ,0.04363 + ,0.04441 + ,19.368 + ,0 + ,0.508479 + ,0.683761 + ,-6.934474 + ,0.15989 + ,2.316346 + ,0.112838 + ,174.188 + ,230.978 + ,94.261 + ,0.00459 + ,0.00003 + ,0.00263 + ,0.00259 + ,0.0079 + ,0.04087 + ,0.405 + ,0.02336 + ,0.02498 + ,0.02745 + ,0.07008 + ,0.02764 + ,19.517 + ,0 + ,0.448439 + ,0.657899 + ,-6.538586 + ,0.121952 + ,2.657476 + ,0.13305 + ,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 + ,0.168895 + ,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 + ,0.131728 + ,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 + ,0.123306 + ,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 + ,0.148569) + ,dim=c(23 + ,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' + ,'PPE') + ,1:195)) > y <- array(NA,dim=c(23,195),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','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 = '18' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '18' > #'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 RPDE MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) 1 0.414783 119.992 157.302 74.997 0.00784 2 0.458359 122.400 148.650 113.819 0.00968 3 0.429895 116.682 131.111 111.555 0.01050 4 0.434969 116.676 137.871 111.366 0.00997 5 0.417356 116.014 141.781 110.655 0.01284 6 0.415564 120.552 131.162 113.787 0.00968 7 0.596040 120.267 137.244 114.820 0.00333 8 0.637420 107.332 113.840 104.315 0.00290 9 0.615551 95.730 132.068 91.754 0.00551 10 0.547037 95.056 120.103 91.226 0.00532 11 0.611137 88.333 112.240 84.072 0.00505 12 0.583390 91.904 115.871 86.292 0.00540 13 0.460600 136.926 159.866 131.276 0.00293 14 0.430166 139.173 179.139 76.556 0.00390 15 0.474791 152.845 163.305 75.836 0.00294 16 0.565924 142.167 217.455 83.159 0.00369 17 0.567380 144.188 349.259 82.764 0.00544 18 0.631099 168.778 232.181 75.603 0.00718 19 0.665318 153.046 175.829 68.623 0.00742 20 0.649554 156.405 189.398 142.822 0.00768 21 0.660125 153.848 165.738 65.782 0.00840 22 0.629017 153.880 172.860 78.128 0.00480 23 0.619060 167.930 193.221 79.068 0.00442 24 0.537264 173.917 192.735 86.180 0.00476 25 0.397937 163.656 200.841 76.779 0.00742 26 0.522746 104.400 206.002 77.968 0.00633 27 0.418622 171.041 208.313 75.501 0.00455 28 0.358773 146.845 208.701 81.737 0.00496 29 0.470478 155.358 227.383 80.055 0.00310 30 0.427785 162.568 198.346 77.630 0.00502 31 0.422229 197.076 206.896 192.055 0.00289 32 0.432439 199.228 209.512 192.091 0.00241 33 0.465946 198.383 215.203 193.104 0.00212 34 0.368535 202.266 211.604 197.079 0.00180 35 0.340068 203.184 211.526 196.160 0.00178 36 0.344252 201.464 210.565 195.708 0.00198 37 0.360148 177.876 192.921 168.013 0.00411 38 0.341435 176.170 185.604 163.564 0.00369 39 0.403884 180.198 201.249 175.456 0.00284 40 0.396793 187.733 202.324 173.015 0.00316 41 0.326480 186.163 197.724 177.584 0.00298 42 0.306443 184.055 196.537 166.977 0.00258 43 0.305062 237.226 247.326 225.227 0.00298 44 0.457702 241.404 248.834 232.483 0.00281 45 0.438296 243.439 250.912 232.435 0.00210 46 0.431285 242.852 255.034 227.911 0.00225 47 0.467489 245.510 262.090 231.848 0.00235 48 0.610367 252.455 261.487 182.786 0.00185 49 0.579597 122.188 128.611 115.765 0.00524 50 0.538688 122.964 130.049 114.676 0.00428 51 0.553134 124.445 135.069 117.495 0.00431 52 0.507504 126.344 134.231 112.773 0.00448 53 0.459766 128.001 138.052 122.080 0.00436 54 0.420383 129.336 139.867 118.604 0.00490 55 0.536009 108.807 134.656 102.874 0.00761 56 0.558586 109.860 126.358 104.437 0.00874 57 0.541781 110.417 131.067 103.370 0.00784 58 0.530529 117.274 129.916 110.402 0.00752 59 0.540049 116.879 131.897 108.153 0.00788 60 0.547975 114.847 271.314 104.680 0.00867 61 0.341788 209.144 237.494 109.379 0.00282 62 0.447979 223.365 238.987 98.664 0.00264 63 0.364867 222.236 231.345 205.495 0.00266 64 0.256570 228.832 234.619 223.634 0.00296 65 0.276850 229.401 252.221 221.156 0.00205 66 0.305429 228.969 239.541 113.201 0.00238 67 0.460139 140.341 159.774 67.021 0.00817 68 0.498133 136.969 166.607 66.004 0.00923 69 0.513237 143.533 162.215 65.809 0.01101 70 0.487407 148.090 162.824 67.343 0.00762 71 0.489345 142.729 162.408 65.476 0.00831 72 0.543299 136.358 176.595 65.750 0.00971 73 0.495954 120.080 139.710 111.208 0.00405 74 0.509127 112.014 588.518 107.024 0.00533 75 0.437031 110.793 128.101 107.316 0.00494 76 0.463514 110.707 122.611 105.007 0.00516 77 0.489538 112.876 148.826 106.981 0.00500 78 0.429484 110.568 125.394 106.821 0.00462 79 0.644954 95.385 102.145 90.264 0.00608 80 0.594387 100.770 115.697 85.545 0.01038 81 0.544805 96.106 108.664 84.510 0.00694 82 0.576084 95.605 107.715 87.549 0.00702 83 0.554610 100.960 110.019 95.628 0.00606 84 0.576644 98.804 102.305 87.804 0.00432 85 0.556494 176.858 205.560 75.344 0.00747 86 0.583574 180.978 200.125 155.495 0.00406 87 0.598714 178.222 202.450 141.047 0.00321 88 0.602874 176.281 227.381 125.610 0.00520 89 0.599371 173.898 211.350 74.677 0.00448 90 0.590951 179.711 225.930 144.878 0.00709 91 0.653410 166.605 206.008 78.032 0.00742 92 0.501037 151.955 163.335 147.226 0.00419 93 0.454444 148.272 164.989 142.299 0.00459 94 0.447456 152.125 161.469 76.596 0.00382 95 0.502380 157.821 172.975 68.401 0.00358 96 0.447285 157.447 163.267 149.605 0.00369 97 0.366329 159.116 168.913 144.811 0.00342 98 0.629574 125.036 143.946 116.187 0.01280 99 0.571010 125.791 140.557 96.206 0.01378 100 0.638545 126.512 141.756 99.770 0.01936 101 0.671299 125.641 141.068 116.346 0.03316 102 0.639808 128.451 150.449 75.632 0.01551 103 0.596362 139.224 586.567 66.157 0.03011 104 0.296888 150.258 154.609 75.349 0.00248 105 0.263654 154.003 160.267 128.621 0.00183 106 0.365488 149.689 160.368 133.608 0.00257 107 0.334171 155.078 163.736 144.148 0.00168 108 0.393563 151.884 157.765 133.751 0.00258 109 0.311369 151.989 157.339 132.857 0.00174 110 0.497554 193.030 208.900 80.297 0.00766 111 0.436084 200.714 223.982 89.686 0.00621 112 0.338097 208.519 220.315 199.020 0.00609 113 0.498877 204.664 221.300 189.621 0.00841 114 0.441097 210.141 232.706 185.258 0.00534 115 0.331508 206.327 226.355 92.020 0.00495 116 0.407701 151.872 492.892 69.085 0.00856 117 0.450798 158.219 442.557 71.948 0.00476 118 0.486738 170.756 450.247 79.032 0.00555 119 0.470422 178.285 442.824 82.063 0.00462 120 0.462516 217.116 233.481 93.978 0.00404 121 0.487756 128.940 479.697 88.251 0.00581 122 0.400088 176.824 215.293 83.961 0.00460 123 0.538016 138.190 203.522 83.340 0.00704 124 0.589956 182.018 197.173 79.187 0.00842 125 0.618663 156.239 195.107 79.820 0.00694 126 0.637518 145.174 198.109 80.637 0.00733 127 0.623209 138.145 197.238 81.114 0.00544 128 0.585169 166.888 198.966 79.512 0.00638 129 0.457541 119.031 127.533 109.216 0.00440 130 0.491345 120.078 126.632 105.667 0.00270 131 0.467160 120.289 128.143 100.209 0.00492 132 0.468621 120.256 125.306 104.773 0.00407 133 0.470972 119.056 125.213 86.795 0.00346 134 0.482296 118.747 123.723 109.836 0.00331 135 0.637814 106.516 112.777 93.105 0.00589 136 0.653427 110.453 127.611 105.554 0.00494 137 0.647900 113.400 133.344 107.816 0.00451 138 0.625362 113.166 130.270 100.673 0.00502 139 0.640945 112.239 126.609 104.095 0.00472 140 0.624811 116.150 131.731 109.815 0.00381 141 0.677131 170.368 268.796 79.543 0.00571 142 0.606344 208.083 253.792 91.802 0.00757 143 0.606273 198.458 219.290 148.691 0.00376 144 0.536102 202.805 231.508 86.232 0.00370 145 0.497480 202.544 241.350 164.168 0.00254 146 0.566849 223.361 263.872 87.638 0.00352 147 0.561610 169.774 191.759 151.451 0.01568 148 0.478024 183.520 216.814 161.340 0.01466 149 0.552870 188.620 216.302 165.982 0.01719 150 0.427627 202.632 565.740 177.258 0.01627 151 0.507826 186.695 211.961 149.442 0.01872 152 0.625866 192.818 224.429 168.793 0.03107 153 0.584164 198.116 233.099 174.478 0.02714 154 0.566867 121.345 139.644 98.250 0.00684 155 0.651680 119.100 128.442 88.833 0.00692 156 0.628300 117.870 127.349 95.654 0.00647 157 0.611679 122.336 142.369 94.794 0.00727 158 0.630547 117.963 134.209 100.757 0.01813 159 0.635015 126.144 154.284 97.543 0.00975 160 0.654945 127.930 138.752 112.173 0.00605 161 0.653139 114.238 124.393 77.022 0.00581 162 0.577802 115.322 135.738 107.802 0.00619 163 0.685151 114.554 126.778 91.121 0.00651 164 0.557045 112.150 131.669 97.527 0.00519 165 0.671378 102.273 142.830 85.902 0.00907 166 0.469928 236.200 244.663 102.137 0.00277 167 0.384868 237.323 243.709 229.256 0.00303 168 0.440988 260.105 264.919 237.303 0.00339 169 0.372222 197.569 217.627 90.794 0.00803 170 0.371837 240.301 245.135 219.783 0.00517 171 0.522812 244.990 272.210 239.170 0.00451 172 0.413295 112.547 133.374 105.715 0.00355 173 0.369090 110.739 113.597 100.139 0.00356 174 0.380253 113.715 116.443 96.913 0.00349 175 0.387482 117.004 144.466 99.923 0.00353 176 0.405991 115.380 123.109 108.634 0.00332 177 0.361232 116.388 129.038 108.970 0.00346 178 0.396610 151.737 190.204 129.859 0.00314 179 0.402591 148.790 158.359 138.990 0.00309 180 0.398499 148.143 155.982 135.041 0.00392 181 0.352396 150.440 163.441 144.736 0.00396 182 0.408598 148.462 161.078 141.998 0.00397 183 0.329577 149.818 163.417 144.786 0.00336 184 0.603515 117.226 123.925 106.656 0.00417 185 0.663842 116.848 217.552 99.503 0.00531 186 0.598515 116.286 177.291 96.983 0.00314 187 0.566424 116.556 592.030 86.228 0.00496 188 0.528485 116.342 581.289 94.246 0.00267 189 0.555303 114.563 119.167 86.647 0.00327 190 0.508479 201.774 262.707 78.228 0.00694 191 0.448439 174.188 230.978 94.261 0.00459 192 0.431674 209.516 253.017 89.488 0.00564 193 0.407567 174.688 240.005 74.287 0.01360 194 0.451221 198.764 396.961 74.904 0.00740 195 0.462803 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 MDVP:APQ Shimmer:DDA NHR HNR status 1 0.02182 0.03130 0.02971 0.06545 0.02211 21.033 1 2 0.03134 0.04518 0.04368 0.09403 0.01929 19.085 1 3 0.02757 0.03858 0.03590 0.08270 0.01309 20.651 1 4 0.02924 0.04005 0.03772 0.08771 0.01353 20.644 1 5 0.03490 0.04825 0.04465 0.10470 0.01767 19.649 1 6 0.02328 0.03526 0.03243 0.06985 0.01222 21.378 1 7 0.00779 0.00937 0.01351 0.02337 0.00607 24.886 1 8 0.00829 0.00946 0.01256 0.02487 0.00344 26.892 1 9 0.01073 0.01277 0.01717 0.03218 0.01070 21.812 1 10 0.01441 0.01725 0.02444 0.04324 0.01022 21.862 1 11 0.01079 0.01342 0.01892 0.03237 0.01166 21.118 1 12 0.01424 0.01641 0.02214 0.04272 0.01141 21.414 1 13 0.00656 0.00717 0.01140 0.01968 0.00581 25.703 1 14 0.00728 0.00932 0.01797 0.02184 0.01041 24.889 1 15 0.01064 0.00972 0.01246 0.03191 0.00609 24.922 1 16 0.00772 0.00888 0.01359 0.02316 0.00839 25.175 1 17 0.00969 0.01200 0.02074 0.02908 0.01859 22.333 1 18 0.01441 0.01893 0.03430 0.04322 0.02919 20.376 1 19 0.02471 0.03572 0.05767 0.07413 0.03160 17.280 1 20 0.01721 0.02374 0.04310 0.05164 0.03365 17.153 1 21 0.01667 0.02383 0.04055 0.05000 0.03871 17.536 1 22 0.02021 0.02591 0.04525 0.06062 0.01849 19.493 1 23 0.02228 0.02540 0.04246 0.06685 0.01280 22.468 1 24 0.02187 0.02470 0.03772 0.06562 0.01840 20.422 1 25 0.00738 0.00948 0.01497 0.02214 0.01778 23.831 1 26 0.01732 0.02245 0.03780 0.05197 0.02887 22.066 1 27 0.00889 0.01169 0.01872 0.02666 0.01095 25.908 1 28 0.00883 0.01144 0.01826 0.02650 0.01328 25.119 1 29 0.00769 0.01012 0.01661 0.02307 0.00677 25.970 1 30 0.00793 0.01057 0.01799 0.02380 0.01170 25.678 1 31 0.00563 0.00680 0.00802 0.01689 0.00339 26.775 0 32 0.00504 0.00641 0.00762 0.01513 0.00167 30.940 0 33 0.00640 0.00825 0.00951 0.01919 0.00119 30.775 0 34 0.00469 0.00606 0.00719 0.01407 0.00072 32.684 0 35 0.00468 0.00610 0.00726 0.01403 0.00065 33.047 0 36 0.00586 0.00760 0.00957 0.01758 0.00135 31.732 0 37 0.01154 0.01347 0.01612 0.03463 0.00586 23.216 1 38 0.00938 0.01160 0.01491 0.02814 0.00340 24.951 1 39 0.00726 0.00885 0.01190 0.02177 0.00231 26.738 1 40 0.00829 0.01003 0.01366 0.02488 0.00265 26.310 1 41 0.00774 0.00941 0.01233 0.02321 0.00231 26.822 1 42 0.00742 0.00901 0.01234 0.02226 0.00257 26.453 1 43 0.01035 0.01024 0.01133 0.03104 0.00740 22.736 0 44 0.01006 0.01038 0.01251 0.03017 0.00675 23.145 0 45 0.00777 0.00898 0.01033 0.02330 0.00454 25.368 0 46 0.00847 0.00879 0.01014 0.02542 0.00476 25.032 0 47 0.00906 0.00977 0.01149 0.02719 0.00476 24.602 0 48 0.00614 0.00730 0.00860 0.01841 0.00432 26.805 0 49 0.00855 0.00776 0.01433 0.02566 0.00839 23.162 0 50 0.00930 0.00802 0.01400 0.02789 0.00462 24.971 0 51 0.01241 0.01024 0.01685 0.03724 0.00479 25.135 0 52 0.01143 0.00959 0.01614 0.03429 0.00474 25.030 0 53 0.01323 0.01072 0.01677 0.03969 0.00481 24.692 0 54 0.01396 0.01219 0.01947 0.04188 0.00484 25.429 0 55 0.01483 0.01609 0.02067 0.04450 0.01036 21.028 1 56 0.01789 0.01992 0.02454 0.05368 0.01180 20.767 1 57 0.02032 0.02302 0.02802 0.06097 0.00969 21.422 1 58 0.01189 0.01459 0.01948 0.03568 0.00681 22.817 1 59 0.01394 0.01625 0.02137 0.04183 0.00786 22.603 1 60 0.01805 0.01974 0.02519 0.05414 0.01143 21.660 1 61 0.00975 0.01258 0.01382 0.02925 0.00871 25.554 0 62 0.01013 0.01296 0.01340 0.03039 0.00301 26.138 0 63 0.00867 0.01108 0.01200 0.02602 0.00340 25.856 0 64 0.00882 0.01075 0.01179 0.02647 0.00351 25.964 0 65 0.00769 0.00957 0.01016 0.02308 0.00300 26.415 0 66 0.00942 0.01160 0.01234 0.02827 0.00420 24.547 0 67 0.01830 0.01810 0.02428 0.05490 0.02183 19.560 1 68 0.01638 0.01759 0.02603 0.04914 0.02659 19.979 1 69 0.03152 0.02422 0.03392 0.09455 0.04882 20.338 1 70 0.03357 0.02494 0.03635 0.10070 0.02431 21.718 1 71 0.01868 0.01906 0.02949 0.05605 0.02599 20.264 1 72 0.02749 0.02466 0.03736 0.08247 0.03361 18.570 1 73 0.00974 0.00925 0.01345 0.02921 0.00442 25.742 1 74 0.01373 0.01375 0.01956 0.04120 0.00623 24.178 1 75 0.01432 0.01325 0.01831 0.04295 0.00479 25.438 1 76 0.01284 0.01219 0.01715 0.03851 0.00472 25.197 1 77 0.02413 0.02231 0.02704 0.07238 0.00905 23.370 1 78 0.01284 0.01199 0.01636 0.03852 0.00420 25.820 1 79 0.01803 0.01886 0.02455 0.05408 0.01062 21.875 1 80 0.01773 0.01783 0.02139 0.05320 0.02220 19.200 1 81 0.02266 0.02451 0.02876 0.06799 0.01823 19.055 1 82 0.01792 0.01841 0.02190 0.05377 0.01825 19.659 1 83 0.01371 0.01421 0.01751 0.04114 0.01237 20.536 1 84 0.01277 0.01343 0.01552 0.03831 0.00882 22.244 1 85 0.02679 0.03022 0.03510 0.08037 0.05470 13.893 1 86 0.02107 0.02493 0.02877 0.06321 0.02782 16.176 1 87 0.02073 0.02415 0.02784 0.06219 0.03151 15.924 1 88 0.03671 0.04159 0.04683 0.11012 0.04824 13.922 1 89 0.03788 0.04254 0.04802 0.11363 0.04214 14.739 1 90 0.02297 0.02768 0.03455 0.06892 0.07223 11.866 1 91 0.03650 0.04282 0.05114 0.10949 0.08725 11.744 1 92 0.04421 0.04962 0.05690 0.13262 0.01658 19.664 1 93 0.02383 0.02521 0.03051 0.07150 0.01914 18.780 1 94 0.03341 0.03794 0.04398 0.10024 0.01211 20.969 1 95 0.02062 0.02321 0.02764 0.06185 0.00850 22.219 1 96 0.01813 0.01909 0.02571 0.05439 0.01018 21.693 1 97 0.01806 0.02024 0.02809 0.05417 0.00852 22.663 1 98 0.02135 0.02174 0.03088 0.06406 0.08151 15.338 1 99 0.02542 0.02630 0.03908 0.07625 0.10323 15.433 1 100 0.03611 0.03963 0.05783 0.10833 0.16744 12.435 1 101 0.05358 0.04791 0.06196 0.16074 0.31482 8.867 1 102 0.03223 0.03672 0.05174 0.09669 0.11843 15.060 1 103 0.05551 0.05005 0.06023 0.16654 0.25930 10.489 1 104 0.00522 0.00659 0.01009 0.01567 0.00495 26.759 1 105 0.00469 0.00582 0.00871 0.01406 0.00243 28.409 1 106 0.00660 0.00818 0.01059 0.01979 0.00578 27.421 1 107 0.00522 0.00632 0.00928 0.01567 0.00233 29.746 1 108 0.00633 0.00788 0.01267 0.01898 0.00659 26.833 1 109 0.00455 0.00576 0.00993 0.01364 0.00238 29.928 1 110 0.01771 0.01815 0.02084 0.05312 0.00947 21.934 1 111 0.01192 0.01439 0.01852 0.03576 0.00704 23.239 1 112 0.00952 0.01058 0.01307 0.02855 0.00830 22.407 1 113 0.01277 0.01483 0.01767 0.03831 0.01316 21.305 1 114 0.00861 0.01017 0.01301 0.02583 0.00620 23.671 1 115 0.01107 0.01284 0.01604 0.03320 0.01048 21.864 1 116 0.00796 0.00832 0.01271 0.02389 0.06051 23.693 1 117 0.00606 0.00747 0.01312 0.01818 0.01554 26.356 1 118 0.00757 0.00971 0.01652 0.02270 0.01802 25.690 1 119 0.00617 0.00744 0.01151 0.01851 0.00856 25.020 1 120 0.00679 0.00631 0.01075 0.02038 0.00681 24.581 1 121 0.00849 0.01117 0.01734 0.02548 0.02350 24.743 1 122 0.00534 0.00630 0.01104 0.01603 0.01161 27.166 1 123 0.02587 0.02567 0.03220 0.07761 0.01968 18.305 1 124 0.01372 0.01580 0.01931 0.04115 0.01813 18.784 1 125 0.01289 0.01420 0.01720 0.03867 0.02020 19.196 1 126 0.01235 0.01495 0.01944 0.03706 0.01874 18.857 1 127 0.01484 0.01805 0.02259 0.04451 0.01794 18.178 1 128 0.01547 0.01859 0.02301 0.04641 0.01796 18.330 1 129 0.00538 0.00570 0.00811 0.01614 0.01724 26.842 1 130 0.00476 0.00588 0.00903 0.01428 0.00487 26.369 1 131 0.00703 0.00820 0.01194 0.02110 0.01610 23.949 1 132 0.00721 0.00815 0.01310 0.02164 0.01015 26.017 1 133 0.00633 0.00701 0.00915 0.01898 0.00903 23.389 1 134 0.00490 0.00621 0.00903 0.01471 0.00504 25.619 1 135 0.02683 0.03112 0.03651 0.08050 0.03031 17.060 1 136 0.02229 0.02592 0.03316 0.06688 0.02529 17.707 1 137 0.02385 0.02973 0.04370 0.07154 0.02278 19.013 1 138 0.02896 0.03347 0.04134 0.08689 0.03690 16.747 1 139 0.03070 0.03530 0.04451 0.09211 0.02629 17.366 1 140 0.01514 0.01812 0.02770 0.04543 0.01827 18.801 1 141 0.01713 0.01964 0.02824 0.05139 0.02485 18.540 1 142 0.04016 0.04003 0.04464 0.12047 0.04238 15.648 1 143 0.02055 0.02076 0.02530 0.06165 0.01728 18.702 1 144 0.01117 0.01177 0.01506 0.03350 0.02010 18.687 1 145 0.01475 0.01558 0.02006 0.04426 0.01049 20.680 1 146 0.01379 0.01478 0.01909 0.04137 0.01493 20.366 1 147 0.03804 0.05426 0.08808 0.11411 0.07530 12.359 1 148 0.02865 0.04101 0.06359 0.08595 0.06057 14.367 1 149 0.03474 0.04580 0.06824 0.10422 0.08069 12.298 1 150 0.03515 0.04265 0.06460 0.10546 0.07889 14.989 1 151 0.02699 0.03714 0.06259 0.08096 0.10952 12.529 1 152 0.05647 0.07940 0.13778 0.16942 0.21713 8.441 1 153 0.04284 0.05556 0.08318 0.12851 0.16265 9.449 1 154 0.01340 0.01399 0.02056 0.04019 0.04179 21.520 1 155 0.01484 0.01405 0.02018 0.04451 0.04611 21.824 1 156 0.01659 0.01804 0.02402 0.04977 0.02631 22.431 1 157 0.01205 0.01289 0.01771 0.03615 0.03191 22.953 1 158 0.02610 0.02161 0.02916 0.07830 0.10748 19.075 1 159 0.01500 0.01581 0.02157 0.04499 0.03828 21.534 1 160 0.01360 0.01650 0.03105 0.04079 0.02663 19.651 1 161 0.01579 0.01994 0.04114 0.04736 0.02073 20.437 1 162 0.01644 0.01722 0.02931 0.04933 0.02810 19.388 1 163 0.01864 0.01940 0.03091 0.05592 0.02707 18.954 1 164 0.00967 0.01033 0.01363 0.02902 0.01435 21.219 1 165 0.01579 0.01553 0.02073 0.04736 0.03882 18.447 1 166 0.01410 0.01426 0.01621 0.04231 0.00620 24.078 0 167 0.00696 0.00747 0.00882 0.02089 0.00533 24.679 0 168 0.01186 0.01230 0.01367 0.03557 0.00910 21.083 0 169 0.01279 0.01272 0.01439 0.03836 0.01337 19.269 0 170 0.01176 0.01191 0.01344 0.03529 0.00965 21.020 0 171 0.01084 0.01121 0.01255 0.03253 0.01049 21.528 0 172 0.00664 0.00786 0.01140 0.01992 0.00435 26.436 0 173 0.00754 0.00950 0.01285 0.02261 0.00430 26.550 0 174 0.00748 0.00905 0.01148 0.02245 0.00478 26.547 0 175 0.00881 0.01062 0.01318 0.02643 0.00590 25.445 0 176 0.00812 0.00933 0.01133 0.02436 0.00401 26.005 0 177 0.00874 0.01021 0.01331 0.02623 0.00415 26.143 0 178 0.00728 0.00886 0.01230 0.02184 0.00570 24.151 1 179 0.00839 0.00956 0.01309 0.02518 0.00488 24.412 1 180 0.00725 0.00876 0.01263 0.02175 0.00540 23.683 1 181 0.01321 0.01574 0.02148 0.03964 0.00611 23.133 1 182 0.00950 0.01103 0.01559 0.02849 0.00639 22.866 1 183 0.01155 0.01341 0.01666 0.03464 0.00595 23.008 1 184 0.00864 0.01223 0.01949 0.02592 0.00955 23.079 0 185 0.00810 0.01144 0.01756 0.02429 0.01179 22.085 0 186 0.00667 0.00990 0.01691 0.02001 0.00737 24.199 0 187 0.00820 0.00972 0.01491 0.02460 0.01397 23.958 0 188 0.00631 0.00789 0.01144 0.01892 0.00680 25.023 0 189 0.00557 0.00721 0.01095 0.01672 0.00703 24.775 0 190 0.01454 0.01582 0.01758 0.04363 0.04441 19.368 0 191 0.02336 0.02498 0.02745 0.07008 0.02764 19.517 0 192 0.01604 0.01657 0.01879 0.04812 0.01810 19.147 0 193 0.01268 0.01365 0.01667 0.03804 0.10715 17.883 0 194 0.01265 0.01321 0.01588 0.03794 0.07223 19.020 0 195 0.01026 0.01161 0.01373 0.03078 0.04398 21.209 0 DFA spread1 spread2 D2 PPE 1 0.815285 -4.813031 0.266482 2.301442 0.284654 2 0.819521 -4.075192 0.335590 2.486855 0.368674 3 0.825288 -4.443179 0.311173 2.342259 0.332634 4 0.819235 -4.117501 0.334147 2.405554 0.368975 5 0.823484 -3.747787 0.234513 2.332180 0.410335 6 0.825069 -4.242867 0.299111 2.187560 0.357775 7 0.764112 -5.634322 0.257682 1.854785 0.211756 8 0.763262 -6.167603 0.183721 2.064693 0.163755 9 0.773587 -5.498678 0.327769 2.322511 0.231571 10 0.798463 -5.011879 0.325996 2.432792 0.271362 11 0.776156 -5.249770 0.391002 2.407313 0.249740 12 0.792520 -4.960234 0.363566 2.642476 0.275931 13 0.646846 -6.547148 0.152813 2.041277 0.138512 14 0.665833 -5.660217 0.254989 2.519422 0.199889 15 0.654027 -6.105098 0.203653 2.125618 0.170100 16 0.658245 -5.340115 0.210185 2.205546 0.234589 17 0.644692 -5.440040 0.239764 2.264501 0.218164 18 0.605417 -2.931070 0.434326 3.007463 0.430788 19 0.719467 -3.949079 0.357870 3.109010 0.377429 20 0.686080 -4.554466 0.340176 2.856676 0.322111 21 0.704087 -4.095442 0.262564 2.739710 0.365391 22 0.698951 -5.186960 0.237622 2.557536 0.259765 23 0.679834 -4.330956 0.262384 2.916777 0.285695 24 0.686894 -5.248776 0.210279 2.547508 0.253556 25 0.732479 -5.557447 0.220890 2.692176 0.215961 26 0.737948 -5.571843 0.236853 2.846369 0.219514 27 0.720916 -6.183590 0.226278 2.589702 0.147403 28 0.726652 -6.271690 0.196102 2.314209 0.162999 29 0.676258 -7.120925 0.279789 2.241742 0.108514 30 0.723797 -6.635729 0.209866 1.957961 0.135242 31 0.741367 -7.348300 0.177551 1.743867 0.085569 32 0.742055 -7.682587 0.173319 2.103106 0.068501 33 0.738703 -7.067931 0.175181 1.512275 0.096320 34 0.742133 -7.695734 0.178540 1.544609 0.056141 35 0.741899 -7.964984 0.163519 1.423287 0.044539 36 0.742737 -7.777685 0.170183 2.447064 0.057610 37 0.778834 -6.149653 0.218037 2.477082 0.165827 38 0.783626 -6.006414 0.196371 2.536527 0.173218 39 0.766209 -6.452058 0.212294 2.269398 0.141929 40 0.758324 -6.006647 0.266892 2.382544 0.160691 41 0.765623 -6.647379 0.201095 2.374073 0.130554 42 0.759203 -7.044105 0.063412 2.361532 0.115730 43 0.654172 -7.310550 0.098648 2.416838 0.095032 44 0.634267 -6.793547 0.158266 2.256699 0.117399 45 0.635285 -7.057869 0.091608 2.330716 0.091470 46 0.638928 -6.995820 0.102083 2.365800 0.102706 47 0.631653 -7.156076 0.127642 2.392122 0.097336 48 0.635204 -7.319510 0.200873 2.028612 0.086398 49 0.733659 -6.439398 0.266392 2.079922 0.133867 50 0.754073 -6.482096 0.264967 2.054419 0.128872 51 0.775933 -6.650471 0.254498 1.840198 0.103561 52 0.760361 -6.689151 0.291954 2.431854 0.105993 53 0.766204 -7.072419 0.220434 1.972297 0.119308 54 0.785714 -6.836811 0.269866 2.223719 0.147491 55 0.819032 -4.649573 0.205558 1.986899 0.316700 56 0.811843 -4.333543 0.221727 2.014606 0.344834 57 0.821364 -4.438453 0.238298 1.922940 0.335041 58 0.817756 -4.608260 0.290024 2.021591 0.314464 59 0.813432 -4.476755 0.262633 1.827012 0.326197 60 0.817396 -4.609161 0.221711 1.831691 0.316395 61 0.678874 -7.040508 0.066994 2.460791 0.101516 62 0.686264 -7.293801 0.086372 2.321560 0.098555 63 0.694399 -6.966321 0.095882 2.278687 0.103224 64 0.683296 -7.245620 0.018689 2.498224 0.093534 65 0.673636 -7.496264 0.056844 2.003032 0.073581 66 0.681811 -7.314237 0.006274 2.118596 0.091546 67 0.720908 -5.409423 0.226850 2.359973 0.226156 68 0.729067 -5.324574 0.205660 2.291558 0.226247 69 0.731444 -5.869750 0.151814 2.118496 0.185580 70 0.727313 -6.261141 0.120956 2.137075 0.141958 71 0.730387 -5.720868 0.158830 2.277927 0.180828 72 0.733232 -5.207985 0.224852 2.642276 0.242981 73 0.762959 -5.791820 0.329066 2.205024 0.188180 74 0.789532 -5.389129 0.306636 1.928708 0.225461 75 0.815908 -5.313360 0.201861 2.225815 0.244512 76 0.807217 -5.477592 0.315074 1.862092 0.228624 77 0.789977 -5.775966 0.341169 2.007923 0.193918 78 0.816340 -5.391029 0.250572 1.777901 0.232744 79 0.779612 -5.115212 0.249494 2.017753 0.260015 80 0.790117 -4.913885 0.265699 2.398422 0.277948 81 0.770466 -4.441519 0.155097 2.645959 0.327978 82 0.778747 -5.132032 0.210458 2.232576 0.260633 83 0.787896 -5.022288 0.146948 2.428306 0.264666 84 0.772416 -6.025367 0.078202 2.053601 0.177275 85 0.729586 -5.288912 0.343073 3.099301 0.242119 86 0.727747 -5.657899 0.315903 3.098256 0.200423 87 0.712199 -6.366916 0.335753 2.654271 0.144614 88 0.740837 -5.515071 0.299549 3.136550 0.220968 89 0.743937 -5.783272 0.299793 3.007096 0.194052 90 0.745526 -4.379411 0.375531 3.671155 0.332086 91 0.733165 -4.508984 0.389232 3.317586 0.301952 92 0.714360 -6.411497 0.207156 2.344876 0.134120 93 0.734504 -5.952058 0.087840 2.344336 0.186489 94 0.697790 -6.152551 0.173520 2.080121 0.160809 95 0.712170 -6.251425 0.188056 2.143851 0.160812 96 0.705658 -6.247076 0.180528 2.344348 0.164916 97 0.693429 -6.417440 0.194627 2.473239 0.151709 98 0.714485 -4.020042 0.265315 2.671825 0.340623 99 0.690892 -5.159169 0.202146 2.441612 0.260375 100 0.674953 -3.760348 0.242861 2.634633 0.378483 101 0.656846 -3.700544 0.260481 2.991063 0.370961 102 0.643327 -4.202730 0.310163 2.638279 0.356881 103 0.641418 -3.269487 0.270641 2.690917 0.444774 104 0.722356 -6.878393 0.089267 2.004055 0.113942 105 0.691483 -7.111576 0.144780 2.065477 0.093193 106 0.719974 -6.997403 0.210279 1.994387 0.112878 107 0.677930 -6.981201 0.184550 2.129924 0.106802 108 0.700246 -6.600023 0.249172 2.499148 0.105306 109 0.676066 -6.739151 0.160686 2.296873 0.115130 110 0.740539 -5.845099 0.278679 2.608749 0.185668 111 0.727863 -5.258320 0.256454 2.550961 0.232520 112 0.712466 -6.471427 0.184378 2.502336 0.136390 113 0.722085 -4.876336 0.212054 2.376749 0.268144 114 0.722254 -5.963040 0.250283 2.489191 0.177807 115 0.715121 -6.729713 0.181701 2.938114 0.115515 116 0.662668 -4.673241 0.261549 2.702355 0.274407 117 0.653823 -6.051233 0.273280 2.640798 0.170106 118 0.676023 -4.597834 0.372114 2.975889 0.282780 119 0.655239 -4.913137 0.393056 2.816781 0.251972 120 0.582710 -5.517173 0.389295 2.925862 0.220657 121 0.684130 -6.186128 0.279933 2.686240 0.152428 122 0.656182 -4.711007 0.281618 2.655744 0.234809 123 0.741480 -5.418787 0.160267 2.090438 0.229892 124 0.732903 -5.445140 0.142466 2.174306 0.215558 125 0.728421 -5.944191 0.143359 1.929715 0.181988 126 0.735546 -5.594275 0.127950 1.765957 0.222716 127 0.738245 -5.540351 0.087165 1.821297 0.214075 128 0.736964 -5.825257 0.115697 1.996146 0.196535 129 0.699787 -6.890021 0.152941 2.328513 0.112856 130 0.718839 -5.892061 0.195976 2.108873 0.183572 131 0.724045 -6.135296 0.203630 2.539724 0.169923 132 0.735136 -6.112667 0.217013 2.527742 0.170633 133 0.721308 -5.436135 0.254909 2.516320 0.232209 134 0.723096 -6.448134 0.178713 2.034827 0.141422 135 0.744064 -5.301321 0.320385 2.375138 0.243080 136 0.706687 -5.333619 0.322044 2.631793 0.228319 137 0.708144 -4.378916 0.300067 2.445502 0.259451 138 0.708617 -4.654894 0.304107 2.672362 0.274387 139 0.701404 -5.634576 0.306014 2.419253 0.209191 140 0.696049 -5.866357 0.233070 2.445646 0.184985 141 0.685057 -4.796845 0.397749 2.963799 0.277227 142 0.665945 -5.410336 0.288917 2.665133 0.231723 143 0.661735 -5.585259 0.310746 2.465528 0.209863 144 0.632631 -5.898673 0.213353 2.470746 0.189032 145 0.630409 -6.132663 0.220617 2.576563 0.159777 146 0.574282 -5.456811 0.345238 2.840556 0.232861 147 0.793509 -3.297668 0.414758 3.413649 0.457533 148 0.768974 -4.276605 0.355736 3.142364 0.336085 149 0.764036 -3.377325 0.335357 3.274865 0.418646 150 0.775708 -4.892495 0.262281 2.910213 0.270173 151 0.762726 -4.484303 0.340256 2.958815 0.301487 152 0.768320 -2.434031 0.450493 3.079221 0.527367 153 0.754449 -2.839756 0.356224 3.184027 0.454721 154 0.670475 -4.865194 0.246404 2.013530 0.168581 155 0.659333 -4.239028 0.175691 2.451130 0.247455 156 0.652025 -3.583722 0.207914 2.439597 0.206256 157 0.623731 -5.435100 0.230532 2.699645 0.220546 158 0.646786 -3.444478 0.303214 2.964568 0.261305 159 0.627337 -5.070096 0.280091 2.892300 0.249703 160 0.675865 -5.498456 0.234196 2.103014 0.216638 161 0.694571 -5.185987 0.259229 2.151121 0.244948 162 0.684373 -5.283009 0.226528 2.442906 0.238281 163 0.719576 -5.529833 0.242750 2.408689 0.220520 164 0.673086 -5.617124 0.184896 1.871871 0.212386 165 0.674562 -2.929379 0.396746 2.560422 0.367233 166 0.628232 -6.816086 0.172270 2.235197 0.119652 167 0.626710 -7.018057 0.176316 1.852402 0.091604 168 0.628058 -7.517934 0.160414 1.881767 0.075587 169 0.725216 -5.736781 0.164529 2.882450 0.202879 170 0.646167 -7.169701 0.073298 2.266432 0.100881 171 0.646818 -7.304500 0.171088 2.095237 0.096220 172 0.756700 -6.323531 0.218885 2.193412 0.160376 173 0.776158 -6.085567 0.192375 1.889002 0.174152 174 0.766700 -5.943501 0.192150 1.852542 0.179677 175 0.756482 -6.012559 0.229298 1.872946 0.163118 176 0.761255 -5.966779 0.197938 1.974857 0.184067 177 0.763242 -6.016891 0.109256 2.004719 0.174429 178 0.745957 -6.486822 0.197919 2.449763 0.132703 179 0.762508 -6.311987 0.182459 2.251553 0.160306 180 0.778349 -5.711205 0.240875 2.845109 0.192730 181 0.759320 -6.261446 0.183218 2.264226 0.144105 182 0.768845 -5.704053 0.216204 2.679185 0.197710 183 0.757180 -6.277170 0.109397 2.209021 0.156368 184 0.669565 -5.619070 0.191576 2.027228 0.215724 185 0.656516 -5.198864 0.206768 2.120412 0.252404 186 0.654331 -5.592584 0.133917 2.058658 0.214346 187 0.667654 -6.431119 0.153310 2.161936 0.120605 188 0.663884 -6.359018 0.116636 2.152083 0.138868 189 0.659132 -6.710219 0.149694 1.913990 0.121777 190 0.683761 -6.934474 0.159890 2.316346 0.112838 191 0.657899 -6.538586 0.121952 2.657476 0.133050 192 0.683244 -6.195325 0.129303 2.784312 0.168895 193 0.655683 -6.787197 0.158453 2.679772 0.131728 194 0.643956 -6.744577 0.207454 2.138608 0.123306 195 0.664357 -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)` 1.667e+00 -3.832e-04 2.678e-05 -8.035e-05 `MDVP:Jitter(%)` `MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ` -2.707e+01 1.456e+03 2.473e+03 -4.281e+00 `Jitter:DDP` `MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3` -8.164e+02 2.186e+00 -3.966e-01 6.651e+02 `Shimmer:APQ5` `MDVP:APQ` `Shimmer:DDA` NHR -6.000e+00 5.436e+00 -2.211e+02 -2.153e-01 HNR status DFA spread1 -1.802e-02 -2.961e-02 -4.946e-01 2.707e-02 spread2 D2 PPE 4.020e-01 -9.320e-02 -3.883e-02 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.128974 -0.032597 -0.003913 0.033093 0.193170 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.667e+00 1.544e-01 10.796 < 2e-16 *** `MDVP:Fo(Hz)` -3.832e-04 2.582e-04 -1.484 0.13965 `MDVP:Fhi(Hz)` 2.678e-05 5.484e-05 0.488 0.62586 `MDVP:Flo(Hz)` -8.035e-05 1.384e-04 -0.581 0.56227 `MDVP:Jitter(%)` -2.707e+01 1.150e+01 -2.354 0.01970 * `MDVP:Jitter(Abs)` 1.456e+03 7.836e+02 1.858 0.06485 . `MDVP:RAP` 2.473e+03 1.583e+03 1.562 0.12013 `MDVP:PPQ` -4.281e+00 1.510e+01 -0.283 0.77721 `Jitter:DDP` -8.164e+02 5.280e+02 -1.546 0.12387 `MDVP:Shimmer` 2.186e+00 5.866e+00 0.373 0.70984 `MDVP:Shimmer(dB)` -3.966e-01 2.028e-01 -1.956 0.05211 . `Shimmer:APQ3` 6.651e+02 1.532e+03 0.434 0.66476 `Shimmer:APQ5` -6.000e+00 3.425e+00 -1.752 0.08154 . `MDVP:APQ` 5.436e+00 1.814e+00 2.996 0.00314 ** `Shimmer:DDA` -2.211e+02 5.106e+02 -0.433 0.66556 NHR -2.153e-01 3.396e-01 -0.634 0.52691 HNR -1.802e-02 2.039e-03 -8.834 1.14e-15 *** status -2.961e-02 1.283e-02 -2.308 0.02219 * DFA -4.946e-01 1.207e-01 -4.100 6.37e-05 *** spread1 2.707e-02 1.668e-02 1.623 0.10647 spread2 4.020e-01 7.747e-02 5.189 5.91e-07 *** D2 -9.320e-02 1.821e-02 -5.119 8.15e-07 *** PPE -3.883e-02 2.369e-01 -0.164 0.86998 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.05581 on 172 degrees of freedom Multiple R-squared: 0.7444, Adjusted R-squared: 0.7117 F-statistic: 22.77 on 22 and 172 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,] 0.7689165 0.46216698 0.231083490 [2,] 0.6594566 0.68108687 0.340543433 [3,] 0.8388896 0.32222075 0.161110375 [4,] 0.8192113 0.36157736 0.180788680 [5,] 0.7448546 0.51029088 0.255145442 [6,] 0.6526512 0.69469769 0.347348843 [7,] 0.6471766 0.70564684 0.352823421 [8,] 0.5898795 0.82024104 0.410120518 [9,] 0.5389804 0.92203914 0.461019568 [10,] 0.4930552 0.98611033 0.506944833 [11,] 0.4580257 0.91605149 0.541974257 [12,] 0.5412539 0.91749213 0.458746064 [13,] 0.4849876 0.96997526 0.515012369 [14,] 0.4696052 0.93921041 0.530394795 [15,] 0.4007871 0.80157412 0.599212941 [16,] 0.3307982 0.66159636 0.669201818 [17,] 0.2750622 0.55012438 0.724937812 [18,] 0.2403077 0.48061546 0.759692270 [19,] 0.2186876 0.43737516 0.781312422 [20,] 0.2330246 0.46604912 0.766975438 [21,] 0.2012499 0.40249972 0.798750142 [22,] 0.2018085 0.40361704 0.798191478 [23,] 0.7642050 0.47159007 0.235795036 [24,] 0.7897307 0.42053862 0.210269309 [25,] 0.7692943 0.46141144 0.230705720 [26,] 0.7789058 0.44218849 0.221094243 [27,] 0.7596087 0.48078258 0.240391289 [28,] 0.7234691 0.55306183 0.276530916 [29,] 0.7008747 0.59825062 0.299125312 [30,] 0.6791648 0.64167031 0.320835155 [31,] 0.6444209 0.71115811 0.355579056 [32,] 0.5957129 0.80857417 0.404287084 [33,] 0.5594591 0.88108177 0.440540883 [34,] 0.5190052 0.96198954 0.480994771 [35,] 0.5950563 0.80988742 0.404943709 [36,] 0.5950577 0.80988454 0.404942268 [37,] 0.6774816 0.64503673 0.322518366 [38,] 0.6839905 0.63201903 0.316009515 [39,] 0.6687954 0.66240913 0.331204565 [40,] 0.7580451 0.48390977 0.241954885 [41,] 0.7810335 0.43793302 0.218966511 [42,] 0.7996962 0.40060756 0.200303780 [43,] 0.7841039 0.43179213 0.215896065 [44,] 0.8176386 0.36472281 0.182361406 [45,] 0.7892321 0.42153576 0.210767878 [46,] 0.7645092 0.47098153 0.235490767 [47,] 0.7490279 0.50194417 0.250972085 [48,] 0.7286740 0.54265209 0.271326047 [49,] 0.6873581 0.62528375 0.312641873 [50,] 0.6876758 0.62464835 0.312324173 [51,] 0.7539365 0.49212698 0.246063488 [52,] 0.7381770 0.52364607 0.261823035 [53,] 0.7819657 0.43606857 0.218034285 [54,] 0.8185176 0.36296474 0.181482371 [55,] 0.8275022 0.34499552 0.172497762 [56,] 0.7968054 0.40638917 0.203194587 [57,] 0.7618149 0.47637019 0.238185096 [58,] 0.7511708 0.49765837 0.248829187 [59,] 0.8686705 0.26265895 0.131329475 [60,] 0.8653902 0.26921962 0.134609810 [61,] 0.8682465 0.26350709 0.131753546 [62,] 0.8430955 0.31380894 0.156904472 [63,] 0.8373133 0.32537348 0.162686738 [64,] 0.8434816 0.31303686 0.156518428 [65,] 0.8296245 0.34075096 0.170375481 [66,] 0.8370993 0.32580139 0.162900697 [67,] 0.8268065 0.34638696 0.173193480 [68,] 0.8004597 0.39908066 0.199540330 [69,] 0.7716908 0.45661850 0.228309248 [70,] 0.7350350 0.52992994 0.264964970 [71,] 0.7160410 0.56791795 0.283958977 [72,] 0.7817987 0.43640252 0.218201260 [73,] 0.7891122 0.42177552 0.210887761 [74,] 0.8324983 0.33500339 0.167501697 [75,] 0.8159202 0.36815964 0.184079820 [76,] 0.8443089 0.31138211 0.155691054 [77,] 0.8298924 0.34021524 0.170107622 [78,] 0.8243980 0.35120401 0.175602006 [79,] 0.8766487 0.24670267 0.123351335 [80,] 0.9284288 0.14314243 0.071571217 [81,] 0.9124326 0.17513481 0.087567405 [82,] 0.8969905 0.20601905 0.103009525 [83,] 0.8758854 0.24822913 0.124114567 [84,] 0.8687246 0.26255082 0.131275409 [85,] 0.8945375 0.21092509 0.105462543 [86,] 0.8735577 0.25288459 0.126442297 [87,] 0.8843390 0.23132200 0.115660999 [88,] 0.8786221 0.24275575 0.121377875 [89,] 0.8787332 0.24253361 0.121266804 [90,] 0.8748296 0.25034078 0.125170391 [91,] 0.8784070 0.24318609 0.121593046 [92,] 0.8637396 0.27252071 0.136260353 [93,] 0.8425005 0.31499893 0.157499464 [94,] 0.8160778 0.36784448 0.183922238 [95,] 0.7977535 0.40449291 0.202246457 [96,] 0.7906102 0.41877965 0.209389823 [97,] 0.7986864 0.40262724 0.201313621 [98,] 0.7768710 0.44625800 0.223128998 [99,] 0.7915267 0.41694664 0.208473319 [100,] 0.8293610 0.34127795 0.170638974 [101,] 0.8436930 0.31261410 0.156307048 [102,] 0.8612642 0.27747157 0.138735785 [103,] 0.9379244 0.12415115 0.062075576 [104,] 0.9373524 0.12529513 0.062647565 [105,] 0.9383477 0.12330453 0.061652265 [106,] 0.9230326 0.15393489 0.076967445 [107,] 0.9080053 0.18398938 0.091994688 [108,] 0.8892135 0.22157298 0.110786488 [109,] 0.8861731 0.22765371 0.113826855 [110,] 0.8894988 0.22100233 0.110501164 [111,] 0.8634581 0.27308372 0.136541859 [112,] 0.8373802 0.32523965 0.162619827 [113,] 0.8027637 0.39447253 0.197236263 [114,] 0.7613487 0.47730264 0.238651322 [115,] 0.7279830 0.54403404 0.272017019 [116,] 0.8218904 0.35621924 0.178109621 [117,] 0.8216042 0.35679162 0.178395808 [118,] 0.8483904 0.30321919 0.151609594 [119,] 0.8157205 0.36855905 0.184279527 [120,] 0.7762133 0.44757347 0.223786736 [121,] 0.8113650 0.37727008 0.188635039 [122,] 0.7734988 0.45300249 0.226501244 [123,] 0.7304037 0.53919251 0.269596253 [124,] 0.6795319 0.64093614 0.320468071 [125,] 0.6330021 0.73399577 0.366997884 [126,] 0.5969719 0.80605627 0.403028137 [127,] 0.6761787 0.64764263 0.323821316 [128,] 0.7809146 0.43817086 0.219085429 [129,] 0.7488082 0.50238351 0.251191757 [130,] 0.8149789 0.37004223 0.185021117 [131,] 0.8671802 0.26563958 0.132819790 [132,] 0.8770651 0.24586977 0.122934885 [133,] 0.8729293 0.25414147 0.127070737 [134,] 0.8296533 0.34069334 0.170346671 [135,] 0.7673588 0.46528243 0.232641214 [136,] 0.8423882 0.31522369 0.157611843 [137,] 0.8004330 0.39913403 0.199567014 [138,] 0.7355135 0.52897304 0.264486521 [139,] 0.7941596 0.41168085 0.205840423 [140,] 0.8542450 0.29150992 0.145754958 [141,] 0.7791258 0.44174847 0.220874234 [142,] 0.9860128 0.02797447 0.013987236 [143,] 0.9925793 0.01484139 0.007420696 [144,] 0.9881181 0.02376373 0.011881867 > postscript(file="/var/wessaorg/rcomp/tmp/1zouh1386790450.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2jevi1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/39udr1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/468981386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5rtzp1386790450.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 -4.444846e-02 -3.711888e-03 -2.274669e-02 -5.184791e-02 -1.303356e-02 6 7 8 9 10 -3.004261e-02 8.286117e-02 1.931696e-01 4.465732e-02 -3.286575e-02 11 12 13 14 15 -2.756609e-03 1.510675e-02 8.034284e-05 -6.980058e-02 -1.300558e-02 16 17 18 19 20 4.913747e-02 -3.912712e-03 -1.050460e-02 3.803441e-02 -7.861252e-03 21 22 23 24 25 4.626037e-02 1.490350e-02 6.479613e-02 -1.424073e-02 -1.465345e-02 26 27 28 29 30 1.712489e-02 6.860326e-03 -6.719225e-02 -1.112212e-02 -1.513912e-02 31 32 33 34 35 1.629830e-02 1.409465e-01 9.208586e-02 3.914520e-02 3.202293e-02 36 37 38 39 40 8.601405e-02 -3.232814e-02 -1.896315e-02 2.322169e-02 -6.523539e-03 41 42 43 44 45 -2.121215e-02 2.144957e-02 -9.888493e-02 -1.821240e-02 4.733019e-02 46 47 48 49 50 3.186202e-02 5.116698e-02 1.774137e-01 4.192417e-02 4.800806e-02 51 52 53 54 55 4.823206e-02 3.336574e-02 -5.545850e-03 -3.386358e-02 6.049335e-03 56 57 58 59 60 2.288520e-02 1.242683e-02 4.180620e-02 2.848336e-02 4.532089e-02 61 62 63 64 65 2.669414e-03 9.032165e-02 1.420339e-02 -3.305232e-02 -8.250061e-02 66 67 68 69 70 -6.076084e-02 -8.570378e-02 -4.906117e-02 -7.191868e-03 -1.505567e-02 71 72 73 74 75 -1.605124e-02 -7.745728e-03 6.689852e-03 -3.502609e-02 -1.087028e-03 76 77 78 79 80 -6.760500e-02 -5.597239e-02 -6.450568e-02 6.608449e-02 4.033968e-02 81 82 83 84 85 2.020683e-02 -1.964535e-03 4.393917e-02 1.191537e-01 -1.515581e-02 86 87 88 89 90 3.450210e-02 -6.568944e-03 5.700447e-02 5.158803e-02 1.797865e-02 91 92 93 94 95 4.527665e-02 1.692032e-02 -2.617146e-02 -2.350701e-02 -9.298022e-03 96 97 98 99 100 -5.370974e-02 -1.001076e-01 -2.413658e-02 -7.077257e-02 -5.280696e-02 101 102 103 104 105 1.569186e-02 -2.938812e-02 -2.108659e-02 -8.542933e-02 -1.032971e-01 106 107 108 109 110 -3.737974e-02 -3.371223e-02 -1.872499e-02 -4.779196e-02 6.494192e-02 111 112 113 114 115 -1.890290e-02 -6.006423e-02 4.302417e-02 1.890069e-02 -4.888438e-02 116 117 118 119 120 -4.990640e-02 8.297748e-03 8.677885e-03 -2.573946e-02 -3.856536e-02 121 122 123 124 125 3.787728e-02 -4.156505e-02 -1.225025e-02 7.424041e-02 9.902617e-02 126 127 128 129 130 8.700091e-02 6.294399e-02 5.536771e-02 5.729102e-02 4.199472e-02 131 132 133 134 135 2.244353e-02 3.915677e-02 -2.963115e-02 2.495647e-02 -2.711325e-03 136 137 138 139 140 2.531172e-02 -1.680039e-02 -4.571559e-03 1.023166e-02 1.440494e-02 141 142 143 144 145 7.889684e-02 2.892316e-02 1.118432e-02 -2.073620e-02 -9.673034e-03 146 147 148 149 150 -2.927007e-02 -6.356316e-02 -8.547313e-02 -6.286902e-03 3.166478e-04 151 152 153 154 155 1.580738e-02 -5.634029e-03 1.095322e-01 -5.973461e-02 7.412073e-02 156 157 158 159 160 3.257950e-02 9.887833e-02 1.406885e-02 6.847811e-02 1.152124e-02 161 162 163 164 165 -1.874648e-02 -2.139630e-02 7.225242e-02 -4.855794e-02 -5.625824e-02 166 167 168 169 170 5.400982e-03 -9.024693e-02 -5.112799e-02 -8.193670e-02 -3.723084e-02 171 172 173 174 175 4.771475e-02 -3.689886e-02 -1.051736e-01 -8.907027e-02 -1.289742e-01 176 177 178 179 180 -7.500234e-02 -7.647941e-02 -1.075904e-02 -1.832546e-02 -1.783339e-02 181 182 183 184 185 -8.785106e-02 -4.260441e-02 -9.643693e-02 7.425478e-03 3.911600e-02 186 187 188 189 190 3.858395e-02 3.226214e-02 2.112312e-02 3.217684e-02 3.282109e-02 191 192 193 194 195 -2.089350e-02 -2.353185e-02 5.909980e-03 -8.904637e-02 -1.711114e-02 > postscript(file="/var/wessaorg/rcomp/tmp/6v1g81386790450.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 -4.444846e-02 NA 1 -3.711888e-03 -4.444846e-02 2 -2.274669e-02 -3.711888e-03 3 -5.184791e-02 -2.274669e-02 4 -1.303356e-02 -5.184791e-02 5 -3.004261e-02 -1.303356e-02 6 8.286117e-02 -3.004261e-02 7 1.931696e-01 8.286117e-02 8 4.465732e-02 1.931696e-01 9 -3.286575e-02 4.465732e-02 10 -2.756609e-03 -3.286575e-02 11 1.510675e-02 -2.756609e-03 12 8.034284e-05 1.510675e-02 13 -6.980058e-02 8.034284e-05 14 -1.300558e-02 -6.980058e-02 15 4.913747e-02 -1.300558e-02 16 -3.912712e-03 4.913747e-02 17 -1.050460e-02 -3.912712e-03 18 3.803441e-02 -1.050460e-02 19 -7.861252e-03 3.803441e-02 20 4.626037e-02 -7.861252e-03 21 1.490350e-02 4.626037e-02 22 6.479613e-02 1.490350e-02 23 -1.424073e-02 6.479613e-02 24 -1.465345e-02 -1.424073e-02 25 1.712489e-02 -1.465345e-02 26 6.860326e-03 1.712489e-02 27 -6.719225e-02 6.860326e-03 28 -1.112212e-02 -6.719225e-02 29 -1.513912e-02 -1.112212e-02 30 1.629830e-02 -1.513912e-02 31 1.409465e-01 1.629830e-02 32 9.208586e-02 1.409465e-01 33 3.914520e-02 9.208586e-02 34 3.202293e-02 3.914520e-02 35 8.601405e-02 3.202293e-02 36 -3.232814e-02 8.601405e-02 37 -1.896315e-02 -3.232814e-02 38 2.322169e-02 -1.896315e-02 39 -6.523539e-03 2.322169e-02 40 -2.121215e-02 -6.523539e-03 41 2.144957e-02 -2.121215e-02 42 -9.888493e-02 2.144957e-02 43 -1.821240e-02 -9.888493e-02 44 4.733019e-02 -1.821240e-02 45 3.186202e-02 4.733019e-02 46 5.116698e-02 3.186202e-02 47 1.774137e-01 5.116698e-02 48 4.192417e-02 1.774137e-01 49 4.800806e-02 4.192417e-02 50 4.823206e-02 4.800806e-02 51 3.336574e-02 4.823206e-02 52 -5.545850e-03 3.336574e-02 53 -3.386358e-02 -5.545850e-03 54 6.049335e-03 -3.386358e-02 55 2.288520e-02 6.049335e-03 56 1.242683e-02 2.288520e-02 57 4.180620e-02 1.242683e-02 58 2.848336e-02 4.180620e-02 59 4.532089e-02 2.848336e-02 60 2.669414e-03 4.532089e-02 61 9.032165e-02 2.669414e-03 62 1.420339e-02 9.032165e-02 63 -3.305232e-02 1.420339e-02 64 -8.250061e-02 -3.305232e-02 65 -6.076084e-02 -8.250061e-02 66 -8.570378e-02 -6.076084e-02 67 -4.906117e-02 -8.570378e-02 68 -7.191868e-03 -4.906117e-02 69 -1.505567e-02 -7.191868e-03 70 -1.605124e-02 -1.505567e-02 71 -7.745728e-03 -1.605124e-02 72 6.689852e-03 -7.745728e-03 73 -3.502609e-02 6.689852e-03 74 -1.087028e-03 -3.502609e-02 75 -6.760500e-02 -1.087028e-03 76 -5.597239e-02 -6.760500e-02 77 -6.450568e-02 -5.597239e-02 78 6.608449e-02 -6.450568e-02 79 4.033968e-02 6.608449e-02 80 2.020683e-02 4.033968e-02 81 -1.964535e-03 2.020683e-02 82 4.393917e-02 -1.964535e-03 83 1.191537e-01 4.393917e-02 84 -1.515581e-02 1.191537e-01 85 3.450210e-02 -1.515581e-02 86 -6.568944e-03 3.450210e-02 87 5.700447e-02 -6.568944e-03 88 5.158803e-02 5.700447e-02 89 1.797865e-02 5.158803e-02 90 4.527665e-02 1.797865e-02 91 1.692032e-02 4.527665e-02 92 -2.617146e-02 1.692032e-02 93 -2.350701e-02 -2.617146e-02 94 -9.298022e-03 -2.350701e-02 95 -5.370974e-02 -9.298022e-03 96 -1.001076e-01 -5.370974e-02 97 -2.413658e-02 -1.001076e-01 98 -7.077257e-02 -2.413658e-02 99 -5.280696e-02 -7.077257e-02 100 1.569186e-02 -5.280696e-02 101 -2.938812e-02 1.569186e-02 102 -2.108659e-02 -2.938812e-02 103 -8.542933e-02 -2.108659e-02 104 -1.032971e-01 -8.542933e-02 105 -3.737974e-02 -1.032971e-01 106 -3.371223e-02 -3.737974e-02 107 -1.872499e-02 -3.371223e-02 108 -4.779196e-02 -1.872499e-02 109 6.494192e-02 -4.779196e-02 110 -1.890290e-02 6.494192e-02 111 -6.006423e-02 -1.890290e-02 112 4.302417e-02 -6.006423e-02 113 1.890069e-02 4.302417e-02 114 -4.888438e-02 1.890069e-02 115 -4.990640e-02 -4.888438e-02 116 8.297748e-03 -4.990640e-02 117 8.677885e-03 8.297748e-03 118 -2.573946e-02 8.677885e-03 119 -3.856536e-02 -2.573946e-02 120 3.787728e-02 -3.856536e-02 121 -4.156505e-02 3.787728e-02 122 -1.225025e-02 -4.156505e-02 123 7.424041e-02 -1.225025e-02 124 9.902617e-02 7.424041e-02 125 8.700091e-02 9.902617e-02 126 6.294399e-02 8.700091e-02 127 5.536771e-02 6.294399e-02 128 5.729102e-02 5.536771e-02 129 4.199472e-02 5.729102e-02 130 2.244353e-02 4.199472e-02 131 3.915677e-02 2.244353e-02 132 -2.963115e-02 3.915677e-02 133 2.495647e-02 -2.963115e-02 134 -2.711325e-03 2.495647e-02 135 2.531172e-02 -2.711325e-03 136 -1.680039e-02 2.531172e-02 137 -4.571559e-03 -1.680039e-02 138 1.023166e-02 -4.571559e-03 139 1.440494e-02 1.023166e-02 140 7.889684e-02 1.440494e-02 141 2.892316e-02 7.889684e-02 142 1.118432e-02 2.892316e-02 143 -2.073620e-02 1.118432e-02 144 -9.673034e-03 -2.073620e-02 145 -2.927007e-02 -9.673034e-03 146 -6.356316e-02 -2.927007e-02 147 -8.547313e-02 -6.356316e-02 148 -6.286902e-03 -8.547313e-02 149 3.166478e-04 -6.286902e-03 150 1.580738e-02 3.166478e-04 151 -5.634029e-03 1.580738e-02 152 1.095322e-01 -5.634029e-03 153 -5.973461e-02 1.095322e-01 154 7.412073e-02 -5.973461e-02 155 3.257950e-02 7.412073e-02 156 9.887833e-02 3.257950e-02 157 1.406885e-02 9.887833e-02 158 6.847811e-02 1.406885e-02 159 1.152124e-02 6.847811e-02 160 -1.874648e-02 1.152124e-02 161 -2.139630e-02 -1.874648e-02 162 7.225242e-02 -2.139630e-02 163 -4.855794e-02 7.225242e-02 164 -5.625824e-02 -4.855794e-02 165 5.400982e-03 -5.625824e-02 166 -9.024693e-02 5.400982e-03 167 -5.112799e-02 -9.024693e-02 168 -8.193670e-02 -5.112799e-02 169 -3.723084e-02 -8.193670e-02 170 4.771475e-02 -3.723084e-02 171 -3.689886e-02 4.771475e-02 172 -1.051736e-01 -3.689886e-02 173 -8.907027e-02 -1.051736e-01 174 -1.289742e-01 -8.907027e-02 175 -7.500234e-02 -1.289742e-01 176 -7.647941e-02 -7.500234e-02 177 -1.075904e-02 -7.647941e-02 178 -1.832546e-02 -1.075904e-02 179 -1.783339e-02 -1.832546e-02 180 -8.785106e-02 -1.783339e-02 181 -4.260441e-02 -8.785106e-02 182 -9.643693e-02 -4.260441e-02 183 7.425478e-03 -9.643693e-02 184 3.911600e-02 7.425478e-03 185 3.858395e-02 3.911600e-02 186 3.226214e-02 3.858395e-02 187 2.112312e-02 3.226214e-02 188 3.217684e-02 2.112312e-02 189 3.282109e-02 3.217684e-02 190 -2.089350e-02 3.282109e-02 191 -2.353185e-02 -2.089350e-02 192 5.909980e-03 -2.353185e-02 193 -8.904637e-02 5.909980e-03 194 -1.711114e-02 -8.904637e-02 195 NA -1.711114e-02 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -3.711888e-03 -4.444846e-02 [2,] -2.274669e-02 -3.711888e-03 [3,] -5.184791e-02 -2.274669e-02 [4,] -1.303356e-02 -5.184791e-02 [5,] -3.004261e-02 -1.303356e-02 [6,] 8.286117e-02 -3.004261e-02 [7,] 1.931696e-01 8.286117e-02 [8,] 4.465732e-02 1.931696e-01 [9,] -3.286575e-02 4.465732e-02 [10,] -2.756609e-03 -3.286575e-02 [11,] 1.510675e-02 -2.756609e-03 [12,] 8.034284e-05 1.510675e-02 [13,] -6.980058e-02 8.034284e-05 [14,] -1.300558e-02 -6.980058e-02 [15,] 4.913747e-02 -1.300558e-02 [16,] -3.912712e-03 4.913747e-02 [17,] -1.050460e-02 -3.912712e-03 [18,] 3.803441e-02 -1.050460e-02 [19,] -7.861252e-03 3.803441e-02 [20,] 4.626037e-02 -7.861252e-03 [21,] 1.490350e-02 4.626037e-02 [22,] 6.479613e-02 1.490350e-02 [23,] -1.424073e-02 6.479613e-02 [24,] -1.465345e-02 -1.424073e-02 [25,] 1.712489e-02 -1.465345e-02 [26,] 6.860326e-03 1.712489e-02 [27,] -6.719225e-02 6.860326e-03 [28,] -1.112212e-02 -6.719225e-02 [29,] -1.513912e-02 -1.112212e-02 [30,] 1.629830e-02 -1.513912e-02 [31,] 1.409465e-01 1.629830e-02 [32,] 9.208586e-02 1.409465e-01 [33,] 3.914520e-02 9.208586e-02 [34,] 3.202293e-02 3.914520e-02 [35,] 8.601405e-02 3.202293e-02 [36,] -3.232814e-02 8.601405e-02 [37,] -1.896315e-02 -3.232814e-02 [38,] 2.322169e-02 -1.896315e-02 [39,] -6.523539e-03 2.322169e-02 [40,] -2.121215e-02 -6.523539e-03 [41,] 2.144957e-02 -2.121215e-02 [42,] -9.888493e-02 2.144957e-02 [43,] -1.821240e-02 -9.888493e-02 [44,] 4.733019e-02 -1.821240e-02 [45,] 3.186202e-02 4.733019e-02 [46,] 5.116698e-02 3.186202e-02 [47,] 1.774137e-01 5.116698e-02 [48,] 4.192417e-02 1.774137e-01 [49,] 4.800806e-02 4.192417e-02 [50,] 4.823206e-02 4.800806e-02 [51,] 3.336574e-02 4.823206e-02 [52,] -5.545850e-03 3.336574e-02 [53,] -3.386358e-02 -5.545850e-03 [54,] 6.049335e-03 -3.386358e-02 [55,] 2.288520e-02 6.049335e-03 [56,] 1.242683e-02 2.288520e-02 [57,] 4.180620e-02 1.242683e-02 [58,] 2.848336e-02 4.180620e-02 [59,] 4.532089e-02 2.848336e-02 [60,] 2.669414e-03 4.532089e-02 [61,] 9.032165e-02 2.669414e-03 [62,] 1.420339e-02 9.032165e-02 [63,] -3.305232e-02 1.420339e-02 [64,] -8.250061e-02 -3.305232e-02 [65,] -6.076084e-02 -8.250061e-02 [66,] -8.570378e-02 -6.076084e-02 [67,] -4.906117e-02 -8.570378e-02 [68,] -7.191868e-03 -4.906117e-02 [69,] -1.505567e-02 -7.191868e-03 [70,] -1.605124e-02 -1.505567e-02 [71,] -7.745728e-03 -1.605124e-02 [72,] 6.689852e-03 -7.745728e-03 [73,] -3.502609e-02 6.689852e-03 [74,] -1.087028e-03 -3.502609e-02 [75,] -6.760500e-02 -1.087028e-03 [76,] -5.597239e-02 -6.760500e-02 [77,] -6.450568e-02 -5.597239e-02 [78,] 6.608449e-02 -6.450568e-02 [79,] 4.033968e-02 6.608449e-02 [80,] 2.020683e-02 4.033968e-02 [81,] -1.964535e-03 2.020683e-02 [82,] 4.393917e-02 -1.964535e-03 [83,] 1.191537e-01 4.393917e-02 [84,] -1.515581e-02 1.191537e-01 [85,] 3.450210e-02 -1.515581e-02 [86,] -6.568944e-03 3.450210e-02 [87,] 5.700447e-02 -6.568944e-03 [88,] 5.158803e-02 5.700447e-02 [89,] 1.797865e-02 5.158803e-02 [90,] 4.527665e-02 1.797865e-02 [91,] 1.692032e-02 4.527665e-02 [92,] -2.617146e-02 1.692032e-02 [93,] -2.350701e-02 -2.617146e-02 [94,] -9.298022e-03 -2.350701e-02 [95,] -5.370974e-02 -9.298022e-03 [96,] -1.001076e-01 -5.370974e-02 [97,] -2.413658e-02 -1.001076e-01 [98,] -7.077257e-02 -2.413658e-02 [99,] -5.280696e-02 -7.077257e-02 [100,] 1.569186e-02 -5.280696e-02 [101,] -2.938812e-02 1.569186e-02 [102,] -2.108659e-02 -2.938812e-02 [103,] -8.542933e-02 -2.108659e-02 [104,] -1.032971e-01 -8.542933e-02 [105,] -3.737974e-02 -1.032971e-01 [106,] -3.371223e-02 -3.737974e-02 [107,] -1.872499e-02 -3.371223e-02 [108,] -4.779196e-02 -1.872499e-02 [109,] 6.494192e-02 -4.779196e-02 [110,] -1.890290e-02 6.494192e-02 [111,] -6.006423e-02 -1.890290e-02 [112,] 4.302417e-02 -6.006423e-02 [113,] 1.890069e-02 4.302417e-02 [114,] -4.888438e-02 1.890069e-02 [115,] -4.990640e-02 -4.888438e-02 [116,] 8.297748e-03 -4.990640e-02 [117,] 8.677885e-03 8.297748e-03 [118,] -2.573946e-02 8.677885e-03 [119,] -3.856536e-02 -2.573946e-02 [120,] 3.787728e-02 -3.856536e-02 [121,] -4.156505e-02 3.787728e-02 [122,] -1.225025e-02 -4.156505e-02 [123,] 7.424041e-02 -1.225025e-02 [124,] 9.902617e-02 7.424041e-02 [125,] 8.700091e-02 9.902617e-02 [126,] 6.294399e-02 8.700091e-02 [127,] 5.536771e-02 6.294399e-02 [128,] 5.729102e-02 5.536771e-02 [129,] 4.199472e-02 5.729102e-02 [130,] 2.244353e-02 4.199472e-02 [131,] 3.915677e-02 2.244353e-02 [132,] -2.963115e-02 3.915677e-02 [133,] 2.495647e-02 -2.963115e-02 [134,] -2.711325e-03 2.495647e-02 [135,] 2.531172e-02 -2.711325e-03 [136,] -1.680039e-02 2.531172e-02 [137,] -4.571559e-03 -1.680039e-02 [138,] 1.023166e-02 -4.571559e-03 [139,] 1.440494e-02 1.023166e-02 [140,] 7.889684e-02 1.440494e-02 [141,] 2.892316e-02 7.889684e-02 [142,] 1.118432e-02 2.892316e-02 [143,] -2.073620e-02 1.118432e-02 [144,] -9.673034e-03 -2.073620e-02 [145,] -2.927007e-02 -9.673034e-03 [146,] -6.356316e-02 -2.927007e-02 [147,] -8.547313e-02 -6.356316e-02 [148,] -6.286902e-03 -8.547313e-02 [149,] 3.166478e-04 -6.286902e-03 [150,] 1.580738e-02 3.166478e-04 [151,] -5.634029e-03 1.580738e-02 [152,] 1.095322e-01 -5.634029e-03 [153,] -5.973461e-02 1.095322e-01 [154,] 7.412073e-02 -5.973461e-02 [155,] 3.257950e-02 7.412073e-02 [156,] 9.887833e-02 3.257950e-02 [157,] 1.406885e-02 9.887833e-02 [158,] 6.847811e-02 1.406885e-02 [159,] 1.152124e-02 6.847811e-02 [160,] -1.874648e-02 1.152124e-02 [161,] -2.139630e-02 -1.874648e-02 [162,] 7.225242e-02 -2.139630e-02 [163,] -4.855794e-02 7.225242e-02 [164,] -5.625824e-02 -4.855794e-02 [165,] 5.400982e-03 -5.625824e-02 [166,] -9.024693e-02 5.400982e-03 [167,] -5.112799e-02 -9.024693e-02 [168,] -8.193670e-02 -5.112799e-02 [169,] -3.723084e-02 -8.193670e-02 [170,] 4.771475e-02 -3.723084e-02 [171,] -3.689886e-02 4.771475e-02 [172,] -1.051736e-01 -3.689886e-02 [173,] -8.907027e-02 -1.051736e-01 [174,] -1.289742e-01 -8.907027e-02 [175,] -7.500234e-02 -1.289742e-01 [176,] -7.647941e-02 -7.500234e-02 [177,] -1.075904e-02 -7.647941e-02 [178,] -1.832546e-02 -1.075904e-02 [179,] -1.783339e-02 -1.832546e-02 [180,] -8.785106e-02 -1.783339e-02 [181,] -4.260441e-02 -8.785106e-02 [182,] -9.643693e-02 -4.260441e-02 [183,] 7.425478e-03 -9.643693e-02 [184,] 3.911600e-02 7.425478e-03 [185,] 3.858395e-02 3.911600e-02 [186,] 3.226214e-02 3.858395e-02 [187,] 2.112312e-02 3.226214e-02 [188,] 3.217684e-02 2.112312e-02 [189,] 3.282109e-02 3.217684e-02 [190,] -2.089350e-02 3.282109e-02 [191,] -2.353185e-02 -2.089350e-02 [192,] 5.909980e-03 -2.353185e-02 [193,] -8.904637e-02 5.909980e-03 [194,] -1.711114e-02 -8.904637e-02 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -3.711888e-03 -4.444846e-02 2 -2.274669e-02 -3.711888e-03 3 -5.184791e-02 -2.274669e-02 4 -1.303356e-02 -5.184791e-02 5 -3.004261e-02 -1.303356e-02 6 8.286117e-02 -3.004261e-02 7 1.931696e-01 8.286117e-02 8 4.465732e-02 1.931696e-01 9 -3.286575e-02 4.465732e-02 10 -2.756609e-03 -3.286575e-02 11 1.510675e-02 -2.756609e-03 12 8.034284e-05 1.510675e-02 13 -6.980058e-02 8.034284e-05 14 -1.300558e-02 -6.980058e-02 15 4.913747e-02 -1.300558e-02 16 -3.912712e-03 4.913747e-02 17 -1.050460e-02 -3.912712e-03 18 3.803441e-02 -1.050460e-02 19 -7.861252e-03 3.803441e-02 20 4.626037e-02 -7.861252e-03 21 1.490350e-02 4.626037e-02 22 6.479613e-02 1.490350e-02 23 -1.424073e-02 6.479613e-02 24 -1.465345e-02 -1.424073e-02 25 1.712489e-02 -1.465345e-02 26 6.860326e-03 1.712489e-02 27 -6.719225e-02 6.860326e-03 28 -1.112212e-02 -6.719225e-02 29 -1.513912e-02 -1.112212e-02 30 1.629830e-02 -1.513912e-02 31 1.409465e-01 1.629830e-02 32 9.208586e-02 1.409465e-01 33 3.914520e-02 9.208586e-02 34 3.202293e-02 3.914520e-02 35 8.601405e-02 3.202293e-02 36 -3.232814e-02 8.601405e-02 37 -1.896315e-02 -3.232814e-02 38 2.322169e-02 -1.896315e-02 39 -6.523539e-03 2.322169e-02 40 -2.121215e-02 -6.523539e-03 41 2.144957e-02 -2.121215e-02 42 -9.888493e-02 2.144957e-02 43 -1.821240e-02 -9.888493e-02 44 4.733019e-02 -1.821240e-02 45 3.186202e-02 4.733019e-02 46 5.116698e-02 3.186202e-02 47 1.774137e-01 5.116698e-02 48 4.192417e-02 1.774137e-01 49 4.800806e-02 4.192417e-02 50 4.823206e-02 4.800806e-02 51 3.336574e-02 4.823206e-02 52 -5.545850e-03 3.336574e-02 53 -3.386358e-02 -5.545850e-03 54 6.049335e-03 -3.386358e-02 55 2.288520e-02 6.049335e-03 56 1.242683e-02 2.288520e-02 57 4.180620e-02 1.242683e-02 58 2.848336e-02 4.180620e-02 59 4.532089e-02 2.848336e-02 60 2.669414e-03 4.532089e-02 61 9.032165e-02 2.669414e-03 62 1.420339e-02 9.032165e-02 63 -3.305232e-02 1.420339e-02 64 -8.250061e-02 -3.305232e-02 65 -6.076084e-02 -8.250061e-02 66 -8.570378e-02 -6.076084e-02 67 -4.906117e-02 -8.570378e-02 68 -7.191868e-03 -4.906117e-02 69 -1.505567e-02 -7.191868e-03 70 -1.605124e-02 -1.505567e-02 71 -7.745728e-03 -1.605124e-02 72 6.689852e-03 -7.745728e-03 73 -3.502609e-02 6.689852e-03 74 -1.087028e-03 -3.502609e-02 75 -6.760500e-02 -1.087028e-03 76 -5.597239e-02 -6.760500e-02 77 -6.450568e-02 -5.597239e-02 78 6.608449e-02 -6.450568e-02 79 4.033968e-02 6.608449e-02 80 2.020683e-02 4.033968e-02 81 -1.964535e-03 2.020683e-02 82 4.393917e-02 -1.964535e-03 83 1.191537e-01 4.393917e-02 84 -1.515581e-02 1.191537e-01 85 3.450210e-02 -1.515581e-02 86 -6.568944e-03 3.450210e-02 87 5.700447e-02 -6.568944e-03 88 5.158803e-02 5.700447e-02 89 1.797865e-02 5.158803e-02 90 4.527665e-02 1.797865e-02 91 1.692032e-02 4.527665e-02 92 -2.617146e-02 1.692032e-02 93 -2.350701e-02 -2.617146e-02 94 -9.298022e-03 -2.350701e-02 95 -5.370974e-02 -9.298022e-03 96 -1.001076e-01 -5.370974e-02 97 -2.413658e-02 -1.001076e-01 98 -7.077257e-02 -2.413658e-02 99 -5.280696e-02 -7.077257e-02 100 1.569186e-02 -5.280696e-02 101 -2.938812e-02 1.569186e-02 102 -2.108659e-02 -2.938812e-02 103 -8.542933e-02 -2.108659e-02 104 -1.032971e-01 -8.542933e-02 105 -3.737974e-02 -1.032971e-01 106 -3.371223e-02 -3.737974e-02 107 -1.872499e-02 -3.371223e-02 108 -4.779196e-02 -1.872499e-02 109 6.494192e-02 -4.779196e-02 110 -1.890290e-02 6.494192e-02 111 -6.006423e-02 -1.890290e-02 112 4.302417e-02 -6.006423e-02 113 1.890069e-02 4.302417e-02 114 -4.888438e-02 1.890069e-02 115 -4.990640e-02 -4.888438e-02 116 8.297748e-03 -4.990640e-02 117 8.677885e-03 8.297748e-03 118 -2.573946e-02 8.677885e-03 119 -3.856536e-02 -2.573946e-02 120 3.787728e-02 -3.856536e-02 121 -4.156505e-02 3.787728e-02 122 -1.225025e-02 -4.156505e-02 123 7.424041e-02 -1.225025e-02 124 9.902617e-02 7.424041e-02 125 8.700091e-02 9.902617e-02 126 6.294399e-02 8.700091e-02 127 5.536771e-02 6.294399e-02 128 5.729102e-02 5.536771e-02 129 4.199472e-02 5.729102e-02 130 2.244353e-02 4.199472e-02 131 3.915677e-02 2.244353e-02 132 -2.963115e-02 3.915677e-02 133 2.495647e-02 -2.963115e-02 134 -2.711325e-03 2.495647e-02 135 2.531172e-02 -2.711325e-03 136 -1.680039e-02 2.531172e-02 137 -4.571559e-03 -1.680039e-02 138 1.023166e-02 -4.571559e-03 139 1.440494e-02 1.023166e-02 140 7.889684e-02 1.440494e-02 141 2.892316e-02 7.889684e-02 142 1.118432e-02 2.892316e-02 143 -2.073620e-02 1.118432e-02 144 -9.673034e-03 -2.073620e-02 145 -2.927007e-02 -9.673034e-03 146 -6.356316e-02 -2.927007e-02 147 -8.547313e-02 -6.356316e-02 148 -6.286902e-03 -8.547313e-02 149 3.166478e-04 -6.286902e-03 150 1.580738e-02 3.166478e-04 151 -5.634029e-03 1.580738e-02 152 1.095322e-01 -5.634029e-03 153 -5.973461e-02 1.095322e-01 154 7.412073e-02 -5.973461e-02 155 3.257950e-02 7.412073e-02 156 9.887833e-02 3.257950e-02 157 1.406885e-02 9.887833e-02 158 6.847811e-02 1.406885e-02 159 1.152124e-02 6.847811e-02 160 -1.874648e-02 1.152124e-02 161 -2.139630e-02 -1.874648e-02 162 7.225242e-02 -2.139630e-02 163 -4.855794e-02 7.225242e-02 164 -5.625824e-02 -4.855794e-02 165 5.400982e-03 -5.625824e-02 166 -9.024693e-02 5.400982e-03 167 -5.112799e-02 -9.024693e-02 168 -8.193670e-02 -5.112799e-02 169 -3.723084e-02 -8.193670e-02 170 4.771475e-02 -3.723084e-02 171 -3.689886e-02 4.771475e-02 172 -1.051736e-01 -3.689886e-02 173 -8.907027e-02 -1.051736e-01 174 -1.289742e-01 -8.907027e-02 175 -7.500234e-02 -1.289742e-01 176 -7.647941e-02 -7.500234e-02 177 -1.075904e-02 -7.647941e-02 178 -1.832546e-02 -1.075904e-02 179 -1.783339e-02 -1.832546e-02 180 -8.785106e-02 -1.783339e-02 181 -4.260441e-02 -8.785106e-02 182 -9.643693e-02 -4.260441e-02 183 7.425478e-03 -9.643693e-02 184 3.911600e-02 7.425478e-03 185 3.858395e-02 3.911600e-02 186 3.226214e-02 3.858395e-02 187 2.112312e-02 3.226214e-02 188 3.217684e-02 2.112312e-02 189 3.282109e-02 3.217684e-02 190 -2.089350e-02 3.282109e-02 191 -2.353185e-02 -2.089350e-02 192 5.909980e-03 -2.353185e-02 193 -8.904637e-02 5.909980e-03 194 -1.711114e-02 -8.904637e-02 > 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/7axfi1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/87gml1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9euam1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10c03d1386790450.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11xs921386790450.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/12tmdo1386790450.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/13qhkl1386790450.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/149a1l1386790450.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/15y4cw1386790450.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/16slah1386790450.tab") + } > > try(system("convert tmp/1zouh1386790450.ps tmp/1zouh1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/2jevi1386790450.ps tmp/2jevi1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/39udr1386790450.ps tmp/39udr1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/468981386790450.ps tmp/468981386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/5rtzp1386790450.ps tmp/5rtzp1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/6v1g81386790450.ps tmp/6v1g81386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/7axfi1386790450.ps tmp/7axfi1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/87gml1386790450.ps tmp/87gml1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/9euam1386790450.ps tmp/9euam1386790450.png",intern=TRUE)) character(0) > try(system("convert tmp/10c03d1386790450.ps tmp/10c03d1386790450.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 33.634 5.934 40.427