R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-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(829 + ,58198 + ,49 + ,233 + ,538 + ,65968 + ,24 + ,157 + ,186 + ,7176 + ,17 + ,70 + ,1405 + ,78306 + ,66 + ,360 + ,1947 + ,127587 + ,83 + ,683 + ,3534 + ,250877 + ,127 + ,906 + ,811 + ,65936 + ,33 + ,275 + ,609 + ,72513 + ,30 + ,142 + ,1151 + ,72507 + ,32 + ,297 + ,1779 + ,170683 + ,63 + ,604 + ,834 + ,66288 + ,34 + ,256 + ,1211 + ,94815 + ,43 + ,380 + ,897 + ,45496 + ,67 + ,330 + ,1574 + ,83049 + ,59 + ,525 + ,688 + ,66960 + ,24 + ,202 + ,854 + ,72377 + ,38 + ,313 + ,848 + ,61175 + ,32 + ,197 + ,324 + ,15580 + ,20 + ,85 + ,1602 + ,71693 + ,54 + ,494 + ,412 + ,13397 + ,13 + ,131 + ,618 + ,38921 + ,35 + ,233 + ,1244 + ,97709 + ,49 + ,351 + ,616 + ,47899 + ,27 + ,227 + ,1107 + ,61674 + ,30 + ,317 + ,1079 + ,77395 + ,50 + ,367 + ,611 + ,65152 + ,11 + ,223 + ,1188 + ,88286 + ,94 + ,390 + ,618 + ,75108 + ,50 + ,145 + ,1392 + ,182314 + ,58 + ,445 + ,1189 + ,91721 + ,25 + ,481 + ,752 + ,56374 + ,27 + ,223 + ,1055 + ,104756 + ,23 + ,361 + ,1044 + ,50485 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,17 + ,154 + ,226 + ,12137 + ,10 + ,65 + ,81 + ,7131 + ,4 + ,27 + ,61 + ,4194 + ,11 + ,14 + ,313 + ,21416 + ,9 + ,96 + ,239 + ,19205 + ,10 + ,76 + ,462 + ,38232 + ,8 + ,185) + ,dim=c(4 + ,144) + ,dimnames=list(c('Pageviews' + ,'time' + ,'logins' + ,'compendiumviews') + ,1:144)) > y <- array(NA,dim=c(4,144),dimnames=list(c('Pageviews','time','logins','compendiumviews'),1:144)) > 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' > library(lattice) > library(lmtest) Loading required package: zoo > 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 Pageviews time logins compendiumviews 1 829 58198 49 233 2 538 65968 24 157 3 186 7176 17 70 4 1405 78306 66 360 5 1947 127587 83 683 6 3534 250877 127 906 7 811 65936 33 275 8 609 72513 30 142 9 1151 72507 32 297 10 1779 170683 63 604 11 834 66288 34 256 12 1211 94815 43 380 13 897 45496 67 330 14 1574 83049 59 525 15 688 66960 24 202 16 854 72377 38 313 17 848 61175 32 197 18 324 15580 20 85 19 1602 71693 54 494 20 412 13397 13 131 21 618 38921 35 233 22 1244 97709 49 351 23 616 47899 27 227 24 1107 61674 30 317 25 1079 77395 50 367 26 611 65152 11 223 27 1188 88286 94 390 28 618 75108 50 145 29 1392 182314 58 445 30 1189 91721 25 481 31 752 56374 27 223 32 1055 104756 23 361 33 1044 50485 56 325 34 580 29013 39 169 35 1116 90349 29 380 36 0 0 0 0 37 626 61484 33 280 38 1183 65245 34 363 39 1016 35361 20 211 40 1076 106880 34 381 41 1061 82577 33 340 42 680 53655 25 277 43 404 40064 12 140 44 1026 66118 44 397 45 643 55561 28 218 46 415 31331 30 140 47 328 31350 12 92 48 960 93341 53 333 49 769 57002 39 256 50 1066 60206 27 414 51 425 33820 20 129 52 696 49791 35 189 53 1020 113697 41 422 54 890 97673 43 310 55 916 89612 32 333 56 898 66268 29 285 57 696 64319 24 204 58 383 25090 11 118 59 566 62131 37 193 60 548 23630 22 194 61 457 31969 21 139 62 782 32592 34 291 63 535 35738 19 176 64 475 42406 18 145 65 374 47859 12 122 66 771 55240 22 256 67 1140 65341 42 296 68 1502 61854 44 425 69 500 35185 19 138 70 82 12207 10 25 71 1569 112537 72 490 72 568 43886 24 179 73 606 49028 33 224 74 918 40699 39 265 75 833 46357 20 293 76 460 17667 19 136 77 685 59058 27 209 78 888 54106 38 301 79 410 23795 13 118 80 615 34323 34 241 81 447 37071 29 106 82 650 78258 26 254 83 545 32392 15 172 84 830 55020 19 307 85 515 29613 25 176 86 853 56879 28 260 87 1312 109785 108 291 88 400 24612 25 107 89 404 38010 22 139 90 639 53398 22 194 91 773 54198 20 295 92 1075 66038 43 317 93 510 61352 28 166 94 573 48096 29 210 95 434 25194 22 182 96 1294 118291 57 442 97 718 71876 27 225 98 222 19349 11 67 99 880 67369 51 271 100 816 54015 35 332 101 305 19719 14 111 102 425 25497 11 141 103 578 55049 36 182 104 306 24912 21 83 105 367 28591 19 80 106 463 24716 13 152 107 520 52452 16 130 108 294 17850 16 71 109 0 0 0 0 110 566 35269 12 152 111 463 27554 31 149 112 630 55167 12 196 113 632 42982 33 179 114 462 42115 40 163 115 38 3058 4 1 116 0 0 0 0 117 592 96347 24 196 118 631 43490 26 238 119 925 62694 47 263 120 441 36901 20 170 121 778 43410 19 292 122 797 78320 31 224 123 469 37972 20 136 124 639 34563 21 173 125 484 39841 18 129 126 214 16145 9 56 127 696 45310 17 233 128 492 57938 14 172 129 638 48187 14 221 130 256 11796 9 79 131 80 7627 8 25 132 587 62522 28 207 133 41 6836 3 11 134 497 28834 14 209 135 42 5118 3 6 136 340 20825 13 112 137 0 0 0 0 138 395 34363 17 154 139 226 12137 10 65 140 81 7131 4 27 141 61 4194 11 14 142 313 21416 9 96 143 239 19205 10 76 144 462 38232 8 185 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) time logins compendiumviews -16.418563 0.001535 4.330579 2.275536 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -275.95 -62.07 8.76 39.14 553.68 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.642e+01 1.700e+01 -0.966 0.33572 time 1.535e-03 5.285e-04 2.904 0.00428 ** logins 4.331e+00 7.739e-01 5.596 1.12e-07 *** compendiumviews 2.276e+00 1.404e-01 16.212 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 106.3 on 140 degrees of freedom Multiple R-squared: 0.9451, Adjusted R-squared: 0.9439 F-statistic: 803.7 on 3 and 140 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,] 0.7293763 5.412474e-01 2.706237e-01 [2,] 0.6990293 6.019414e-01 3.009707e-01 [3,] 0.9921210 1.575800e-02 7.878998e-03 [4,] 0.9985609 2.878212e-03 1.439106e-03 [5,] 0.9970795 5.841000e-03 2.920500e-03 [6,] 0.9950571 9.885814e-03 4.942907e-03 [7,] 0.9990758 1.848312e-03 9.241559e-04 [8,] 0.9992528 1.494486e-03 7.472431e-04 [9,] 0.9986278 2.744338e-03 1.372169e-03 [10,] 0.9983194 3.361276e-03 1.680638e-03 [11,] 0.9991080 1.784027e-03 8.920133e-04 [12,] 0.9987679 2.464229e-03 1.232114e-03 [13,] 0.9998329 3.341821e-04 1.670910e-04 [14,] 0.9998363 3.274896e-04 1.637448e-04 [15,] 0.9998007 3.985573e-04 1.992787e-04 [16,] 0.9997480 5.039545e-04 2.519772e-04 [17,] 0.9996200 7.600957e-04 3.800479e-04 [18,] 0.9998981 2.037541e-04 1.018770e-04 [19,] 0.9998768 2.464779e-04 1.232389e-04 [20,] 0.9997891 4.217467e-04 2.108734e-04 [21,] 0.9999756 4.887969e-05 2.443985e-05 [22,] 0.9999598 8.033834e-05 4.016917e-05 [23,] 0.9999957 8.554292e-06 4.277146e-06 [24,] 0.9999976 4.842074e-06 2.421037e-06 [25,] 0.9999963 7.417743e-06 3.708872e-06 [26,] 0.9999940 1.209772e-05 6.048858e-06 [27,] 0.9999888 2.232098e-05 1.116049e-05 [28,] 0.9999803 3.947594e-05 1.973797e-05 [29,] 0.9999674 6.513069e-05 3.256535e-05 [30,] 0.9999489 1.022426e-04 5.112128e-05 [31,] 0.9999914 1.721334e-05 8.606672e-06 [32,] 0.9999940 1.200428e-05 6.002141e-06 [33,] 1.0000000 5.483421e-10 2.741710e-10 [34,] 1.0000000 7.820652e-10 3.910326e-10 [35,] 1.0000000 1.240055e-09 6.200277e-10 [36,] 1.0000000 1.038205e-09 5.191023e-10 [37,] 1.0000000 2.272238e-09 1.136119e-09 [38,] 1.0000000 1.133770e-09 5.668850e-10 [39,] 1.0000000 2.276539e-09 1.138269e-09 [40,] 1.0000000 3.376952e-09 1.688476e-09 [41,] 1.0000000 6.434673e-09 3.217337e-09 [42,] 1.0000000 3.677927e-09 1.838963e-09 [43,] 1.0000000 6.621840e-09 3.310920e-09 [44,] 1.0000000 1.085630e-08 5.428151e-09 [45,] 1.0000000 2.202350e-08 1.101175e-08 [46,] 1.0000000 3.522569e-08 1.761285e-08 [47,] 1.0000000 8.726518e-10 4.363259e-10 [48,] 1.0000000 6.561309e-10 3.280654e-10 [49,] 1.0000000 7.863034e-10 3.931517e-10 [50,] 1.0000000 1.439479e-09 7.197393e-10 [51,] 1.0000000 2.393913e-09 1.196956e-09 [52,] 1.0000000 4.311819e-09 2.155910e-09 [53,] 1.0000000 3.817416e-09 1.908708e-09 [54,] 1.0000000 7.696783e-09 3.848392e-09 [55,] 1.0000000 1.550497e-08 7.752485e-09 [56,] 1.0000000 2.052926e-08 1.026463e-08 [57,] 1.0000000 4.087034e-08 2.043517e-08 [58,] 1.0000000 7.867326e-08 3.933663e-08 [59,] 0.9999999 1.553308e-07 7.766540e-08 [60,] 0.9999999 2.847912e-07 1.423956e-07 [61,] 1.0000000 2.436490e-08 1.218245e-08 [62,] 1.0000000 3.118226e-11 1.559113e-11 [63,] 1.0000000 4.578702e-11 2.289351e-11 [64,] 1.0000000 8.879780e-11 4.439890e-11 [65,] 1.0000000 1.559614e-10 7.798068e-11 [66,] 1.0000000 3.527831e-10 1.763916e-10 [67,] 1.0000000 3.086704e-10 1.543352e-10 [68,] 1.0000000 1.464778e-10 7.323891e-11 [69,] 1.0000000 2.409323e-10 1.204661e-10 [70,] 1.0000000 3.761114e-10 1.880557e-10 [71,] 1.0000000 7.791523e-10 3.895761e-10 [72,] 1.0000000 1.701081e-09 8.505407e-10 [73,] 1.0000000 2.499369e-09 1.249685e-09 [74,] 1.0000000 2.030631e-09 1.015315e-09 [75,] 1.0000000 4.030998e-09 2.015499e-09 [76,] 1.0000000 1.404642e-09 7.023212e-10 [77,] 1.0000000 2.065352e-09 1.032676e-09 [78,] 1.0000000 4.532633e-09 2.266316e-09 [79,] 1.0000000 9.959732e-09 4.979866e-09 [80,] 1.0000000 8.243970e-09 4.121985e-09 [81,] 1.0000000 7.685422e-09 3.842711e-09 [82,] 1.0000000 1.504811e-08 7.524056e-09 [83,] 1.0000000 2.638510e-08 1.319255e-08 [84,] 1.0000000 4.603451e-08 2.301726e-08 [85,] 1.0000000 8.976030e-08 4.488015e-08 [86,] 1.0000000 1.907105e-08 9.535523e-09 [87,] 1.0000000 2.820832e-08 1.410416e-08 [88,] 1.0000000 3.872092e-08 1.936046e-08 [89,] 1.0000000 3.936304e-08 1.968152e-08 [90,] 1.0000000 5.736374e-08 2.868187e-08 [91,] 0.9999999 1.299284e-07 6.496421e-08 [92,] 0.9999999 2.847642e-07 1.423821e-07 [93,] 0.9999997 6.003124e-07 3.001562e-07 [94,] 0.9999999 2.009932e-07 1.004966e-07 [95,] 0.9999998 3.968571e-07 1.984286e-07 [96,] 0.9999996 8.332156e-07 4.166078e-07 [97,] 0.9999993 1.420976e-06 7.104878e-07 [98,] 0.9999985 3.090462e-06 1.545231e-06 [99,] 0.9999981 3.722975e-06 1.861487e-06 [100,] 0.9999964 7.150341e-06 3.575170e-06 [101,] 0.9999969 6.132118e-06 3.066059e-06 [102,] 0.9999950 1.007260e-05 5.036300e-06 [103,] 0.9999894 2.124675e-05 1.062337e-05 [104,] 0.9999969 6.233404e-06 3.116702e-06 [105,] 0.9999937 1.265891e-05 6.329453e-06 [106,] 0.9999931 1.384296e-05 6.921481e-06 [107,] 0.9999883 2.341303e-05 1.170652e-05 [108,] 0.9999986 2.797334e-06 1.398667e-06 [109,] 0.9999966 6.816619e-06 3.408309e-06 [110,] 0.9999917 1.651991e-05 8.259954e-06 [111,] 0.9999910 1.799911e-05 8.999555e-06 [112,] 0.9999912 1.751996e-05 8.759981e-06 [113,] 0.9999793 4.145757e-05 2.072878e-05 [114,] 0.9999852 2.969066e-05 1.484533e-05 [115,] 0.9999632 7.360283e-05 3.680141e-05 [116,] 0.9999419 1.161232e-04 5.806161e-05 [117,] 0.9998711 2.577827e-04 1.288913e-04 [118,] 0.9999860 2.794335e-05 1.397168e-05 [119,] 0.9999963 7.460199e-06 3.730099e-06 [120,] 0.9999923 1.534984e-05 7.674920e-06 [121,] 0.9999965 6.973624e-06 3.486812e-06 [122,] 0.9999869 2.616723e-05 1.308361e-05 [123,] 0.9999907 1.865870e-05 9.329352e-06 [124,] 0.9999824 3.513088e-05 1.756544e-05 [125,] 0.9999400 1.199495e-04 5.997475e-05 [126,] 0.9997945 4.110430e-04 2.055215e-04 [127,] 0.9993005 1.398919e-03 6.994593e-04 [128,] 0.9985355 2.928931e-03 1.464465e-03 [129,] 0.9945818 1.083640e-02 5.418201e-03 [130,] 0.9809768 3.804636e-02 1.902318e-02 [131,] 0.9496027 1.007946e-01 5.039728e-02 > postscript(file="/var/www/rcomp/tmp/15jiy1322067264.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/www/rcomp/tmp/28dys1322067264.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3r61b1322067264.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4njhs1322067264.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5y4fq1322067264.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 144 Frequency = 1 1 2 3 4 5 6 13.6816464 -8.0406862 -41.5045566 196.2013073 -146.0670204 553.6828962 7 8 9 10 11 12 -42.4800532 61.0617822 241.7017187 -113.8438768 18.8842075 30.9512741 13 14 15 16 17 18 -197.4972113 12.7710015 38.0373842 -117.4907771 183.6508676 36.4698496 19 20 21 22 23 24 150.3978898 53.4603187 -107.0985050 99.5158267 -74.5826003 177.4816743 25 26 27 28 29 30 -75.0397177 -27.6759195 -225.6411014 -27.3599474 -135.2352348 -138.1779178 31 32 33 34 35 36 57.5097418 -10.4621792 0.8583295 -1.5769318 3.4350532 16.4185633 37 38 39 40 41 42 -232.0235583 126.0029196 411.3868680 -85.8697873 34.0648261 -124.5341732 43 44 45 46 47 48 -11.6249056 -153.0112311 -43.1951365 -65.1694818 34.9775202 -154.1416096 49 50 51 52 53 54 -53.5139369 -69.0001040 9.3463969 54.3387696 -275.9454687 -135.1484486 55 56 57 58 59 60 -101.4751285 38.5772556 45.5404580 44.7537583 -112.3674210 -8.5821518 61 62 63 64 65 66 17.1018882 -61.0335056 13.7824902 18.4187794 -12.6312020 24.8107241 67 68 69 70 71 72 200.6718438 265.8193356 66.1017661 -20.5143578 -14.1492014 5.7951528 73 74 75 76 77 78 -105.4725734 100.0326459 24.9131580 57.5443695 18.2470943 -28.1368961 79 80 81 82 83 84 65.0805281 -116.9139177 39.7179703 -144.2949920 55.3433304 -18.9121676 85 86 87 88 89 90 -22.7986214 69.2091066 30.0061887 26.8903132 -49.5021093 36.7215875 91 92 93 94 95 96 -51.6744766 82.4850529 -66.7569008 -87.8620540 -97.6765821 -123.7976214 97 98 99 100 101 102 -4.8381404 8.6190000 -44.5281075 -157.5470886 -22.0643118 33.7916476 103 104 105 106 107 108 -60.1345067 4.3649763 75.2051846 39.2984877 90.7915682 52.1650429 109 110 111 112 113 114 16.4185633 130.4293681 -36.1818902 63.7607528 32.2076503 -130.3669117 115 116 117 118 119 120 30.1264349 16.4185633 -89.4207937 -73.5147518 43.1749989 -72.6801698 121 122 123 124 125 126 -18.9568457 49.2230227 31.0439912 117.7516590 67.7648392 39.2294536 127 128 129 130 131 132 39.0442986 -32.5412432 16.9260465 35.5681832 -6.8225327 -84.8499297 133 134 135 136 137 138 8.9021199 -67.0591160 23.9170684 13.2929329 16.4185633 -65.3838190 139 140 141 142 143 144 32.5716487 7.7101122 -8.5134429 39.1165980 9.6908049 -35.8894517 > postscript(file="/var/www/rcomp/tmp/6afso1322067264.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 = 144 Frequency = 1 lag(myerror, k = 1) myerror 0 13.6816464 NA 1 -8.0406862 13.6816464 2 -41.5045566 -8.0406862 3 196.2013073 -41.5045566 4 -146.0670204 196.2013073 5 553.6828962 -146.0670204 6 -42.4800532 553.6828962 7 61.0617822 -42.4800532 8 241.7017187 61.0617822 9 -113.8438768 241.7017187 10 18.8842075 -113.8438768 11 30.9512741 18.8842075 12 -197.4972113 30.9512741 13 12.7710015 -197.4972113 14 38.0373842 12.7710015 15 -117.4907771 38.0373842 16 183.6508676 -117.4907771 17 36.4698496 183.6508676 18 150.3978898 36.4698496 19 53.4603187 150.3978898 20 -107.0985050 53.4603187 21 99.5158267 -107.0985050 22 -74.5826003 99.5158267 23 177.4816743 -74.5826003 24 -75.0397177 177.4816743 25 -27.6759195 -75.0397177 26 -225.6411014 -27.6759195 27 -27.3599474 -225.6411014 28 -135.2352348 -27.3599474 29 -138.1779178 -135.2352348 30 57.5097418 -138.1779178 31 -10.4621792 57.5097418 32 0.8583295 -10.4621792 33 -1.5769318 0.8583295 34 3.4350532 -1.5769318 35 16.4185633 3.4350532 36 -232.0235583 16.4185633 37 126.0029196 -232.0235583 38 411.3868680 126.0029196 39 -85.8697873 411.3868680 40 34.0648261 -85.8697873 41 -124.5341732 34.0648261 42 -11.6249056 -124.5341732 43 -153.0112311 -11.6249056 44 -43.1951365 -153.0112311 45 -65.1694818 -43.1951365 46 34.9775202 -65.1694818 47 -154.1416096 34.9775202 48 -53.5139369 -154.1416096 49 -69.0001040 -53.5139369 50 9.3463969 -69.0001040 51 54.3387696 9.3463969 52 -275.9454687 54.3387696 53 -135.1484486 -275.9454687 54 -101.4751285 -135.1484486 55 38.5772556 -101.4751285 56 45.5404580 38.5772556 57 44.7537583 45.5404580 58 -112.3674210 44.7537583 59 -8.5821518 -112.3674210 60 17.1018882 -8.5821518 61 -61.0335056 17.1018882 62 13.7824902 -61.0335056 63 18.4187794 13.7824902 64 -12.6312020 18.4187794 65 24.8107241 -12.6312020 66 200.6718438 24.8107241 67 265.8193356 200.6718438 68 66.1017661 265.8193356 69 -20.5143578 66.1017661 70 -14.1492014 -20.5143578 71 5.7951528 -14.1492014 72 -105.4725734 5.7951528 73 100.0326459 -105.4725734 74 24.9131580 100.0326459 75 57.5443695 24.9131580 76 18.2470943 57.5443695 77 -28.1368961 18.2470943 78 65.0805281 -28.1368961 79 -116.9139177 65.0805281 80 39.7179703 -116.9139177 81 -144.2949920 39.7179703 82 55.3433304 -144.2949920 83 -18.9121676 55.3433304 84 -22.7986214 -18.9121676 85 69.2091066 -22.7986214 86 30.0061887 69.2091066 87 26.8903132 30.0061887 88 -49.5021093 26.8903132 89 36.7215875 -49.5021093 90 -51.6744766 36.7215875 91 82.4850529 -51.6744766 92 -66.7569008 82.4850529 93 -87.8620540 -66.7569008 94 -97.6765821 -87.8620540 95 -123.7976214 -97.6765821 96 -4.8381404 -123.7976214 97 8.6190000 -4.8381404 98 -44.5281075 8.6190000 99 -157.5470886 -44.5281075 100 -22.0643118 -157.5470886 101 33.7916476 -22.0643118 102 -60.1345067 33.7916476 103 4.3649763 -60.1345067 104 75.2051846 4.3649763 105 39.2984877 75.2051846 106 90.7915682 39.2984877 107 52.1650429 90.7915682 108 16.4185633 52.1650429 109 130.4293681 16.4185633 110 -36.1818902 130.4293681 111 63.7607528 -36.1818902 112 32.2076503 63.7607528 113 -130.3669117 32.2076503 114 30.1264349 -130.3669117 115 16.4185633 30.1264349 116 -89.4207937 16.4185633 117 -73.5147518 -89.4207937 118 43.1749989 -73.5147518 119 -72.6801698 43.1749989 120 -18.9568457 -72.6801698 121 49.2230227 -18.9568457 122 31.0439912 49.2230227 123 117.7516590 31.0439912 124 67.7648392 117.7516590 125 39.2294536 67.7648392 126 39.0442986 39.2294536 127 -32.5412432 39.0442986 128 16.9260465 -32.5412432 129 35.5681832 16.9260465 130 -6.8225327 35.5681832 131 -84.8499297 -6.8225327 132 8.9021199 -84.8499297 133 -67.0591160 8.9021199 134 23.9170684 -67.0591160 135 13.2929329 23.9170684 136 16.4185633 13.2929329 137 -65.3838190 16.4185633 138 32.5716487 -65.3838190 139 7.7101122 32.5716487 140 -8.5134429 7.7101122 141 39.1165980 -8.5134429 142 9.6908049 39.1165980 143 -35.8894517 9.6908049 144 NA -35.8894517 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -8.0406862 13.6816464 [2,] -41.5045566 -8.0406862 [3,] 196.2013073 -41.5045566 [4,] -146.0670204 196.2013073 [5,] 553.6828962 -146.0670204 [6,] -42.4800532 553.6828962 [7,] 61.0617822 -42.4800532 [8,] 241.7017187 61.0617822 [9,] -113.8438768 241.7017187 [10,] 18.8842075 -113.8438768 [11,] 30.9512741 18.8842075 [12,] -197.4972113 30.9512741 [13,] 12.7710015 -197.4972113 [14,] 38.0373842 12.7710015 [15,] -117.4907771 38.0373842 [16,] 183.6508676 -117.4907771 [17,] 36.4698496 183.6508676 [18,] 150.3978898 36.4698496 [19,] 53.4603187 150.3978898 [20,] -107.0985050 53.4603187 [21,] 99.5158267 -107.0985050 [22,] -74.5826003 99.5158267 [23,] 177.4816743 -74.5826003 [24,] -75.0397177 177.4816743 [25,] -27.6759195 -75.0397177 [26,] -225.6411014 -27.6759195 [27,] -27.3599474 -225.6411014 [28,] -135.2352348 -27.3599474 [29,] -138.1779178 -135.2352348 [30,] 57.5097418 -138.1779178 [31,] -10.4621792 57.5097418 [32,] 0.8583295 -10.4621792 [33,] -1.5769318 0.8583295 [34,] 3.4350532 -1.5769318 [35,] 16.4185633 3.4350532 [36,] -232.0235583 16.4185633 [37,] 126.0029196 -232.0235583 [38,] 411.3868680 126.0029196 [39,] -85.8697873 411.3868680 [40,] 34.0648261 -85.8697873 [41,] -124.5341732 34.0648261 [42,] -11.6249056 -124.5341732 [43,] -153.0112311 -11.6249056 [44,] -43.1951365 -153.0112311 [45,] -65.1694818 -43.1951365 [46,] 34.9775202 -65.1694818 [47,] -154.1416096 34.9775202 [48,] -53.5139369 -154.1416096 [49,] -69.0001040 -53.5139369 [50,] 9.3463969 -69.0001040 [51,] 54.3387696 9.3463969 [52,] -275.9454687 54.3387696 [53,] -135.1484486 -275.9454687 [54,] -101.4751285 -135.1484486 [55,] 38.5772556 -101.4751285 [56,] 45.5404580 38.5772556 [57,] 44.7537583 45.5404580 [58,] -112.3674210 44.7537583 [59,] -8.5821518 -112.3674210 [60,] 17.1018882 -8.5821518 [61,] -61.0335056 17.1018882 [62,] 13.7824902 -61.0335056 [63,] 18.4187794 13.7824902 [64,] -12.6312020 18.4187794 [65,] 24.8107241 -12.6312020 [66,] 200.6718438 24.8107241 [67,] 265.8193356 200.6718438 [68,] 66.1017661 265.8193356 [69,] -20.5143578 66.1017661 [70,] -14.1492014 -20.5143578 [71,] 5.7951528 -14.1492014 [72,] -105.4725734 5.7951528 [73,] 100.0326459 -105.4725734 [74,] 24.9131580 100.0326459 [75,] 57.5443695 24.9131580 [76,] 18.2470943 57.5443695 [77,] -28.1368961 18.2470943 [78,] 65.0805281 -28.1368961 [79,] -116.9139177 65.0805281 [80,] 39.7179703 -116.9139177 [81,] -144.2949920 39.7179703 [82,] 55.3433304 -144.2949920 [83,] -18.9121676 55.3433304 [84,] -22.7986214 -18.9121676 [85,] 69.2091066 -22.7986214 [86,] 30.0061887 69.2091066 [87,] 26.8903132 30.0061887 [88,] -49.5021093 26.8903132 [89,] 36.7215875 -49.5021093 [90,] -51.6744766 36.7215875 [91,] 82.4850529 -51.6744766 [92,] -66.7569008 82.4850529 [93,] -87.8620540 -66.7569008 [94,] -97.6765821 -87.8620540 [95,] -123.7976214 -97.6765821 [96,] -4.8381404 -123.7976214 [97,] 8.6190000 -4.8381404 [98,] -44.5281075 8.6190000 [99,] -157.5470886 -44.5281075 [100,] -22.0643118 -157.5470886 [101,] 33.7916476 -22.0643118 [102,] -60.1345067 33.7916476 [103,] 4.3649763 -60.1345067 [104,] 75.2051846 4.3649763 [105,] 39.2984877 75.2051846 [106,] 90.7915682 39.2984877 [107,] 52.1650429 90.7915682 [108,] 16.4185633 52.1650429 [109,] 130.4293681 16.4185633 [110,] -36.1818902 130.4293681 [111,] 63.7607528 -36.1818902 [112,] 32.2076503 63.7607528 [113,] -130.3669117 32.2076503 [114,] 30.1264349 -130.3669117 [115,] 16.4185633 30.1264349 [116,] -89.4207937 16.4185633 [117,] -73.5147518 -89.4207937 [118,] 43.1749989 -73.5147518 [119,] -72.6801698 43.1749989 [120,] -18.9568457 -72.6801698 [121,] 49.2230227 -18.9568457 [122,] 31.0439912 49.2230227 [123,] 117.7516590 31.0439912 [124,] 67.7648392 117.7516590 [125,] 39.2294536 67.7648392 [126,] 39.0442986 39.2294536 [127,] -32.5412432 39.0442986 [128,] 16.9260465 -32.5412432 [129,] 35.5681832 16.9260465 [130,] -6.8225327 35.5681832 [131,] -84.8499297 -6.8225327 [132,] 8.9021199 -84.8499297 [133,] -67.0591160 8.9021199 [134,] 23.9170684 -67.0591160 [135,] 13.2929329 23.9170684 [136,] 16.4185633 13.2929329 [137,] -65.3838190 16.4185633 [138,] 32.5716487 -65.3838190 [139,] 7.7101122 32.5716487 [140,] -8.5134429 7.7101122 [141,] 39.1165980 -8.5134429 [142,] 9.6908049 39.1165980 [143,] -35.8894517 9.6908049 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -8.0406862 13.6816464 2 -41.5045566 -8.0406862 3 196.2013073 -41.5045566 4 -146.0670204 196.2013073 5 553.6828962 -146.0670204 6 -42.4800532 553.6828962 7 61.0617822 -42.4800532 8 241.7017187 61.0617822 9 -113.8438768 241.7017187 10 18.8842075 -113.8438768 11 30.9512741 18.8842075 12 -197.4972113 30.9512741 13 12.7710015 -197.4972113 14 38.0373842 12.7710015 15 -117.4907771 38.0373842 16 183.6508676 -117.4907771 17 36.4698496 183.6508676 18 150.3978898 36.4698496 19 53.4603187 150.3978898 20 -107.0985050 53.4603187 21 99.5158267 -107.0985050 22 -74.5826003 99.5158267 23 177.4816743 -74.5826003 24 -75.0397177 177.4816743 25 -27.6759195 -75.0397177 26 -225.6411014 -27.6759195 27 -27.3599474 -225.6411014 28 -135.2352348 -27.3599474 29 -138.1779178 -135.2352348 30 57.5097418 -138.1779178 31 -10.4621792 57.5097418 32 0.8583295 -10.4621792 33 -1.5769318 0.8583295 34 3.4350532 -1.5769318 35 16.4185633 3.4350532 36 -232.0235583 16.4185633 37 126.0029196 -232.0235583 38 411.3868680 126.0029196 39 -85.8697873 411.3868680 40 34.0648261 -85.8697873 41 -124.5341732 34.0648261 42 -11.6249056 -124.5341732 43 -153.0112311 -11.6249056 44 -43.1951365 -153.0112311 45 -65.1694818 -43.1951365 46 34.9775202 -65.1694818 47 -154.1416096 34.9775202 48 -53.5139369 -154.1416096 49 -69.0001040 -53.5139369 50 9.3463969 -69.0001040 51 54.3387696 9.3463969 52 -275.9454687 54.3387696 53 -135.1484486 -275.9454687 54 -101.4751285 -135.1484486 55 38.5772556 -101.4751285 56 45.5404580 38.5772556 57 44.7537583 45.5404580 58 -112.3674210 44.7537583 59 -8.5821518 -112.3674210 60 17.1018882 -8.5821518 61 -61.0335056 17.1018882 62 13.7824902 -61.0335056 63 18.4187794 13.7824902 64 -12.6312020 18.4187794 65 24.8107241 -12.6312020 66 200.6718438 24.8107241 67 265.8193356 200.6718438 68 66.1017661 265.8193356 69 -20.5143578 66.1017661 70 -14.1492014 -20.5143578 71 5.7951528 -14.1492014 72 -105.4725734 5.7951528 73 100.0326459 -105.4725734 74 24.9131580 100.0326459 75 57.5443695 24.9131580 76 18.2470943 57.5443695 77 -28.1368961 18.2470943 78 65.0805281 -28.1368961 79 -116.9139177 65.0805281 80 39.7179703 -116.9139177 81 -144.2949920 39.7179703 82 55.3433304 -144.2949920 83 -18.9121676 55.3433304 84 -22.7986214 -18.9121676 85 69.2091066 -22.7986214 86 30.0061887 69.2091066 87 26.8903132 30.0061887 88 -49.5021093 26.8903132 89 36.7215875 -49.5021093 90 -51.6744766 36.7215875 91 82.4850529 -51.6744766 92 -66.7569008 82.4850529 93 -87.8620540 -66.7569008 94 -97.6765821 -87.8620540 95 -123.7976214 -97.6765821 96 -4.8381404 -123.7976214 97 8.6190000 -4.8381404 98 -44.5281075 8.6190000 99 -157.5470886 -44.5281075 100 -22.0643118 -157.5470886 101 33.7916476 -22.0643118 102 -60.1345067 33.7916476 103 4.3649763 -60.1345067 104 75.2051846 4.3649763 105 39.2984877 75.2051846 106 90.7915682 39.2984877 107 52.1650429 90.7915682 108 16.4185633 52.1650429 109 130.4293681 16.4185633 110 -36.1818902 130.4293681 111 63.7607528 -36.1818902 112 32.2076503 63.7607528 113 -130.3669117 32.2076503 114 30.1264349 -130.3669117 115 16.4185633 30.1264349 116 -89.4207937 16.4185633 117 -73.5147518 -89.4207937 118 43.1749989 -73.5147518 119 -72.6801698 43.1749989 120 -18.9568457 -72.6801698 121 49.2230227 -18.9568457 122 31.0439912 49.2230227 123 117.7516590 31.0439912 124 67.7648392 117.7516590 125 39.2294536 67.7648392 126 39.0442986 39.2294536 127 -32.5412432 39.0442986 128 16.9260465 -32.5412432 129 35.5681832 16.9260465 130 -6.8225327 35.5681832 131 -84.8499297 -6.8225327 132 8.9021199 -84.8499297 133 -67.0591160 8.9021199 134 23.9170684 -67.0591160 135 13.2929329 23.9170684 136 16.4185633 13.2929329 137 -65.3838190 16.4185633 138 32.5716487 -65.3838190 139 7.7101122 32.5716487 140 -8.5134429 7.7101122 141 39.1165980 -8.5134429 142 9.6908049 39.1165980 143 -35.8894517 9.6908049 > 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/www/rcomp/tmp/716rn1322067264.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/www/rcomp/tmp/8e38j1322067264.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/www/rcomp/tmp/9mriv1322067264.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/www/rcomp/tmp/104gnv1322067264.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/11np6a1322067264.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/128o271322067264.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > 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, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/13six21322067264.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/14yqr01322067264.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,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/15wina1322067264.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,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + 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,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + 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,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + 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/www/rcomp/tmp/16mwt91322067264.tab") + } > > try(system("convert tmp/15jiy1322067264.ps tmp/15jiy1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/28dys1322067264.ps tmp/28dys1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/3r61b1322067264.ps tmp/3r61b1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/4njhs1322067264.ps tmp/4njhs1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/5y4fq1322067264.ps tmp/5y4fq1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/6afso1322067264.ps tmp/6afso1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/716rn1322067264.ps tmp/716rn1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/8e38j1322067264.ps tmp/8e38j1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/9mriv1322067264.ps tmp/9mriv1322067264.png",intern=TRUE)) character(0) > try(system("convert tmp/104gnv1322067264.ps tmp/104gnv1322067264.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.380 0.410 5.772