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Type 'q()' to quit R. > x <- array(list(12 + ,65 + ,22 + ,114468 + ,2 + ,13 + ,54 + ,20 + ,88594 + ,4 + ,11 + ,58 + ,24 + ,74151 + ,9 + ,12 + ,77 + ,21 + ,77921 + ,2 + ,8 + ,41 + ,15 + ,53212 + ,1 + ,7 + ,0 + ,16 + ,34956 + ,2 + ,18 + ,111 + ,20 + ,149703 + ,0 + ,0 + ,1 + ,18 + ,6853 + ,0 + ,9 + ,36 + ,19 + ,58907 + ,5 + ,11 + ,60 + ,20 + ,67067 + ,0 + ,13 + ,63 + ,25 + ,110563 + ,0 + ,13 + ,71 + ,37 + ,58126 + ,7 + ,9 + ,38 + ,23 + ,57113 + ,6 + ,12 + ,76 + ,28 + ,77993 + ,3 + ,11 + ,61 + ,25 + ,68091 + ,4 + ,17 + ,125 + ,35 + ,124676 + ,0 + ,14 + ,84 + ,20 + ,109522 + ,4 + ,15 + ,69 + ,22 + ,75865 + ,3 + ,13 + ,77 + ,19 + ,79746 + ,0 + ,15 + ,100 + ,26 + ,77844 + ,5 + ,13 + ,78 + ,27 + ,98681 + ,0 + ,13 + ,76 + ,22 + ,105531 + ,1 + ,8 + ,40 + ,15 + ,51428 + ,3 + ,16 + ,81 + ,26 + ,65703 + ,5 + ,14 + ,102 + ,24 + ,72562 + ,0 + ,14 + ,70 + ,22 + ,81728 + ,0 + ,14 + ,75 + ,21 + ,95580 + ,4 + ,14 + ,93 + ,23 + ,98278 + ,0 + ,12 + ,42 + ,21 + ,46629 + ,0 + ,14 + ,95 + ,25 + ,115189 + ,0 + ,2 + ,8 + ,4 + ,15049 + ,0 + ,12 + ,87 + ,30 + ,109011 + ,5 + ,13 + ,87 + ,20 + ,134245 + ,5 + ,16 + ,112 + ,26 + ,136692 + ,0 + ,15 + ,96 + ,27 + ,149510 + ,6 + ,16 + ,93 + ,18 + ,147888 + ,6 + ,15 + ,98 + ,20 + ,79169 + ,2 + ,16 + ,99 + ,17 + ,65469 + ,5 + ,14 + ,94 + ,22 + ,56756 + ,0 + ,17 + ,98 + ,25 + ,81399 + ,3 + ,18 + ,109 + ,30 + ,104953 + ,0 + ,16 + ,108 + ,26 + ,59633 + ,1 + ,10 + ,42 + ,20 + ,63249 + ,1 + ,15 + ,108 + ,25 + ,82928 + ,2 + ,10 + ,27 + ,21 + ,50000 + ,4 + ,16 + ,115 + ,23 + ,139357 + ,0 + ,17 + ,92 + ,33 + ,110044 + ,7 + ,17 + ,106 + ,19 + ,155118 + ,7 + ,13 + ,73 + ,31 + ,83061 + ,6 + ,14 + ,105 + ,25 + ,127122 + ,0 + ,12 + ,30 + ,20 + ,45653 + ,0 + ,7 + ,13 + ,19 + ,19630 + ,4 + ,14 + ,69 + ,15 + ,67229 + ,4 + ,12 + ,72 + ,21 + ,86060 + ,0 + ,16 + ,80 + ,22 + ,88003 + ,0 + ,14 + ,106 + ,24 + ,95815 + ,0 + ,8 + ,28 + ,19 + ,85499 + ,0 + ,14 + ,70 + ,20 + ,27220 + ,0 + ,15 + ,51 + ,23 + ,109882 + ,4 + ,16 + ,90 + ,27 + ,72579 + ,0 + ,0 + ,12 + ,1 + ,5841 + ,0 + ,12 + ,84 + ,20 + ,68369 + ,0 + ,8 + ,23 + ,11 + ,24610 + ,4 + ,12 + ,57 + ,27 + ,30995 + ,0 + ,15 + ,84 + ,22 + ,150662 + ,1 + ,0 + ,4 + ,0 + ,6622 + ,0 + ,11 + ,56 + ,17 + ,93694 + ,5 + ,15 + ,18 + ,8 + ,13155 + ,0 + ,17 + ,86 + ,23 + ,111908 + ,1 + ,13 + ,39 + ,26 + ,57550 + ,7 + ,8 + ,16 + ,20 + ,16356 + ,5 + ,15 + ,18 + ,16 + ,40174 + ,2 + ,12 + ,16 + ,8 + ,13983 + ,0 + ,10 + ,42 + ,22 + ,52316 + ,1 + ,13 + ,77 + ,33 + ,99585 + ,0 + ,17 + ,30 + ,28 + ,86271 + ,0 + ,17 + ,104 + ,26 + ,131012 + ,2 + ,16 + ,121 + ,27 + ,130274 + ,0 + ,18 + ,109 + ,35 + ,159051 + ,2 + ,14 + ,57 + ,21 + ,76506 + ,0 + ,9 + ,28 + ,20 + ,49145 + ,0 + ,10 + ,56 + ,24 + ,66398 + ,4 + ,15 + ,81 + ,26 + ,127546 + ,4 + ,2 + ,2 + ,20 + ,6802 + ,8 + ,11 + ,88 + ,22 + ,99509 + ,0 + ,15 + ,41 + ,24 + ,43106 + ,4 + ,14 + ,83 + ,23 + ,108303 + ,0 + ,13 + ,55 + ,22 + ,64167 + ,1 + ,4 + ,3 + ,12 + ,8579 + ,0 + ,12 + ,54 + ,21 + ,97811 + ,9 + ,11 + ,89 + ,24 + ,84365 + ,0 + ,9 + ,41 + ,21 + ,10901 + ,3 + ,15 + ,94 + ,25 + ,91346 + ,7 + ,16 + ,101 + ,32 + ,33660 + ,5 + ,14 + ,70 + ,24 + ,93634 + ,2 + ,16 + ,111 + ,29 + ,109348 + ,1 + ,0 + ,0 + ,0 + ,0 + ,9 + ,0 + ,4 + ,0 + ,7953 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,10 + ,42 + ,20 + ,63538 + ,2 + ,12 + ,97 + ,27 + ,108281 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,7 + ,0 + ,4245 + ,0 + ,4 + ,12 + ,5 + ,21509 + ,0 + ,0 + ,0 + ,1 + ,7670 + ,0 + ,5 + ,37 + ,23 + ,10641 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,3 + ,39 + ,16 + ,41243 + ,2) + ,dim=c(5 + ,112) + ,dimnames=list(c('Score_op_20' + ,'Blogs' + ,'Reviews' + ,'Compendium_Writing' + ,'Gedeelde_compendia') + ,1:112)) > y <- array(NA,dim=c(5,112),dimnames=list(c('Score_op_20','Blogs','Reviews','Compendium_Writing','Gedeelde_compendia'),1:112)) > 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 Score_op_20 Blogs Reviews Compendium_Writing Gedeelde_compendia 1 12 65 22 114468 2 2 13 54 20 88594 4 3 11 58 24 74151 9 4 12 77 21 77921 2 5 8 41 15 53212 1 6 7 0 16 34956 2 7 18 111 20 149703 0 8 0 1 18 6853 0 9 9 36 19 58907 5 10 11 60 20 67067 0 11 13 63 25 110563 0 12 13 71 37 58126 7 13 9 38 23 57113 6 14 12 76 28 77993 3 15 11 61 25 68091 4 16 17 125 35 124676 0 17 14 84 20 109522 4 18 15 69 22 75865 3 19 13 77 19 79746 0 20 15 100 26 77844 5 21 13 78 27 98681 0 22 13 76 22 105531 1 23 8 40 15 51428 3 24 16 81 26 65703 5 25 14 102 24 72562 0 26 14 70 22 81728 0 27 14 75 21 95580 4 28 14 93 23 98278 0 29 12 42 21 46629 0 30 14 95 25 115189 0 31 2 8 4 15049 0 32 12 87 30 109011 5 33 13 87 20 134245 5 34 16 112 26 136692 0 35 15 96 27 149510 6 36 16 93 18 147888 6 37 15 98 20 79169 2 38 16 99 17 65469 5 39 14 94 22 56756 0 40 17 98 25 81399 3 41 18 109 30 104953 0 42 16 108 26 59633 1 43 10 42 20 63249 1 44 15 108 25 82928 2 45 10 27 21 50000 4 46 16 115 23 139357 0 47 17 92 33 110044 7 48 17 106 19 155118 7 49 13 73 31 83061 6 50 14 105 25 127122 0 51 12 30 20 45653 0 52 7 13 19 19630 4 53 14 69 15 67229 4 54 12 72 21 86060 0 55 16 80 22 88003 0 56 14 106 24 95815 0 57 8 28 19 85499 0 58 14 70 20 27220 0 59 15 51 23 109882 4 60 16 90 27 72579 0 61 0 12 1 5841 0 62 12 84 20 68369 0 63 8 23 11 24610 4 64 12 57 27 30995 0 65 15 84 22 150662 1 66 0 4 0 6622 0 67 11 56 17 93694 5 68 15 18 8 13155 0 69 17 86 23 111908 1 70 13 39 26 57550 7 71 8 16 20 16356 5 72 15 18 16 40174 2 73 12 16 8 13983 0 74 10 42 22 52316 1 75 13 77 33 99585 0 76 17 30 28 86271 0 77 17 104 26 131012 2 78 16 121 27 130274 0 79 18 109 35 159051 2 80 14 57 21 76506 0 81 9 28 20 49145 0 82 10 56 24 66398 4 83 15 81 26 127546 4 84 2 2 20 6802 8 85 11 88 22 99509 0 86 15 41 24 43106 4 87 14 83 23 108303 0 88 13 55 22 64167 1 89 4 3 12 8579 0 90 12 54 21 97811 9 91 11 89 24 84365 0 92 9 41 21 10901 3 93 15 94 25 91346 7 94 16 101 32 33660 5 95 14 70 24 93634 2 96 16 111 29 109348 1 97 0 0 0 0 9 98 0 4 0 7953 0 99 0 0 0 0 0 100 0 0 0 0 0 101 0 0 0 0 1 102 0 0 0 0 0 103 10 42 20 63538 2 104 12 97 27 108281 1 105 0 0 0 0 0 106 0 0 0 0 0 107 2 7 0 4245 0 108 4 12 5 21509 0 109 0 0 1 7670 0 110 5 37 23 10641 0 111 0 0 0 0 0 112 3 39 16 41243 2 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Blogs Reviews Compendium_Writing 1.580e+00 5.884e-02 2.184e-01 2.378e-05 Gedeelde_compendia 1.710e-02 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -5.733 -1.580 -0.121 1.065 10.301 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.580e+00 5.746e-01 2.751 0.00699 ** Blogs 5.884e-02 1.340e-02 4.389 2.68e-05 *** Reviews 2.184e-01 4.207e-02 5.191 1.00e-06 *** Compendium_Writing 2.378e-05 1.003e-05 2.371 0.01953 * Gedeelde_compendia 1.710e-02 9.685e-02 0.177 0.86020 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.476 on 107 degrees of freedom Multiple R-squared: 0.7924, Adjusted R-squared: 0.7846 F-statistic: 102.1 on 4 and 107 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 2.750515e-01 5.501029e-01 0.724948533 [2,] 1.505424e-01 3.010849e-01 0.849457564 [3,] 1.832062e-01 3.664123e-01 0.816793833 [4,] 1.327488e-01 2.654975e-01 0.867251227 [5,] 1.373370e-01 2.746740e-01 0.862663004 [6,] 8.249047e-02 1.649809e-01 0.917509528 [7,] 4.844871e-02 9.689741e-02 0.951551295 [8,] 2.629457e-02 5.258913e-02 0.973705433 [9,] 1.496155e-02 2.992311e-02 0.985038447 [10,] 8.194167e-03 1.638833e-02 0.991805833 [11,] 2.896434e-02 5.792868e-02 0.971035660 [12,] 1.882079e-02 3.764158e-02 0.981179209 [13,] 1.048128e-02 2.096257e-02 0.989518716 [14,] 5.773511e-03 1.154702e-02 0.994226489 [15,] 3.148477e-03 6.296955e-03 0.996851523 [16,] 1.750676e-03 3.501351e-03 0.998249324 [17,] 4.115161e-03 8.230322e-03 0.995884839 [18,] 2.224434e-03 4.448869e-03 0.997775566 [19,] 2.575023e-03 5.150047e-03 0.997424977 [20,] 1.412953e-03 2.825907e-03 0.998587047 [21,] 7.718586e-04 1.543717e-03 0.999228141 [22,] 2.945996e-03 5.891992e-03 0.997054004 [23,] 2.094064e-03 4.188127e-03 0.997905936 [24,] 2.138406e-03 4.276813e-03 0.997861594 [25,] 5.398916e-03 1.079783e-02 0.994601084 [26,] 5.648477e-03 1.129695e-02 0.994351523 [27,] 3.864183e-03 7.728366e-03 0.996135817 [28,] 2.945909e-03 5.891818e-03 0.997054091 [29,] 1.857550e-03 3.715100e-03 0.998142450 [30,] 1.152818e-03 2.305637e-03 0.998847182 [31,] 1.003394e-03 2.006788e-03 0.998996606 [32,] 5.864806e-04 1.172961e-03 0.999413519 [33,] 5.511779e-04 1.102356e-03 0.999448822 [34,] 4.190697e-04 8.381395e-04 0.999580930 [35,] 2.488328e-04 4.976655e-04 0.999751167 [36,] 1.542052e-04 3.084103e-04 0.999845795 [37,] 9.984840e-05 1.996968e-04 0.999900152 [38,] 9.462706e-05 1.892541e-04 0.999905373 [39,] 5.895150e-05 1.179030e-04 0.999941048 [40,] 3.734708e-05 7.469417e-05 0.999962653 [41,] 2.250734e-05 4.501468e-05 0.999977493 [42,] 1.373737e-05 2.747475e-05 0.999986263 [43,] 1.278955e-05 2.557910e-05 0.999987210 [44,] 5.489195e-05 1.097839e-04 0.999945108 [45,] 3.075484e-05 6.150969e-05 0.999969245 [46,] 4.185524e-05 8.371048e-05 0.999958145 [47,] 2.291631e-05 4.583262e-05 0.999977084 [48,] 3.699526e-05 7.399051e-05 0.999963005 [49,] 2.718908e-05 5.437816e-05 0.999972811 [50,] 1.877836e-05 3.755672e-05 0.999981222 [51,] 2.986167e-05 5.972334e-05 0.999970138 [52,] 6.510520e-05 1.302104e-04 0.999934895 [53,] 5.451248e-05 1.090250e-04 0.999945488 [54,] 1.889112e-04 3.778224e-04 0.999811089 [55,] 1.202396e-04 2.404792e-04 0.999879760 [56,] 9.157655e-05 1.831531e-04 0.999908423 [57,] 5.521723e-05 1.104345e-04 0.999944783 [58,] 3.144004e-05 6.288008e-05 0.999968560 [59,] 3.718576e-05 7.437152e-05 0.999962814 [60,] 2.034248e-05 4.068496e-05 0.999979658 [61,] 3.933362e-02 7.866724e-02 0.960666381 [62,] 4.577785e-02 9.155570e-02 0.954222149 [63,] 4.021497e-02 8.042994e-02 0.959785028 [64,] 2.933397e-02 5.866793e-02 0.970666034 [65,] 2.494520e-01 4.989040e-01 0.750547980 [66,] 7.593783e-01 4.812435e-01 0.240621732 [67,] 7.099865e-01 5.800269e-01 0.290013462 [68,] 7.359314e-01 5.281372e-01 0.264068623 [69,] 8.873146e-01 2.253708e-01 0.112685388 [70,] 8.628938e-01 2.742124e-01 0.137106176 [71,] 8.310242e-01 3.379517e-01 0.168975825 [72,] 8.027471e-01 3.945057e-01 0.197252851 [73,] 8.443631e-01 3.112737e-01 0.155636860 [74,] 8.113152e-01 3.773696e-01 0.188684805 [75,] 7.799442e-01 4.401115e-01 0.220055774 [76,] 7.272449e-01 5.455102e-01 0.272755112 [77,] 9.074078e-01 1.851844e-01 0.092592194 [78,] 8.954991e-01 2.090017e-01 0.104500866 [79,] 9.740003e-01 5.199948e-02 0.025999738 [80,] 9.645744e-01 7.085127e-02 0.035425634 [81,] 9.796505e-01 4.069905e-02 0.020349527 [82,] 9.734646e-01 5.307077e-02 0.026535383 [83,] 9.592929e-01 8.141421e-02 0.040707105 [84,] 9.558623e-01 8.827541e-02 0.044137706 [85,] 9.512126e-01 9.757481e-02 0.048787406 [86,] 9.264558e-01 1.470883e-01 0.073544174 [87,] 9.802178e-01 3.956439e-02 0.019782195 [88,] 9.803747e-01 3.925058e-02 0.019625290 [89,] 9.917337e-01 1.653268e-02 0.008266342 [90,] 9.937213e-01 1.255736e-02 0.006278681 [91,] 9.897713e-01 2.045733e-02 0.010228666 [92,] 9.788908e-01 4.221849e-02 0.021109247 [93,] 9.577230e-01 8.455405e-02 0.042277024 [94,] 9.353562e-01 1.292876e-01 0.064643821 [95,] 8.747365e-01 2.505270e-01 0.125263491 [96,] 9.497576e-01 1.004848e-01 0.050242390 [97,] 9.982763e-01 3.447330e-03 0.001723665 > postscript(file="/var/www/rcomp/tmp/146iz1321699728.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/2roju1321699728.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3m4cn1321699728.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/47ns71321699728.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/584ug1321699728.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 112 Frequency = 1 1 2 3 4 5 6 -0.96524550 1.69983165 -1.15096067 -0.58376313 -0.55072634 1.06031014 7 8 9 10 11 12 1.96119181 -5.73270231 -0.33381233 -0.07284254 -0.37558891 -2.33922945 13 14 15 16 17 18 -1.29936181 -2.07226069 -1.31622595 -2.54274298 0.43700055 2.70037285 19 20 21 22 23 24 0.84375057 -0.07828407 -1.41228864 -0.38281607 -0.48365642 2.32836318 25 26 27 28 29 30 -0.54813250 1.55339268 1.07974650 -0.41181999 2.25392775 -1.36839688 31 32 33 34 35 36 -1.28243175 -3.92806310 -1.34457613 -1.09837944 -1.78276915 1.39756384 37 38 39 40 41 42 1.36933550 3.24010457 0.73518844 2.20740015 0.95951293 0.95250546 43 44 45 46 47 48 0.05993074 -0.40023779 0.98792685 -0.68318855 0.06390675 1.22527631 49 50 51 52 53 54 -1.72265159 -2.24056233 3.20154671 -0.02936469 3.41718372 -0.44894559 55 56 57 58 59 60 2.81578698 -1.33648917 -1.41004406 3.28643487 2.71498547 1.50242782 61 62 63 64 65 66 -2.64371191 -0.51590058 2.01071339 0.43301596 0.07317113 -1.97322722 67 68 69 70 71 72 0.09885270 10.30079651 2.65879172 1.95922856 0.63652845 7.87714437 73 74 75 76 77 78 7.39877931 -0.11677980 -2.68511489 5.48867506 0.47320660 -1.69364104 79 80 81 82 83 84 -1.45305551 2.66082814 0.23617370 -1.76341578 -0.12530267 -4.36382721 85 86 87 88 89 90 -2.92854900 4.67307797 -0.06186432 1.83649319 -0.58126050 0.17678334 91 92 93 94 95 96 -3.06394989 0.11116363 0.13779788 0.60350753 0.79932545 -1.06142102 97 98 99 100 101 102 -1.73426900 -2.00488135 -1.58039249 -1.58039249 -1.59748988 -1.58039249 103 104 105 106 107 108 0.03596030 -3.77560268 -1.58039249 -1.58039249 -0.09320861 0.11022551 109 110 111 112 -1.98116278 -4.03273335 -1.58039249 -5.38386071 > postscript(file="/var/www/rcomp/tmp/6103o1321699728.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 = 112 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.96524550 NA 1 1.69983165 -0.96524550 2 -1.15096067 1.69983165 3 -0.58376313 -1.15096067 4 -0.55072634 -0.58376313 5 1.06031014 -0.55072634 6 1.96119181 1.06031014 7 -5.73270231 1.96119181 8 -0.33381233 -5.73270231 9 -0.07284254 -0.33381233 10 -0.37558891 -0.07284254 11 -2.33922945 -0.37558891 12 -1.29936181 -2.33922945 13 -2.07226069 -1.29936181 14 -1.31622595 -2.07226069 15 -2.54274298 -1.31622595 16 0.43700055 -2.54274298 17 2.70037285 0.43700055 18 0.84375057 2.70037285 19 -0.07828407 0.84375057 20 -1.41228864 -0.07828407 21 -0.38281607 -1.41228864 22 -0.48365642 -0.38281607 23 2.32836318 -0.48365642 24 -0.54813250 2.32836318 25 1.55339268 -0.54813250 26 1.07974650 1.55339268 27 -0.41181999 1.07974650 28 2.25392775 -0.41181999 29 -1.36839688 2.25392775 30 -1.28243175 -1.36839688 31 -3.92806310 -1.28243175 32 -1.34457613 -3.92806310 33 -1.09837944 -1.34457613 34 -1.78276915 -1.09837944 35 1.39756384 -1.78276915 36 1.36933550 1.39756384 37 3.24010457 1.36933550 38 0.73518844 3.24010457 39 2.20740015 0.73518844 40 0.95951293 2.20740015 41 0.95250546 0.95951293 42 0.05993074 0.95250546 43 -0.40023779 0.05993074 44 0.98792685 -0.40023779 45 -0.68318855 0.98792685 46 0.06390675 -0.68318855 47 1.22527631 0.06390675 48 -1.72265159 1.22527631 49 -2.24056233 -1.72265159 50 3.20154671 -2.24056233 51 -0.02936469 3.20154671 52 3.41718372 -0.02936469 53 -0.44894559 3.41718372 54 2.81578698 -0.44894559 55 -1.33648917 2.81578698 56 -1.41004406 -1.33648917 57 3.28643487 -1.41004406 58 2.71498547 3.28643487 59 1.50242782 2.71498547 60 -2.64371191 1.50242782 61 -0.51590058 -2.64371191 62 2.01071339 -0.51590058 63 0.43301596 2.01071339 64 0.07317113 0.43301596 65 -1.97322722 0.07317113 66 0.09885270 -1.97322722 67 10.30079651 0.09885270 68 2.65879172 10.30079651 69 1.95922856 2.65879172 70 0.63652845 1.95922856 71 7.87714437 0.63652845 72 7.39877931 7.87714437 73 -0.11677980 7.39877931 74 -2.68511489 -0.11677980 75 5.48867506 -2.68511489 76 0.47320660 5.48867506 77 -1.69364104 0.47320660 78 -1.45305551 -1.69364104 79 2.66082814 -1.45305551 80 0.23617370 2.66082814 81 -1.76341578 0.23617370 82 -0.12530267 -1.76341578 83 -4.36382721 -0.12530267 84 -2.92854900 -4.36382721 85 4.67307797 -2.92854900 86 -0.06186432 4.67307797 87 1.83649319 -0.06186432 88 -0.58126050 1.83649319 89 0.17678334 -0.58126050 90 -3.06394989 0.17678334 91 0.11116363 -3.06394989 92 0.13779788 0.11116363 93 0.60350753 0.13779788 94 0.79932545 0.60350753 95 -1.06142102 0.79932545 96 -1.73426900 -1.06142102 97 -2.00488135 -1.73426900 98 -1.58039249 -2.00488135 99 -1.58039249 -1.58039249 100 -1.59748988 -1.58039249 101 -1.58039249 -1.59748988 102 0.03596030 -1.58039249 103 -3.77560268 0.03596030 104 -1.58039249 -3.77560268 105 -1.58039249 -1.58039249 106 -0.09320861 -1.58039249 107 0.11022551 -0.09320861 108 -1.98116278 0.11022551 109 -4.03273335 -1.98116278 110 -1.58039249 -4.03273335 111 -5.38386071 -1.58039249 112 NA -5.38386071 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 1.69983165 -0.96524550 [2,] -1.15096067 1.69983165 [3,] -0.58376313 -1.15096067 [4,] -0.55072634 -0.58376313 [5,] 1.06031014 -0.55072634 [6,] 1.96119181 1.06031014 [7,] -5.73270231 1.96119181 [8,] -0.33381233 -5.73270231 [9,] -0.07284254 -0.33381233 [10,] -0.37558891 -0.07284254 [11,] -2.33922945 -0.37558891 [12,] -1.29936181 -2.33922945 [13,] -2.07226069 -1.29936181 [14,] -1.31622595 -2.07226069 [15,] -2.54274298 -1.31622595 [16,] 0.43700055 -2.54274298 [17,] 2.70037285 0.43700055 [18,] 0.84375057 2.70037285 [19,] -0.07828407 0.84375057 [20,] -1.41228864 -0.07828407 [21,] -0.38281607 -1.41228864 [22,] -0.48365642 -0.38281607 [23,] 2.32836318 -0.48365642 [24,] -0.54813250 2.32836318 [25,] 1.55339268 -0.54813250 [26,] 1.07974650 1.55339268 [27,] -0.41181999 1.07974650 [28,] 2.25392775 -0.41181999 [29,] -1.36839688 2.25392775 [30,] -1.28243175 -1.36839688 [31,] -3.92806310 -1.28243175 [32,] -1.34457613 -3.92806310 [33,] -1.09837944 -1.34457613 [34,] -1.78276915 -1.09837944 [35,] 1.39756384 -1.78276915 [36,] 1.36933550 1.39756384 [37,] 3.24010457 1.36933550 [38,] 0.73518844 3.24010457 [39,] 2.20740015 0.73518844 [40,] 0.95951293 2.20740015 [41,] 0.95250546 0.95951293 [42,] 0.05993074 0.95250546 [43,] -0.40023779 0.05993074 [44,] 0.98792685 -0.40023779 [45,] -0.68318855 0.98792685 [46,] 0.06390675 -0.68318855 [47,] 1.22527631 0.06390675 [48,] -1.72265159 1.22527631 [49,] -2.24056233 -1.72265159 [50,] 3.20154671 -2.24056233 [51,] -0.02936469 3.20154671 [52,] 3.41718372 -0.02936469 [53,] -0.44894559 3.41718372 [54,] 2.81578698 -0.44894559 [55,] -1.33648917 2.81578698 [56,] -1.41004406 -1.33648917 [57,] 3.28643487 -1.41004406 [58,] 2.71498547 3.28643487 [59,] 1.50242782 2.71498547 [60,] -2.64371191 1.50242782 [61,] -0.51590058 -2.64371191 [62,] 2.01071339 -0.51590058 [63,] 0.43301596 2.01071339 [64,] 0.07317113 0.43301596 [65,] -1.97322722 0.07317113 [66,] 0.09885270 -1.97322722 [67,] 10.30079651 0.09885270 [68,] 2.65879172 10.30079651 [69,] 1.95922856 2.65879172 [70,] 0.63652845 1.95922856 [71,] 7.87714437 0.63652845 [72,] 7.39877931 7.87714437 [73,] -0.11677980 7.39877931 [74,] -2.68511489 -0.11677980 [75,] 5.48867506 -2.68511489 [76,] 0.47320660 5.48867506 [77,] -1.69364104 0.47320660 [78,] -1.45305551 -1.69364104 [79,] 2.66082814 -1.45305551 [80,] 0.23617370 2.66082814 [81,] -1.76341578 0.23617370 [82,] -0.12530267 -1.76341578 [83,] -4.36382721 -0.12530267 [84,] -2.92854900 -4.36382721 [85,] 4.67307797 -2.92854900 [86,] -0.06186432 4.67307797 [87,] 1.83649319 -0.06186432 [88,] -0.58126050 1.83649319 [89,] 0.17678334 -0.58126050 [90,] -3.06394989 0.17678334 [91,] 0.11116363 -3.06394989 [92,] 0.13779788 0.11116363 [93,] 0.60350753 0.13779788 [94,] 0.79932545 0.60350753 [95,] -1.06142102 0.79932545 [96,] -1.73426900 -1.06142102 [97,] -2.00488135 -1.73426900 [98,] -1.58039249 -2.00488135 [99,] -1.58039249 -1.58039249 [100,] -1.59748988 -1.58039249 [101,] -1.58039249 -1.59748988 [102,] 0.03596030 -1.58039249 [103,] -3.77560268 0.03596030 [104,] -1.58039249 -3.77560268 [105,] -1.58039249 -1.58039249 [106,] -0.09320861 -1.58039249 [107,] 0.11022551 -0.09320861 [108,] -1.98116278 0.11022551 [109,] -4.03273335 -1.98116278 [110,] -1.58039249 -4.03273335 [111,] -5.38386071 -1.58039249 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 1.69983165 -0.96524550 2 -1.15096067 1.69983165 3 -0.58376313 -1.15096067 4 -0.55072634 -0.58376313 5 1.06031014 -0.55072634 6 1.96119181 1.06031014 7 -5.73270231 1.96119181 8 -0.33381233 -5.73270231 9 -0.07284254 -0.33381233 10 -0.37558891 -0.07284254 11 -2.33922945 -0.37558891 12 -1.29936181 -2.33922945 13 -2.07226069 -1.29936181 14 -1.31622595 -2.07226069 15 -2.54274298 -1.31622595 16 0.43700055 -2.54274298 17 2.70037285 0.43700055 18 0.84375057 2.70037285 19 -0.07828407 0.84375057 20 -1.41228864 -0.07828407 21 -0.38281607 -1.41228864 22 -0.48365642 -0.38281607 23 2.32836318 -0.48365642 24 -0.54813250 2.32836318 25 1.55339268 -0.54813250 26 1.07974650 1.55339268 27 -0.41181999 1.07974650 28 2.25392775 -0.41181999 29 -1.36839688 2.25392775 30 -1.28243175 -1.36839688 31 -3.92806310 -1.28243175 32 -1.34457613 -3.92806310 33 -1.09837944 -1.34457613 34 -1.78276915 -1.09837944 35 1.39756384 -1.78276915 36 1.36933550 1.39756384 37 3.24010457 1.36933550 38 0.73518844 3.24010457 39 2.20740015 0.73518844 40 0.95951293 2.20740015 41 0.95250546 0.95951293 42 0.05993074 0.95250546 43 -0.40023779 0.05993074 44 0.98792685 -0.40023779 45 -0.68318855 0.98792685 46 0.06390675 -0.68318855 47 1.22527631 0.06390675 48 -1.72265159 1.22527631 49 -2.24056233 -1.72265159 50 3.20154671 -2.24056233 51 -0.02936469 3.20154671 52 3.41718372 -0.02936469 53 -0.44894559 3.41718372 54 2.81578698 -0.44894559 55 -1.33648917 2.81578698 56 -1.41004406 -1.33648917 57 3.28643487 -1.41004406 58 2.71498547 3.28643487 59 1.50242782 2.71498547 60 -2.64371191 1.50242782 61 -0.51590058 -2.64371191 62 2.01071339 -0.51590058 63 0.43301596 2.01071339 64 0.07317113 0.43301596 65 -1.97322722 0.07317113 66 0.09885270 -1.97322722 67 10.30079651 0.09885270 68 2.65879172 10.30079651 69 1.95922856 2.65879172 70 0.63652845 1.95922856 71 7.87714437 0.63652845 72 7.39877931 7.87714437 73 -0.11677980 7.39877931 74 -2.68511489 -0.11677980 75 5.48867506 -2.68511489 76 0.47320660 5.48867506 77 -1.69364104 0.47320660 78 -1.45305551 -1.69364104 79 2.66082814 -1.45305551 80 0.23617370 2.66082814 81 -1.76341578 0.23617370 82 -0.12530267 -1.76341578 83 -4.36382721 -0.12530267 84 -2.92854900 -4.36382721 85 4.67307797 -2.92854900 86 -0.06186432 4.67307797 87 1.83649319 -0.06186432 88 -0.58126050 1.83649319 89 0.17678334 -0.58126050 90 -3.06394989 0.17678334 91 0.11116363 -3.06394989 92 0.13779788 0.11116363 93 0.60350753 0.13779788 94 0.79932545 0.60350753 95 -1.06142102 0.79932545 96 -1.73426900 -1.06142102 97 -2.00488135 -1.73426900 98 -1.58039249 -2.00488135 99 -1.58039249 -1.58039249 100 -1.59748988 -1.58039249 101 -1.58039249 -1.59748988 102 0.03596030 -1.58039249 103 -3.77560268 0.03596030 104 -1.58039249 -3.77560268 105 -1.58039249 -1.58039249 106 -0.09320861 -1.58039249 107 0.11022551 -0.09320861 108 -1.98116278 0.11022551 109 -4.03273335 -1.98116278 110 -1.58039249 -4.03273335 111 -5.38386071 -1.58039249 > 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/7u9vr1321699728.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/8dl5i1321699728.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/9rohj1321699728.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/10d0ez1321699728.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/114qmc1321699728.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/12dfjm1321699728.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/13je2l1321699728.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$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/14e5991321699728.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/15f50t1321699728.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/16r6bi1321699728.tab") + } > > try(system("convert tmp/146iz1321699728.ps tmp/146iz1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/2roju1321699728.ps tmp/2roju1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/3m4cn1321699728.ps tmp/3m4cn1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/47ns71321699728.ps tmp/47ns71321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/584ug1321699728.ps tmp/584ug1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/6103o1321699728.ps tmp/6103o1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/7u9vr1321699728.ps tmp/7u9vr1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/8dl5i1321699728.ps tmp/8dl5i1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/9rohj1321699728.ps tmp/9rohj1321699728.png",intern=TRUE)) character(0) > try(system("convert tmp/10d0ez1321699728.ps tmp/10d0ez1321699728.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.900 0.230 4.126