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Type 'q()' to quit R. > x <- array(list(91.6 + ,0 + ,104.6 + ,111.6 + ,98.3 + ,0 + ,91.6 + ,104.6 + ,97.7 + ,0 + ,98.3 + ,91.6 + ,106.3 + ,0 + ,97.7 + ,98.3 + ,102.3 + ,0 + ,106.3 + ,97.7 + ,106.6 + ,0 + ,102.3 + ,106.3 + ,108.1 + ,0 + ,106.6 + ,102.3 + ,93.8 + ,0 + ,108.1 + ,106.6 + ,88.2 + ,0 + ,93.8 + ,108.1 + ,108.9 + ,0 + ,88.2 + ,93.8 + ,114.2 + ,0 + ,108.9 + ,88.2 + ,102.5 + ,0 + ,114.2 + ,108.9 + ,94.2 + ,0 + ,102.5 + ,114.2 + ,97.4 + ,0 + ,94.2 + ,102.5 + ,98.5 + ,0 + ,97.4 + ,94.2 + ,106.5 + ,0 + ,98.5 + ,97.4 + ,102.9 + ,0 + ,106.5 + ,98.5 + ,97.1 + ,0 + ,102.9 + ,106.5 + ,103.7 + ,0 + ,97.1 + ,102.9 + ,93.4 + ,0 + ,103.7 + ,97.1 + ,85.8 + ,0 + ,93.4 + ,103.7 + ,108.6 + ,0 + ,85.8 + ,93.4 + ,110.2 + ,0 + ,108.6 + ,85.8 + ,101.2 + ,0 + ,110.2 + ,108.6 + ,101.2 + ,0 + ,101.2 + ,110.2 + ,96.9 + ,0 + ,101.2 + ,101.2 + ,99.4 + ,0 + ,96.9 + ,101.2 + ,118.7 + ,0 + ,99.4 + ,96.9 + ,108.0 + ,0 + ,118.7 + ,99.4 + ,101.2 + ,0 + ,108.0 + ,118.7 + ,119.9 + ,0 + ,101.2 + ,108.0 + ,94.8 + ,0 + ,119.9 + ,101.2 + ,95.3 + ,0 + ,94.8 + ,119.9 + ,118.0 + ,0 + ,95.3 + ,94.8 + ,115.9 + ,0 + ,118.0 + ,95.3 + ,111.4 + ,0 + ,115.9 + ,118.0 + ,108.2 + ,0 + ,111.4 + ,115.9 + ,108.8 + ,0 + ,108.2 + ,111.4 + ,109.5 + ,0 + ,108.8 + ,108.2 + ,124.8 + ,0 + ,109.5 + ,108.8 + ,115.3 + ,0 + ,124.8 + ,109.5 + ,109.5 + ,0 + ,115.3 + ,124.8 + ,124.2 + ,0 + ,109.5 + ,115.3 + ,92.9 + ,0 + ,124.2 + ,109.5 + ,98.4 + ,0 + ,92.9 + ,124.2 + ,120.9 + ,0 + ,98.4 + ,92.9 + ,111.7 + ,0 + ,120.9 + ,98.4 + ,116.1 + ,0 + ,111.7 + ,120.9 + ,109.4 + ,0 + ,116.1 + ,111.7 + ,111.7 + ,0 + ,109.4 + ,116.1 + ,114.3 + ,0 + ,111.7 + ,109.4 + ,133.7 + ,0 + ,114.3 + ,111.7 + ,114.3 + ,0 + ,133.7 + ,114.3 + ,126.5 + ,0 + ,114.3 + ,133.7 + ,131.0 + ,0 + ,126.5 + ,114.3 + ,104.0 + ,0 + ,131.0 + ,126.5 + ,108.9 + ,0 + ,104.0 + ,131.0 + ,128.5 + ,0 + ,108.9 + ,104.0 + ,132.4 + ,0 + ,128.5 + ,108.9 + ,128.0 + ,0 + ,132.4 + ,128.5 + ,116.4 + ,0 + ,128.0 + ,132.4 + ,120.9 + ,0 + ,116.4 + ,128.0 + ,118.6 + ,0 + ,120.9 + ,116.4 + ,133.1 + ,0 + ,118.6 + ,120.9 + ,121.1 + ,0 + ,133.1 + ,118.6 + ,127.6 + ,0 + ,121.1 + ,133.1 + ,135.4 + ,0 + ,127.6 + ,121.1 + ,114.9 + ,0 + ,135.4 + ,127.6 + ,114.3 + ,0 + ,114.9 + ,135.4 + ,128.9 + ,0 + ,114.3 + ,114.9 + ,138.9 + ,0 + ,128.9 + ,114.3 + ,129.4 + ,0 + ,138.9 + ,128.9 + ,115.0 + ,0 + ,129.4 + ,138.9 + ,128.0 + ,0 + ,115.0 + ,129.4 + ,127.0 + ,0 + ,128.0 + ,115.0 + ,128.8 + ,0 + ,127.0 + ,128.0 + ,137.9 + ,0 + ,128.8 + ,127.0 + ,128.4 + ,0 + ,137.9 + ,128.8 + ,135.9 + ,0 + ,128.4 + ,137.9 + ,122.2 + ,0 + ,135.9 + ,128.4 + ,113.1 + ,0 + ,122.2 + ,135.9 + ,136.2 + ,1 + ,113.1 + ,122.2 + ,138.0 + ,1 + ,136.2 + ,113.1 + ,115.2 + ,1 + ,138.0 + ,136.2 + ,111.0 + ,1 + ,115.2 + ,138.0 + ,99.2 + ,1 + ,111.0 + ,115.2 + ,102.4 + ,1 + ,99.2 + ,111.0 + ,112.7 + ,1 + ,102.4 + ,99.2 + ,105.5 + ,1 + ,112.7 + ,102.4 + ,98.3 + ,1 + ,105.5 + ,112.7 + ,116.4 + ,1 + ,98.3 + ,105.5 + ,97.4 + ,1 + ,116.4 + ,98.3 + ,93.3 + ,1 + ,97.4 + ,116.4 + ,117.4 + ,1 + ,93.3 + ,97.4) + ,dim=c(4 + ,94) + ,dimnames=list(c('y' + ,'dummy' + ,'y1' + ,'y2') + ,1:94)) > y <- array(NA,dim=c(4,94),dimnames=list(c('y','dummy','y1','y2'),1:94)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : 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 y dummy y1 y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 91.6 0 104.6 111.6 1 0 0 0 0 0 0 0 0 0 0 1 2 98.3 0 91.6 104.6 0 1 0 0 0 0 0 0 0 0 0 2 3 97.7 0 98.3 91.6 0 0 1 0 0 0 0 0 0 0 0 3 4 106.3 0 97.7 98.3 0 0 0 1 0 0 0 0 0 0 0 4 5 102.3 0 106.3 97.7 0 0 0 0 1 0 0 0 0 0 0 5 6 106.6 0 102.3 106.3 0 0 0 0 0 1 0 0 0 0 0 6 7 108.1 0 106.6 102.3 0 0 0 0 0 0 1 0 0 0 0 7 8 93.8 0 108.1 106.6 0 0 0 0 0 0 0 1 0 0 0 8 9 88.2 0 93.8 108.1 0 0 0 0 0 0 0 0 1 0 0 9 10 108.9 0 88.2 93.8 0 0 0 0 0 0 0 0 0 1 0 10 11 114.2 0 108.9 88.2 0 0 0 0 0 0 0 0 0 0 1 11 12 102.5 0 114.2 108.9 0 0 0 0 0 0 0 0 0 0 0 12 13 94.2 0 102.5 114.2 1 0 0 0 0 0 0 0 0 0 0 13 14 97.4 0 94.2 102.5 0 1 0 0 0 0 0 0 0 0 0 14 15 98.5 0 97.4 94.2 0 0 1 0 0 0 0 0 0 0 0 15 16 106.5 0 98.5 97.4 0 0 0 1 0 0 0 0 0 0 0 16 17 102.9 0 106.5 98.5 0 0 0 0 1 0 0 0 0 0 0 17 18 97.1 0 102.9 106.5 0 0 0 0 0 1 0 0 0 0 0 18 19 103.7 0 97.1 102.9 0 0 0 0 0 0 1 0 0 0 0 19 20 93.4 0 103.7 97.1 0 0 0 0 0 0 0 1 0 0 0 20 21 85.8 0 93.4 103.7 0 0 0 0 0 0 0 0 1 0 0 21 22 108.6 0 85.8 93.4 0 0 0 0 0 0 0 0 0 1 0 22 23 110.2 0 108.6 85.8 0 0 0 0 0 0 0 0 0 0 1 23 24 101.2 0 110.2 108.6 0 0 0 0 0 0 0 0 0 0 0 24 25 101.2 0 101.2 110.2 1 0 0 0 0 0 0 0 0 0 0 25 26 96.9 0 101.2 101.2 0 1 0 0 0 0 0 0 0 0 0 26 27 99.4 0 96.9 101.2 0 0 1 0 0 0 0 0 0 0 0 27 28 118.7 0 99.4 96.9 0 0 0 1 0 0 0 0 0 0 0 28 29 108.0 0 118.7 99.4 0 0 0 0 1 0 0 0 0 0 0 29 30 101.2 0 108.0 118.7 0 0 0 0 0 1 0 0 0 0 0 30 31 119.9 0 101.2 108.0 0 0 0 0 0 0 1 0 0 0 0 31 32 94.8 0 119.9 101.2 0 0 0 0 0 0 0 1 0 0 0 32 33 95.3 0 94.8 119.9 0 0 0 0 0 0 0 0 1 0 0 33 34 118.0 0 95.3 94.8 0 0 0 0 0 0 0 0 0 1 0 34 35 115.9 0 118.0 95.3 0 0 0 0 0 0 0 0 0 0 1 35 36 111.4 0 115.9 118.0 0 0 0 0 0 0 0 0 0 0 0 36 37 108.2 0 111.4 115.9 1 0 0 0 0 0 0 0 0 0 0 37 38 108.8 0 108.2 111.4 0 1 0 0 0 0 0 0 0 0 0 38 39 109.5 0 108.8 108.2 0 0 1 0 0 0 0 0 0 0 0 39 40 124.8 0 109.5 108.8 0 0 0 1 0 0 0 0 0 0 0 40 41 115.3 0 124.8 109.5 0 0 0 0 1 0 0 0 0 0 0 41 42 109.5 0 115.3 124.8 0 0 0 0 0 1 0 0 0 0 0 42 43 124.2 0 109.5 115.3 0 0 0 0 0 0 1 0 0 0 0 43 44 92.9 0 124.2 109.5 0 0 0 0 0 0 0 1 0 0 0 44 45 98.4 0 92.9 124.2 0 0 0 0 0 0 0 0 1 0 0 45 46 120.9 0 98.4 92.9 0 0 0 0 0 0 0 0 0 1 0 46 47 111.7 0 120.9 98.4 0 0 0 0 0 0 0 0 0 0 1 47 48 116.1 0 111.7 120.9 0 0 0 0 0 0 0 0 0 0 0 48 49 109.4 0 116.1 111.7 1 0 0 0 0 0 0 0 0 0 0 49 50 111.7 0 109.4 116.1 0 1 0 0 0 0 0 0 0 0 0 50 51 114.3 0 111.7 109.4 0 0 1 0 0 0 0 0 0 0 0 51 52 133.7 0 114.3 111.7 0 0 0 1 0 0 0 0 0 0 0 52 53 114.3 0 133.7 114.3 0 0 0 0 1 0 0 0 0 0 0 53 54 126.5 0 114.3 133.7 0 0 0 0 0 1 0 0 0 0 0 54 55 131.0 0 126.5 114.3 0 0 0 0 0 0 1 0 0 0 0 55 56 104.0 0 131.0 126.5 0 0 0 0 0 0 0 1 0 0 0 56 57 108.9 0 104.0 131.0 0 0 0 0 0 0 0 0 1 0 0 57 58 128.5 0 108.9 104.0 0 0 0 0 0 0 0 0 0 1 0 58 59 132.4 0 128.5 108.9 0 0 0 0 0 0 0 0 0 0 1 59 60 128.0 0 132.4 128.5 0 0 0 0 0 0 0 0 0 0 0 60 61 116.4 0 128.0 132.4 1 0 0 0 0 0 0 0 0 0 0 61 62 120.9 0 116.4 128.0 0 1 0 0 0 0 0 0 0 0 0 62 63 118.6 0 120.9 116.4 0 0 1 0 0 0 0 0 0 0 0 63 64 133.1 0 118.6 120.9 0 0 0 1 0 0 0 0 0 0 0 64 65 121.1 0 133.1 118.6 0 0 0 0 1 0 0 0 0 0 0 65 66 127.6 0 121.1 133.1 0 0 0 0 0 1 0 0 0 0 0 66 67 135.4 0 127.6 121.1 0 0 0 0 0 0 1 0 0 0 0 67 68 114.9 0 135.4 127.6 0 0 0 0 0 0 0 1 0 0 0 68 69 114.3 0 114.9 135.4 0 0 0 0 0 0 0 0 1 0 0 69 70 128.9 0 114.3 114.9 0 0 0 0 0 0 0 0 0 1 0 70 71 138.9 0 128.9 114.3 0 0 0 0 0 0 0 0 0 0 1 71 72 129.4 0 138.9 128.9 0 0 0 0 0 0 0 0 0 0 0 72 73 115.0 0 129.4 138.9 1 0 0 0 0 0 0 0 0 0 0 73 74 128.0 0 115.0 129.4 0 1 0 0 0 0 0 0 0 0 0 74 75 127.0 0 128.0 115.0 0 0 1 0 0 0 0 0 0 0 0 75 76 128.8 0 127.0 128.0 0 0 0 1 0 0 0 0 0 0 0 76 77 137.9 0 128.8 127.0 0 0 0 0 1 0 0 0 0 0 0 77 78 128.4 0 137.9 128.8 0 0 0 0 0 1 0 0 0 0 0 78 79 135.9 0 128.4 137.9 0 0 0 0 0 0 1 0 0 0 0 79 80 122.2 0 135.9 128.4 0 0 0 0 0 0 0 1 0 0 0 80 81 113.1 0 122.2 135.9 0 0 0 0 0 0 0 0 1 0 0 81 82 136.2 1 113.1 122.2 0 0 0 0 0 0 0 0 0 1 0 82 83 138.0 1 136.2 113.1 0 0 0 0 0 0 0 0 0 0 1 83 84 115.2 1 138.0 136.2 0 0 0 0 0 0 0 0 0 0 0 84 85 111.0 1 115.2 138.0 1 0 0 0 0 0 0 0 0 0 0 85 86 99.2 1 111.0 115.2 0 1 0 0 0 0 0 0 0 0 0 86 87 102.4 1 99.2 111.0 0 0 1 0 0 0 0 0 0 0 0 87 88 112.7 1 102.4 99.2 0 0 0 1 0 0 0 0 0 0 0 88 89 105.5 1 112.7 102.4 0 0 0 0 1 0 0 0 0 0 0 89 90 98.3 1 105.5 112.7 0 0 0 0 0 1 0 0 0 0 0 90 91 116.4 1 98.3 105.5 0 0 0 0 0 0 1 0 0 0 0 91 92 97.4 1 116.4 98.3 0 0 0 0 0 0 0 1 0 0 0 92 93 93.3 1 97.4 116.4 0 0 0 0 0 0 0 0 1 0 0 93 94 117.4 1 93.3 97.4 0 0 0 0 0 0 0 0 0 1 0 94 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) dummy y1 y2 M1 M2 36.8473 -11.7370 0.1817 0.3982 -6.5794 -0.3858 M3 M4 M5 M6 M7 M8 2.9364 14.0524 4.1872 -1.0484 11.8171 -9.7204 M9 M10 M11 t -12.2102 18.7224 16.9993 0.1864 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -12.059 -2.865 0.370 2.986 10.634 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 36.84729 10.45983 3.523 0.000717 *** dummy -11.73702 2.62168 -4.477 2.55e-05 *** y1 0.18170 0.10082 1.802 0.075368 . y2 0.39820 0.09382 4.244 5.99e-05 *** M1 -6.57945 2.63894 -2.493 0.014777 * M2 -0.38581 2.85053 -0.135 0.892686 M3 2.93644 2.86148 1.026 0.307972 M4 14.05240 2.82477 4.975 3.81e-06 *** M5 4.18719 2.72053 1.539 0.127825 M6 -1.04841 2.66237 -0.394 0.694811 M7 11.81711 2.70270 4.372 3.76e-05 *** M8 -9.72043 2.64382 -3.677 0.000432 *** M9 -12.21018 3.36392 -3.630 0.000505 *** M10 18.72244 3.26035 5.742 1.71e-07 *** M11 16.99933 3.16941 5.364 8.09e-07 *** t 0.18642 0.04651 4.008 0.000139 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 4.799 on 78 degrees of freedom Multiple R-squared: 0.8894, Adjusted R-squared: 0.8682 F-statistic: 41.84 on 15 and 78 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,] 0.350948088 0.70189618 0.6490519 [2,] 0.261698533 0.52339707 0.7383015 [3,] 0.149225385 0.29845077 0.8507746 [4,] 0.082073379 0.16414676 0.9179266 [5,] 0.047265718 0.09453144 0.9527343 [6,] 0.023105150 0.04621030 0.9768949 [7,] 0.115319968 0.23063994 0.8846800 [8,] 0.071336656 0.14267331 0.9286633 [9,] 0.043110028 0.08622006 0.9568900 [10,] 0.181867309 0.36373462 0.8181327 [11,] 0.129328148 0.25865630 0.8706719 [12,] 0.106164615 0.21232923 0.8938354 [13,] 0.251529029 0.50305806 0.7484710 [14,] 0.192607751 0.38521550 0.8073922 [15,] 0.152293820 0.30458764 0.8477062 [16,] 0.141030077 0.28206015 0.8589699 [17,] 0.106006533 0.21201307 0.8939935 [18,] 0.086754603 0.17350921 0.9132454 [19,] 0.095567114 0.19113423 0.9044329 [20,] 0.072306482 0.14461296 0.9276935 [21,] 0.049828544 0.09965709 0.9501715 [22,] 0.043182933 0.08636587 0.9568171 [23,] 0.028666621 0.05733324 0.9713334 [24,] 0.022719867 0.04543973 0.9772801 [25,] 0.017690639 0.03538128 0.9823094 [26,] 0.040596120 0.08119224 0.9594039 [27,] 0.027210706 0.05442141 0.9727893 [28,] 0.019805215 0.03961043 0.9801948 [29,] 0.102976110 0.20595222 0.8970239 [30,] 0.082203240 0.16440648 0.9177968 [31,] 0.071228821 0.14245764 0.9287712 [32,] 0.050291643 0.10058329 0.9497084 [33,] 0.036006281 0.07201256 0.9639937 [34,] 0.070577293 0.14115459 0.9294227 [35,] 0.078091653 0.15618331 0.9219083 [36,] 0.105993067 0.21198613 0.8940069 [37,] 0.096771296 0.19354259 0.9032287 [38,] 0.156235173 0.31247035 0.8437648 [39,] 0.123630163 0.24726033 0.8763698 [40,] 0.091889392 0.18377878 0.9081106 [41,] 0.097680345 0.19536069 0.9023197 [42,] 0.089404447 0.17880889 0.9105956 [43,] 0.063783125 0.12756625 0.9362169 [44,] 0.042881002 0.08576200 0.9571190 [45,] 0.028812171 0.05762434 0.9711878 [46,] 0.021732638 0.04346528 0.9782674 [47,] 0.023148962 0.04629792 0.9768510 [48,] 0.021146396 0.04229279 0.9788536 [49,] 0.013890422 0.02778084 0.9861096 [50,] 0.010335031 0.02067006 0.9896650 [51,] 0.006206862 0.01241372 0.9937931 [52,] 0.020822844 0.04164569 0.9791772 [53,] 0.045969838 0.09193968 0.9540302 [54,] 0.026447725 0.05289545 0.9735523 [55,] 0.480976423 0.96195285 0.5190236 [56,] 0.376352545 0.75270509 0.6236475 [57,] 0.316415104 0.63283021 0.6835849 > postscript(file="/var/www/html/rcomp/tmp/1kdnf1262014207.ps",horizontal=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2tnof1262014207.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/html/rcomp/tmp/3b5zc1262014207.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4t1zr1262014207.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5022r1262014207.ps",horizontal=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 = 94 Frequency = 1 1 2 3 4 5 6 -2.2994377 3.1700402 3.0205704 -2.2407233 2.1143451 8.7658208 7 8 9 10 11 12 -1.9746315 3.0916743 1.7960494 -1.9111902 3.3941790 -0.6986642 13 14 15 16 17 18 -2.5901758 0.3968404 0.7117894 -4.0646987 0.1224513 -3.1598340 19 20 21 22 23 24 -7.1243721 5.0370705 -1.0161835 -3.8528179 -1.8326240 -3.3893880 25 26 27 28 29 30 4.0018435 -3.0944100 -3.3217521 5.9338756 0.4103086 -7.0815484 31 32 33 34 35 36 4.0628352 -0.3761214 -0.4583986 1.0265361 -3.8605189 -0.2051641 37 38 39 40 41 42 4.6417462 1.2350409 -0.4084033 3.2231092 0.3431116 -4.7739887 43 44 45 46 47 48 1.7108526 -8.5994943 -0.9624170 1.8828450 -12.0588690 1.8662129 49 50 51 52 53 54 4.4231911 -0.1915349 1.1498264 7.8591646 -6.4223926 6.6267412 55 56 57 58 59 60 3.5831183 -7.7414622 2.5759336 0.9179575 0.8421004 4.7416605 61 62 63 64 65 66 -1.2187987 0.7609761 -1.2462284 0.5774118 -3.4626242 4.4930914 67 68 69 70 71 72 2.8384930 -0.3159661 2.0063045 -6.2406077 2.8821466 2.5643216 73 74 75 76 77 78 -7.6984748 5.3208862 4.1841710 -10.3131010 8.5368236 1.7157573 79 80 81 82 83 84 -5.7336206 4.3376294 -2.9562164 7.8706028 10.6335858 -4.8789787 85 86 87 88 89 90 0.7401061 -7.5978388 -4.0899734 -0.9750381 -1.6420234 -6.5860398 91 92 93 94 2.6373251 4.5666699 -0.9850720 0.3066744 > postscript(file="/var/www/html/rcomp/tmp/6eeeo1262014208.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 94 Frequency = 1 lag(myerror, k = 1) myerror 0 -2.2994377 NA 1 3.1700402 -2.2994377 2 3.0205704 3.1700402 3 -2.2407233 3.0205704 4 2.1143451 -2.2407233 5 8.7658208 2.1143451 6 -1.9746315 8.7658208 7 3.0916743 -1.9746315 8 1.7960494 3.0916743 9 -1.9111902 1.7960494 10 3.3941790 -1.9111902 11 -0.6986642 3.3941790 12 -2.5901758 -0.6986642 13 0.3968404 -2.5901758 14 0.7117894 0.3968404 15 -4.0646987 0.7117894 16 0.1224513 -4.0646987 17 -3.1598340 0.1224513 18 -7.1243721 -3.1598340 19 5.0370705 -7.1243721 20 -1.0161835 5.0370705 21 -3.8528179 -1.0161835 22 -1.8326240 -3.8528179 23 -3.3893880 -1.8326240 24 4.0018435 -3.3893880 25 -3.0944100 4.0018435 26 -3.3217521 -3.0944100 27 5.9338756 -3.3217521 28 0.4103086 5.9338756 29 -7.0815484 0.4103086 30 4.0628352 -7.0815484 31 -0.3761214 4.0628352 32 -0.4583986 -0.3761214 33 1.0265361 -0.4583986 34 -3.8605189 1.0265361 35 -0.2051641 -3.8605189 36 4.6417462 -0.2051641 37 1.2350409 4.6417462 38 -0.4084033 1.2350409 39 3.2231092 -0.4084033 40 0.3431116 3.2231092 41 -4.7739887 0.3431116 42 1.7108526 -4.7739887 43 -8.5994943 1.7108526 44 -0.9624170 -8.5994943 45 1.8828450 -0.9624170 46 -12.0588690 1.8828450 47 1.8662129 -12.0588690 48 4.4231911 1.8662129 49 -0.1915349 4.4231911 50 1.1498264 -0.1915349 51 7.8591646 1.1498264 52 -6.4223926 7.8591646 53 6.6267412 -6.4223926 54 3.5831183 6.6267412 55 -7.7414622 3.5831183 56 2.5759336 -7.7414622 57 0.9179575 2.5759336 58 0.8421004 0.9179575 59 4.7416605 0.8421004 60 -1.2187987 4.7416605 61 0.7609761 -1.2187987 62 -1.2462284 0.7609761 63 0.5774118 -1.2462284 64 -3.4626242 0.5774118 65 4.4930914 -3.4626242 66 2.8384930 4.4930914 67 -0.3159661 2.8384930 68 2.0063045 -0.3159661 69 -6.2406077 2.0063045 70 2.8821466 -6.2406077 71 2.5643216 2.8821466 72 -7.6984748 2.5643216 73 5.3208862 -7.6984748 74 4.1841710 5.3208862 75 -10.3131010 4.1841710 76 8.5368236 -10.3131010 77 1.7157573 8.5368236 78 -5.7336206 1.7157573 79 4.3376294 -5.7336206 80 -2.9562164 4.3376294 81 7.8706028 -2.9562164 82 10.6335858 7.8706028 83 -4.8789787 10.6335858 84 0.7401061 -4.8789787 85 -7.5978388 0.7401061 86 -4.0899734 -7.5978388 87 -0.9750381 -4.0899734 88 -1.6420234 -0.9750381 89 -6.5860398 -1.6420234 90 2.6373251 -6.5860398 91 4.5666699 2.6373251 92 -0.9850720 4.5666699 93 0.3066744 -0.9850720 94 NA 0.3066744 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 3.1700402 -2.2994377 [2,] 3.0205704 3.1700402 [3,] -2.2407233 3.0205704 [4,] 2.1143451 -2.2407233 [5,] 8.7658208 2.1143451 [6,] -1.9746315 8.7658208 [7,] 3.0916743 -1.9746315 [8,] 1.7960494 3.0916743 [9,] -1.9111902 1.7960494 [10,] 3.3941790 -1.9111902 [11,] -0.6986642 3.3941790 [12,] -2.5901758 -0.6986642 [13,] 0.3968404 -2.5901758 [14,] 0.7117894 0.3968404 [15,] -4.0646987 0.7117894 [16,] 0.1224513 -4.0646987 [17,] -3.1598340 0.1224513 [18,] -7.1243721 -3.1598340 [19,] 5.0370705 -7.1243721 [20,] -1.0161835 5.0370705 [21,] -3.8528179 -1.0161835 [22,] -1.8326240 -3.8528179 [23,] -3.3893880 -1.8326240 [24,] 4.0018435 -3.3893880 [25,] -3.0944100 4.0018435 [26,] -3.3217521 -3.0944100 [27,] 5.9338756 -3.3217521 [28,] 0.4103086 5.9338756 [29,] -7.0815484 0.4103086 [30,] 4.0628352 -7.0815484 [31,] -0.3761214 4.0628352 [32,] -0.4583986 -0.3761214 [33,] 1.0265361 -0.4583986 [34,] -3.8605189 1.0265361 [35,] -0.2051641 -3.8605189 [36,] 4.6417462 -0.2051641 [37,] 1.2350409 4.6417462 [38,] -0.4084033 1.2350409 [39,] 3.2231092 -0.4084033 [40,] 0.3431116 3.2231092 [41,] -4.7739887 0.3431116 [42,] 1.7108526 -4.7739887 [43,] -8.5994943 1.7108526 [44,] -0.9624170 -8.5994943 [45,] 1.8828450 -0.9624170 [46,] -12.0588690 1.8828450 [47,] 1.8662129 -12.0588690 [48,] 4.4231911 1.8662129 [49,] -0.1915349 4.4231911 [50,] 1.1498264 -0.1915349 [51,] 7.8591646 1.1498264 [52,] -6.4223926 7.8591646 [53,] 6.6267412 -6.4223926 [54,] 3.5831183 6.6267412 [55,] -7.7414622 3.5831183 [56,] 2.5759336 -7.7414622 [57,] 0.9179575 2.5759336 [58,] 0.8421004 0.9179575 [59,] 4.7416605 0.8421004 [60,] -1.2187987 4.7416605 [61,] 0.7609761 -1.2187987 [62,] -1.2462284 0.7609761 [63,] 0.5774118 -1.2462284 [64,] -3.4626242 0.5774118 [65,] 4.4930914 -3.4626242 [66,] 2.8384930 4.4930914 [67,] -0.3159661 2.8384930 [68,] 2.0063045 -0.3159661 [69,] -6.2406077 2.0063045 [70,] 2.8821466 -6.2406077 [71,] 2.5643216 2.8821466 [72,] -7.6984748 2.5643216 [73,] 5.3208862 -7.6984748 [74,] 4.1841710 5.3208862 [75,] -10.3131010 4.1841710 [76,] 8.5368236 -10.3131010 [77,] 1.7157573 8.5368236 [78,] -5.7336206 1.7157573 [79,] 4.3376294 -5.7336206 [80,] -2.9562164 4.3376294 [81,] 7.8706028 -2.9562164 [82,] 10.6335858 7.8706028 [83,] -4.8789787 10.6335858 [84,] 0.7401061 -4.8789787 [85,] -7.5978388 0.7401061 [86,] -4.0899734 -7.5978388 [87,] -0.9750381 -4.0899734 [88,] -1.6420234 -0.9750381 [89,] -6.5860398 -1.6420234 [90,] 2.6373251 -6.5860398 [91,] 4.5666699 2.6373251 [92,] -0.9850720 4.5666699 [93,] 0.3066744 -0.9850720 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 3.1700402 -2.2994377 2 3.0205704 3.1700402 3 -2.2407233 3.0205704 4 2.1143451 -2.2407233 5 8.7658208 2.1143451 6 -1.9746315 8.7658208 7 3.0916743 -1.9746315 8 1.7960494 3.0916743 9 -1.9111902 1.7960494 10 3.3941790 -1.9111902 11 -0.6986642 3.3941790 12 -2.5901758 -0.6986642 13 0.3968404 -2.5901758 14 0.7117894 0.3968404 15 -4.0646987 0.7117894 16 0.1224513 -4.0646987 17 -3.1598340 0.1224513 18 -7.1243721 -3.1598340 19 5.0370705 -7.1243721 20 -1.0161835 5.0370705 21 -3.8528179 -1.0161835 22 -1.8326240 -3.8528179 23 -3.3893880 -1.8326240 24 4.0018435 -3.3893880 25 -3.0944100 4.0018435 26 -3.3217521 -3.0944100 27 5.9338756 -3.3217521 28 0.4103086 5.9338756 29 -7.0815484 0.4103086 30 4.0628352 -7.0815484 31 -0.3761214 4.0628352 32 -0.4583986 -0.3761214 33 1.0265361 -0.4583986 34 -3.8605189 1.0265361 35 -0.2051641 -3.8605189 36 4.6417462 -0.2051641 37 1.2350409 4.6417462 38 -0.4084033 1.2350409 39 3.2231092 -0.4084033 40 0.3431116 3.2231092 41 -4.7739887 0.3431116 42 1.7108526 -4.7739887 43 -8.5994943 1.7108526 44 -0.9624170 -8.5994943 45 1.8828450 -0.9624170 46 -12.0588690 1.8828450 47 1.8662129 -12.0588690 48 4.4231911 1.8662129 49 -0.1915349 4.4231911 50 1.1498264 -0.1915349 51 7.8591646 1.1498264 52 -6.4223926 7.8591646 53 6.6267412 -6.4223926 54 3.5831183 6.6267412 55 -7.7414622 3.5831183 56 2.5759336 -7.7414622 57 0.9179575 2.5759336 58 0.8421004 0.9179575 59 4.7416605 0.8421004 60 -1.2187987 4.7416605 61 0.7609761 -1.2187987 62 -1.2462284 0.7609761 63 0.5774118 -1.2462284 64 -3.4626242 0.5774118 65 4.4930914 -3.4626242 66 2.8384930 4.4930914 67 -0.3159661 2.8384930 68 2.0063045 -0.3159661 69 -6.2406077 2.0063045 70 2.8821466 -6.2406077 71 2.5643216 2.8821466 72 -7.6984748 2.5643216 73 5.3208862 -7.6984748 74 4.1841710 5.3208862 75 -10.3131010 4.1841710 76 8.5368236 -10.3131010 77 1.7157573 8.5368236 78 -5.7336206 1.7157573 79 4.3376294 -5.7336206 80 -2.9562164 4.3376294 81 7.8706028 -2.9562164 82 10.6335858 7.8706028 83 -4.8789787 10.6335858 84 0.7401061 -4.8789787 85 -7.5978388 0.7401061 86 -4.0899734 -7.5978388 87 -0.9750381 -4.0899734 88 -1.6420234 -0.9750381 89 -6.5860398 -1.6420234 90 2.6373251 -6.5860398 91 4.5666699 2.6373251 92 -0.9850720 4.5666699 93 0.3066744 -0.9850720 > 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/html/rcomp/tmp/7c2a41262014208.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8484u1262014208.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9lzck1262014208.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10qh5h1262014208.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/html/rcomp/tmp/11oag61262014208.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/html/rcomp/tmp/12ea2a1262014208.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/html/rcomp/tmp/13636t1262014208.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/html/rcomp/tmp/14raah1262014208.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/html/rcomp/tmp/1521rg1262014208.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/html/rcomp/tmp/16y5sy1262014208.tab") + } > > try(system("convert tmp/1kdnf1262014207.ps tmp/1kdnf1262014207.png",intern=TRUE)) character(0) > try(system("convert tmp/2tnof1262014207.ps tmp/2tnof1262014207.png",intern=TRUE)) character(0) > try(system("convert tmp/3b5zc1262014207.ps tmp/3b5zc1262014207.png",intern=TRUE)) character(0) > try(system("convert tmp/4t1zr1262014207.ps tmp/4t1zr1262014207.png",intern=TRUE)) character(0) > try(system("convert tmp/5022r1262014207.ps tmp/5022r1262014207.png",intern=TRUE)) character(0) > try(system("convert tmp/6eeeo1262014208.ps tmp/6eeeo1262014208.png",intern=TRUE)) character(0) > try(system("convert tmp/7c2a41262014208.ps tmp/7c2a41262014208.png",intern=TRUE)) character(0) > try(system("convert tmp/8484u1262014208.ps tmp/8484u1262014208.png",intern=TRUE)) character(0) > try(system("convert tmp/9lzck1262014208.ps tmp/9lzck1262014208.png",intern=TRUE)) character(0) > try(system("convert tmp/10qh5h1262014208.ps tmp/10qh5h1262014208.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.014 1.651 6.803