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Type 'q()' to quit R. > x <- array(list(82.4 + ,0 + ,82.4 + ,111.1 + ,105.7 + ,105.7 + ,60 + ,0 + ,60 + ,82.4 + ,111.1 + ,105.7 + ,107.3 + ,0 + ,107.3 + ,60 + ,82.4 + ,111.1 + ,99.3 + ,0 + ,99.3 + ,107.3 + ,60 + ,82.4 + ,113.5 + ,0 + ,113.5 + ,99.3 + ,107.3 + ,60 + ,108.9 + ,0 + ,108.9 + ,113.5 + ,99.3 + ,107.3 + ,100.2 + ,0 + ,100.2 + ,108.9 + ,113.5 + ,99.3 + ,103.9 + ,0 + ,103.9 + ,100.2 + ,108.9 + ,113.5 + ,138.7 + ,0 + ,138.7 + ,103.9 + ,100.2 + ,108.9 + ,120.2 + ,0 + ,120.2 + ,138.7 + ,103.9 + ,100.2 + ,100.2 + ,0 + ,100.2 + ,120.2 + ,138.7 + ,103.9 + ,143.2 + ,0 + ,143.2 + ,100.2 + ,120.2 + ,138.7 + ,70.9 + ,0 + ,70.9 + ,143.2 + ,100.2 + ,120.2 + ,85.2 + ,0 + ,85.2 + ,70.9 + ,143.2 + ,100.2 + ,133 + ,0 + ,133 + ,85.2 + ,70.9 + ,143.2 + ,136.6 + ,0 + ,136.6 + ,133 + ,85.2 + ,70.9 + ,117.9 + ,0 + ,117.9 + ,136.6 + ,133 + ,85.2 + ,106.3 + ,0 + ,106.3 + ,117.9 + ,136.6 + ,133 + ,122.3 + ,0 + ,122.3 + ,106.3 + ,117.9 + ,136.6 + ,125.5 + ,0 + ,125.5 + ,122.3 + ,106.3 + ,117.9 + ,148.4 + ,0 + ,148.4 + ,125.5 + ,122.3 + ,106.3 + ,126.3 + ,0 + ,126.3 + ,148.4 + ,125.5 + ,122.3 + ,99.6 + ,0 + ,99.6 + ,126.3 + ,148.4 + ,125.5 + ,140.4 + ,0 + ,140.4 + ,99.6 + ,126.3 + ,148.4 + ,80.3 + ,0 + ,80.3 + ,140.4 + ,99.6 + ,126.3 + ,92.6 + ,0 + ,92.6 + ,80.3 + ,140.4 + ,99.6 + ,138.5 + ,0 + ,138.5 + ,92.6 + ,80.3 + ,140.4 + ,110.9 + ,0 + ,110.9 + ,138.5 + ,92.6 + ,80.3 + ,119.6 + ,0 + ,119.6 + ,110.9 + ,138.5 + ,92.6 + ,105 + ,0 + ,105 + ,119.6 + ,110.9 + ,138.5 + ,109 + ,0 + ,109 + ,105 + ,119.6 + ,110.9 + ,129.4 + ,0 + ,129.4 + ,109 + ,105 + ,119.6 + ,148.6 + ,0 + ,148.6 + ,129.4 + ,109 + ,105 + ,101.4 + ,0 + ,101.4 + ,148.6 + ,129.4 + ,109 + ,134.8 + ,0 + ,134.8 + ,101.4 + ,148.6 + ,129.4 + ,143.7 + ,0 + ,143.7 + ,134.8 + ,101.4 + ,148.6 + ,81.6 + ,0 + ,81.6 + ,143.7 + ,134.8 + ,101.4 + ,90.3 + ,0 + ,90.3 + ,81.6 + ,143.7 + ,134.8 + ,141.5 + ,0 + ,141.5 + ,90.3 + ,81.6 + ,143.7 + ,140.7 + ,0 + ,140.7 + ,141.5 + ,90.3 + ,81.6 + ,140.2 + ,0 + ,140.2 + ,140.7 + ,141.5 + ,90.3 + ,100.2 + ,0 + ,100.2 + ,140.2 + ,140.7 + ,141.5 + ,125.7 + ,0 + ,125.7 + ,100.2 + ,140.2 + ,140.7 + ,119.6 + ,0 + ,119.6 + ,125.7 + ,100.2 + ,140.2 + ,134.7 + ,0 + ,134.7 + ,119.6 + ,125.7 + ,100.2 + ,109 + ,0 + ,109 + ,134.7 + ,119.6 + ,125.7 + ,116.3 + ,0 + ,116.3 + ,109 + ,134.7 + ,119.6 + ,146.9 + ,0 + ,146.9 + ,116.3 + ,109 + ,134.7 + ,97.4 + ,0 + ,97.4 + ,146.9 + ,116.3 + ,109 + ,89.4 + ,0 + ,89.4 + ,97.4 + ,146.9 + ,116.3 + ,132.1 + ,0 + ,132.1 + ,89.4 + ,97.4 + ,146.9 + ,139.8 + ,0 + ,139.8 + ,132.1 + ,89.4 + ,97.4 + ,129 + ,0 + ,129 + ,139.8 + ,132.1 + ,89.4 + ,112.5 + ,0 + ,112.5 + ,129 + ,139.8 + ,132.1 + ,121.9 + ,1 + ,121.9 + ,112.5 + ,129 + ,139.8 + ,121.7 + ,1 + ,121.7 + ,121.9 + ,112.5 + ,129 + ,123.1 + ,1 + ,123.1 + ,121.7 + ,121.9 + ,112.5 + ,131.6 + ,1 + ,131.6 + ,123.1 + ,121.7 + ,121.9 + ,119.3 + ,1 + ,119.3 + ,131.6 + ,123.1 + ,121.7 + ,132.5 + ,1 + ,132.5 + ,119.3 + ,131.6 + ,123.1 + ,98.3 + ,1 + ,98.3 + ,132.5 + ,119.3 + ,131.6 + ,85.1 + ,1 + ,85.1 + ,98.3 + ,132.5 + ,119.3 + ,131.7 + ,1 + ,131.7 + ,85.1 + ,98.3 + ,132.5 + ,129.3 + ,1 + ,129.3 + ,131.7 + ,85.1 + ,98.3 + ,90.7 + ,1 + ,90.7 + ,129.3 + ,131.7 + ,85.1 + ,78.6 + ,1 + ,78.6 + ,90.7 + ,129.3 + ,131.7 + ,68.9 + ,1 + ,68.9 + ,78.6 + ,90.7 + ,129.3 + ,79.1 + ,1 + ,79.1 + ,68.9 + ,78.6 + ,90.7 + ,83.5 + ,1 + ,83.5 + ,79.1 + ,68.9 + ,78.6 + ,74.1 + ,1 + ,74.1 + ,83.5 + ,79.1 + ,68.9 + ,59.7 + ,1 + ,59.7 + ,74.1 + ,83.5 + ,79.1 + ,93.3 + ,1 + ,93.3 + ,59.7 + ,74.1 + ,83.5 + ,61.3 + ,1 + ,61.3 + ,93.3 + ,59.7 + ,74.1 + ,56.6 + ,1 + ,56.6 + ,61.3 + ,93.3 + ,59.7) + ,dim=c(6 + ,74) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2' + ,'Y3' + ,'Y4') + ,1:74)) > y <- array(NA,dim=c(6,74),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:74)) > 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 X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 82.4 0 82.4 111.1 105.7 105.7 1 0 0 0 0 0 0 0 0 0 0 1 2 60.0 0 60.0 82.4 111.1 105.7 0 1 0 0 0 0 0 0 0 0 0 2 3 107.3 0 107.3 60.0 82.4 111.1 0 0 1 0 0 0 0 0 0 0 0 3 4 99.3 0 99.3 107.3 60.0 82.4 0 0 0 1 0 0 0 0 0 0 0 4 5 113.5 0 113.5 99.3 107.3 60.0 0 0 0 0 1 0 0 0 0 0 0 5 6 108.9 0 108.9 113.5 99.3 107.3 0 0 0 0 0 1 0 0 0 0 0 6 7 100.2 0 100.2 108.9 113.5 99.3 0 0 0 0 0 0 1 0 0 0 0 7 8 103.9 0 103.9 100.2 108.9 113.5 0 0 0 0 0 0 0 1 0 0 0 8 9 138.7 0 138.7 103.9 100.2 108.9 0 0 0 0 0 0 0 0 1 0 0 9 10 120.2 0 120.2 138.7 103.9 100.2 0 0 0 0 0 0 0 0 0 1 0 10 11 100.2 0 100.2 120.2 138.7 103.9 0 0 0 0 0 0 0 0 0 0 1 11 12 143.2 0 143.2 100.2 120.2 138.7 0 0 0 0 0 0 0 0 0 0 0 12 13 70.9 0 70.9 143.2 100.2 120.2 1 0 0 0 0 0 0 0 0 0 0 13 14 85.2 0 85.2 70.9 143.2 100.2 0 1 0 0 0 0 0 0 0 0 0 14 15 133.0 0 133.0 85.2 70.9 143.2 0 0 1 0 0 0 0 0 0 0 0 15 16 136.6 0 136.6 133.0 85.2 70.9 0 0 0 1 0 0 0 0 0 0 0 16 17 117.9 0 117.9 136.6 133.0 85.2 0 0 0 0 1 0 0 0 0 0 0 17 18 106.3 0 106.3 117.9 136.6 133.0 0 0 0 0 0 1 0 0 0 0 0 18 19 122.3 0 122.3 106.3 117.9 136.6 0 0 0 0 0 0 1 0 0 0 0 19 20 125.5 0 125.5 122.3 106.3 117.9 0 0 0 0 0 0 0 1 0 0 0 20 21 148.4 0 148.4 125.5 122.3 106.3 0 0 0 0 0 0 0 0 1 0 0 21 22 126.3 0 126.3 148.4 125.5 122.3 0 0 0 0 0 0 0 0 0 1 0 22 23 99.6 0 99.6 126.3 148.4 125.5 0 0 0 0 0 0 0 0 0 0 1 23 24 140.4 0 140.4 99.6 126.3 148.4 0 0 0 0 0 0 0 0 0 0 0 24 25 80.3 0 80.3 140.4 99.6 126.3 1 0 0 0 0 0 0 0 0 0 0 25 26 92.6 0 92.6 80.3 140.4 99.6 0 1 0 0 0 0 0 0 0 0 0 26 27 138.5 0 138.5 92.6 80.3 140.4 0 0 1 0 0 0 0 0 0 0 0 27 28 110.9 0 110.9 138.5 92.6 80.3 0 0 0 1 0 0 0 0 0 0 0 28 29 119.6 0 119.6 110.9 138.5 92.6 0 0 0 0 1 0 0 0 0 0 0 29 30 105.0 0 105.0 119.6 110.9 138.5 0 0 0 0 0 1 0 0 0 0 0 30 31 109.0 0 109.0 105.0 119.6 110.9 0 0 0 0 0 0 1 0 0 0 0 31 32 129.4 0 129.4 109.0 105.0 119.6 0 0 0 0 0 0 0 1 0 0 0 32 33 148.6 0 148.6 129.4 109.0 105.0 0 0 0 0 0 0 0 0 1 0 0 33 34 101.4 0 101.4 148.6 129.4 109.0 0 0 0 0 0 0 0 0 0 1 0 34 35 134.8 0 134.8 101.4 148.6 129.4 0 0 0 0 0 0 0 0 0 0 1 35 36 143.7 0 143.7 134.8 101.4 148.6 0 0 0 0 0 0 0 0 0 0 0 36 37 81.6 0 81.6 143.7 134.8 101.4 1 0 0 0 0 0 0 0 0 0 0 37 38 90.3 0 90.3 81.6 143.7 134.8 0 1 0 0 0 0 0 0 0 0 0 38 39 141.5 0 141.5 90.3 81.6 143.7 0 0 1 0 0 0 0 0 0 0 0 39 40 140.7 0 140.7 141.5 90.3 81.6 0 0 0 1 0 0 0 0 0 0 0 40 41 140.2 0 140.2 140.7 141.5 90.3 0 0 0 0 1 0 0 0 0 0 0 41 42 100.2 0 100.2 140.2 140.7 141.5 0 0 0 0 0 1 0 0 0 0 0 42 43 125.7 0 125.7 100.2 140.2 140.7 0 0 0 0 0 0 1 0 0 0 0 43 44 119.6 0 119.6 125.7 100.2 140.2 0 0 0 0 0 0 0 1 0 0 0 44 45 134.7 0 134.7 119.6 125.7 100.2 0 0 0 0 0 0 0 0 1 0 0 45 46 109.0 0 109.0 134.7 119.6 125.7 0 0 0 0 0 0 0 0 0 1 0 46 47 116.3 0 116.3 109.0 134.7 119.6 0 0 0 0 0 0 0 0 0 0 1 47 48 146.9 0 146.9 116.3 109.0 134.7 0 0 0 0 0 0 0 0 0 0 0 48 49 97.4 0 97.4 146.9 116.3 109.0 1 0 0 0 0 0 0 0 0 0 0 49 50 89.4 0 89.4 97.4 146.9 116.3 0 1 0 0 0 0 0 0 0 0 0 50 51 132.1 0 132.1 89.4 97.4 146.9 0 0 1 0 0 0 0 0 0 0 0 51 52 139.8 0 139.8 132.1 89.4 97.4 0 0 0 1 0 0 0 0 0 0 0 52 53 129.0 0 129.0 139.8 132.1 89.4 0 0 0 0 1 0 0 0 0 0 0 53 54 112.5 0 112.5 129.0 139.8 132.1 0 0 0 0 0 1 0 0 0 0 0 54 55 121.9 1 121.9 112.5 129.0 139.8 0 0 0 0 0 0 1 0 0 0 0 55 56 121.7 1 121.7 121.9 112.5 129.0 0 0 0 0 0 0 0 1 0 0 0 56 57 123.1 1 123.1 121.7 121.9 112.5 0 0 0 0 0 0 0 0 1 0 0 57 58 131.6 1 131.6 123.1 121.7 121.9 0 0 0 0 0 0 0 0 0 1 0 58 59 119.3 1 119.3 131.6 123.1 121.7 0 0 0 0 0 0 0 0 0 0 1 59 60 132.5 1 132.5 119.3 131.6 123.1 0 0 0 0 0 0 0 0 0 0 0 60 61 98.3 1 98.3 132.5 119.3 131.6 1 0 0 0 0 0 0 0 0 0 0 61 62 85.1 1 85.1 98.3 132.5 119.3 0 1 0 0 0 0 0 0 0 0 0 62 63 131.7 1 131.7 85.1 98.3 132.5 0 0 1 0 0 0 0 0 0 0 0 63 64 129.3 1 129.3 131.7 85.1 98.3 0 0 0 1 0 0 0 0 0 0 0 64 65 90.7 1 90.7 129.3 131.7 85.1 0 0 0 0 1 0 0 0 0 0 0 65 66 78.6 1 78.6 90.7 129.3 131.7 0 0 0 0 0 1 0 0 0 0 0 66 67 68.9 1 68.9 78.6 90.7 129.3 0 0 0 0 0 0 1 0 0 0 0 67 68 79.1 1 79.1 68.9 78.6 90.7 0 0 0 0 0 0 0 1 0 0 0 68 69 83.5 1 83.5 79.1 68.9 78.6 0 0 0 0 0 0 0 0 1 0 0 69 70 74.1 1 74.1 83.5 79.1 68.9 0 0 0 0 0 0 0 0 0 1 0 70 71 59.7 1 59.7 74.1 83.5 79.1 0 0 0 0 0 0 0 0 0 0 1 71 72 93.3 1 93.3 59.7 74.1 83.5 0 0 0 0 0 0 0 0 0 0 0 72 73 61.3 1 61.3 93.3 59.7 74.1 1 0 0 0 0 0 0 0 0 0 0 73 74 56.6 1 56.6 61.3 93.3 59.7 0 1 0 0 0 0 0 0 0 0 0 74 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 Y3 Y4 2.844e-14 -7.440e-15 1.000e+00 -4.924e-17 6.071e-17 -3.775e-17 M1 M2 M3 M4 M5 M6 -1.846e-15 -6.363e-15 7.523e-15 4.628e-16 -1.876e-15 -1.934e-15 M7 M8 M9 M10 M11 t -1.509e-15 4.677e-16 3.204e-16 -1.238e-15 -2.315e-15 -4.106e-17 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -8.330e-15 -1.608e-15 -2.347e-16 1.288e-15 3.064e-14 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.844e-14 6.401e-15 4.443e+00 4.23e-05 *** X -7.440e-15 2.400e-15 -3.100e+00 0.00303 ** Y1 1.000e+00 5.559e-17 1.799e+16 < 2e-16 *** Y2 -4.924e-17 5.474e-17 -8.990e-01 0.37225 Y3 6.071e-17 5.431e-17 1.118e+00 0.26848 Y4 -3.775e-17 5.488e-17 -6.880e-01 0.49438 M1 -1.846e-15 4.550e-15 -4.060e-01 0.68644 M2 -6.363e-15 4.462e-15 -1.426e+00 0.15943 M3 7.523e-15 3.452e-15 2.179e+00 0.03355 * M4 4.628e-16 4.394e-15 1.050e-01 0.91649 M5 -1.876e-15 4.565e-15 -4.110e-01 0.68277 M6 -1.934e-15 3.814e-15 -5.070e-01 0.61412 M7 -1.509e-15 3.346e-15 -4.510e-01 0.65381 M8 4.677e-16 3.174e-15 1.470e-01 0.88338 M9 3.204e-16 3.394e-15 9.400e-02 0.92513 M10 -1.238e-15 3.850e-15 -3.220e-01 0.74901 M11 -2.315e-15 3.770e-15 -6.140e-01 0.54155 t -4.106e-17 4.503e-17 -9.120e-01 0.36576 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 5.134e-15 on 56 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 9.82e+31 on 17 and 56 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 1.182822e-01 2.365644e-01 8.817178e-01 [2,] 9.999904e-01 1.916920e-05 9.584601e-06 [3,] 8.450878e-01 3.098244e-01 1.549122e-01 [4,] 7.670527e-04 1.534105e-03 9.992329e-01 [5,] 4.546581e-05 9.093162e-05 9.999545e-01 [6,] 4.238012e-01 8.476025e-01 5.761988e-01 [7,] 9.986347e-01 2.730636e-03 1.365318e-03 [8,] 3.624389e-01 7.248777e-01 6.375611e-01 [9,] 1.812214e-01 3.624428e-01 8.187786e-01 [10,] 6.475969e-01 7.048062e-01 3.524031e-01 [11,] 9.999998e-01 4.740475e-07 2.370238e-07 [12,] 9.976834e-01 4.633280e-03 2.316640e-03 [13,] 7.041843e-05 1.408369e-04 9.999296e-01 [14,] 7.304703e-01 5.390595e-01 2.695297e-01 [15,] 1.000000e+00 6.241535e-08 3.120768e-08 [16,] 9.997178e-01 5.644725e-04 2.822363e-04 [17,] 9.999825e-01 3.498806e-05 1.749403e-05 [18,] 9.998885e-01 2.230373e-04 1.115187e-04 [19,] 1.000000e+00 5.171238e-13 2.585619e-13 [20,] 9.999938e-01 1.249158e-05 6.245789e-06 [21,] 1.941335e-01 3.882669e-01 8.058665e-01 [22,] 1.607270e-05 3.214541e-05 9.999839e-01 [23,] 2.088049e-01 4.176098e-01 7.911951e-01 [24,] 3.514783e-12 7.029566e-12 1.000000e+00 [25,] 1.070047e-16 2.140095e-16 1.000000e+00 [26,] 9.206046e-02 1.841209e-01 9.079395e-01 [27,] 2.311675e-01 4.623351e-01 7.688325e-01 [28,] 1.000000e+00 0.000000e+00 0.000000e+00 [29,] 9.886432e-01 2.271356e-02 1.135678e-02 [30,] 2.639078e-08 5.278157e-08 1.000000e+00 [31,] 7.844807e-02 1.568961e-01 9.215519e-01 [32,] 2.569830e-03 5.139661e-03 9.974302e-01 [33,] 9.780778e-01 4.384437e-02 2.192218e-02 > postscript(file="/var/www/html/rcomp/tmp/15cba1258741837.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/23jwg1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ad5g1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4l9gi1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5x2fu1258741837.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 = 74 Frequency = 1 1 2 3 4 5 -5.810159e-15 -5.649799e-15 3.063963e-14 -1.618985e-15 -3.043610e-15 6 7 8 9 10 -1.539083e-16 -2.204726e-15 -4.367452e-15 -5.386932e-16 -3.619284e-17 11 12 13 14 15 -2.033410e-15 -1.113639e-15 1.200370e-15 1.116980e-17 -7.948929e-15 16 17 18 19 20 -2.688762e-15 -1.165397e-15 -1.139599e-15 9.606399e-16 -7.198704e-16 21 22 23 24 25 5.072786e-15 1.220770e-15 -9.140998e-16 -1.896433e-16 2.612123e-16 26 27 28 29 30 -1.145551e-16 -1.575895e-15 -8.610192e-16 -4.985455e-16 1.420482e-15 31 32 33 34 35 -1.056163e-15 2.166259e-15 -6.227374e-16 -1.098373e-15 -2.027769e-15 36 37 38 39 40 3.007579e-15 -2.376194e-15 1.952582e-15 -5.201551e-15 1.681599e-15 41 42 43 44 45 1.324990e-15 1.140619e-15 -1.176836e-16 2.624826e-15 -3.052312e-15 46 47 48 49 50 1.310190e-15 -2.797714e-16 1.071989e-15 6.134225e-16 2.480142e-15 51 52 53 54 55 -7.583417e-15 2.512024e-15 4.169710e-15 9.598662e-16 1.761973e-15 56 57 58 59 60 9.166855e-16 -3.307384e-16 2.932338e-16 3.780076e-15 -1.754787e-15 61 62 63 64 65 3.087631e-15 4.222960e-15 -8.329841e-15 9.751435e-16 -7.871480e-16 66 67 68 69 70 -2.227460e-15 6.559597e-16 -6.204476e-16 -5.283052e-16 -1.689628e-15 71 72 73 74 1.474974e-15 -1.021498e-15 3.023718e-15 -2.902501e-15 > postscript(file="/var/www/html/rcomp/tmp/619c81258741837.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 = 74 Frequency = 1 lag(myerror, k = 1) myerror 0 -5.810159e-15 NA 1 -5.649799e-15 -5.810159e-15 2 3.063963e-14 -5.649799e-15 3 -1.618985e-15 3.063963e-14 4 -3.043610e-15 -1.618985e-15 5 -1.539083e-16 -3.043610e-15 6 -2.204726e-15 -1.539083e-16 7 -4.367452e-15 -2.204726e-15 8 -5.386932e-16 -4.367452e-15 9 -3.619284e-17 -5.386932e-16 10 -2.033410e-15 -3.619284e-17 11 -1.113639e-15 -2.033410e-15 12 1.200370e-15 -1.113639e-15 13 1.116980e-17 1.200370e-15 14 -7.948929e-15 1.116980e-17 15 -2.688762e-15 -7.948929e-15 16 -1.165397e-15 -2.688762e-15 17 -1.139599e-15 -1.165397e-15 18 9.606399e-16 -1.139599e-15 19 -7.198704e-16 9.606399e-16 20 5.072786e-15 -7.198704e-16 21 1.220770e-15 5.072786e-15 22 -9.140998e-16 1.220770e-15 23 -1.896433e-16 -9.140998e-16 24 2.612123e-16 -1.896433e-16 25 -1.145551e-16 2.612123e-16 26 -1.575895e-15 -1.145551e-16 27 -8.610192e-16 -1.575895e-15 28 -4.985455e-16 -8.610192e-16 29 1.420482e-15 -4.985455e-16 30 -1.056163e-15 1.420482e-15 31 2.166259e-15 -1.056163e-15 32 -6.227374e-16 2.166259e-15 33 -1.098373e-15 -6.227374e-16 34 -2.027769e-15 -1.098373e-15 35 3.007579e-15 -2.027769e-15 36 -2.376194e-15 3.007579e-15 37 1.952582e-15 -2.376194e-15 38 -5.201551e-15 1.952582e-15 39 1.681599e-15 -5.201551e-15 40 1.324990e-15 1.681599e-15 41 1.140619e-15 1.324990e-15 42 -1.176836e-16 1.140619e-15 43 2.624826e-15 -1.176836e-16 44 -3.052312e-15 2.624826e-15 45 1.310190e-15 -3.052312e-15 46 -2.797714e-16 1.310190e-15 47 1.071989e-15 -2.797714e-16 48 6.134225e-16 1.071989e-15 49 2.480142e-15 6.134225e-16 50 -7.583417e-15 2.480142e-15 51 2.512024e-15 -7.583417e-15 52 4.169710e-15 2.512024e-15 53 9.598662e-16 4.169710e-15 54 1.761973e-15 9.598662e-16 55 9.166855e-16 1.761973e-15 56 -3.307384e-16 9.166855e-16 57 2.932338e-16 -3.307384e-16 58 3.780076e-15 2.932338e-16 59 -1.754787e-15 3.780076e-15 60 3.087631e-15 -1.754787e-15 61 4.222960e-15 3.087631e-15 62 -8.329841e-15 4.222960e-15 63 9.751435e-16 -8.329841e-15 64 -7.871480e-16 9.751435e-16 65 -2.227460e-15 -7.871480e-16 66 6.559597e-16 -2.227460e-15 67 -6.204476e-16 6.559597e-16 68 -5.283052e-16 -6.204476e-16 69 -1.689628e-15 -5.283052e-16 70 1.474974e-15 -1.689628e-15 71 -1.021498e-15 1.474974e-15 72 3.023718e-15 -1.021498e-15 73 -2.902501e-15 3.023718e-15 74 NA -2.902501e-15 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -5.649799e-15 -5.810159e-15 [2,] 3.063963e-14 -5.649799e-15 [3,] -1.618985e-15 3.063963e-14 [4,] -3.043610e-15 -1.618985e-15 [5,] -1.539083e-16 -3.043610e-15 [6,] -2.204726e-15 -1.539083e-16 [7,] -4.367452e-15 -2.204726e-15 [8,] -5.386932e-16 -4.367452e-15 [9,] -3.619284e-17 -5.386932e-16 [10,] -2.033410e-15 -3.619284e-17 [11,] -1.113639e-15 -2.033410e-15 [12,] 1.200370e-15 -1.113639e-15 [13,] 1.116980e-17 1.200370e-15 [14,] -7.948929e-15 1.116980e-17 [15,] -2.688762e-15 -7.948929e-15 [16,] -1.165397e-15 -2.688762e-15 [17,] -1.139599e-15 -1.165397e-15 [18,] 9.606399e-16 -1.139599e-15 [19,] -7.198704e-16 9.606399e-16 [20,] 5.072786e-15 -7.198704e-16 [21,] 1.220770e-15 5.072786e-15 [22,] -9.140998e-16 1.220770e-15 [23,] -1.896433e-16 -9.140998e-16 [24,] 2.612123e-16 -1.896433e-16 [25,] -1.145551e-16 2.612123e-16 [26,] -1.575895e-15 -1.145551e-16 [27,] -8.610192e-16 -1.575895e-15 [28,] -4.985455e-16 -8.610192e-16 [29,] 1.420482e-15 -4.985455e-16 [30,] -1.056163e-15 1.420482e-15 [31,] 2.166259e-15 -1.056163e-15 [32,] -6.227374e-16 2.166259e-15 [33,] -1.098373e-15 -6.227374e-16 [34,] -2.027769e-15 -1.098373e-15 [35,] 3.007579e-15 -2.027769e-15 [36,] -2.376194e-15 3.007579e-15 [37,] 1.952582e-15 -2.376194e-15 [38,] -5.201551e-15 1.952582e-15 [39,] 1.681599e-15 -5.201551e-15 [40,] 1.324990e-15 1.681599e-15 [41,] 1.140619e-15 1.324990e-15 [42,] -1.176836e-16 1.140619e-15 [43,] 2.624826e-15 -1.176836e-16 [44,] -3.052312e-15 2.624826e-15 [45,] 1.310190e-15 -3.052312e-15 [46,] -2.797714e-16 1.310190e-15 [47,] 1.071989e-15 -2.797714e-16 [48,] 6.134225e-16 1.071989e-15 [49,] 2.480142e-15 6.134225e-16 [50,] -7.583417e-15 2.480142e-15 [51,] 2.512024e-15 -7.583417e-15 [52,] 4.169710e-15 2.512024e-15 [53,] 9.598662e-16 4.169710e-15 [54,] 1.761973e-15 9.598662e-16 [55,] 9.166855e-16 1.761973e-15 [56,] -3.307384e-16 9.166855e-16 [57,] 2.932338e-16 -3.307384e-16 [58,] 3.780076e-15 2.932338e-16 [59,] -1.754787e-15 3.780076e-15 [60,] 3.087631e-15 -1.754787e-15 [61,] 4.222960e-15 3.087631e-15 [62,] -8.329841e-15 4.222960e-15 [63,] 9.751435e-16 -8.329841e-15 [64,] -7.871480e-16 9.751435e-16 [65,] -2.227460e-15 -7.871480e-16 [66,] 6.559597e-16 -2.227460e-15 [67,] -6.204476e-16 6.559597e-16 [68,] -5.283052e-16 -6.204476e-16 [69,] -1.689628e-15 -5.283052e-16 [70,] 1.474974e-15 -1.689628e-15 [71,] -1.021498e-15 1.474974e-15 [72,] 3.023718e-15 -1.021498e-15 [73,] -2.902501e-15 3.023718e-15 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -5.649799e-15 -5.810159e-15 2 3.063963e-14 -5.649799e-15 3 -1.618985e-15 3.063963e-14 4 -3.043610e-15 -1.618985e-15 5 -1.539083e-16 -3.043610e-15 6 -2.204726e-15 -1.539083e-16 7 -4.367452e-15 -2.204726e-15 8 -5.386932e-16 -4.367452e-15 9 -3.619284e-17 -5.386932e-16 10 -2.033410e-15 -3.619284e-17 11 -1.113639e-15 -2.033410e-15 12 1.200370e-15 -1.113639e-15 13 1.116980e-17 1.200370e-15 14 -7.948929e-15 1.116980e-17 15 -2.688762e-15 -7.948929e-15 16 -1.165397e-15 -2.688762e-15 17 -1.139599e-15 -1.165397e-15 18 9.606399e-16 -1.139599e-15 19 -7.198704e-16 9.606399e-16 20 5.072786e-15 -7.198704e-16 21 1.220770e-15 5.072786e-15 22 -9.140998e-16 1.220770e-15 23 -1.896433e-16 -9.140998e-16 24 2.612123e-16 -1.896433e-16 25 -1.145551e-16 2.612123e-16 26 -1.575895e-15 -1.145551e-16 27 -8.610192e-16 -1.575895e-15 28 -4.985455e-16 -8.610192e-16 29 1.420482e-15 -4.985455e-16 30 -1.056163e-15 1.420482e-15 31 2.166259e-15 -1.056163e-15 32 -6.227374e-16 2.166259e-15 33 -1.098373e-15 -6.227374e-16 34 -2.027769e-15 -1.098373e-15 35 3.007579e-15 -2.027769e-15 36 -2.376194e-15 3.007579e-15 37 1.952582e-15 -2.376194e-15 38 -5.201551e-15 1.952582e-15 39 1.681599e-15 -5.201551e-15 40 1.324990e-15 1.681599e-15 41 1.140619e-15 1.324990e-15 42 -1.176836e-16 1.140619e-15 43 2.624826e-15 -1.176836e-16 44 -3.052312e-15 2.624826e-15 45 1.310190e-15 -3.052312e-15 46 -2.797714e-16 1.310190e-15 47 1.071989e-15 -2.797714e-16 48 6.134225e-16 1.071989e-15 49 2.480142e-15 6.134225e-16 50 -7.583417e-15 2.480142e-15 51 2.512024e-15 -7.583417e-15 52 4.169710e-15 2.512024e-15 53 9.598662e-16 4.169710e-15 54 1.761973e-15 9.598662e-16 55 9.166855e-16 1.761973e-15 56 -3.307384e-16 9.166855e-16 57 2.932338e-16 -3.307384e-16 58 3.780076e-15 2.932338e-16 59 -1.754787e-15 3.780076e-15 60 3.087631e-15 -1.754787e-15 61 4.222960e-15 3.087631e-15 62 -8.329841e-15 4.222960e-15 63 9.751435e-16 -8.329841e-15 64 -7.871480e-16 9.751435e-16 65 -2.227460e-15 -7.871480e-16 66 6.559597e-16 -2.227460e-15 67 -6.204476e-16 6.559597e-16 68 -5.283052e-16 -6.204476e-16 69 -1.689628e-15 -5.283052e-16 70 1.474974e-15 -1.689628e-15 71 -1.021498e-15 1.474974e-15 72 3.023718e-15 -1.021498e-15 73 -2.902501e-15 3.023718e-15 > 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/77pbn1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8nz1f1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/96nok1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/105w0v1258741837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11chkj1258741837.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/12pw1j1258741837.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/13pvhc1258741837.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/14lr1z1258741837.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/1523pl1258741837.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/163t3m1258741837.tab") + } > > system("convert tmp/15cba1258741837.ps tmp/15cba1258741837.png") > system("convert tmp/23jwg1258741837.ps tmp/23jwg1258741837.png") > system("convert tmp/3ad5g1258741837.ps tmp/3ad5g1258741837.png") > system("convert tmp/4l9gi1258741837.ps tmp/4l9gi1258741837.png") > system("convert tmp/5x2fu1258741837.ps tmp/5x2fu1258741837.png") > system("convert tmp/619c81258741837.ps tmp/619c81258741837.png") > system("convert tmp/77pbn1258741837.ps tmp/77pbn1258741837.png") > system("convert tmp/8nz1f1258741837.ps tmp/8nz1f1258741837.png") > system("convert tmp/96nok1258741837.ps tmp/96nok1258741837.png") > system("convert tmp/105w0v1258741837.ps tmp/105w0v1258741837.png") > > > proc.time() user system elapsed 2.584 1.574 2.949