R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1721 + ,0 + ,0.44 + ,1476 + ,0 + ,0.09 + ,1842 + ,0 + ,0.2 + ,2171 + ,0 + ,0.82 + ,1670 + ,0 + ,0.5 + ,1540 + ,0 + ,0.2 + ,1266 + ,0 + ,1 + ,897 + ,0 + ,0.47 + ,1266 + ,0 + ,0.49 + ,1519 + ,0 + ,0.82 + ,1074 + ,0 + ,0.39 + ,1435 + ,0 + ,0.6 + ,1385 + ,0 + ,0.59 + ,1440 + ,0 + ,0.72 + ,1883 + ,0 + ,0.97 + ,1822 + ,0 + ,0.58 + ,1661 + ,0 + ,0.27 + ,1774 + ,0 + ,0.84 + ,1133 + ,0 + ,0.51 + ,1361 + ,0 + ,0.13 + ,1688 + ,0 + ,0.65 + ,2216 + ,0 + ,0.51 + ,2896 + ,0 + ,1.06 + ,1382 + ,0 + ,0.81 + ,1330 + ,0 + ,0.54 + ,1419 + ,0 + ,0.85 + ,1662 + ,0 + ,0.93 + ,2040 + ,0 + ,0.29 + ,2126 + ,0 + ,1.01 + ,1649 + ,0 + ,0.65 + ,1610 + ,0 + ,0.88 + ,1952 + ,0 + ,0.45 + ,2102 + ,0 + ,0.74 + ,1749 + ,0 + ,1.08 + ,2091 + ,0 + ,0.27 + ,3036 + ,0 + ,0.24 + ,2414 + ,0 + ,0.27 + ,2097 + ,0 + ,0.25 + ,2705 + ,0 + ,0.69 + ,2431 + ,0 + ,0.73 + ,4192 + ,1 + ,1.04 + ,3990 + ,0 + ,1.04 + ,2854 + ,0 + ,0.3 + ,1966 + ,0 + ,0.59 + ,2431 + ,0 + ,0.72 + ,2763 + ,0 + ,0.22 + ,2831 + ,0 + ,1.12 + ,2023 + ,0 + ,0.93 + ,2934 + ,0 + ,0.99 + ,2489 + ,0 + ,0.56 + ,3252 + ,0 + ,1 + ,3018 + ,0 + ,0.57 + ,3193 + ,0 + ,1 + ,3976 + ,0 + ,0.97 + ,2584 + ,0 + ,0.3 + ,2512 + ,0 + ,0.45 + ,2169 + ,0 + ,0.73 + ,2504 + ,0 + ,1.13 + ,1843 + ,0 + ,0.65 + ,1408 + ,-1 + ,0.64 + ,2179 + ,0 + ,0.68 + ,3690 + ,0 + ,0.41 + ,2372 + ,0 + ,0.98 + ,2494 + ,0 + ,0.3 + ,3872 + ,0 + ,0.37 + ,2786 + ,0 + ,1.12 + ,2312 + ,0 + ,0.4 + ,1599 + ,0 + ,0.5 + ,3167 + ,0 + ,1.23 + ,3433 + ,0 + ,0.94 + ,2648 + ,0 + ,1.08 + ,1978 + ,0 + ,1.12 + ,1947 + ,0 + ,0.83 + ,3113 + ,0 + ,1.22 + ,2856 + ,0 + ,0.55 + ,3174 + ,0 + ,0.38 + ,3507 + ,0 + ,1.26 + ,4174 + ,0 + ,0.49 + ,2978 + ,0 + ,1.13 + ,4428 + ,0 + ,1.07 + ,2832 + ,0 + ,0.86 + ,2930 + ,0 + ,0.94 + ,3681 + ,0 + ,0.45 + ,3253 + ,0 + ,0.66 + ,1660 + ,-1 + ,0.71 + ,2208 + ,0 + ,0.54 + ,3139 + ,0 + ,0.9 + ,3409 + ,0 + ,1.23 + ,3445 + ,0 + ,0.46 + ,2410 + ,0 + ,1.33 + ,3262 + ,0 + ,0.64 + ,2897 + ,0 + ,0.9 + ,2526 + ,0 + ,0.5 + ,3982 + ,0 + ,1.37 + ,4097 + ,0 + ,0.96 + ,3403 + ,0 + ,0.62 + ,3362 + ,0 + ,1.24 + ,2708 + ,0 + ,1.1 + ,3129 + ,0 + ,0.86 + ,3550 + ,0 + ,1.2 + ,2696 + ,0 + ,0.77 + ,2885 + ,0 + ,0.67 + ,2945 + ,0 + ,1.05 + ,3600 + ,0 + ,1.32 + ,3808 + ,0 + ,0.6 + ,3671 + ,0 + ,1.31 + ,4005 + ,0 + ,1.41) + ,dim=c(3 + ,107) + ,dimnames=list(c('Y' + ,'D' + ,'X') + ,1:107)) > y <- array(NA,dim=c(3,107),dimnames=list(c('Y','D','X'),1:107)) > 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 D X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 1721 0 0.44 1 0 0 0 0 0 0 0 0 0 0 1 2 1476 0 0.09 0 1 0 0 0 0 0 0 0 0 0 2 3 1842 0 0.20 0 0 1 0 0 0 0 0 0 0 0 3 4 2171 0 0.82 0 0 0 1 0 0 0 0 0 0 0 4 5 1670 0 0.50 0 0 0 0 1 0 0 0 0 0 0 5 6 1540 0 0.20 0 0 0 0 0 1 0 0 0 0 0 6 7 1266 0 1.00 0 0 0 0 0 0 1 0 0 0 0 7 8 897 0 0.47 0 0 0 0 0 0 0 1 0 0 0 8 9 1266 0 0.49 0 0 0 0 0 0 0 0 1 0 0 9 10 1519 0 0.82 0 0 0 0 0 0 0 0 0 1 0 10 11 1074 0 0.39 0 0 0 0 0 0 0 0 0 0 1 11 12 1435 0 0.60 0 0 0 0 0 0 0 0 0 0 0 12 13 1385 0 0.59 1 0 0 0 0 0 0 0 0 0 0 13 14 1440 0 0.72 0 1 0 0 0 0 0 0 0 0 0 14 15 1883 0 0.97 0 0 1 0 0 0 0 0 0 0 0 15 16 1822 0 0.58 0 0 0 1 0 0 0 0 0 0 0 16 17 1661 0 0.27 0 0 0 0 1 0 0 0 0 0 0 17 18 1774 0 0.84 0 0 0 0 0 1 0 0 0 0 0 18 19 1133 0 0.51 0 0 0 0 0 0 1 0 0 0 0 19 20 1361 0 0.13 0 0 0 0 0 0 0 1 0 0 0 20 21 1688 0 0.65 0 0 0 0 0 0 0 0 1 0 0 21 22 2216 0 0.51 0 0 0 0 0 0 0 0 0 1 0 22 23 2896 0 1.06 0 0 0 0 0 0 0 0 0 0 1 23 24 1382 0 0.81 0 0 0 0 0 0 0 0 0 0 0 24 25 1330 0 0.54 1 0 0 0 0 0 0 0 0 0 0 25 26 1419 0 0.85 0 1 0 0 0 0 0 0 0 0 0 26 27 1662 0 0.93 0 0 1 0 0 0 0 0 0 0 0 27 28 2040 0 0.29 0 0 0 1 0 0 0 0 0 0 0 28 29 2126 0 1.01 0 0 0 0 1 0 0 0 0 0 0 29 30 1649 0 0.65 0 0 0 0 0 1 0 0 0 0 0 30 31 1610 0 0.88 0 0 0 0 0 0 1 0 0 0 0 31 32 1952 0 0.45 0 0 0 0 0 0 0 1 0 0 0 32 33 2102 0 0.74 0 0 0 0 0 0 0 0 1 0 0 33 34 1749 0 1.08 0 0 0 0 0 0 0 0 0 1 0 34 35 2091 0 0.27 0 0 0 0 0 0 0 0 0 0 1 35 36 3036 0 0.24 0 0 0 0 0 0 0 0 0 0 0 36 37 2414 0 0.27 1 0 0 0 0 0 0 0 0 0 0 37 38 2097 0 0.25 0 1 0 0 0 0 0 0 0 0 0 38 39 2705 0 0.69 0 0 1 0 0 0 0 0 0 0 0 39 40 2431 0 0.73 0 0 0 1 0 0 0 0 0 0 0 40 41 4192 1 1.04 0 0 0 0 1 0 0 0 0 0 0 41 42 3990 0 1.04 0 0 0 0 0 1 0 0 0 0 0 42 43 2854 0 0.30 0 0 0 0 0 0 1 0 0 0 0 43 44 1966 0 0.59 0 0 0 0 0 0 0 1 0 0 0 44 45 2431 0 0.72 0 0 0 0 0 0 0 0 1 0 0 45 46 2763 0 0.22 0 0 0 0 0 0 0 0 0 1 0 46 47 2831 0 1.12 0 0 0 0 0 0 0 0 0 0 1 47 48 2023 0 0.93 0 0 0 0 0 0 0 0 0 0 0 48 49 2934 0 0.99 1 0 0 0 0 0 0 0 0 0 0 49 50 2489 0 0.56 0 1 0 0 0 0 0 0 0 0 0 50 51 3252 0 1.00 0 0 1 0 0 0 0 0 0 0 0 51 52 3018 0 0.57 0 0 0 1 0 0 0 0 0 0 0 52 53 3193 0 1.00 0 0 0 0 1 0 0 0 0 0 0 53 54 3976 0 0.97 0 0 0 0 0 1 0 0 0 0 0 54 55 2584 0 0.30 0 0 0 0 0 0 1 0 0 0 0 55 56 2512 0 0.45 0 0 0 0 0 0 0 1 0 0 0 56 57 2169 0 0.73 0 0 0 0 0 0 0 0 1 0 0 57 58 2504 0 1.13 0 0 0 0 0 0 0 0 0 1 0 58 59 1843 0 0.65 0 0 0 0 0 0 0 0 0 0 1 59 60 1408 -1 0.64 0 0 0 0 0 0 0 0 0 0 0 60 61 2179 0 0.68 1 0 0 0 0 0 0 0 0 0 0 61 62 3690 0 0.41 0 1 0 0 0 0 0 0 0 0 0 62 63 2372 0 0.98 0 0 1 0 0 0 0 0 0 0 0 63 64 2494 0 0.30 0 0 0 1 0 0 0 0 0 0 0 64 65 3872 0 0.37 0 0 0 0 1 0 0 0 0 0 0 65 66 2786 0 1.12 0 0 0 0 0 1 0 0 0 0 0 66 67 2312 0 0.40 0 0 0 0 0 0 1 0 0 0 0 67 68 1599 0 0.50 0 0 0 0 0 0 0 1 0 0 0 68 69 3167 0 1.23 0 0 0 0 0 0 0 0 1 0 0 69 70 3433 0 0.94 0 0 0 0 0 0 0 0 0 1 0 70 71 2648 0 1.08 0 0 0 0 0 0 0 0 0 0 1 71 72 1978 0 1.12 0 0 0 0 0 0 0 0 0 0 0 72 73 1947 0 0.83 1 0 0 0 0 0 0 0 0 0 0 73 74 3113 0 1.22 0 1 0 0 0 0 0 0 0 0 0 74 75 2856 0 0.55 0 0 1 0 0 0 0 0 0 0 0 75 76 3174 0 0.38 0 0 0 1 0 0 0 0 0 0 0 76 77 3507 0 1.26 0 0 0 0 1 0 0 0 0 0 0 77 78 4174 0 0.49 0 0 0 0 0 1 0 0 0 0 0 78 79 2978 0 1.13 0 0 0 0 0 0 1 0 0 0 0 79 80 4428 0 1.07 0 0 0 0 0 0 0 1 0 0 0 80 81 2832 0 0.86 0 0 0 0 0 0 0 0 1 0 0 81 82 2930 0 0.94 0 0 0 0 0 0 0 0 0 1 0 82 83 3681 0 0.45 0 0 0 0 0 0 0 0 0 0 1 83 84 3253 0 0.66 0 0 0 0 0 0 0 0 0 0 0 84 85 1660 -1 0.71 1 0 0 0 0 0 0 0 0 0 0 85 86 2208 0 0.54 0 1 0 0 0 0 0 0 0 0 0 86 87 3139 0 0.90 0 0 1 0 0 0 0 0 0 0 0 87 88 3409 0 1.23 0 0 0 1 0 0 0 0 0 0 0 88 89 3445 0 0.46 0 0 0 0 1 0 0 0 0 0 0 89 90 2410 0 1.33 0 0 0 0 0 1 0 0 0 0 0 90 91 3262 0 0.64 0 0 0 0 0 0 1 0 0 0 0 91 92 2897 0 0.90 0 0 0 0 0 0 0 1 0 0 0 92 93 2526 0 0.50 0 0 0 0 0 0 0 0 1 0 0 93 94 3982 0 1.37 0 0 0 0 0 0 0 0 0 1 0 94 95 4097 0 0.96 0 0 0 0 0 0 0 0 0 0 1 95 96 3403 0 0.62 0 0 0 0 0 0 0 0 0 0 0 96 97 3362 0 1.24 1 0 0 0 0 0 0 0 0 0 0 97 98 2708 0 1.10 0 1 0 0 0 0 0 0 0 0 0 98 99 3129 0 0.86 0 0 1 0 0 0 0 0 0 0 0 99 100 3550 0 1.20 0 0 0 1 0 0 0 0 0 0 0 100 101 2696 0 0.77 0 0 0 0 1 0 0 0 0 0 0 101 102 2885 0 0.67 0 0 0 0 0 1 0 0 0 0 0 102 103 2945 0 1.05 0 0 0 0 0 0 1 0 0 0 0 103 104 3600 0 1.32 0 0 0 0 0 0 0 1 0 0 0 104 105 3808 0 0.60 0 0 0 0 0 0 0 0 1 0 0 105 106 3671 0 1.31 0 0 0 0 0 0 0 0 0 1 0 106 107 4005 0 1.41 0 0 0 0 0 0 0 0 0 0 1 107 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) D X M1 M2 M3 1289.31 1344.84 84.79 -56.51 -30.59 181.62 M4 M5 M6 M7 M8 M9 312.24 388.07 381.06 -99.29 -86.02 -25.33 M10 M11 t 246.77 280.26 19.61 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1138.1 -300.8 -54.9 283.8 1565.1 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1289.310 236.229 5.458 4.05e-07 *** D 1344.841 341.437 3.939 0.000159 *** X 84.794 189.530 0.447 0.655643 M1 -56.513 266.836 -0.212 0.832739 M2 -30.591 270.338 -0.113 0.910152 M3 181.618 270.282 0.672 0.503295 M4 312.240 270.085 1.156 0.250642 M5 388.072 278.349 1.394 0.166617 M6 381.063 270.436 1.409 0.162186 M7 -99.295 270.162 -0.368 0.714063 M8 -86.019 270.568 -0.318 0.751267 M9 -25.326 270.154 -0.094 0.925515 M10 246.771 272.238 0.906 0.367063 M11 280.256 270.579 1.036 0.303026 t 19.611 1.939 10.112 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 548.8 on 92 degrees of freedom Multiple R-squared: 0.6405, Adjusted R-squared: 0.5858 F-statistic: 11.71 on 14 and 92 DF, p-value: 5.53e-15 > 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,] 0.02731568 0.05463136 0.97268432 [2,] 0.00778041 0.01556082 0.99221959 [3,] 0.02054294 0.04108589 0.97945706 [4,] 0.01442042 0.02884083 0.98557958 [5,] 0.02014594 0.04029189 0.97985406 [6,] 0.24166446 0.48332893 0.75833554 [7,] 0.18063295 0.36126589 0.81936705 [8,] 0.14984563 0.29969126 0.85015437 [9,] 0.11459179 0.22918359 0.88540821 [10,] 0.09106239 0.18212477 0.90893761 [11,] 0.05865971 0.11731943 0.94134029 [12,] 0.03909994 0.07819988 0.96090006 [13,] 0.02951828 0.05903656 0.97048172 [14,] 0.02139080 0.04278160 0.97860920 [15,] 0.02314147 0.04628293 0.97685853 [16,] 0.01720799 0.03441599 0.98279201 [17,] 0.01644501 0.03289002 0.98355499 [18,] 0.01045831 0.02091662 0.98954169 [19,] 0.07127573 0.14255147 0.92872427 [20,] 0.06095355 0.12190709 0.93904645 [21,] 0.04261461 0.08522923 0.95738539 [22,] 0.03328244 0.06656489 0.96671756 [23,] 0.02251348 0.04502695 0.97748652 [24,] 0.01439669 0.02879339 0.98560331 [25,] 0.14434486 0.28868971 0.85565514 [26,] 0.16411184 0.32822369 0.83588816 [27,] 0.13469557 0.26939115 0.86530443 [28,] 0.10117312 0.20234623 0.89882688 [29,] 0.07558125 0.15116250 0.92441875 [30,] 0.05483141 0.10966283 0.94516859 [31,] 0.05124772 0.10249545 0.94875228 [32,] 0.04587740 0.09175480 0.95412260 [33,] 0.03195850 0.06391700 0.96804150 [34,] 0.02835431 0.05670861 0.97164569 [35,] 0.01989554 0.03979107 0.98010446 [36,] 0.01419935 0.02839870 0.98580065 [37,] 0.03096615 0.06193230 0.96903385 [38,] 0.02211252 0.04422505 0.97788748 [39,] 0.01479217 0.02958433 0.98520783 [40,] 0.01411917 0.02823834 0.98588083 [41,] 0.01203322 0.02406645 0.98796678 [42,] 0.04377052 0.08754104 0.95622948 [43,] 0.03111517 0.06223034 0.96888483 [44,] 0.03066155 0.06132309 0.96933845 [45,] 0.06956164 0.13912327 0.93043836 [46,] 0.07512254 0.15024507 0.92487746 [47,] 0.07469561 0.14939122 0.92530439 [48,] 0.10085226 0.20170452 0.89914774 [49,] 0.09075472 0.18150945 0.90924528 [50,] 0.07488048 0.14976097 0.92511952 [51,] 0.22281739 0.44563478 0.77718261 [52,] 0.19097319 0.38194638 0.80902681 [53,] 0.15462848 0.30925695 0.84537152 [54,] 0.19039026 0.38078053 0.80960974 [55,] 0.34050369 0.68100739 0.65949631 [56,] 0.49214585 0.98429170 0.50785415 [57,] 0.45737265 0.91474531 0.54262735 [58,] 0.39904731 0.79809462 0.60095269 [59,] 0.33735570 0.67471140 0.66264430 [60,] 0.29270761 0.58541521 0.70729239 [61,] 0.62406670 0.75186660 0.37593330 [62,] 0.53892194 0.92215612 0.46107806 [63,] 0.90965334 0.18069333 0.09034666 [64,] 0.86424590 0.27150820 0.13575410 [65,] 0.86278141 0.27443719 0.13721859 [66,] 0.80575625 0.38848749 0.19424375 [67,] 0.71985601 0.56028799 0.28014399 [68,] 0.61350886 0.77298229 0.38649114 [69,] 0.57562173 0.84875654 0.42437827 [70,] 0.45342222 0.90684443 0.54657778 [71,] 0.31704687 0.63409374 0.68295313 [72,] 0.33301829 0.66603658 0.66698171 > postscript(file="/var/www/html/freestat/rcomp/tmp/1mtpd1229539183.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2turv1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/freestat/rcomp/tmp/330ct1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/46gpa1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5gv8l1229539183.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 = 107 Frequency = 1 1 2 3 4 5 6 431.28275 170.42789 295.28101 421.47531 -147.83252 -264.99647 7 8 9 10 11 12 -146.08464 -503.03051 -216.02991 -282.71985 -744.35368 -140.51503 13 14 15 16 17 18 -152.76459 -154.32076 35.66114 -142.50222 -372.65800 -320.59307 19 20 21 22 23 24 -472.86357 -245.52860 -42.92520 205.23823 785.50589 -446.65004 25 26 27 28 29 30 -438.85306 -421.67222 -417.27527 -135.24002 -205.73404 -664.81032 31 32 33 34 35 36 -262.56568 83.00901 128.11512 -545.42276 -187.83472 1020.35458 37 38 39 40 41 42 432.71324 71.87624 410.74720 -16.87775 277.55310 1407.79168 43 44 45 46 47 48 795.28689 -150.19039 223.48283 306.17224 244.76186 -286.48174 49 50 51 52 53 54 656.33309 202.26179 696.13275 348.36117 391.45754 1164.39911 55 56 57 58 59 60 289.95870 172.35264 -274.69330 -265.31885 -938.71296 232.62129 61 62 63 64 65 66 -307.70883 1180.65276 -417.49955 -388.07252 888.54982 -273.64824 67 68 69 70 71 72 -225.84892 -980.21527 445.58131 444.46390 -405.50273 -818.24904 73 74 75 76 77 78 -787.75617 299.64111 -132.36614 49.81574 212.75462 932.44405 79 80 81 82 83 84 142.92298 1565.12374 -93.37294 -293.86428 445.58955 260.42820 85 86 87 88 89 90 44.93181 -783.02688 -114.37236 -22.58768 -16.73804 -1138.11143 91 92 93 94 95 96 233.14406 -186.78939 -604.17514 486.34594 583.01622 178.49179 97 98 99 100 101 102 121.82175 -565.83993 -356.30877 -114.37204 -1027.35249 -842.47531 103 104 105 106 107 -353.94983 245.26877 434.01723 -54.89458 217.53056 > postscript(file="/var/www/html/freestat/rcomp/tmp/62wij1229539183.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 = 107 Frequency = 1 lag(myerror, k = 1) myerror 0 431.28275 NA 1 170.42789 431.28275 2 295.28101 170.42789 3 421.47531 295.28101 4 -147.83252 421.47531 5 -264.99647 -147.83252 6 -146.08464 -264.99647 7 -503.03051 -146.08464 8 -216.02991 -503.03051 9 -282.71985 -216.02991 10 -744.35368 -282.71985 11 -140.51503 -744.35368 12 -152.76459 -140.51503 13 -154.32076 -152.76459 14 35.66114 -154.32076 15 -142.50222 35.66114 16 -372.65800 -142.50222 17 -320.59307 -372.65800 18 -472.86357 -320.59307 19 -245.52860 -472.86357 20 -42.92520 -245.52860 21 205.23823 -42.92520 22 785.50589 205.23823 23 -446.65004 785.50589 24 -438.85306 -446.65004 25 -421.67222 -438.85306 26 -417.27527 -421.67222 27 -135.24002 -417.27527 28 -205.73404 -135.24002 29 -664.81032 -205.73404 30 -262.56568 -664.81032 31 83.00901 -262.56568 32 128.11512 83.00901 33 -545.42276 128.11512 34 -187.83472 -545.42276 35 1020.35458 -187.83472 36 432.71324 1020.35458 37 71.87624 432.71324 38 410.74720 71.87624 39 -16.87775 410.74720 40 277.55310 -16.87775 41 1407.79168 277.55310 42 795.28689 1407.79168 43 -150.19039 795.28689 44 223.48283 -150.19039 45 306.17224 223.48283 46 244.76186 306.17224 47 -286.48174 244.76186 48 656.33309 -286.48174 49 202.26179 656.33309 50 696.13275 202.26179 51 348.36117 696.13275 52 391.45754 348.36117 53 1164.39911 391.45754 54 289.95870 1164.39911 55 172.35264 289.95870 56 -274.69330 172.35264 57 -265.31885 -274.69330 58 -938.71296 -265.31885 59 232.62129 -938.71296 60 -307.70883 232.62129 61 1180.65276 -307.70883 62 -417.49955 1180.65276 63 -388.07252 -417.49955 64 888.54982 -388.07252 65 -273.64824 888.54982 66 -225.84892 -273.64824 67 -980.21527 -225.84892 68 445.58131 -980.21527 69 444.46390 445.58131 70 -405.50273 444.46390 71 -818.24904 -405.50273 72 -787.75617 -818.24904 73 299.64111 -787.75617 74 -132.36614 299.64111 75 49.81574 -132.36614 76 212.75462 49.81574 77 932.44405 212.75462 78 142.92298 932.44405 79 1565.12374 142.92298 80 -93.37294 1565.12374 81 -293.86428 -93.37294 82 445.58955 -293.86428 83 260.42820 445.58955 84 44.93181 260.42820 85 -783.02688 44.93181 86 -114.37236 -783.02688 87 -22.58768 -114.37236 88 -16.73804 -22.58768 89 -1138.11143 -16.73804 90 233.14406 -1138.11143 91 -186.78939 233.14406 92 -604.17514 -186.78939 93 486.34594 -604.17514 94 583.01622 486.34594 95 178.49179 583.01622 96 121.82175 178.49179 97 -565.83993 121.82175 98 -356.30877 -565.83993 99 -114.37204 -356.30877 100 -1027.35249 -114.37204 101 -842.47531 -1027.35249 102 -353.94983 -842.47531 103 245.26877 -353.94983 104 434.01723 245.26877 105 -54.89458 434.01723 106 217.53056 -54.89458 107 NA 217.53056 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 170.42789 431.28275 [2,] 295.28101 170.42789 [3,] 421.47531 295.28101 [4,] -147.83252 421.47531 [5,] -264.99647 -147.83252 [6,] -146.08464 -264.99647 [7,] -503.03051 -146.08464 [8,] -216.02991 -503.03051 [9,] -282.71985 -216.02991 [10,] -744.35368 -282.71985 [11,] -140.51503 -744.35368 [12,] -152.76459 -140.51503 [13,] -154.32076 -152.76459 [14,] 35.66114 -154.32076 [15,] -142.50222 35.66114 [16,] -372.65800 -142.50222 [17,] -320.59307 -372.65800 [18,] -472.86357 -320.59307 [19,] -245.52860 -472.86357 [20,] -42.92520 -245.52860 [21,] 205.23823 -42.92520 [22,] 785.50589 205.23823 [23,] -446.65004 785.50589 [24,] -438.85306 -446.65004 [25,] -421.67222 -438.85306 [26,] -417.27527 -421.67222 [27,] -135.24002 -417.27527 [28,] -205.73404 -135.24002 [29,] -664.81032 -205.73404 [30,] -262.56568 -664.81032 [31,] 83.00901 -262.56568 [32,] 128.11512 83.00901 [33,] -545.42276 128.11512 [34,] -187.83472 -545.42276 [35,] 1020.35458 -187.83472 [36,] 432.71324 1020.35458 [37,] 71.87624 432.71324 [38,] 410.74720 71.87624 [39,] -16.87775 410.74720 [40,] 277.55310 -16.87775 [41,] 1407.79168 277.55310 [42,] 795.28689 1407.79168 [43,] -150.19039 795.28689 [44,] 223.48283 -150.19039 [45,] 306.17224 223.48283 [46,] 244.76186 306.17224 [47,] -286.48174 244.76186 [48,] 656.33309 -286.48174 [49,] 202.26179 656.33309 [50,] 696.13275 202.26179 [51,] 348.36117 696.13275 [52,] 391.45754 348.36117 [53,] 1164.39911 391.45754 [54,] 289.95870 1164.39911 [55,] 172.35264 289.95870 [56,] -274.69330 172.35264 [57,] -265.31885 -274.69330 [58,] -938.71296 -265.31885 [59,] 232.62129 -938.71296 [60,] -307.70883 232.62129 [61,] 1180.65276 -307.70883 [62,] -417.49955 1180.65276 [63,] -388.07252 -417.49955 [64,] 888.54982 -388.07252 [65,] -273.64824 888.54982 [66,] -225.84892 -273.64824 [67,] -980.21527 -225.84892 [68,] 445.58131 -980.21527 [69,] 444.46390 445.58131 [70,] -405.50273 444.46390 [71,] -818.24904 -405.50273 [72,] -787.75617 -818.24904 [73,] 299.64111 -787.75617 [74,] -132.36614 299.64111 [75,] 49.81574 -132.36614 [76,] 212.75462 49.81574 [77,] 932.44405 212.75462 [78,] 142.92298 932.44405 [79,] 1565.12374 142.92298 [80,] -93.37294 1565.12374 [81,] -293.86428 -93.37294 [82,] 445.58955 -293.86428 [83,] 260.42820 445.58955 [84,] 44.93181 260.42820 [85,] -783.02688 44.93181 [86,] -114.37236 -783.02688 [87,] -22.58768 -114.37236 [88,] -16.73804 -22.58768 [89,] -1138.11143 -16.73804 [90,] 233.14406 -1138.11143 [91,] -186.78939 233.14406 [92,] -604.17514 -186.78939 [93,] 486.34594 -604.17514 [94,] 583.01622 486.34594 [95,] 178.49179 583.01622 [96,] 121.82175 178.49179 [97,] -565.83993 121.82175 [98,] -356.30877 -565.83993 [99,] -114.37204 -356.30877 [100,] -1027.35249 -114.37204 [101,] -842.47531 -1027.35249 [102,] -353.94983 -842.47531 [103,] 245.26877 -353.94983 [104,] 434.01723 245.26877 [105,] -54.89458 434.01723 [106,] 217.53056 -54.89458 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 170.42789 431.28275 2 295.28101 170.42789 3 421.47531 295.28101 4 -147.83252 421.47531 5 -264.99647 -147.83252 6 -146.08464 -264.99647 7 -503.03051 -146.08464 8 -216.02991 -503.03051 9 -282.71985 -216.02991 10 -744.35368 -282.71985 11 -140.51503 -744.35368 12 -152.76459 -140.51503 13 -154.32076 -152.76459 14 35.66114 -154.32076 15 -142.50222 35.66114 16 -372.65800 -142.50222 17 -320.59307 -372.65800 18 -472.86357 -320.59307 19 -245.52860 -472.86357 20 -42.92520 -245.52860 21 205.23823 -42.92520 22 785.50589 205.23823 23 -446.65004 785.50589 24 -438.85306 -446.65004 25 -421.67222 -438.85306 26 -417.27527 -421.67222 27 -135.24002 -417.27527 28 -205.73404 -135.24002 29 -664.81032 -205.73404 30 -262.56568 -664.81032 31 83.00901 -262.56568 32 128.11512 83.00901 33 -545.42276 128.11512 34 -187.83472 -545.42276 35 1020.35458 -187.83472 36 432.71324 1020.35458 37 71.87624 432.71324 38 410.74720 71.87624 39 -16.87775 410.74720 40 277.55310 -16.87775 41 1407.79168 277.55310 42 795.28689 1407.79168 43 -150.19039 795.28689 44 223.48283 -150.19039 45 306.17224 223.48283 46 244.76186 306.17224 47 -286.48174 244.76186 48 656.33309 -286.48174 49 202.26179 656.33309 50 696.13275 202.26179 51 348.36117 696.13275 52 391.45754 348.36117 53 1164.39911 391.45754 54 289.95870 1164.39911 55 172.35264 289.95870 56 -274.69330 172.35264 57 -265.31885 -274.69330 58 -938.71296 -265.31885 59 232.62129 -938.71296 60 -307.70883 232.62129 61 1180.65276 -307.70883 62 -417.49955 1180.65276 63 -388.07252 -417.49955 64 888.54982 -388.07252 65 -273.64824 888.54982 66 -225.84892 -273.64824 67 -980.21527 -225.84892 68 445.58131 -980.21527 69 444.46390 445.58131 70 -405.50273 444.46390 71 -818.24904 -405.50273 72 -787.75617 -818.24904 73 299.64111 -787.75617 74 -132.36614 299.64111 75 49.81574 -132.36614 76 212.75462 49.81574 77 932.44405 212.75462 78 142.92298 932.44405 79 1565.12374 142.92298 80 -93.37294 1565.12374 81 -293.86428 -93.37294 82 445.58955 -293.86428 83 260.42820 445.58955 84 44.93181 260.42820 85 -783.02688 44.93181 86 -114.37236 -783.02688 87 -22.58768 -114.37236 88 -16.73804 -22.58768 89 -1138.11143 -16.73804 90 233.14406 -1138.11143 91 -186.78939 233.14406 92 -604.17514 -186.78939 93 486.34594 -604.17514 94 583.01622 486.34594 95 178.49179 583.01622 96 121.82175 178.49179 97 -565.83993 121.82175 98 -356.30877 -565.83993 99 -114.37204 -356.30877 100 -1027.35249 -114.37204 101 -842.47531 -1027.35249 102 -353.94983 -842.47531 103 245.26877 -353.94983 104 434.01723 245.26877 105 -54.89458 434.01723 106 217.53056 -54.89458 > 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/freestat/rcomp/tmp/7vkdq1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8i2yh1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9pmfe1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10ki831229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/11c8dl1229539183.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/freestat/rcomp/tmp/12f6en1229539184.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/freestat/rcomp/tmp/13p4g41229539184.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/freestat/rcomp/tmp/14fc2i1229539184.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/freestat/rcomp/tmp/15zt211229539184.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/freestat/rcomp/tmp/16w85l1229539184.tab") + } > > system("convert tmp/1mtpd1229539183.ps tmp/1mtpd1229539183.png") > system("convert tmp/2turv1229539183.ps tmp/2turv1229539183.png") > system("convert tmp/330ct1229539183.ps tmp/330ct1229539183.png") > system("convert tmp/46gpa1229539183.ps tmp/46gpa1229539183.png") > system("convert tmp/5gv8l1229539183.ps tmp/5gv8l1229539183.png") > system("convert tmp/62wij1229539183.ps tmp/62wij1229539183.png") > system("convert tmp/7vkdq1229539183.ps tmp/7vkdq1229539183.png") > system("convert tmp/8i2yh1229539183.ps tmp/8i2yh1229539183.png") > system("convert tmp/9pmfe1229539183.ps tmp/9pmfe1229539183.png") > system("convert tmp/10ki831229539183.ps tmp/10ki831229539183.png") > > > proc.time() user system elapsed 4.498 2.622 4.868