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Type 'q()' to quit R. > x <- array(list(100.01 + ,0 + ,103.84 + ,0 + ,104.48 + ,0 + ,95.43 + ,0 + ,104.80 + ,0 + ,108.64 + ,0 + ,105.65 + ,0 + ,108.42 + ,0 + ,115.35 + ,0 + ,113.64 + ,0 + ,115.24 + ,0 + ,100.33 + ,0 + ,101.29 + ,0 + ,104.48 + ,0 + ,99.26 + ,0 + ,100.11 + ,0 + ,103.52 + ,0 + ,101.18 + ,0 + ,96.39 + ,0 + ,97.56 + ,0 + ,96.39 + ,0 + ,85.10 + ,0 + ,79.77 + ,0 + ,79.13 + ,0 + ,80.84 + ,0 + ,82.75 + ,0 + ,92.55 + ,0 + ,96.60 + ,0 + ,96.92 + ,0 + ,95.32 + ,0 + ,98.52 + ,0 + ,100.22 + ,0 + ,104.91 + ,0 + ,103.10 + ,0 + ,97.13 + ,0 + ,103.42 + ,0 + ,111.72 + ,0 + ,118.11 + ,0 + ,111.62 + ,0 + ,100.22 + ,0 + ,102.03 + ,0 + ,105.76 + ,0 + ,107.68 + ,0 + ,110.77 + ,0 + ,105.44 + ,0 + ,112.26 + ,0 + ,114.07 + ,0 + ,117.90 + ,0 + ,124.72 + ,0 + ,126.42 + ,0 + ,134.73 + ,0 + ,135.79 + ,0 + ,143.36 + ,0 + ,140.37 + ,0 + ,144.74 + ,0 + ,151.98 + ,0 + ,150.92 + ,0 + ,163.38 + ,0 + ,154.43 + ,0 + ,146.66 + ,0 + ,157.95 + ,0 + ,162.10 + ,0 + ,180.42 + ,0 + ,179.57 + ,0 + ,171.58 + ,0 + ,185.43 + ,0 + ,190.64 + ,0 + ,203.00 + ,0 + ,202.36 + ,0 + ,193.41 + ,0 + ,186.17 + ,0 + ,192.24 + ,0 + ,209.60 + ,0 + ,206.41 + ,0 + ,209.82 + ,0 + ,230.37 + ,0 + ,235.80 + ,0 + ,232.07 + ,0 + ,244.64 + ,0 + ,242.19 + ,0 + ,217.48 + ,0 + ,209.39 + ,0 + ,211.73 + ,0 + ,221.00 + ,0 + ,203.11 + ,0 + ,214.71 + ,0 + ,224.19 + ,0 + ,238.04 + ,0 + ,238.36 + ,0 + ,246.24 + ,0 + ,259.87 + ,0 + ,249.97 + ,0 + ,266.48 + ,0 + ,282.98 + ,0 + ,306.31 + ,0 + ,301.73 + ,1 + ,314.62 + ,1 + ,332.62 + ,1 + ,355.51 + ,1 + ,370.32 + ,1 + ,408.13 + ,1 + ,433.58 + ,1 + ,440.51 + ,1 + ,386.29 + ,1 + ,342.84 + ,1 + ,254.97 + ,1 + ,203.42 + ,1 + ,170.09 + ,1 + ,174.03 + ,1 + ,167.85 + ,1 + ,177.01 + ,1 + ,188.19 + ,1 + ,211.20 + ,1 + ,240.91 + ,1 + ,230.26 + ,1 + ,251.25 + ,1 + ,241.66 + ,1) + ,dim=c(2 + ,117) + ,dimnames=list(c('Y' + ,'X') + ,1:117)) > y <- array(NA,dim=c(2,117),dimnames=list(c('Y','X'),1:117)) > 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 100.01 0 1 0 0 0 0 0 0 0 0 0 0 1 2 103.84 0 0 1 0 0 0 0 0 0 0 0 0 2 3 104.48 0 0 0 1 0 0 0 0 0 0 0 0 3 4 95.43 0 0 0 0 1 0 0 0 0 0 0 0 4 5 104.80 0 0 0 0 0 1 0 0 0 0 0 0 5 6 108.64 0 0 0 0 0 0 1 0 0 0 0 0 6 7 105.65 0 0 0 0 0 0 0 1 0 0 0 0 7 8 108.42 0 0 0 0 0 0 0 0 1 0 0 0 8 9 115.35 0 0 0 0 0 0 0 0 0 1 0 0 9 10 113.64 0 0 0 0 0 0 0 0 0 0 1 0 10 11 115.24 0 0 0 0 0 0 0 0 0 0 0 1 11 12 100.33 0 0 0 0 0 0 0 0 0 0 0 0 12 13 101.29 0 1 0 0 0 0 0 0 0 0 0 0 13 14 104.48 0 0 1 0 0 0 0 0 0 0 0 0 14 15 99.26 0 0 0 1 0 0 0 0 0 0 0 0 15 16 100.11 0 0 0 0 1 0 0 0 0 0 0 0 16 17 103.52 0 0 0 0 0 1 0 0 0 0 0 0 17 18 101.18 0 0 0 0 0 0 1 0 0 0 0 0 18 19 96.39 0 0 0 0 0 0 0 1 0 0 0 0 19 20 97.56 0 0 0 0 0 0 0 0 1 0 0 0 20 21 96.39 0 0 0 0 0 0 0 0 0 1 0 0 21 22 85.10 0 0 0 0 0 0 0 0 0 0 1 0 22 23 79.77 0 0 0 0 0 0 0 0 0 0 0 1 23 24 79.13 0 0 0 0 0 0 0 0 0 0 0 0 24 25 80.84 0 1 0 0 0 0 0 0 0 0 0 0 25 26 82.75 0 0 1 0 0 0 0 0 0 0 0 0 26 27 92.55 0 0 0 1 0 0 0 0 0 0 0 0 27 28 96.60 0 0 0 0 1 0 0 0 0 0 0 0 28 29 96.92 0 0 0 0 0 1 0 0 0 0 0 0 29 30 95.32 0 0 0 0 0 0 1 0 0 0 0 0 30 31 98.52 0 0 0 0 0 0 0 1 0 0 0 0 31 32 100.22 0 0 0 0 0 0 0 0 1 0 0 0 32 33 104.91 0 0 0 0 0 0 0 0 0 1 0 0 33 34 103.10 0 0 0 0 0 0 0 0 0 0 1 0 34 35 97.13 0 0 0 0 0 0 0 0 0 0 0 1 35 36 103.42 0 0 0 0 0 0 0 0 0 0 0 0 36 37 111.72 0 1 0 0 0 0 0 0 0 0 0 0 37 38 118.11 0 0 1 0 0 0 0 0 0 0 0 0 38 39 111.62 0 0 0 1 0 0 0 0 0 0 0 0 39 40 100.22 0 0 0 0 1 0 0 0 0 0 0 0 40 41 102.03 0 0 0 0 0 1 0 0 0 0 0 0 41 42 105.76 0 0 0 0 0 0 1 0 0 0 0 0 42 43 107.68 0 0 0 0 0 0 0 1 0 0 0 0 43 44 110.77 0 0 0 0 0 0 0 0 1 0 0 0 44 45 105.44 0 0 0 0 0 0 0 0 0 1 0 0 45 46 112.26 0 0 0 0 0 0 0 0 0 0 1 0 46 47 114.07 0 0 0 0 0 0 0 0 0 0 0 1 47 48 117.90 0 0 0 0 0 0 0 0 0 0 0 0 48 49 124.72 0 1 0 0 0 0 0 0 0 0 0 0 49 50 126.42 0 0 1 0 0 0 0 0 0 0 0 0 50 51 134.73 0 0 0 1 0 0 0 0 0 0 0 0 51 52 135.79 0 0 0 0 1 0 0 0 0 0 0 0 52 53 143.36 0 0 0 0 0 1 0 0 0 0 0 0 53 54 140.37 0 0 0 0 0 0 1 0 0 0 0 0 54 55 144.74 0 0 0 0 0 0 0 1 0 0 0 0 55 56 151.98 0 0 0 0 0 0 0 0 1 0 0 0 56 57 150.92 0 0 0 0 0 0 0 0 0 1 0 0 57 58 163.38 0 0 0 0 0 0 0 0 0 0 1 0 58 59 154.43 0 0 0 0 0 0 0 0 0 0 0 1 59 60 146.66 0 0 0 0 0 0 0 0 0 0 0 0 60 61 157.95 0 1 0 0 0 0 0 0 0 0 0 0 61 62 162.10 0 0 1 0 0 0 0 0 0 0 0 0 62 63 180.42 0 0 0 1 0 0 0 0 0 0 0 0 63 64 179.57 0 0 0 0 1 0 0 0 0 0 0 0 64 65 171.58 0 0 0 0 0 1 0 0 0 0 0 0 65 66 185.43 0 0 0 0 0 0 1 0 0 0 0 0 66 67 190.64 0 0 0 0 0 0 0 1 0 0 0 0 67 68 203.00 0 0 0 0 0 0 0 0 1 0 0 0 68 69 202.36 0 0 0 0 0 0 0 0 0 1 0 0 69 70 193.41 0 0 0 0 0 0 0 0 0 0 1 0 70 71 186.17 0 0 0 0 0 0 0 0 0 0 0 1 71 72 192.24 0 0 0 0 0 0 0 0 0 0 0 0 72 73 209.60 0 1 0 0 0 0 0 0 0 0 0 0 73 74 206.41 0 0 1 0 0 0 0 0 0 0 0 0 74 75 209.82 0 0 0 1 0 0 0 0 0 0 0 0 75 76 230.37 0 0 0 0 1 0 0 0 0 0 0 0 76 77 235.80 0 0 0 0 0 1 0 0 0 0 0 0 77 78 232.07 0 0 0 0 0 0 1 0 0 0 0 0 78 79 244.64 0 0 0 0 0 0 0 1 0 0 0 0 79 80 242.19 0 0 0 0 0 0 0 0 1 0 0 0 80 81 217.48 0 0 0 0 0 0 0 0 0 1 0 0 81 82 209.39 0 0 0 0 0 0 0 0 0 0 1 0 82 83 211.73 0 0 0 0 0 0 0 0 0 0 0 1 83 84 221.00 0 0 0 0 0 0 0 0 0 0 0 0 84 85 203.11 0 1 0 0 0 0 0 0 0 0 0 0 85 86 214.71 0 0 1 0 0 0 0 0 0 0 0 0 86 87 224.19 0 0 0 1 0 0 0 0 0 0 0 0 87 88 238.04 0 0 0 0 1 0 0 0 0 0 0 0 88 89 238.36 0 0 0 0 0 1 0 0 0 0 0 0 89 90 246.24 0 0 0 0 0 0 1 0 0 0 0 0 90 91 259.87 0 0 0 0 0 0 0 1 0 0 0 0 91 92 249.97 0 0 0 0 0 0 0 0 1 0 0 0 92 93 266.48 0 0 0 0 0 0 0 0 0 1 0 0 93 94 282.98 0 0 0 0 0 0 0 0 0 0 1 0 94 95 306.31 0 0 0 0 0 0 0 0 0 0 0 1 95 96 301.73 1 0 0 0 0 0 0 0 0 0 0 0 96 97 314.62 1 1 0 0 0 0 0 0 0 0 0 0 97 98 332.62 1 0 1 0 0 0 0 0 0 0 0 0 98 99 355.51 1 0 0 1 0 0 0 0 0 0 0 0 99 100 370.32 1 0 0 0 1 0 0 0 0 0 0 0 100 101 408.13 1 0 0 0 0 1 0 0 0 0 0 0 101 102 433.58 1 0 0 0 0 0 1 0 0 0 0 0 102 103 440.51 1 0 0 0 0 0 0 1 0 0 0 0 103 104 386.29 1 0 0 0 0 0 0 0 1 0 0 0 104 105 342.84 1 0 0 0 0 0 0 0 0 1 0 0 105 106 254.97 1 0 0 0 0 0 0 0 0 0 1 0 106 107 203.42 1 0 0 0 0 0 0 0 0 0 0 1 107 108 170.09 1 0 0 0 0 0 0 0 0 0 0 0 108 109 174.03 1 1 0 0 0 0 0 0 0 0 0 0 109 110 167.85 1 0 1 0 0 0 0 0 0 0 0 0 110 111 177.01 1 0 0 1 0 0 0 0 0 0 0 0 111 112 188.19 1 0 0 0 1 0 0 0 0 0 0 0 112 113 211.20 1 0 0 0 0 1 0 0 0 0 0 0 113 114 240.91 1 0 0 0 0 0 1 0 0 0 0 0 114 115 230.26 1 0 0 0 0 0 0 1 0 0 0 0 115 116 251.25 1 0 0 0 0 0 0 0 1 0 0 0 116 117 241.66 1 0 0 0 0 0 0 0 0 1 0 0 117 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X M1 M2 M3 M4 47.471 29.216 8.039 10.425 15.702 18.453 M5 M6 M7 M8 M9 M10 24.806 30.433 31.619 28.141 20.605 16.279 M11 t 8.974 1.753 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -112.134 -21.028 -4.506 22.036 151.605 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 47.4711 18.7093 2.537 0.0127 * X 29.2156 15.9316 1.834 0.0696 . M1 8.0385 22.6075 0.356 0.7229 M2 10.4251 22.6027 0.461 0.6456 M3 15.7017 22.5994 0.695 0.4888 M4 18.4533 22.5976 0.817 0.4160 M5 24.8060 22.5973 1.098 0.2749 M6 30.4326 22.5985 1.347 0.1810 M7 31.6192 22.6013 1.399 0.1648 M8 28.1408 22.6055 1.245 0.2160 M9 20.6054 22.6112 0.911 0.3643 M10 16.2785 23.2341 0.701 0.4851 M11 8.9740 23.2415 0.386 0.7002 t 1.7534 0.1841 9.525 8.4e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 49.18 on 103 degrees of freedom Multiple R-squared: 0.6874, Adjusted R-squared: 0.648 F-statistic: 17.42 on 13 and 103 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 2.744357e-04 5.488715e-04 0.9997256 [2,] 4.563515e-05 9.127031e-05 0.9999544 [3,] 7.972513e-06 1.594503e-05 0.9999920 [4,] 1.466278e-06 2.932557e-06 0.9999985 [5,] 1.158950e-06 2.317899e-06 0.9999988 [6,] 2.233958e-06 4.467917e-06 0.9999978 [7,] 3.625753e-06 7.251506e-06 0.9999964 [8,] 8.350713e-07 1.670143e-06 0.9999992 [9,] 1.410069e-07 2.820138e-07 0.9999999 [10,] 2.347306e-08 4.694612e-08 1.0000000 [11,] 4.692349e-09 9.384698e-09 1.0000000 [12,] 1.781668e-09 3.563335e-09 1.0000000 [13,] 3.357165e-10 6.714330e-10 1.0000000 [14,] 5.392531e-11 1.078506e-10 1.0000000 [15,] 1.315154e-11 2.630308e-11 1.0000000 [16,] 2.856120e-12 5.712240e-12 1.0000000 [17,] 6.712242e-13 1.342448e-12 1.0000000 [18,] 2.383382e-13 4.766764e-13 1.0000000 [19,] 4.994730e-14 9.989461e-14 1.0000000 [20,] 5.813901e-14 1.162780e-13 1.0000000 [21,] 1.450867e-13 2.901733e-13 1.0000000 [22,] 2.662585e-13 5.325171e-13 1.0000000 [23,] 1.076647e-13 2.153294e-13 1.0000000 [24,] 2.183394e-14 4.366789e-14 1.0000000 [25,] 4.174738e-15 8.349476e-15 1.0000000 [26,] 8.951583e-16 1.790317e-15 1.0000000 [27,] 2.261422e-16 4.522844e-16 1.0000000 [28,] 5.783939e-17 1.156788e-16 1.0000000 [29,] 1.080889e-17 2.161778e-17 1.0000000 [30,] 3.101455e-18 6.202911e-18 1.0000000 [31,] 1.280538e-18 2.561076e-18 1.0000000 [32,] 1.022298e-18 2.044597e-18 1.0000000 [33,] 9.038353e-19 1.807671e-18 1.0000000 [34,] 4.735543e-19 9.471085e-19 1.0000000 [35,] 5.902846e-19 1.180569e-18 1.0000000 [36,] 1.063091e-18 2.126182e-18 1.0000000 [37,] 2.225826e-18 4.451651e-18 1.0000000 [38,] 2.514531e-18 5.029061e-18 1.0000000 [39,] 4.325446e-18 8.650892e-18 1.0000000 [40,] 9.346773e-18 1.869355e-17 1.0000000 [41,] 1.160293e-17 2.320585e-17 1.0000000 [42,] 4.704554e-17 9.409109e-17 1.0000000 [43,] 6.470880e-17 1.294176e-16 1.0000000 [44,] 4.257624e-17 8.515248e-17 1.0000000 [45,] 3.194987e-17 6.389973e-17 1.0000000 [46,] 2.265023e-17 4.530047e-17 1.0000000 [47,] 5.493682e-17 1.098736e-16 1.0000000 [48,] 1.341980e-16 2.683961e-16 1.0000000 [49,] 1.602018e-16 3.204037e-16 1.0000000 [50,] 5.425077e-16 1.085015e-15 1.0000000 [51,] 2.863242e-15 5.726484e-15 1.0000000 [52,] 1.944593e-14 3.889186e-14 1.0000000 [53,] 8.501814e-14 1.700363e-13 1.0000000 [54,] 1.844913e-13 3.689826e-13 1.0000000 [55,] 4.239924e-13 8.479849e-13 1.0000000 [56,] 4.669267e-13 9.338533e-13 1.0000000 [57,] 5.659147e-13 1.131829e-12 1.0000000 [58,] 4.937194e-13 9.874388e-13 1.0000000 [59,] 4.746228e-13 9.492455e-13 1.0000000 [60,] 1.307829e-12 2.615659e-12 1.0000000 [61,] 5.083102e-12 1.016620e-11 1.0000000 [62,] 3.202474e-11 6.404947e-11 1.0000000 [63,] 3.818774e-10 7.637548e-10 1.0000000 [64,] 3.593996e-09 7.187992e-09 1.0000000 [65,] 1.036759e-07 2.073518e-07 0.9999999 [66,] 1.504801e-06 3.009602e-06 0.9999985 [67,] 2.893832e-05 5.787664e-05 0.9999711 [68,] 1.788520e-05 3.577039e-05 0.9999821 [69,] 8.990019e-06 1.798004e-05 0.9999910 [70,] 4.251328e-06 8.502655e-06 0.9999957 [71,] 2.102419e-06 4.204838e-06 0.9999979 [72,] 1.163022e-06 2.326044e-06 0.9999988 [73,] 1.226192e-06 2.452384e-06 0.9999988 [74,] 5.395907e-06 1.079181e-05 0.9999946 [75,] 4.422587e-05 8.845174e-05 0.9999558 [76,] 2.120177e-03 4.240353e-03 0.9978798 [77,] 2.983137e-01 5.966274e-01 0.7016863 [78,] 4.290103e-01 8.580207e-01 0.5709897 [79,] 4.101784e-01 8.203568e-01 0.5898216 [80,] 3.804112e-01 7.608224e-01 0.6195888 [81,] 3.249482e-01 6.498964e-01 0.6750518 [82,] 2.240348e-01 4.480695e-01 0.7759652 [83,] 1.423876e-01 2.847752e-01 0.8576124 [84,] 8.261620e-02 1.652324e-01 0.9173838 > postscript(file="/var/www/html/rcomp/tmp/1x4mb1258726645.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2pkij1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3kjiy1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/45gh91258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5xmio1258726645.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 = 117 Frequency = 1 1 2 3 4 5 6 42.746989 42.436989 36.046989 22.491989 23.755989 20.215989 7 8 9 10 11 12 14.285989 18.780989 31.492989 32.356506 39.507617 31.818239 13 14 15 16 17 18 22.986351 22.036351 9.786351 6.131351 1.435351 -8.284649 19 20 21 22 23 24 -16.014649 -13.119649 -8.507649 -17.224132 -17.003020 -10.422399 25 26 27 28 29 30 -18.504287 -20.734287 -17.964287 -18.419287 -26.205287 -35.185287 31 32 33 34 35 36 -34.925287 -31.500287 -21.028287 -20.264769 -20.683658 -7.173037 37 38 39 40 41 42 -8.664925 -6.414925 -19.934925 -35.839925 -42.135925 -45.785925 43 44 45 46 47 48 -46.805925 -41.990925 -41.538925 -32.145407 -24.784296 -13.733675 49 50 51 52 53 54 -16.705563 -19.145563 -17.865563 -21.310563 -21.846563 -32.216563 55 56 57 58 59 60 -30.786563 -21.821563 -17.099563 -2.066045 -5.464934 -6.014313 61 62 63 64 65 66 -4.516201 -4.506201 6.783799 1.428799 -14.667201 -8.197201 67 68 69 70 71 72 -5.927201 8.157799 13.299799 6.923317 5.234428 18.525049 73 74 75 76 77 78 26.093162 18.763162 15.143162 31.188162 28.512162 17.402162 79 80 81 82 83 84 27.032162 26.307162 7.379162 1.862679 9.753790 26.244411 85 86 87 88 89 90 -1.437476 6.022524 8.472524 17.817524 10.031524 10.531524 91 92 93 94 95 96 21.221524 13.046524 35.338524 54.412041 83.293152 56.718181 97 98 99 100 101 102 59.816294 73.676294 89.536294 99.841294 129.545294 147.615294 103 104 105 106 107 108 151.605294 99.110294 61.442294 -23.854189 -69.853078 -95.962457 109 110 111 112 113 114 -101.814344 -112.134344 -110.004344 -103.329344 -88.425344 -66.095344 115 116 117 -79.685344 -56.970344 -60.778344 > postscript(file="/var/www/html/rcomp/tmp/6ubd31258726645.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 = 117 Frequency = 1 lag(myerror, k = 1) myerror 0 42.746989 NA 1 42.436989 42.746989 2 36.046989 42.436989 3 22.491989 36.046989 4 23.755989 22.491989 5 20.215989 23.755989 6 14.285989 20.215989 7 18.780989 14.285989 8 31.492989 18.780989 9 32.356506 31.492989 10 39.507617 32.356506 11 31.818239 39.507617 12 22.986351 31.818239 13 22.036351 22.986351 14 9.786351 22.036351 15 6.131351 9.786351 16 1.435351 6.131351 17 -8.284649 1.435351 18 -16.014649 -8.284649 19 -13.119649 -16.014649 20 -8.507649 -13.119649 21 -17.224132 -8.507649 22 -17.003020 -17.224132 23 -10.422399 -17.003020 24 -18.504287 -10.422399 25 -20.734287 -18.504287 26 -17.964287 -20.734287 27 -18.419287 -17.964287 28 -26.205287 -18.419287 29 -35.185287 -26.205287 30 -34.925287 -35.185287 31 -31.500287 -34.925287 32 -21.028287 -31.500287 33 -20.264769 -21.028287 34 -20.683658 -20.264769 35 -7.173037 -20.683658 36 -8.664925 -7.173037 37 -6.414925 -8.664925 38 -19.934925 -6.414925 39 -35.839925 -19.934925 40 -42.135925 -35.839925 41 -45.785925 -42.135925 42 -46.805925 -45.785925 43 -41.990925 -46.805925 44 -41.538925 -41.990925 45 -32.145407 -41.538925 46 -24.784296 -32.145407 47 -13.733675 -24.784296 48 -16.705563 -13.733675 49 -19.145563 -16.705563 50 -17.865563 -19.145563 51 -21.310563 -17.865563 52 -21.846563 -21.310563 53 -32.216563 -21.846563 54 -30.786563 -32.216563 55 -21.821563 -30.786563 56 -17.099563 -21.821563 57 -2.066045 -17.099563 58 -5.464934 -2.066045 59 -6.014313 -5.464934 60 -4.516201 -6.014313 61 -4.506201 -4.516201 62 6.783799 -4.506201 63 1.428799 6.783799 64 -14.667201 1.428799 65 -8.197201 -14.667201 66 -5.927201 -8.197201 67 8.157799 -5.927201 68 13.299799 8.157799 69 6.923317 13.299799 70 5.234428 6.923317 71 18.525049 5.234428 72 26.093162 18.525049 73 18.763162 26.093162 74 15.143162 18.763162 75 31.188162 15.143162 76 28.512162 31.188162 77 17.402162 28.512162 78 27.032162 17.402162 79 26.307162 27.032162 80 7.379162 26.307162 81 1.862679 7.379162 82 9.753790 1.862679 83 26.244411 9.753790 84 -1.437476 26.244411 85 6.022524 -1.437476 86 8.472524 6.022524 87 17.817524 8.472524 88 10.031524 17.817524 89 10.531524 10.031524 90 21.221524 10.531524 91 13.046524 21.221524 92 35.338524 13.046524 93 54.412041 35.338524 94 83.293152 54.412041 95 56.718181 83.293152 96 59.816294 56.718181 97 73.676294 59.816294 98 89.536294 73.676294 99 99.841294 89.536294 100 129.545294 99.841294 101 147.615294 129.545294 102 151.605294 147.615294 103 99.110294 151.605294 104 61.442294 99.110294 105 -23.854189 61.442294 106 -69.853078 -23.854189 107 -95.962457 -69.853078 108 -101.814344 -95.962457 109 -112.134344 -101.814344 110 -110.004344 -112.134344 111 -103.329344 -110.004344 112 -88.425344 -103.329344 113 -66.095344 -88.425344 114 -79.685344 -66.095344 115 -56.970344 -79.685344 116 -60.778344 -56.970344 117 NA -60.778344 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 42.436989 42.746989 [2,] 36.046989 42.436989 [3,] 22.491989 36.046989 [4,] 23.755989 22.491989 [5,] 20.215989 23.755989 [6,] 14.285989 20.215989 [7,] 18.780989 14.285989 [8,] 31.492989 18.780989 [9,] 32.356506 31.492989 [10,] 39.507617 32.356506 [11,] 31.818239 39.507617 [12,] 22.986351 31.818239 [13,] 22.036351 22.986351 [14,] 9.786351 22.036351 [15,] 6.131351 9.786351 [16,] 1.435351 6.131351 [17,] -8.284649 1.435351 [18,] -16.014649 -8.284649 [19,] -13.119649 -16.014649 [20,] -8.507649 -13.119649 [21,] -17.224132 -8.507649 [22,] -17.003020 -17.224132 [23,] -10.422399 -17.003020 [24,] -18.504287 -10.422399 [25,] -20.734287 -18.504287 [26,] -17.964287 -20.734287 [27,] -18.419287 -17.964287 [28,] -26.205287 -18.419287 [29,] -35.185287 -26.205287 [30,] -34.925287 -35.185287 [31,] -31.500287 -34.925287 [32,] -21.028287 -31.500287 [33,] -20.264769 -21.028287 [34,] -20.683658 -20.264769 [35,] -7.173037 -20.683658 [36,] -8.664925 -7.173037 [37,] -6.414925 -8.664925 [38,] -19.934925 -6.414925 [39,] -35.839925 -19.934925 [40,] -42.135925 -35.839925 [41,] -45.785925 -42.135925 [42,] -46.805925 -45.785925 [43,] -41.990925 -46.805925 [44,] -41.538925 -41.990925 [45,] -32.145407 -41.538925 [46,] -24.784296 -32.145407 [47,] -13.733675 -24.784296 [48,] -16.705563 -13.733675 [49,] -19.145563 -16.705563 [50,] -17.865563 -19.145563 [51,] -21.310563 -17.865563 [52,] -21.846563 -21.310563 [53,] -32.216563 -21.846563 [54,] -30.786563 -32.216563 [55,] -21.821563 -30.786563 [56,] -17.099563 -21.821563 [57,] -2.066045 -17.099563 [58,] -5.464934 -2.066045 [59,] -6.014313 -5.464934 [60,] -4.516201 -6.014313 [61,] -4.506201 -4.516201 [62,] 6.783799 -4.506201 [63,] 1.428799 6.783799 [64,] -14.667201 1.428799 [65,] -8.197201 -14.667201 [66,] -5.927201 -8.197201 [67,] 8.157799 -5.927201 [68,] 13.299799 8.157799 [69,] 6.923317 13.299799 [70,] 5.234428 6.923317 [71,] 18.525049 5.234428 [72,] 26.093162 18.525049 [73,] 18.763162 26.093162 [74,] 15.143162 18.763162 [75,] 31.188162 15.143162 [76,] 28.512162 31.188162 [77,] 17.402162 28.512162 [78,] 27.032162 17.402162 [79,] 26.307162 27.032162 [80,] 7.379162 26.307162 [81,] 1.862679 7.379162 [82,] 9.753790 1.862679 [83,] 26.244411 9.753790 [84,] -1.437476 26.244411 [85,] 6.022524 -1.437476 [86,] 8.472524 6.022524 [87,] 17.817524 8.472524 [88,] 10.031524 17.817524 [89,] 10.531524 10.031524 [90,] 21.221524 10.531524 [91,] 13.046524 21.221524 [92,] 35.338524 13.046524 [93,] 54.412041 35.338524 [94,] 83.293152 54.412041 [95,] 56.718181 83.293152 [96,] 59.816294 56.718181 [97,] 73.676294 59.816294 [98,] 89.536294 73.676294 [99,] 99.841294 89.536294 [100,] 129.545294 99.841294 [101,] 147.615294 129.545294 [102,] 151.605294 147.615294 [103,] 99.110294 151.605294 [104,] 61.442294 99.110294 [105,] -23.854189 61.442294 [106,] -69.853078 -23.854189 [107,] -95.962457 -69.853078 [108,] -101.814344 -95.962457 [109,] -112.134344 -101.814344 [110,] -110.004344 -112.134344 [111,] -103.329344 -110.004344 [112,] -88.425344 -103.329344 [113,] -66.095344 -88.425344 [114,] -79.685344 -66.095344 [115,] -56.970344 -79.685344 [116,] -60.778344 -56.970344 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 42.436989 42.746989 2 36.046989 42.436989 3 22.491989 36.046989 4 23.755989 22.491989 5 20.215989 23.755989 6 14.285989 20.215989 7 18.780989 14.285989 8 31.492989 18.780989 9 32.356506 31.492989 10 39.507617 32.356506 11 31.818239 39.507617 12 22.986351 31.818239 13 22.036351 22.986351 14 9.786351 22.036351 15 6.131351 9.786351 16 1.435351 6.131351 17 -8.284649 1.435351 18 -16.014649 -8.284649 19 -13.119649 -16.014649 20 -8.507649 -13.119649 21 -17.224132 -8.507649 22 -17.003020 -17.224132 23 -10.422399 -17.003020 24 -18.504287 -10.422399 25 -20.734287 -18.504287 26 -17.964287 -20.734287 27 -18.419287 -17.964287 28 -26.205287 -18.419287 29 -35.185287 -26.205287 30 -34.925287 -35.185287 31 -31.500287 -34.925287 32 -21.028287 -31.500287 33 -20.264769 -21.028287 34 -20.683658 -20.264769 35 -7.173037 -20.683658 36 -8.664925 -7.173037 37 -6.414925 -8.664925 38 -19.934925 -6.414925 39 -35.839925 -19.934925 40 -42.135925 -35.839925 41 -45.785925 -42.135925 42 -46.805925 -45.785925 43 -41.990925 -46.805925 44 -41.538925 -41.990925 45 -32.145407 -41.538925 46 -24.784296 -32.145407 47 -13.733675 -24.784296 48 -16.705563 -13.733675 49 -19.145563 -16.705563 50 -17.865563 -19.145563 51 -21.310563 -17.865563 52 -21.846563 -21.310563 53 -32.216563 -21.846563 54 -30.786563 -32.216563 55 -21.821563 -30.786563 56 -17.099563 -21.821563 57 -2.066045 -17.099563 58 -5.464934 -2.066045 59 -6.014313 -5.464934 60 -4.516201 -6.014313 61 -4.506201 -4.516201 62 6.783799 -4.506201 63 1.428799 6.783799 64 -14.667201 1.428799 65 -8.197201 -14.667201 66 -5.927201 -8.197201 67 8.157799 -5.927201 68 13.299799 8.157799 69 6.923317 13.299799 70 5.234428 6.923317 71 18.525049 5.234428 72 26.093162 18.525049 73 18.763162 26.093162 74 15.143162 18.763162 75 31.188162 15.143162 76 28.512162 31.188162 77 17.402162 28.512162 78 27.032162 17.402162 79 26.307162 27.032162 80 7.379162 26.307162 81 1.862679 7.379162 82 9.753790 1.862679 83 26.244411 9.753790 84 -1.437476 26.244411 85 6.022524 -1.437476 86 8.472524 6.022524 87 17.817524 8.472524 88 10.031524 17.817524 89 10.531524 10.031524 90 21.221524 10.531524 91 13.046524 21.221524 92 35.338524 13.046524 93 54.412041 35.338524 94 83.293152 54.412041 95 56.718181 83.293152 96 59.816294 56.718181 97 73.676294 59.816294 98 89.536294 73.676294 99 99.841294 89.536294 100 129.545294 99.841294 101 147.615294 129.545294 102 151.605294 147.615294 103 99.110294 151.605294 104 61.442294 99.110294 105 -23.854189 61.442294 106 -69.853078 -23.854189 107 -95.962457 -69.853078 108 -101.814344 -95.962457 109 -112.134344 -101.814344 110 -110.004344 -112.134344 111 -103.329344 -110.004344 112 -88.425344 -103.329344 113 -66.095344 -88.425344 114 -79.685344 -66.095344 115 -56.970344 -79.685344 116 -60.778344 -56.970344 > 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/7tmyn1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/85g7d1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9ms9i1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10kcrt1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11mzrs1258726645.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/1200at1258726645.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/13oe241258726645.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/14aazo1258726645.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/15nar81258726645.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/16yuwk1258726645.tab") + } > system("convert tmp/1x4mb1258726645.ps tmp/1x4mb1258726645.png") > system("convert tmp/2pkij1258726645.ps tmp/2pkij1258726645.png") > system("convert tmp/3kjiy1258726645.ps tmp/3kjiy1258726645.png") > system("convert tmp/45gh91258726645.ps tmp/45gh91258726645.png") > system("convert tmp/5xmio1258726645.ps tmp/5xmio1258726645.png") > system("convert tmp/6ubd31258726645.ps tmp/6ubd31258726645.png") > system("convert tmp/7tmyn1258726645.ps tmp/7tmyn1258726645.png") > system("convert tmp/85g7d1258726645.ps tmp/85g7d1258726645.png") > system("convert tmp/9ms9i1258726645.ps tmp/9ms9i1258726645.png") > system("convert tmp/10kcrt1258726645.ps tmp/10kcrt1258726645.png") > > > proc.time() user system elapsed 3.307 1.637 4.399