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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 = 'No 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 1 100.01 0 1 0 0 0 0 0 0 0 0 0 0 2 103.84 0 0 1 0 0 0 0 0 0 0 0 0 3 104.48 0 0 0 1 0 0 0 0 0 0 0 0 4 95.43 0 0 0 0 1 0 0 0 0 0 0 0 5 104.80 0 0 0 0 0 1 0 0 0 0 0 0 6 108.64 0 0 0 0 0 0 1 0 0 0 0 0 7 105.65 0 0 0 0 0 0 0 1 0 0 0 0 8 108.42 0 0 0 0 0 0 0 0 1 0 0 0 9 115.35 0 0 0 0 0 0 0 0 0 1 0 0 10 113.64 0 0 0 0 0 0 0 0 0 0 1 0 11 115.24 0 0 0 0 0 0 0 0 0 0 0 1 12 100.33 0 0 0 0 0 0 0 0 0 0 0 0 13 101.29 0 1 0 0 0 0 0 0 0 0 0 0 14 104.48 0 0 1 0 0 0 0 0 0 0 0 0 15 99.26 0 0 0 1 0 0 0 0 0 0 0 0 16 100.11 0 0 0 0 1 0 0 0 0 0 0 0 17 103.52 0 0 0 0 0 1 0 0 0 0 0 0 18 101.18 0 0 0 0 0 0 1 0 0 0 0 0 19 96.39 0 0 0 0 0 0 0 1 0 0 0 0 20 97.56 0 0 0 0 0 0 0 0 1 0 0 0 21 96.39 0 0 0 0 0 0 0 0 0 1 0 0 22 85.10 0 0 0 0 0 0 0 0 0 0 1 0 23 79.77 0 0 0 0 0 0 0 0 0 0 0 1 24 79.13 0 0 0 0 0 0 0 0 0 0 0 0 25 80.84 0 1 0 0 0 0 0 0 0 0 0 0 26 82.75 0 0 1 0 0 0 0 0 0 0 0 0 27 92.55 0 0 0 1 0 0 0 0 0 0 0 0 28 96.60 0 0 0 0 1 0 0 0 0 0 0 0 29 96.92 0 0 0 0 0 1 0 0 0 0 0 0 30 95.32 0 0 0 0 0 0 1 0 0 0 0 0 31 98.52 0 0 0 0 0 0 0 1 0 0 0 0 32 100.22 0 0 0 0 0 0 0 0 1 0 0 0 33 104.91 0 0 0 0 0 0 0 0 0 1 0 0 34 103.10 0 0 0 0 0 0 0 0 0 0 1 0 35 97.13 0 0 0 0 0 0 0 0 0 0 0 1 36 103.42 0 0 0 0 0 0 0 0 0 0 0 0 37 111.72 0 1 0 0 0 0 0 0 0 0 0 0 38 118.11 0 0 1 0 0 0 0 0 0 0 0 0 39 111.62 0 0 0 1 0 0 0 0 0 0 0 0 40 100.22 0 0 0 0 1 0 0 0 0 0 0 0 41 102.03 0 0 0 0 0 1 0 0 0 0 0 0 42 105.76 0 0 0 0 0 0 1 0 0 0 0 0 43 107.68 0 0 0 0 0 0 0 1 0 0 0 0 44 110.77 0 0 0 0 0 0 0 0 1 0 0 0 45 105.44 0 0 0 0 0 0 0 0 0 1 0 0 46 112.26 0 0 0 0 0 0 0 0 0 0 1 0 47 114.07 0 0 0 0 0 0 0 0 0 0 0 1 48 117.90 0 0 0 0 0 0 0 0 0 0 0 0 49 124.72 0 1 0 0 0 0 0 0 0 0 0 0 50 126.42 0 0 1 0 0 0 0 0 0 0 0 0 51 134.73 0 0 0 1 0 0 0 0 0 0 0 0 52 135.79 0 0 0 0 1 0 0 0 0 0 0 0 53 143.36 0 0 0 0 0 1 0 0 0 0 0 0 54 140.37 0 0 0 0 0 0 1 0 0 0 0 0 55 144.74 0 0 0 0 0 0 0 1 0 0 0 0 56 151.98 0 0 0 0 0 0 0 0 1 0 0 0 57 150.92 0 0 0 0 0 0 0 0 0 1 0 0 58 163.38 0 0 0 0 0 0 0 0 0 0 1 0 59 154.43 0 0 0 0 0 0 0 0 0 0 0 1 60 146.66 0 0 0 0 0 0 0 0 0 0 0 0 61 157.95 0 1 0 0 0 0 0 0 0 0 0 0 62 162.10 0 0 1 0 0 0 0 0 0 0 0 0 63 180.42 0 0 0 1 0 0 0 0 0 0 0 0 64 179.57 0 0 0 0 1 0 0 0 0 0 0 0 65 171.58 0 0 0 0 0 1 0 0 0 0 0 0 66 185.43 0 0 0 0 0 0 1 0 0 0 0 0 67 190.64 0 0 0 0 0 0 0 1 0 0 0 0 68 203.00 0 0 0 0 0 0 0 0 1 0 0 0 69 202.36 0 0 0 0 0 0 0 0 0 1 0 0 70 193.41 0 0 0 0 0 0 0 0 0 0 1 0 71 186.17 0 0 0 0 0 0 0 0 0 0 0 1 72 192.24 0 0 0 0 0 0 0 0 0 0 0 0 73 209.60 0 1 0 0 0 0 0 0 0 0 0 0 74 206.41 0 0 1 0 0 0 0 0 0 0 0 0 75 209.82 0 0 0 1 0 0 0 0 0 0 0 0 76 230.37 0 0 0 0 1 0 0 0 0 0 0 0 77 235.80 0 0 0 0 0 1 0 0 0 0 0 0 78 232.07 0 0 0 0 0 0 1 0 0 0 0 0 79 244.64 0 0 0 0 0 0 0 1 0 0 0 0 80 242.19 0 0 0 0 0 0 0 0 1 0 0 0 81 217.48 0 0 0 0 0 0 0 0 0 1 0 0 82 209.39 0 0 0 0 0 0 0 0 0 0 1 0 83 211.73 0 0 0 0 0 0 0 0 0 0 0 1 84 221.00 0 0 0 0 0 0 0 0 0 0 0 0 85 203.11 0 1 0 0 0 0 0 0 0 0 0 0 86 214.71 0 0 1 0 0 0 0 0 0 0 0 0 87 224.19 0 0 0 1 0 0 0 0 0 0 0 0 88 238.04 0 0 0 0 1 0 0 0 0 0 0 0 89 238.36 0 0 0 0 0 1 0 0 0 0 0 0 90 246.24 0 0 0 0 0 0 1 0 0 0 0 0 91 259.87 0 0 0 0 0 0 0 1 0 0 0 0 92 249.97 0 0 0 0 0 0 0 0 1 0 0 0 93 266.48 0 0 0 0 0 0 0 0 0 1 0 0 94 282.98 0 0 0 0 0 0 0 0 0 0 1 0 95 306.31 0 0 0 0 0 0 0 0 0 0 0 1 96 301.73 1 0 0 0 0 0 0 0 0 0 0 0 97 314.62 1 1 0 0 0 0 0 0 0 0 0 0 98 332.62 1 0 1 0 0 0 0 0 0 0 0 0 99 355.51 1 0 0 1 0 0 0 0 0 0 0 0 100 370.32 1 0 0 0 1 0 0 0 0 0 0 0 101 408.13 1 0 0 0 0 1 0 0 0 0 0 0 102 433.58 1 0 0 0 0 0 1 0 0 0 0 0 103 440.51 1 0 0 0 0 0 0 1 0 0 0 0 104 386.29 1 0 0 0 0 0 0 0 1 0 0 0 105 342.84 1 0 0 0 0 0 0 0 0 1 0 0 106 254.97 1 0 0 0 0 0 0 0 0 0 1 0 107 203.42 1 0 0 0 0 0 0 0 0 0 0 1 108 170.09 1 0 0 0 0 0 0 0 0 0 0 0 109 174.03 1 1 0 0 0 0 0 0 0 0 0 0 110 167.85 1 0 1 0 0 0 0 0 0 0 0 0 111 177.01 1 0 0 1 0 0 0 0 0 0 0 0 112 188.19 1 0 0 0 1 0 0 0 0 0 0 0 113 211.20 1 0 0 0 0 1 0 0 0 0 0 0 114 240.91 1 0 0 0 0 0 1 0 0 0 0 0 115 230.26 1 0 0 0 0 0 0 1 0 0 0 0 116 251.25 1 0 0 0 0 0 0 0 1 0 0 0 117 241.66 1 0 0 0 0 0 0 0 0 1 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X M1 M2 M3 M4 129.735 132.441 1.565 5.705 12.735 17.240 M5 M6 M7 M8 M9 M10 25.346 32.726 35.666 33.941 28.159 24.241 M11 18.690 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -100.03 -51.56 -20.66 59.59 157.88 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 129.735 22.652 5.727 9.99e-08 *** X 132.441 15.939 8.309 3.87e-13 *** M1 1.565 30.842 0.051 0.960 M2 5.705 30.842 0.185 0.854 M3 12.735 30.842 0.413 0.681 M4 17.240 30.842 0.559 0.577 M5 25.346 30.842 0.822 0.413 M6 32.726 30.842 1.061 0.291 M7 35.666 30.842 1.156 0.250 M8 33.941 30.842 1.100 0.274 M9 28.159 30.842 0.913 0.363 M10 24.241 31.691 0.765 0.446 M11 18.690 31.691 0.590 0.557 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 67.12 on 104 degrees of freedom Multiple R-squared: 0.4121, Adjusted R-squared: 0.3442 F-statistic: 6.074 on 12 and 104 DF, p-value: 5.795e-08 > 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,] 1.005686e-04 2.011372e-04 0.9998994 [2,] 3.666482e-06 7.332965e-06 0.9999963 [3,] 7.046308e-07 1.409262e-06 0.9999993 [4,] 1.724347e-07 3.448694e-07 0.9999998 [5,] 4.846534e-08 9.693068e-08 1.0000000 [6,] 6.538854e-08 1.307771e-07 0.9999999 [7,] 2.034307e-07 4.068614e-07 0.9999998 [8,] 5.313743e-07 1.062749e-06 0.9999995 [9,] 1.959228e-07 3.918455e-07 0.9999998 [10,] 8.133791e-08 1.626758e-07 0.9999999 [11,] 3.820523e-08 7.641046e-08 1.0000000 [12,] 8.626741e-09 1.725348e-08 1.0000000 [13,] 1.627362e-09 3.254724e-09 1.0000000 [14,] 3.482343e-10 6.964686e-10 1.0000000 [15,] 8.573287e-11 1.714657e-10 1.0000000 [16,] 1.749713e-11 3.499426e-11 1.0000000 [17,] 3.510331e-12 7.020662e-12 1.0000000 [18,] 6.475071e-13 1.295014e-12 1.0000000 [19,] 1.219301e-13 2.438602e-13 1.0000000 [20,] 2.184296e-14 4.368592e-14 1.0000000 [21,] 6.195921e-15 1.239184e-14 1.0000000 [22,] 2.827498e-15 5.654996e-15 1.0000000 [23,] 1.873493e-15 3.746987e-15 1.0000000 [24,] 5.625622e-16 1.125124e-15 1.0000000 [25,] 1.202164e-16 2.404329e-16 1.0000000 [26,] 2.715587e-17 5.431174e-17 1.0000000 [27,] 7.107721e-18 1.421544e-17 1.0000000 [28,] 2.295519e-18 4.591037e-18 1.0000000 [29,] 7.745840e-19 1.549168e-18 1.0000000 [30,] 1.995622e-19 3.991245e-19 1.0000000 [31,] 7.571496e-20 1.514299e-19 1.0000000 [32,] 4.414488e-20 8.828976e-20 1.0000000 [33,] 5.148062e-20 1.029612e-19 1.0000000 [34,] 9.017349e-20 1.803470e-19 1.0000000 [35,] 1.028044e-19 2.056088e-19 1.0000000 [36,] 3.900911e-19 7.801823e-19 1.0000000 [37,] 2.625877e-18 5.251753e-18 1.0000000 [38,] 2.237852e-17 4.475705e-17 1.0000000 [39,] 1.024158e-16 2.048317e-16 1.0000000 [40,] 7.311882e-16 1.462376e-15 1.0000000 [41,] 5.992130e-15 1.198426e-14 1.0000000 [42,] 2.541644e-14 5.083289e-14 1.0000000 [43,] 2.840089e-13 5.680177e-13 1.0000000 [44,] 1.100507e-12 2.201014e-12 1.0000000 [45,] 1.990535e-12 3.981070e-12 1.0000000 [46,] 5.698778e-12 1.139756e-11 1.0000000 [47,] 1.459405e-11 2.918809e-11 1.0000000 [48,] 9.738726e-11 1.947745e-10 1.0000000 [49,] 5.692964e-10 1.138593e-09 1.0000000 [50,] 1.621360e-09 3.242721e-09 1.0000000 [51,] 8.311497e-09 1.662299e-08 1.0000000 [52,] 4.381665e-08 8.763330e-08 1.0000000 [53,] 2.152201e-07 4.304401e-07 0.9999998 [54,] 6.832753e-07 1.366551e-06 0.9999993 [55,] 1.280984e-06 2.561968e-06 0.9999987 [56,] 1.947652e-06 3.895304e-06 0.9999981 [57,] 3.160641e-06 6.321282e-06 0.9999968 [58,] 7.193286e-06 1.438657e-05 0.9999928 [59,] 1.170157e-05 2.340314e-05 0.9999883 [60,] 1.713381e-05 3.426762e-05 0.9999829 [61,] 3.895887e-05 7.791773e-05 0.9999610 [62,] 8.148951e-05 1.629790e-04 0.9999185 [63,] 1.439589e-04 2.879179e-04 0.9998560 [64,] 2.689987e-04 5.379974e-04 0.9997310 [65,] 3.827332e-04 7.654663e-04 0.9996173 [66,] 3.870452e-04 7.740904e-04 0.9996130 [67,] 3.509150e-04 7.018300e-04 0.9996491 [68,] 3.143374e-04 6.286747e-04 0.9996857 [69,] 3.031828e-04 6.063655e-04 0.9996968 [70,] 2.269966e-04 4.539933e-04 0.9997730 [71,] 1.797029e-04 3.594057e-04 0.9998203 [72,] 1.455892e-04 2.911783e-04 0.9998544 [73,] 1.302030e-04 2.604060e-04 0.9998698 [74,] 1.173799e-04 2.347597e-04 0.9998826 [75,] 1.275398e-04 2.550795e-04 0.9998725 [76,] 1.467661e-04 2.935321e-04 0.9998532 [77,] 1.593048e-04 3.186096e-04 0.9998407 [78,] 1.781618e-04 3.563236e-04 0.9998218 [79,] 1.897367e-04 3.794734e-04 0.9998103 [80,] 2.142269e-04 4.284537e-04 0.9997858 [81,] 1.847583e-04 3.695166e-04 0.9998152 [82,] 1.757076e-04 3.514151e-04 0.9998243 [83,] 2.334928e-04 4.669855e-04 0.9997665 [84,] 4.070900e-04 8.141801e-04 0.9995929 [85,] 8.131324e-04 1.626265e-03 0.9991869 [86,] 2.504272e-03 5.008544e-03 0.9974957 > postscript(file="/var/www/html/rcomp/tmp/1gfbb1258726527.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2bha21258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3hwx21258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/46c8v1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5xd2v1258726527.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 -31.290744 -31.600744 -37.990744 -51.545744 -50.281744 -53.821744 7 8 9 10 11 12 -59.751744 -55.256744 -42.544744 -40.336525 -33.185414 -29.405272 13 14 15 16 17 18 -30.010744 -30.960744 -43.210744 -46.865744 -51.561744 -61.281744 19 20 21 22 23 24 -69.011744 -66.116744 -61.504744 -68.876525 -68.655414 -50.605272 25 26 27 28 29 30 -50.460744 -52.690744 -49.920744 -50.375744 -58.161744 -67.141744 31 32 33 34 35 36 -66.881744 -63.456744 -52.984744 -50.876525 -51.295414 -26.315272 37 38 39 40 41 42 -19.580744 -17.330744 -30.850744 -46.755744 -53.051744 -56.701744 43 44 45 46 47 48 -57.721744 -52.906744 -52.454744 -41.716525 -34.355414 -11.835272 49 50 51 52 53 54 -6.580744 -9.020744 -7.740744 -11.185744 -11.721744 -22.091744 55 56 57 58 59 60 -20.661744 -11.696744 -6.974744 9.403475 6.004586 16.924728 61 62 63 64 65 66 26.649256 26.659256 37.949256 32.594256 16.498256 22.968256 67 68 69 70 71 72 25.238256 39.323256 44.465256 39.433475 37.744586 62.504728 73 74 75 76 77 78 78.299256 70.969256 67.349256 83.394256 80.718256 69.608256 79 80 81 82 83 84 79.238256 78.513256 59.585256 55.413475 63.304586 91.264728 85 86 87 88 89 90 71.809256 79.269256 81.719256 91.064256 83.278256 83.778256 91 92 93 94 95 96 94.468256 86.293256 108.585256 129.003475 157.884586 39.553450 97 98 99 100 101 102 50.877977 64.737977 80.597977 90.902977 120.606977 138.676977 103 104 105 106 107 108 142.666977 90.171977 52.503977 -31.447803 -77.446692 -92.086550 109 110 111 112 113 114 -89.712023 -100.032023 -97.902023 -91.227023 -76.323023 -53.993023 115 116 117 -67.583023 -44.868023 -48.676023 > postscript(file="/var/www/html/rcomp/tmp/63iqi1258726527.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 -31.290744 NA 1 -31.600744 -31.290744 2 -37.990744 -31.600744 3 -51.545744 -37.990744 4 -50.281744 -51.545744 5 -53.821744 -50.281744 6 -59.751744 -53.821744 7 -55.256744 -59.751744 8 -42.544744 -55.256744 9 -40.336525 -42.544744 10 -33.185414 -40.336525 11 -29.405272 -33.185414 12 -30.010744 -29.405272 13 -30.960744 -30.010744 14 -43.210744 -30.960744 15 -46.865744 -43.210744 16 -51.561744 -46.865744 17 -61.281744 -51.561744 18 -69.011744 -61.281744 19 -66.116744 -69.011744 20 -61.504744 -66.116744 21 -68.876525 -61.504744 22 -68.655414 -68.876525 23 -50.605272 -68.655414 24 -50.460744 -50.605272 25 -52.690744 -50.460744 26 -49.920744 -52.690744 27 -50.375744 -49.920744 28 -58.161744 -50.375744 29 -67.141744 -58.161744 30 -66.881744 -67.141744 31 -63.456744 -66.881744 32 -52.984744 -63.456744 33 -50.876525 -52.984744 34 -51.295414 -50.876525 35 -26.315272 -51.295414 36 -19.580744 -26.315272 37 -17.330744 -19.580744 38 -30.850744 -17.330744 39 -46.755744 -30.850744 40 -53.051744 -46.755744 41 -56.701744 -53.051744 42 -57.721744 -56.701744 43 -52.906744 -57.721744 44 -52.454744 -52.906744 45 -41.716525 -52.454744 46 -34.355414 -41.716525 47 -11.835272 -34.355414 48 -6.580744 -11.835272 49 -9.020744 -6.580744 50 -7.740744 -9.020744 51 -11.185744 -7.740744 52 -11.721744 -11.185744 53 -22.091744 -11.721744 54 -20.661744 -22.091744 55 -11.696744 -20.661744 56 -6.974744 -11.696744 57 9.403475 -6.974744 58 6.004586 9.403475 59 16.924728 6.004586 60 26.649256 16.924728 61 26.659256 26.649256 62 37.949256 26.659256 63 32.594256 37.949256 64 16.498256 32.594256 65 22.968256 16.498256 66 25.238256 22.968256 67 39.323256 25.238256 68 44.465256 39.323256 69 39.433475 44.465256 70 37.744586 39.433475 71 62.504728 37.744586 72 78.299256 62.504728 73 70.969256 78.299256 74 67.349256 70.969256 75 83.394256 67.349256 76 80.718256 83.394256 77 69.608256 80.718256 78 79.238256 69.608256 79 78.513256 79.238256 80 59.585256 78.513256 81 55.413475 59.585256 82 63.304586 55.413475 83 91.264728 63.304586 84 71.809256 91.264728 85 79.269256 71.809256 86 81.719256 79.269256 87 91.064256 81.719256 88 83.278256 91.064256 89 83.778256 83.278256 90 94.468256 83.778256 91 86.293256 94.468256 92 108.585256 86.293256 93 129.003475 108.585256 94 157.884586 129.003475 95 39.553450 157.884586 96 50.877977 39.553450 97 64.737977 50.877977 98 80.597977 64.737977 99 90.902977 80.597977 100 120.606977 90.902977 101 138.676977 120.606977 102 142.666977 138.676977 103 90.171977 142.666977 104 52.503977 90.171977 105 -31.447803 52.503977 106 -77.446692 -31.447803 107 -92.086550 -77.446692 108 -89.712023 -92.086550 109 -100.032023 -89.712023 110 -97.902023 -100.032023 111 -91.227023 -97.902023 112 -76.323023 -91.227023 113 -53.993023 -76.323023 114 -67.583023 -53.993023 115 -44.868023 -67.583023 116 -48.676023 -44.868023 117 NA -48.676023 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -31.600744 -31.290744 [2,] -37.990744 -31.600744 [3,] -51.545744 -37.990744 [4,] -50.281744 -51.545744 [5,] -53.821744 -50.281744 [6,] -59.751744 -53.821744 [7,] -55.256744 -59.751744 [8,] -42.544744 -55.256744 [9,] -40.336525 -42.544744 [10,] -33.185414 -40.336525 [11,] -29.405272 -33.185414 [12,] -30.010744 -29.405272 [13,] -30.960744 -30.010744 [14,] -43.210744 -30.960744 [15,] -46.865744 -43.210744 [16,] -51.561744 -46.865744 [17,] -61.281744 -51.561744 [18,] -69.011744 -61.281744 [19,] -66.116744 -69.011744 [20,] -61.504744 -66.116744 [21,] -68.876525 -61.504744 [22,] -68.655414 -68.876525 [23,] -50.605272 -68.655414 [24,] -50.460744 -50.605272 [25,] -52.690744 -50.460744 [26,] -49.920744 -52.690744 [27,] -50.375744 -49.920744 [28,] -58.161744 -50.375744 [29,] -67.141744 -58.161744 [30,] -66.881744 -67.141744 [31,] -63.456744 -66.881744 [32,] -52.984744 -63.456744 [33,] -50.876525 -52.984744 [34,] -51.295414 -50.876525 [35,] -26.315272 -51.295414 [36,] -19.580744 -26.315272 [37,] -17.330744 -19.580744 [38,] -30.850744 -17.330744 [39,] -46.755744 -30.850744 [40,] -53.051744 -46.755744 [41,] -56.701744 -53.051744 [42,] -57.721744 -56.701744 [43,] -52.906744 -57.721744 [44,] -52.454744 -52.906744 [45,] -41.716525 -52.454744 [46,] -34.355414 -41.716525 [47,] -11.835272 -34.355414 [48,] -6.580744 -11.835272 [49,] -9.020744 -6.580744 [50,] -7.740744 -9.020744 [51,] -11.185744 -7.740744 [52,] -11.721744 -11.185744 [53,] -22.091744 -11.721744 [54,] -20.661744 -22.091744 [55,] -11.696744 -20.661744 [56,] -6.974744 -11.696744 [57,] 9.403475 -6.974744 [58,] 6.004586 9.403475 [59,] 16.924728 6.004586 [60,] 26.649256 16.924728 [61,] 26.659256 26.649256 [62,] 37.949256 26.659256 [63,] 32.594256 37.949256 [64,] 16.498256 32.594256 [65,] 22.968256 16.498256 [66,] 25.238256 22.968256 [67,] 39.323256 25.238256 [68,] 44.465256 39.323256 [69,] 39.433475 44.465256 [70,] 37.744586 39.433475 [71,] 62.504728 37.744586 [72,] 78.299256 62.504728 [73,] 70.969256 78.299256 [74,] 67.349256 70.969256 [75,] 83.394256 67.349256 [76,] 80.718256 83.394256 [77,] 69.608256 80.718256 [78,] 79.238256 69.608256 [79,] 78.513256 79.238256 [80,] 59.585256 78.513256 [81,] 55.413475 59.585256 [82,] 63.304586 55.413475 [83,] 91.264728 63.304586 [84,] 71.809256 91.264728 [85,] 79.269256 71.809256 [86,] 81.719256 79.269256 [87,] 91.064256 81.719256 [88,] 83.278256 91.064256 [89,] 83.778256 83.278256 [90,] 94.468256 83.778256 [91,] 86.293256 94.468256 [92,] 108.585256 86.293256 [93,] 129.003475 108.585256 [94,] 157.884586 129.003475 [95,] 39.553450 157.884586 [96,] 50.877977 39.553450 [97,] 64.737977 50.877977 [98,] 80.597977 64.737977 [99,] 90.902977 80.597977 [100,] 120.606977 90.902977 [101,] 138.676977 120.606977 [102,] 142.666977 138.676977 [103,] 90.171977 142.666977 [104,] 52.503977 90.171977 [105,] -31.447803 52.503977 [106,] -77.446692 -31.447803 [107,] -92.086550 -77.446692 [108,] -89.712023 -92.086550 [109,] -100.032023 -89.712023 [110,] -97.902023 -100.032023 [111,] -91.227023 -97.902023 [112,] -76.323023 -91.227023 [113,] -53.993023 -76.323023 [114,] -67.583023 -53.993023 [115,] -44.868023 -67.583023 [116,] -48.676023 -44.868023 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -31.600744 -31.290744 2 -37.990744 -31.600744 3 -51.545744 -37.990744 4 -50.281744 -51.545744 5 -53.821744 -50.281744 6 -59.751744 -53.821744 7 -55.256744 -59.751744 8 -42.544744 -55.256744 9 -40.336525 -42.544744 10 -33.185414 -40.336525 11 -29.405272 -33.185414 12 -30.010744 -29.405272 13 -30.960744 -30.010744 14 -43.210744 -30.960744 15 -46.865744 -43.210744 16 -51.561744 -46.865744 17 -61.281744 -51.561744 18 -69.011744 -61.281744 19 -66.116744 -69.011744 20 -61.504744 -66.116744 21 -68.876525 -61.504744 22 -68.655414 -68.876525 23 -50.605272 -68.655414 24 -50.460744 -50.605272 25 -52.690744 -50.460744 26 -49.920744 -52.690744 27 -50.375744 -49.920744 28 -58.161744 -50.375744 29 -67.141744 -58.161744 30 -66.881744 -67.141744 31 -63.456744 -66.881744 32 -52.984744 -63.456744 33 -50.876525 -52.984744 34 -51.295414 -50.876525 35 -26.315272 -51.295414 36 -19.580744 -26.315272 37 -17.330744 -19.580744 38 -30.850744 -17.330744 39 -46.755744 -30.850744 40 -53.051744 -46.755744 41 -56.701744 -53.051744 42 -57.721744 -56.701744 43 -52.906744 -57.721744 44 -52.454744 -52.906744 45 -41.716525 -52.454744 46 -34.355414 -41.716525 47 -11.835272 -34.355414 48 -6.580744 -11.835272 49 -9.020744 -6.580744 50 -7.740744 -9.020744 51 -11.185744 -7.740744 52 -11.721744 -11.185744 53 -22.091744 -11.721744 54 -20.661744 -22.091744 55 -11.696744 -20.661744 56 -6.974744 -11.696744 57 9.403475 -6.974744 58 6.004586 9.403475 59 16.924728 6.004586 60 26.649256 16.924728 61 26.659256 26.649256 62 37.949256 26.659256 63 32.594256 37.949256 64 16.498256 32.594256 65 22.968256 16.498256 66 25.238256 22.968256 67 39.323256 25.238256 68 44.465256 39.323256 69 39.433475 44.465256 70 37.744586 39.433475 71 62.504728 37.744586 72 78.299256 62.504728 73 70.969256 78.299256 74 67.349256 70.969256 75 83.394256 67.349256 76 80.718256 83.394256 77 69.608256 80.718256 78 79.238256 69.608256 79 78.513256 79.238256 80 59.585256 78.513256 81 55.413475 59.585256 82 63.304586 55.413475 83 91.264728 63.304586 84 71.809256 91.264728 85 79.269256 71.809256 86 81.719256 79.269256 87 91.064256 81.719256 88 83.278256 91.064256 89 83.778256 83.278256 90 94.468256 83.778256 91 86.293256 94.468256 92 108.585256 86.293256 93 129.003475 108.585256 94 157.884586 129.003475 95 39.553450 157.884586 96 50.877977 39.553450 97 64.737977 50.877977 98 80.597977 64.737977 99 90.902977 80.597977 100 120.606977 90.902977 101 138.676977 120.606977 102 142.666977 138.676977 103 90.171977 142.666977 104 52.503977 90.171977 105 -31.447803 52.503977 106 -77.446692 -31.447803 107 -92.086550 -77.446692 108 -89.712023 -92.086550 109 -100.032023 -89.712023 110 -97.902023 -100.032023 111 -91.227023 -97.902023 112 -76.323023 -91.227023 113 -53.993023 -76.323023 114 -67.583023 -53.993023 115 -44.868023 -67.583023 116 -48.676023 -44.868023 > 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/7rz8u1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/86eam1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/96kuz1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10gcm31258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11fzz41258726527.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/123i001258726527.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/13gbvm1258726527.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/14w3zu1258726528.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/15nm7z1258726528.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/168zyh1258726528.tab") + } > system("convert tmp/1gfbb1258726527.ps tmp/1gfbb1258726527.png") > system("convert tmp/2bha21258726527.ps tmp/2bha21258726527.png") > system("convert tmp/3hwx21258726527.ps tmp/3hwx21258726527.png") > system("convert tmp/46c8v1258726527.ps tmp/46c8v1258726527.png") > system("convert tmp/5xd2v1258726527.ps tmp/5xd2v1258726527.png") > system("convert tmp/63iqi1258726527.ps tmp/63iqi1258726527.png") > system("convert tmp/7rz8u1258726527.ps tmp/7rz8u1258726527.png") > system("convert tmp/86eam1258726527.ps tmp/86eam1258726527.png") > system("convert tmp/96kuz1258726527.ps tmp/96kuz1258726527.png") > system("convert tmp/10gcm31258726527.ps tmp/10gcm31258726527.png") > > > proc.time() user system elapsed 3.328 1.649 3.778