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Type 'q()' to quit R. > x <- array(list(100 + ,0 + ,108.1560276 + ,0 + ,114.0150276 + ,0 + ,102.1880309 + ,0 + ,110.3672031 + ,0 + ,96.8602511 + ,0 + ,94.1944583 + ,0 + ,99.51621961 + ,0 + ,94.06333487 + ,0 + ,97.5541476 + ,0 + ,78.15062422 + ,0 + ,81.2434643 + ,0 + ,92.36262465 + ,0 + ,96.06324371 + ,0 + ,114.0523777 + ,0 + ,110.6616666 + ,0 + ,104.9171949 + ,0 + ,90.00187193 + ,0 + ,95.7008067 + ,0 + ,86.02741157 + ,0 + ,84.85287668 + ,0 + ,100.04328 + ,0 + ,80.91713823 + ,0 + ,74.06539709 + ,0 + ,77.30281369 + ,0 + ,97.23043249 + ,0 + ,90.75515676 + ,0 + ,100.5614455 + ,0 + ,92.01293267 + ,0 + ,99.24012138 + ,0 + ,105.8672755 + ,0 + ,90.9920463 + ,0 + ,93.30624423 + ,0 + ,91.17419413 + ,0 + ,77.33295039 + ,0 + ,91.1277721 + ,0 + ,85.01249943 + ,0 + ,83.90390242 + ,0 + ,104.8626302 + ,0 + ,110.9039108 + ,0 + ,95.43714373 + ,0 + ,111.6238727 + ,0 + ,108.8925403 + ,0 + ,96.17511682 + ,0 + ,101.9740205 + ,0 + ,99.11953031 + ,0 + ,86.78158147 + ,0 + ,118.4195003 + ,0 + ,118.7441447 + ,0 + ,106.5296192 + ,0 + ,134.7772694 + ,0 + ,104.6778714 + ,0 + ,105.2954304 + ,0 + ,139.4139849 + ,0 + ,103.6060491 + ,0 + ,99.78182974 + ,0 + ,103.4610301 + ,0 + ,120.0594945 + ,0 + ,96.71377168 + ,0 + ,107.1308929 + ,0 + ,105.3608372 + ,0 + ,111.6942359 + ,0 + ,132.0519998 + ,0 + ,126.8037879 + ,0 + ,154.4824253 + ,0 + ,141.5570984 + ,0 + ,109.9506882 + ,0 + ,127.904198 + ,0 + ,133.0888617 + ,0 + ,120.0796299 + ,0 + ,117.5557142 + ,0 + ,143.0362309 + ,0 + ,159.982927 + ,1 + ,128.5991124 + ,1 + ,149.7373327 + ,1 + ,126.8169313 + ,1 + ,140.9639674 + ,1 + ,137.6691981 + ,1 + ,117.9402337 + ,1 + ,122.3095247 + ,1 + ,127.7804207 + ,1 + ,136.1677176 + ,1 + ,116.2405856 + ,1 + ,123.1576893 + ,1 + ,116.3400234 + ,1 + ,108.6119282 + ,1 + ,125.8982264 + ,1 + ,112.8003105 + ,1 + ,107.5182447 + ,1 + ,135.0955413 + ,1 + ,115.5096488 + ,1 + ,115.8640759 + ,1 + ,104.5883906 + ,1 + ,163.7213386 + ,1 + ,113.4482275 + ,1 + ,98.0428844 + ,1 + ,116.7868521 + ,1 + ,126.5330444 + ,1 + ,113.0336597 + ,1 + ,124.3392163 + ,1 + ,109.8298759 + ,1 + ,124.4434777 + ,1 + ,111.5039454 + ,1 + ,102.0350019 + ,1 + ,116.8726598 + ,1 + ,112.2073122 + ,1 + ,101.1513902 + ,1 + ,124.4255108 + ,1) + ,dim=c(2 + ,108) + ,dimnames=list(c('Y' + ,'X') + ,1:108)) > y <- array(NA,dim=c(2,108),dimnames=list(c('Y','X'),1:108)) > 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 1 100.00000 0 1 0 0 0 0 0 0 0 0 0 0 1 2 108.15603 0 0 1 0 0 0 0 0 0 0 0 0 2 3 114.01503 0 0 0 1 0 0 0 0 0 0 0 0 3 4 102.18803 0 0 0 0 1 0 0 0 0 0 0 0 4 5 110.36720 0 0 0 0 0 1 0 0 0 0 0 0 5 6 96.86025 0 0 0 0 0 0 1 0 0 0 0 0 6 7 94.19446 0 0 0 0 0 0 0 1 0 0 0 0 7 8 99.51622 0 0 0 0 0 0 0 0 1 0 0 0 8 9 94.06333 0 0 0 0 0 0 0 0 0 1 0 0 9 10 97.55415 0 0 0 0 0 0 0 0 0 0 1 0 10 11 78.15062 0 0 0 0 0 0 0 0 0 0 0 1 11 12 81.24346 0 0 0 0 0 0 0 0 0 0 0 0 12 13 92.36262 0 1 0 0 0 0 0 0 0 0 0 0 13 14 96.06324 0 0 1 0 0 0 0 0 0 0 0 0 14 15 114.05238 0 0 0 1 0 0 0 0 0 0 0 0 15 16 110.66167 0 0 0 0 1 0 0 0 0 0 0 0 16 17 104.91719 0 0 0 0 0 1 0 0 0 0 0 0 17 18 90.00187 0 0 0 0 0 0 1 0 0 0 0 0 18 19 95.70081 0 0 0 0 0 0 0 1 0 0 0 0 19 20 86.02741 0 0 0 0 0 0 0 0 1 0 0 0 20 21 84.85288 0 0 0 0 0 0 0 0 0 1 0 0 21 22 100.04328 0 0 0 0 0 0 0 0 0 0 1 0 22 23 80.91714 0 0 0 0 0 0 0 0 0 0 0 1 23 24 74.06540 0 0 0 0 0 0 0 0 0 0 0 0 24 25 77.30281 0 1 0 0 0 0 0 0 0 0 0 0 25 26 97.23043 0 0 1 0 0 0 0 0 0 0 0 0 26 27 90.75516 0 0 0 1 0 0 0 0 0 0 0 0 27 28 100.56145 0 0 0 0 1 0 0 0 0 0 0 0 28 29 92.01293 0 0 0 0 0 1 0 0 0 0 0 0 29 30 99.24012 0 0 0 0 0 0 1 0 0 0 0 0 30 31 105.86728 0 0 0 0 0 0 0 1 0 0 0 0 31 32 90.99205 0 0 0 0 0 0 0 0 1 0 0 0 32 33 93.30624 0 0 0 0 0 0 0 0 0 1 0 0 33 34 91.17419 0 0 0 0 0 0 0 0 0 0 1 0 34 35 77.33295 0 0 0 0 0 0 0 0 0 0 0 1 35 36 91.12777 0 0 0 0 0 0 0 0 0 0 0 0 36 37 85.01250 0 1 0 0 0 0 0 0 0 0 0 0 37 38 83.90390 0 0 1 0 0 0 0 0 0 0 0 0 38 39 104.86263 0 0 0 1 0 0 0 0 0 0 0 0 39 40 110.90391 0 0 0 0 1 0 0 0 0 0 0 0 40 41 95.43714 0 0 0 0 0 1 0 0 0 0 0 0 41 42 111.62387 0 0 0 0 0 0 1 0 0 0 0 0 42 43 108.89254 0 0 0 0 0 0 0 1 0 0 0 0 43 44 96.17512 0 0 0 0 0 0 0 0 1 0 0 0 44 45 101.97402 0 0 0 0 0 0 0 0 0 1 0 0 45 46 99.11953 0 0 0 0 0 0 0 0 0 0 1 0 46 47 86.78158 0 0 0 0 0 0 0 0 0 0 0 1 47 48 118.41950 0 0 0 0 0 0 0 0 0 0 0 0 48 49 118.74414 0 1 0 0 0 0 0 0 0 0 0 0 49 50 106.52962 0 0 1 0 0 0 0 0 0 0 0 0 50 51 134.77727 0 0 0 1 0 0 0 0 0 0 0 0 51 52 104.67787 0 0 0 0 1 0 0 0 0 0 0 0 52 53 105.29543 0 0 0 0 0 1 0 0 0 0 0 0 53 54 139.41398 0 0 0 0 0 0 1 0 0 0 0 0 54 55 103.60605 0 0 0 0 0 0 0 1 0 0 0 0 55 56 99.78183 0 0 0 0 0 0 0 0 1 0 0 0 56 57 103.46103 0 0 0 0 0 0 0 0 0 1 0 0 57 58 120.05949 0 0 0 0 0 0 0 0 0 0 1 0 58 59 96.71377 0 0 0 0 0 0 0 0 0 0 0 1 59 60 107.13089 0 0 0 0 0 0 0 0 0 0 0 0 60 61 105.36084 0 1 0 0 0 0 0 0 0 0 0 0 61 62 111.69424 0 0 1 0 0 0 0 0 0 0 0 0 62 63 132.05200 0 0 0 1 0 0 0 0 0 0 0 0 63 64 126.80379 0 0 0 0 1 0 0 0 0 0 0 0 64 65 154.48243 0 0 0 0 0 1 0 0 0 0 0 0 65 66 141.55710 0 0 0 0 0 0 1 0 0 0 0 0 66 67 109.95069 0 0 0 0 0 0 0 1 0 0 0 0 67 68 127.90420 0 0 0 0 0 0 0 0 1 0 0 0 68 69 133.08886 0 0 0 0 0 0 0 0 0 1 0 0 69 70 120.07963 0 0 0 0 0 0 0 0 0 0 1 0 70 71 117.55571 0 0 0 0 0 0 0 0 0 0 0 1 71 72 143.03623 0 0 0 0 0 0 0 0 0 0 0 0 72 73 159.98293 1 1 0 0 0 0 0 0 0 0 0 0 73 74 128.59911 1 0 1 0 0 0 0 0 0 0 0 0 74 75 149.73733 1 0 0 1 0 0 0 0 0 0 0 0 75 76 126.81693 1 0 0 0 1 0 0 0 0 0 0 0 76 77 140.96397 1 0 0 0 0 1 0 0 0 0 0 0 77 78 137.66920 1 0 0 0 0 0 1 0 0 0 0 0 78 79 117.94023 1 0 0 0 0 0 0 1 0 0 0 0 79 80 122.30952 1 0 0 0 0 0 0 0 1 0 0 0 80 81 127.78042 1 0 0 0 0 0 0 0 0 1 0 0 81 82 136.16772 1 0 0 0 0 0 0 0 0 0 1 0 82 83 116.24059 1 0 0 0 0 0 0 0 0 0 0 1 83 84 123.15769 1 0 0 0 0 0 0 0 0 0 0 0 84 85 116.34002 1 1 0 0 0 0 0 0 0 0 0 0 85 86 108.61193 1 0 1 0 0 0 0 0 0 0 0 0 86 87 125.89823 1 0 0 1 0 0 0 0 0 0 0 0 87 88 112.80031 1 0 0 0 1 0 0 0 0 0 0 0 88 89 107.51824 1 0 0 0 0 1 0 0 0 0 0 0 89 90 135.09554 1 0 0 0 0 0 1 0 0 0 0 0 90 91 115.50965 1 0 0 0 0 0 0 1 0 0 0 0 91 92 115.86408 1 0 0 0 0 0 0 0 1 0 0 0 92 93 104.58839 1 0 0 0 0 0 0 0 0 1 0 0 93 94 163.72134 1 0 0 0 0 0 0 0 0 0 1 0 94 95 113.44823 1 0 0 0 0 0 0 0 0 0 0 1 95 96 98.04288 1 0 0 0 0 0 0 0 0 0 0 0 96 97 116.78685 1 1 0 0 0 0 0 0 0 0 0 0 97 98 126.53304 1 0 1 0 0 0 0 0 0 0 0 0 98 99 113.03366 1 0 0 1 0 0 0 0 0 0 0 0 99 100 124.33922 1 0 0 0 1 0 0 0 0 0 0 0 100 101 109.82988 1 0 0 0 0 1 0 0 0 0 0 0 101 102 124.44348 1 0 0 0 0 0 1 0 0 0 0 0 102 103 111.50395 1 0 0 0 0 0 0 1 0 0 0 0 103 104 102.03500 1 0 0 0 0 0 0 0 1 0 0 0 104 105 116.87266 1 0 0 0 0 0 0 0 0 1 0 0 105 106 112.20731 1 0 0 0 0 0 0 0 0 0 1 0 106 107 101.15139 1 0 0 0 0 0 0 0 0 0 0 1 107 108 124.42551 1 0 0 0 0 0 0 0 0 0 0 0 108 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X M1 M2 M3 M4 85.364 -1.763 5.276 4.402 16.465 9.495 M5 M6 M7 M8 M9 M10 9.248 15.002 2.110 -0.763 1.025 9.563 M11 t -9.896 0.366 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -23.270 -8.842 -1.441 8.591 44.386 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 85.36443 5.81858 14.671 < 2e-16 *** X -1.76327 5.08157 -0.347 0.7294 M1 5.27566 6.74403 0.782 0.4360 M2 4.40171 6.73472 0.654 0.5150 M3 16.46480 6.72628 2.448 0.0162 * M4 9.49538 6.71872 1.413 0.1609 M5 9.24837 6.71205 1.378 0.1715 M6 15.00244 6.70625 2.237 0.0276 * M7 2.10977 6.70135 0.315 0.7536 M8 -0.76296 6.69734 -0.114 0.9095 M9 1.02461 6.69421 0.153 0.8787 M10 9.56288 6.69198 1.429 0.1563 M11 -9.89589 6.69064 -1.479 0.1425 t 0.36604 0.07731 4.734 7.75e-06 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 14.19 on 94 degrees of freedom Multiple R-squared: 0.4696, Adjusted R-squared: 0.3963 F-statistic: 6.403 on 13 and 94 DF, p-value: 1.6e-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,] 9.698373e-02 0.1939674653 0.9030163 [2,] 3.667026e-02 0.0733405146 0.9633297 [3,] 1.453258e-02 0.0290651605 0.9854674 [4,] 9.608570e-03 0.0192171391 0.9903914 [5,] 3.712354e-03 0.0074247084 0.9962876 [6,] 1.782931e-03 0.0035658624 0.9982171 [7,] 8.174710e-04 0.0016349419 0.9991825 [8,] 3.094032e-04 0.0006188065 0.9996906 [9,] 4.797155e-04 0.0009594311 0.9995203 [10,] 1.810066e-04 0.0003620131 0.9998190 [11,] 4.221239e-04 0.0008442478 0.9995779 [12,] 1.778692e-04 0.0003557385 0.9998221 [13,] 8.913318e-05 0.0001782664 0.9999109 [14,] 2.041066e-04 0.0004082133 0.9997959 [15,] 6.093317e-04 0.0012186634 0.9993907 [16,] 3.060315e-04 0.0006120629 0.9996940 [17,] 2.227161e-04 0.0004454322 0.9997773 [18,] 1.201547e-04 0.0002403094 0.9998798 [19,] 6.214728e-05 0.0001242946 0.9999379 [20,] 1.691715e-04 0.0003383430 0.9998308 [21,] 1.253107e-04 0.0002506214 0.9998747 [22,] 1.448495e-04 0.0002896989 0.9998552 [23,] 9.953452e-05 0.0001990690 0.9999005 [24,] 9.778741e-05 0.0001955748 0.9999022 [25,] 6.777086e-05 0.0001355417 0.9999322 [26,] 3.025073e-04 0.0006050146 0.9996975 [27,] 3.138058e-04 0.0006276116 0.9996862 [28,] 2.250280e-04 0.0004500561 0.9997750 [29,] 2.549666e-04 0.0005099332 0.9997450 [30,] 3.121854e-04 0.0006243708 0.9996878 [31,] 3.699812e-04 0.0007399623 0.9996300 [32,] 6.508426e-03 0.0130168521 0.9934916 [33,] 1.715660e-02 0.0343132003 0.9828434 [34,] 1.353166e-02 0.0270633139 0.9864683 [35,] 2.144029e-02 0.0428805856 0.9785597 [36,] 1.956628e-02 0.0391325623 0.9804337 [37,] 2.035059e-02 0.0407011770 0.9796494 [38,] 5.373739e-02 0.1074747730 0.9462626 [39,] 4.403773e-02 0.0880754576 0.9559623 [40,] 4.256495e-02 0.0851299008 0.9574350 [41,] 4.393706e-02 0.0878741111 0.9560629 [42,] 5.384233e-02 0.1076846567 0.9461577 [43,] 6.361329e-02 0.1272265871 0.9363867 [44,] 8.132977e-02 0.1626595483 0.9186702 [45,] 1.253832e-01 0.2507664143 0.8746168 [46,] 1.228437e-01 0.2456874231 0.8771563 [47,] 1.051931e-01 0.2103861522 0.8948069 [48,] 8.736869e-02 0.1747373817 0.9126313 [49,] 2.923763e-01 0.5847525338 0.7076237 [50,] 2.861229e-01 0.5722458268 0.7138771 [51,] 2.639720e-01 0.5279439338 0.7360280 [52,] 2.528139e-01 0.5056277132 0.7471861 [53,] 2.622545e-01 0.5245090805 0.7377455 [54,] 3.511960e-01 0.7023920209 0.6488040 [55,] 3.638143e-01 0.7276285250 0.6361857 [56,] 3.990987e-01 0.7981974678 0.6009013 [57,] 5.427716e-01 0.9144568159 0.4572284 [58,] 5.307575e-01 0.9384849306 0.4692425 [59,] 5.618987e-01 0.8762026990 0.4381013 [60,] 5.260565e-01 0.9478870277 0.4739435 [61,] 5.980668e-01 0.8038664497 0.4019332 [62,] 5.264268e-01 0.9471464091 0.4735732 [63,] 4.699527e-01 0.9399053748 0.5300473 [64,] 4.030104e-01 0.8060207972 0.5969896 [65,] 3.543427e-01 0.7086854063 0.6456573 [66,] 2.901721e-01 0.5803442787 0.7098279 [67,] 2.204804e-01 0.4409607665 0.7795196 [68,] 1.690748e-01 0.3381495207 0.8309252 [69,] 1.300049e-01 0.2600098178 0.8699951 [70,] 1.521286e-01 0.3042571345 0.8478714 [71,] 1.173238e-01 0.2346475258 0.8826762 [72,] 1.093743e-01 0.2187485231 0.8906257 [73,] 8.748179e-02 0.1749635769 0.9125182 [74,] 4.731592e-02 0.0946318440 0.9526841 [75,] 2.268138e-02 0.0453627597 0.9773186 > postscript(file="/var/www/html/rcomp/tmp/1ihhg1258618159.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2kt9v1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3adhp1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/46c2e1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5kprj1258618159.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 = 108 Frequency = 1 1 2 3 4 5 6 8.9938775 17.6578135 11.0876875 5.8640807 13.9242255 -5.7028376 7 8 9 10 11 12 4.1580109 11.9864635 4.3799771 -1.0335219 -1.3443051 -8.5133938 13 14 15 16 17 18 -3.0359264 1.1726010 6.7326090 9.9452878 4.0817887 -16.9536453 19 20 21 22 23 24 1.2719307 -5.8947731 -9.2229096 -2.9368181 -2.9702197 -20.0838895 25 26 27 28 29 30 -22.4881660 -2.0526387 -20.9570404 -4.5473618 -13.2149021 -12.1078244 31 32 33 34 35 36 7.0459710 -5.3225669 -5.1619706 -16.1983325 -10.9468361 -7.4139431 37 38 39 40 41 42 -19.1709088 -19.7715973 -11.2419956 1.4026749 -14.1831196 -4.1165016 43 44 45 46 47 48 5.6788072 -4.5319250 -0.8866229 -12.6454248 -5.8906335 15.4853566 49 50 51 52 53 54 10.1683080 -1.5383091 14.2802151 -9.2157930 -8.7172614 19.2811820 55 56 57 58 59 60 -4.0001125 -5.3176406 -3.7920419 3.9021108 -0.3508719 -0.1956794 61 62 63 64 65 66 -7.6074281 -0.7661210 7.1625169 8.5176949 36.0773049 17.0318670 67 68 69 70 71 72 -2.0479020 18.4122991 21.4433612 -0.4701824 16.0986421 31.3172301 73 74 75 76 77 78 44.3855027 13.5095965 22.2186908 5.9016793 19.9296880 10.5148076 79 80 81 82 83 84 3.3124845 10.1884668 13.5057611 12.9887463 12.1543544 8.8095294 85 86 87 88 89 90 -3.6498295 -10.8700163 -6.0128441 -12.5073701 -17.9084633 3.5487223 91 92 93 94 95 96 -3.5105290 -0.6494106 -14.0786975 36.1499387 4.9695678 -20.6977040 97 98 99 100 101 102 -7.5954293 2.6586714 -23.2698393 -5.3608928 -19.9892606 -11.4957699 103 104 105 106 107 108 -11.9086609 -18.8709131 -6.1868569 -19.7565162 -11.7196981 1.2924938 > postscript(file="/var/www/html/rcomp/tmp/6a6dk1258618159.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 = 108 Frequency = 1 lag(myerror, k = 1) myerror 0 8.9938775 NA 1 17.6578135 8.9938775 2 11.0876875 17.6578135 3 5.8640807 11.0876875 4 13.9242255 5.8640807 5 -5.7028376 13.9242255 6 4.1580109 -5.7028376 7 11.9864635 4.1580109 8 4.3799771 11.9864635 9 -1.0335219 4.3799771 10 -1.3443051 -1.0335219 11 -8.5133938 -1.3443051 12 -3.0359264 -8.5133938 13 1.1726010 -3.0359264 14 6.7326090 1.1726010 15 9.9452878 6.7326090 16 4.0817887 9.9452878 17 -16.9536453 4.0817887 18 1.2719307 -16.9536453 19 -5.8947731 1.2719307 20 -9.2229096 -5.8947731 21 -2.9368181 -9.2229096 22 -2.9702197 -2.9368181 23 -20.0838895 -2.9702197 24 -22.4881660 -20.0838895 25 -2.0526387 -22.4881660 26 -20.9570404 -2.0526387 27 -4.5473618 -20.9570404 28 -13.2149021 -4.5473618 29 -12.1078244 -13.2149021 30 7.0459710 -12.1078244 31 -5.3225669 7.0459710 32 -5.1619706 -5.3225669 33 -16.1983325 -5.1619706 34 -10.9468361 -16.1983325 35 -7.4139431 -10.9468361 36 -19.1709088 -7.4139431 37 -19.7715973 -19.1709088 38 -11.2419956 -19.7715973 39 1.4026749 -11.2419956 40 -14.1831196 1.4026749 41 -4.1165016 -14.1831196 42 5.6788072 -4.1165016 43 -4.5319250 5.6788072 44 -0.8866229 -4.5319250 45 -12.6454248 -0.8866229 46 -5.8906335 -12.6454248 47 15.4853566 -5.8906335 48 10.1683080 15.4853566 49 -1.5383091 10.1683080 50 14.2802151 -1.5383091 51 -9.2157930 14.2802151 52 -8.7172614 -9.2157930 53 19.2811820 -8.7172614 54 -4.0001125 19.2811820 55 -5.3176406 -4.0001125 56 -3.7920419 -5.3176406 57 3.9021108 -3.7920419 58 -0.3508719 3.9021108 59 -0.1956794 -0.3508719 60 -7.6074281 -0.1956794 61 -0.7661210 -7.6074281 62 7.1625169 -0.7661210 63 8.5176949 7.1625169 64 36.0773049 8.5176949 65 17.0318670 36.0773049 66 -2.0479020 17.0318670 67 18.4122991 -2.0479020 68 21.4433612 18.4122991 69 -0.4701824 21.4433612 70 16.0986421 -0.4701824 71 31.3172301 16.0986421 72 44.3855027 31.3172301 73 13.5095965 44.3855027 74 22.2186908 13.5095965 75 5.9016793 22.2186908 76 19.9296880 5.9016793 77 10.5148076 19.9296880 78 3.3124845 10.5148076 79 10.1884668 3.3124845 80 13.5057611 10.1884668 81 12.9887463 13.5057611 82 12.1543544 12.9887463 83 8.8095294 12.1543544 84 -3.6498295 8.8095294 85 -10.8700163 -3.6498295 86 -6.0128441 -10.8700163 87 -12.5073701 -6.0128441 88 -17.9084633 -12.5073701 89 3.5487223 -17.9084633 90 -3.5105290 3.5487223 91 -0.6494106 -3.5105290 92 -14.0786975 -0.6494106 93 36.1499387 -14.0786975 94 4.9695678 36.1499387 95 -20.6977040 4.9695678 96 -7.5954293 -20.6977040 97 2.6586714 -7.5954293 98 -23.2698393 2.6586714 99 -5.3608928 -23.2698393 100 -19.9892606 -5.3608928 101 -11.4957699 -19.9892606 102 -11.9086609 -11.4957699 103 -18.8709131 -11.9086609 104 -6.1868569 -18.8709131 105 -19.7565162 -6.1868569 106 -11.7196981 -19.7565162 107 1.2924938 -11.7196981 108 NA 1.2924938 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 17.6578135 8.9938775 [2,] 11.0876875 17.6578135 [3,] 5.8640807 11.0876875 [4,] 13.9242255 5.8640807 [5,] -5.7028376 13.9242255 [6,] 4.1580109 -5.7028376 [7,] 11.9864635 4.1580109 [8,] 4.3799771 11.9864635 [9,] -1.0335219 4.3799771 [10,] -1.3443051 -1.0335219 [11,] -8.5133938 -1.3443051 [12,] -3.0359264 -8.5133938 [13,] 1.1726010 -3.0359264 [14,] 6.7326090 1.1726010 [15,] 9.9452878 6.7326090 [16,] 4.0817887 9.9452878 [17,] -16.9536453 4.0817887 [18,] 1.2719307 -16.9536453 [19,] -5.8947731 1.2719307 [20,] -9.2229096 -5.8947731 [21,] -2.9368181 -9.2229096 [22,] -2.9702197 -2.9368181 [23,] -20.0838895 -2.9702197 [24,] -22.4881660 -20.0838895 [25,] -2.0526387 -22.4881660 [26,] -20.9570404 -2.0526387 [27,] -4.5473618 -20.9570404 [28,] -13.2149021 -4.5473618 [29,] -12.1078244 -13.2149021 [30,] 7.0459710 -12.1078244 [31,] -5.3225669 7.0459710 [32,] -5.1619706 -5.3225669 [33,] -16.1983325 -5.1619706 [34,] -10.9468361 -16.1983325 [35,] -7.4139431 -10.9468361 [36,] -19.1709088 -7.4139431 [37,] -19.7715973 -19.1709088 [38,] -11.2419956 -19.7715973 [39,] 1.4026749 -11.2419956 [40,] -14.1831196 1.4026749 [41,] -4.1165016 -14.1831196 [42,] 5.6788072 -4.1165016 [43,] -4.5319250 5.6788072 [44,] -0.8866229 -4.5319250 [45,] -12.6454248 -0.8866229 [46,] -5.8906335 -12.6454248 [47,] 15.4853566 -5.8906335 [48,] 10.1683080 15.4853566 [49,] -1.5383091 10.1683080 [50,] 14.2802151 -1.5383091 [51,] -9.2157930 14.2802151 [52,] -8.7172614 -9.2157930 [53,] 19.2811820 -8.7172614 [54,] -4.0001125 19.2811820 [55,] -5.3176406 -4.0001125 [56,] -3.7920419 -5.3176406 [57,] 3.9021108 -3.7920419 [58,] -0.3508719 3.9021108 [59,] -0.1956794 -0.3508719 [60,] -7.6074281 -0.1956794 [61,] -0.7661210 -7.6074281 [62,] 7.1625169 -0.7661210 [63,] 8.5176949 7.1625169 [64,] 36.0773049 8.5176949 [65,] 17.0318670 36.0773049 [66,] -2.0479020 17.0318670 [67,] 18.4122991 -2.0479020 [68,] 21.4433612 18.4122991 [69,] -0.4701824 21.4433612 [70,] 16.0986421 -0.4701824 [71,] 31.3172301 16.0986421 [72,] 44.3855027 31.3172301 [73,] 13.5095965 44.3855027 [74,] 22.2186908 13.5095965 [75,] 5.9016793 22.2186908 [76,] 19.9296880 5.9016793 [77,] 10.5148076 19.9296880 [78,] 3.3124845 10.5148076 [79,] 10.1884668 3.3124845 [80,] 13.5057611 10.1884668 [81,] 12.9887463 13.5057611 [82,] 12.1543544 12.9887463 [83,] 8.8095294 12.1543544 [84,] -3.6498295 8.8095294 [85,] -10.8700163 -3.6498295 [86,] -6.0128441 -10.8700163 [87,] -12.5073701 -6.0128441 [88,] -17.9084633 -12.5073701 [89,] 3.5487223 -17.9084633 [90,] -3.5105290 3.5487223 [91,] -0.6494106 -3.5105290 [92,] -14.0786975 -0.6494106 [93,] 36.1499387 -14.0786975 [94,] 4.9695678 36.1499387 [95,] -20.6977040 4.9695678 [96,] -7.5954293 -20.6977040 [97,] 2.6586714 -7.5954293 [98,] -23.2698393 2.6586714 [99,] -5.3608928 -23.2698393 [100,] -19.9892606 -5.3608928 [101,] -11.4957699 -19.9892606 [102,] -11.9086609 -11.4957699 [103,] -18.8709131 -11.9086609 [104,] -6.1868569 -18.8709131 [105,] -19.7565162 -6.1868569 [106,] -11.7196981 -19.7565162 [107,] 1.2924938 -11.7196981 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 17.6578135 8.9938775 2 11.0876875 17.6578135 3 5.8640807 11.0876875 4 13.9242255 5.8640807 5 -5.7028376 13.9242255 6 4.1580109 -5.7028376 7 11.9864635 4.1580109 8 4.3799771 11.9864635 9 -1.0335219 4.3799771 10 -1.3443051 -1.0335219 11 -8.5133938 -1.3443051 12 -3.0359264 -8.5133938 13 1.1726010 -3.0359264 14 6.7326090 1.1726010 15 9.9452878 6.7326090 16 4.0817887 9.9452878 17 -16.9536453 4.0817887 18 1.2719307 -16.9536453 19 -5.8947731 1.2719307 20 -9.2229096 -5.8947731 21 -2.9368181 -9.2229096 22 -2.9702197 -2.9368181 23 -20.0838895 -2.9702197 24 -22.4881660 -20.0838895 25 -2.0526387 -22.4881660 26 -20.9570404 -2.0526387 27 -4.5473618 -20.9570404 28 -13.2149021 -4.5473618 29 -12.1078244 -13.2149021 30 7.0459710 -12.1078244 31 -5.3225669 7.0459710 32 -5.1619706 -5.3225669 33 -16.1983325 -5.1619706 34 -10.9468361 -16.1983325 35 -7.4139431 -10.9468361 36 -19.1709088 -7.4139431 37 -19.7715973 -19.1709088 38 -11.2419956 -19.7715973 39 1.4026749 -11.2419956 40 -14.1831196 1.4026749 41 -4.1165016 -14.1831196 42 5.6788072 -4.1165016 43 -4.5319250 5.6788072 44 -0.8866229 -4.5319250 45 -12.6454248 -0.8866229 46 -5.8906335 -12.6454248 47 15.4853566 -5.8906335 48 10.1683080 15.4853566 49 -1.5383091 10.1683080 50 14.2802151 -1.5383091 51 -9.2157930 14.2802151 52 -8.7172614 -9.2157930 53 19.2811820 -8.7172614 54 -4.0001125 19.2811820 55 -5.3176406 -4.0001125 56 -3.7920419 -5.3176406 57 3.9021108 -3.7920419 58 -0.3508719 3.9021108 59 -0.1956794 -0.3508719 60 -7.6074281 -0.1956794 61 -0.7661210 -7.6074281 62 7.1625169 -0.7661210 63 8.5176949 7.1625169 64 36.0773049 8.5176949 65 17.0318670 36.0773049 66 -2.0479020 17.0318670 67 18.4122991 -2.0479020 68 21.4433612 18.4122991 69 -0.4701824 21.4433612 70 16.0986421 -0.4701824 71 31.3172301 16.0986421 72 44.3855027 31.3172301 73 13.5095965 44.3855027 74 22.2186908 13.5095965 75 5.9016793 22.2186908 76 19.9296880 5.9016793 77 10.5148076 19.9296880 78 3.3124845 10.5148076 79 10.1884668 3.3124845 80 13.5057611 10.1884668 81 12.9887463 13.5057611 82 12.1543544 12.9887463 83 8.8095294 12.1543544 84 -3.6498295 8.8095294 85 -10.8700163 -3.6498295 86 -6.0128441 -10.8700163 87 -12.5073701 -6.0128441 88 -17.9084633 -12.5073701 89 3.5487223 -17.9084633 90 -3.5105290 3.5487223 91 -0.6494106 -3.5105290 92 -14.0786975 -0.6494106 93 36.1499387 -14.0786975 94 4.9695678 36.1499387 95 -20.6977040 4.9695678 96 -7.5954293 -20.6977040 97 2.6586714 -7.5954293 98 -23.2698393 2.6586714 99 -5.3608928 -23.2698393 100 -19.9892606 -5.3608928 101 -11.4957699 -19.9892606 102 -11.9086609 -11.4957699 103 -18.8709131 -11.9086609 104 -6.1868569 -18.8709131 105 -19.7565162 -6.1868569 106 -11.7196981 -19.7565162 107 1.2924938 -11.7196981 > 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/7hiit1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8x8hh1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9wm921258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10darg1258618159.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11sl0b1258618159.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/12y4pb1258618159.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/137vk91258618159.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/14y63p1258618159.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/15szl81258618159.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/16g6901258618159.tab") + } > system("convert tmp/1ihhg1258618159.ps tmp/1ihhg1258618159.png") > system("convert tmp/2kt9v1258618159.ps tmp/2kt9v1258618159.png") > system("convert tmp/3adhp1258618159.ps tmp/3adhp1258618159.png") > system("convert tmp/46c2e1258618159.ps tmp/46c2e1258618159.png") > system("convert tmp/5kprj1258618159.ps tmp/5kprj1258618159.png") > system("convert tmp/6a6dk1258618159.ps tmp/6a6dk1258618159.png") > system("convert tmp/7hiit1258618159.ps tmp/7hiit1258618159.png") > system("convert tmp/8x8hh1258618159.ps tmp/8x8hh1258618159.png") > system("convert tmp/9wm921258618159.ps tmp/9wm921258618159.png") > system("convert tmp/10darg1258618159.ps tmp/10darg1258618159.png") > > > proc.time() user system elapsed 3.073 1.611 4.104