R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(0 + ,1.3954 + ,1.0685 + ,0 + ,1.4790 + ,1.1010 + ,0 + ,1.4619 + ,1.0996 + ,0 + ,1.4670 + ,1.0978 + ,0 + ,1.4799 + ,1.0893 + ,0 + ,1.4508 + ,1.1018 + ,0 + ,1.4678 + ,1.0931 + ,0 + ,1.4824 + ,1.0842 + ,0 + ,1.5189 + ,1.0409 + ,0 + ,1.5348 + ,1.0245 + ,0 + ,1.5666 + ,0.9994 + ,0 + ,1.5446 + ,1.0090 + ,0 + ,1.5803 + ,0.9947 + ,0 + ,1.5718 + ,1.0080 + ,0 + ,1.5832 + ,0.9986 + ,0 + ,1.5801 + ,1.0184 + ,0 + ,1.5605 + ,1.0357 + ,0 + ,1.5416 + ,1.0556 + ,0 + ,1.5479 + ,1.0409 + ,0 + ,1.5580 + ,1.0474 + ,0 + ,1.5790 + ,1.0219 + ,0 + ,1.5554 + ,1.0427 + ,0 + ,1.5761 + ,1.0205 + ,0 + ,1.5360 + ,1.0490 + ,0 + ,1.5621 + ,1.0344 + ,0 + ,1.5773 + ,1.0193 + ,0 + ,1.5710 + ,1.0238 + ,0 + ,1.5925 + ,1.0165 + ,0 + ,1.5844 + ,1.0218 + ,0 + ,1.5696 + ,1.0370 + ,0 + ,1.5540 + ,1.0508 + ,0 + ,1.5012 + ,1.0813 + ,0 + ,1.4676 + ,1.0970 + ,0 + ,1.4770 + ,1.0989 + ,0 + ,1.4660 + ,1.1018 + ,0 + ,1.4241 + ,1.1166 + ,0 + ,1.4214 + ,1.1319 + ,1 + ,1.4469 + ,1.1020 + ,1 + ,1.4618 + ,1.0884 + ,1 + ,1.3834 + ,1.1263 + ,1 + ,1.3412 + ,1.1345 + ,1 + ,1.3437 + ,1.1337 + ,1 + ,1.2630 + ,1.1660 + ,1 + ,1.2759 + ,1.1550 + ,1 + ,1.2743 + ,1.1782 + ,1 + ,1.2797 + ,1.1856 + ,1 + ,1.2573 + ,1.2219 + ,1 + ,1.2705 + ,1.2130 + ,1 + ,1.2680 + ,1.2230 + ,1 + ,1.3371 + ,1.1767 + ,1 + ,1.3885 + ,1.1077 + ,1 + ,1.4060 + ,1.0672 + ,1 + ,1.3855 + ,1.0840 + ,1 + ,1.3431 + ,1.1154 + ,1 + ,1.3257 + ,1.1184 + ,1 + ,1.2978 + ,1.1570 + ,1 + ,1.2793 + ,1.1625 + ,1 + ,1.2945 + ,1.1627 + ,1 + ,1.2890 + ,1.1578 + ,1 + ,1.2848 + ,1.1533 + ,1 + ,1.2694 + ,1.1684 + ,1 + ,1.2636 + ,1.1597 + ,1 + ,1.2900 + ,1.1888 + ,1 + ,1.3559 + ,1.1296 + ,1 + ,1.3305 + ,1.1424 + ,1 + ,1.3482 + ,1.1317 + ,1 + ,1.3146 + ,1.1581 + ,1 + ,1.3027 + ,1.1672 + ,1 + ,1.3247 + ,1.1391 + ,1 + ,1.3267 + ,1.1357 + ,1 + ,1.3621 + ,1.1065 + ,1 + ,1.3479 + ,1.1232 + ,1 + ,1.4011 + ,1.0845 + ,1 + ,1.4135 + ,1.0676 + ,1 + ,1.3964 + ,1.0863 + ,1 + ,1.4010 + ,1.0792 + ,1 + ,1.3955 + ,1.0799 + ,1 + ,1.4077 + ,1.0817 + ,1 + ,1.3975 + ,1.0869 + ,1 + ,1.3949 + ,1.0843 + ,1 + ,1.4138 + ,1.0747 + ,1 + ,1.4210 + ,1.0711 + ,1 + ,1.4253 + ,1.0688 + ,1 + ,1.4169 + ,1.0828 + ,1 + ,1.4174 + ,1.0746 + ,1 + ,1.4346 + ,1.0568 + ,1 + ,1.4296 + ,1.0600 + ,1 + ,1.4311 + ,1.0593 + ,1 + ,1.4594 + ,1.0370 + ,1 + ,1.4722 + ,1.0288 + ,1 + ,1.4669 + ,1.0295 + ,1 + ,1.4571 + ,1.0352 + ,1 + ,1.4709 + ,1.0324 + ,1 + ,1.4893 + ,1.0186 + ,1 + ,1.4997 + ,1.0094 + ,1 + ,1.4713 + ,1.0258 + ,1 + ,1.4846 + ,1.0170 + ,1 + ,1.4914 + ,1.0117 + ,1 + ,1.4859 + ,1.0175 + ,1 + ,1.4957 + ,1.0064 + ,1 + ,1.4843 + ,1.0168 + ,1 + ,1.4619 + ,1.0340 + ,1 + ,1.4340 + ,1.0423 + ,1 + ,1.4426 + ,1.0356 + ,1 + ,1.4318 + ,1.0348) + ,dim=c(3 + ,105) + ,dimnames=list(c('Crisis' + ,'eu/us' + ,'us/ch') + ,1:105)) > y <- array(NA,dim=c(3,105),dimnames=list(c('Crisis','eu/us','us/ch'),1:105)) > 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 = 'Do not include Seasonal Dummies' > par1 = '2' > #'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 eu/us Crisis us/ch 1 1.3954 0 1.0685 2 1.4790 0 1.1010 3 1.4619 0 1.0996 4 1.4670 0 1.0978 5 1.4799 0 1.0893 6 1.4508 0 1.1018 7 1.4678 0 1.0931 8 1.4824 0 1.0842 9 1.5189 0 1.0409 10 1.5348 0 1.0245 11 1.5666 0 0.9994 12 1.5446 0 1.0090 13 1.5803 0 0.9947 14 1.5718 0 1.0080 15 1.5832 0 0.9986 16 1.5801 0 1.0184 17 1.5605 0 1.0357 18 1.5416 0 1.0556 19 1.5479 0 1.0409 20 1.5580 0 1.0474 21 1.5790 0 1.0219 22 1.5554 0 1.0427 23 1.5761 0 1.0205 24 1.5360 0 1.0490 25 1.5621 0 1.0344 26 1.5773 0 1.0193 27 1.5710 0 1.0238 28 1.5925 0 1.0165 29 1.5844 0 1.0218 30 1.5696 0 1.0370 31 1.5540 0 1.0508 32 1.5012 0 1.0813 33 1.4676 0 1.0970 34 1.4770 0 1.0989 35 1.4660 0 1.1018 36 1.4241 0 1.1166 37 1.4214 0 1.1319 38 1.4469 1 1.1020 39 1.4618 1 1.0884 40 1.3834 1 1.1263 41 1.3412 1 1.1345 42 1.3437 1 1.1337 43 1.2630 1 1.1660 44 1.2759 1 1.1550 45 1.2743 1 1.1782 46 1.2797 1 1.1856 47 1.2573 1 1.2219 48 1.2705 1 1.2130 49 1.2680 1 1.2230 50 1.3371 1 1.1767 51 1.3885 1 1.1077 52 1.4060 1 1.0672 53 1.3855 1 1.0840 54 1.3431 1 1.1154 55 1.3257 1 1.1184 56 1.2978 1 1.1570 57 1.2793 1 1.1625 58 1.2945 1 1.1627 59 1.2890 1 1.1578 60 1.2848 1 1.1533 61 1.2694 1 1.1684 62 1.2636 1 1.1597 63 1.2900 1 1.1888 64 1.3559 1 1.1296 65 1.3305 1 1.1424 66 1.3482 1 1.1317 67 1.3146 1 1.1581 68 1.3027 1 1.1672 69 1.3247 1 1.1391 70 1.3267 1 1.1357 71 1.3621 1 1.1065 72 1.3479 1 1.1232 73 1.4011 1 1.0845 74 1.4135 1 1.0676 75 1.3964 1 1.0863 76 1.4010 1 1.0792 77 1.3955 1 1.0799 78 1.4077 1 1.0817 79 1.3975 1 1.0869 80 1.3949 1 1.0843 81 1.4138 1 1.0747 82 1.4210 1 1.0711 83 1.4253 1 1.0688 84 1.4169 1 1.0828 85 1.4174 1 1.0746 86 1.4346 1 1.0568 87 1.4296 1 1.0600 88 1.4311 1 1.0593 89 1.4594 1 1.0370 90 1.4722 1 1.0288 91 1.4669 1 1.0295 92 1.4571 1 1.0352 93 1.4709 1 1.0324 94 1.4893 1 1.0186 95 1.4997 1 1.0094 96 1.4713 1 1.0258 97 1.4846 1 1.0170 98 1.4914 1 1.0117 99 1.4859 1 1.0175 100 1.4957 1 1.0064 101 1.4843 1 1.0168 102 1.4619 1 1.0340 103 1.4340 1 1.0423 104 1.4426 1 1.0356 105 1.4318 1 1.0348 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Crisis `us/ch` 2.81719 -0.08588 -1.22772 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.109967 -0.009989 0.001241 0.010754 0.068543 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.817188 0.044156 63.80 <2e-16 *** Crisis -0.085881 0.004943 -17.37 <2e-16 *** `us/ch` -1.227722 0.041776 -29.39 <2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.02227 on 102 degrees of freedom Multiple R-squared: 0.9477, Adjusted R-squared: 0.9466 F-statistic: 923.4 on 2 and 102 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,] 0.7744735 4.510531e-01 2.255265e-01 [2,] 0.6745683 6.508635e-01 3.254317e-01 [3,] 0.8496257 3.007485e-01 1.503743e-01 [4,] 0.9960153 7.969424e-03 3.984712e-03 [5,] 0.9965972 6.805534e-03 3.402767e-03 [6,] 0.9962246 7.550865e-03 3.775432e-03 [7,] 0.9951009 9.798115e-03 4.899058e-03 [8,] 0.9943017 1.139658e-02 5.698289e-03 [9,] 0.9930348 1.393043e-02 6.965215e-03 [10,] 0.9912012 1.759758e-02 8.798791e-03 [11,] 0.9929594 1.408125e-02 7.040625e-03 [12,] 0.9935833 1.283334e-02 6.416669e-03 [13,] 0.9946784 1.064312e-02 5.321561e-03 [14,] 0.9931566 1.368675e-02 6.843375e-03 [15,] 0.9952151 9.569811e-03 4.784905e-03 [16,] 0.9946471 1.070585e-02 5.352924e-03 [17,] 0.9940251 1.194985e-02 5.974926e-03 [18,] 0.9919896 1.602075e-02 8.010373e-03 [19,] 0.9884080 2.318393e-02 1.159197e-02 [20,] 0.9853736 2.925276e-02 1.462638e-02 [21,] 0.9803465 3.930694e-02 1.965347e-02 [22,] 0.9734895 5.302106e-02 2.651053e-02 [23,] 0.9719398 5.612049e-02 2.806025e-02 [24,] 0.9688463 6.230747e-02 3.115374e-02 [25,] 0.9696117 6.077655e-02 3.038828e-02 [26,] 0.9728753 5.424933e-02 2.712467e-02 [27,] 0.9658850 6.822991e-02 3.411496e-02 [28,] 0.9527021 9.459587e-02 4.729793e-02 [29,] 0.9413420 1.173160e-01 5.865800e-02 [30,] 0.9245647 1.508706e-01 7.543529e-02 [31,] 0.9136853 1.726294e-01 8.631468e-02 [32,] 0.8878355 2.243290e-01 1.121645e-01 [33,] 0.9542500 9.150002e-02 4.575001e-02 [34,] 0.9890349 2.193016e-02 1.096508e-02 [35,] 0.9937597 1.248054e-02 6.240271e-03 [36,] 0.9960850 7.829945e-03 3.914972e-03 [37,] 0.9962877 7.424587e-03 3.712293e-03 [38,] 0.9994197 1.160510e-03 5.802550e-04 [39,] 0.9998929 2.142723e-04 1.071362e-04 [40,] 0.9998483 3.033362e-04 1.516681e-04 [41,] 0.9997394 5.212277e-04 2.606139e-04 [42,] 0.9998030 3.940430e-04 1.970215e-04 [43,] 0.9998789 2.422449e-04 1.211224e-04 [44,] 0.9999814 3.727864e-05 1.863932e-05 [45,] 0.9999999 1.691560e-07 8.457800e-08 [46,] 0.9999999 1.166129e-07 5.830644e-08 [47,] 1.0000000 9.615316e-08 4.807658e-08 [48,] 0.9999999 1.056901e-07 5.284503e-08 [49,] 0.9999999 1.095723e-07 5.478616e-08 [50,] 1.0000000 2.267195e-08 1.133598e-08 [51,] 1.0000000 4.254555e-08 2.127277e-08 [52,] 1.0000000 3.422031e-08 1.711015e-08 [53,] 1.0000000 7.431792e-08 3.715896e-08 [54,] 1.0000000 8.373859e-08 4.186930e-08 [55,] 1.0000000 2.326027e-08 1.163014e-08 [56,] 1.0000000 7.531308e-09 3.765654e-09 [57,] 1.0000000 2.702431e-12 1.351216e-12 [58,] 1.0000000 1.683575e-12 8.417876e-13 [59,] 1.0000000 2.300362e-12 1.150181e-12 [60,] 1.0000000 7.506302e-12 3.753151e-12 [61,] 1.0000000 1.717127e-11 8.585634e-12 [62,] 1.0000000 3.828914e-11 1.914457e-11 [63,] 1.0000000 7.294540e-11 3.647270e-11 [64,] 1.0000000 2.187889e-10 1.093944e-10 [65,] 1.0000000 5.253142e-10 2.626571e-10 [66,] 1.0000000 9.928607e-10 4.964304e-10 [67,] 1.0000000 2.910660e-09 1.455330e-09 [68,] 1.0000000 8.927992e-09 4.463996e-09 [69,] 1.0000000 2.107875e-08 1.053938e-08 [70,] 1.0000000 6.306029e-08 3.153015e-08 [71,] 0.9999999 1.580844e-07 7.904219e-08 [72,] 0.9999999 2.442641e-07 1.221321e-07 [73,] 0.9999997 6.729048e-07 3.364524e-07 [74,] 0.9999990 1.900177e-06 9.500886e-07 [75,] 0.9999979 4.105890e-06 2.052945e-06 [76,] 0.9999944 1.114741e-05 5.573705e-06 [77,] 0.9999859 2.828005e-05 1.414003e-05 [78,] 0.9999675 6.496692e-05 3.248346e-05 [79,] 0.9999753 4.941548e-05 2.470774e-05 [80,] 0.9999656 6.889638e-05 3.444819e-05 [81,] 0.9999287 1.425918e-04 7.129590e-05 [82,] 0.9998743 2.514904e-04 1.257452e-04 [83,] 0.9998862 2.276097e-04 1.138048e-04 [84,] 0.9998030 3.939036e-04 1.969518e-04 [85,] 0.9996289 7.421663e-04 3.710832e-04 [86,] 0.9991115 1.776997e-03 8.884983e-04 [87,] 0.9980651 3.869883e-03 1.934941e-03 [88,] 0.9987708 2.458389e-03 1.229194e-03 [89,] 0.9978949 4.210240e-03 2.105120e-03 [90,] 0.9940681 1.186383e-02 5.931913e-03 [91,] 0.9866387 2.672251e-02 1.336126e-02 [92,] 0.9659768 6.804638e-02 3.402319e-02 [93,] 0.9155470 1.689059e-01 8.445295e-02 [94,] 0.8302852 3.394296e-01 1.697148e-01 > postscript(file="/var/www/html/freestat/rcomp/tmp/19ggy1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/29ggy1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/39ggy1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/42pf11290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/52pf11290506277.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 = 105 Frequency = 1 1 2 3 4 5 -1.099668e-01 1.353421e-02 -5.284601e-03 -2.394501e-03 6.985770e-05 6 7 8 9 10 -1.368361e-02 -7.364797e-03 -3.691527e-03 -2.035191e-02 -2.458656e-02 11 12 13 14 15 -2.360239e-02 -3.381626e-02 -1.567269e-02 -7.843978e-03 -7.984570e-03 16 17 18 19 20 1.322434e-02 1.486393e-02 2.039561e-02 8.648091e-03 2.672829e-02 21 22 23 24 25 1.642136e-02 1.835799e-02 1.180255e-02 6.692643e-03 1.486789e-02 26 27 28 29 30 1.152929e-02 1.075404e-02 2.329166e-02 2.169859e-02 2.555997e-02 31 32 33 34 35 2.690254e-02 1.154808e-02 -2.776679e-03 8.955993e-03 1.516388e-03 36 37 38 39 40 -2.221332e-02 -6.129165e-03 6.854333e-02 6.674631e-02 3.487699e-02 41 42 43 44 45 2.744311e-03 4.262133e-03 -3.678243e-02 -3.738738e-02 -1.050422e-02 46 47 48 49 50 3.980928e-03 2.614725e-02 2.842052e-02 3.819775e-02 5.045420e-02 51 52 53 54 55 1.714135e-02 -1.508141e-02 -1.495567e-02 -1.880519e-02 -3.252202e-02 56 57 58 59 60 -1.303193e-02 -2.477946e-02 -9.333916e-03 -2.084976e-02 -3.057451e-02 61 62 63 64 65 -2.743590e-02 -4.391708e-02 1.820964e-02 1.142847e-02 1.743318e-03 66 67 68 69 70 6.306688e-03 5.118561e-03 4.390835e-03 -8.108166e-03 -1.028242e-02 71 72 73 74 75 -1.073192e-02 -4.428953e-03 1.258188e-03 -7.090322e-03 -1.231912e-03 76 77 78 79 80 -5.348741e-03 -9.989336e-03 4.420565e-03 6.047215e-04 -5.187357e-03 81 82 83 84 85 1.926507e-03 4.706707e-03 6.182945e-03 1.497106e-02 5.403735e-03 86 87 88 89 90 7.502754e-04 -3.210127e-04 3.195815e-04 1.241371e-03 3.974046e-03 91 92 93 94 95 -4.665478e-04 -3.268530e-03 7.093847e-03 8.551277e-03 7.656231e-03 96 97 98 99 100 -6.091209e-04 1.886921e-03 2.179992e-03 3.800783e-03 -2.693667e-05 101 102 103 104 105 1.341377e-03 5.820326e-05 -1.765170e-02 -1.727744e-02 -2.905962e-02 > postscript(file="/var/www/html/freestat/rcomp/tmp/62pf11290506277.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 = 105 Frequency = 1 lag(myerror, k = 1) myerror 0 -1.099668e-01 NA 1 1.353421e-02 -1.099668e-01 2 -5.284601e-03 1.353421e-02 3 -2.394501e-03 -5.284601e-03 4 6.985770e-05 -2.394501e-03 5 -1.368361e-02 6.985770e-05 6 -7.364797e-03 -1.368361e-02 7 -3.691527e-03 -7.364797e-03 8 -2.035191e-02 -3.691527e-03 9 -2.458656e-02 -2.035191e-02 10 -2.360239e-02 -2.458656e-02 11 -3.381626e-02 -2.360239e-02 12 -1.567269e-02 -3.381626e-02 13 -7.843978e-03 -1.567269e-02 14 -7.984570e-03 -7.843978e-03 15 1.322434e-02 -7.984570e-03 16 1.486393e-02 1.322434e-02 17 2.039561e-02 1.486393e-02 18 8.648091e-03 2.039561e-02 19 2.672829e-02 8.648091e-03 20 1.642136e-02 2.672829e-02 21 1.835799e-02 1.642136e-02 22 1.180255e-02 1.835799e-02 23 6.692643e-03 1.180255e-02 24 1.486789e-02 6.692643e-03 25 1.152929e-02 1.486789e-02 26 1.075404e-02 1.152929e-02 27 2.329166e-02 1.075404e-02 28 2.169859e-02 2.329166e-02 29 2.555997e-02 2.169859e-02 30 2.690254e-02 2.555997e-02 31 1.154808e-02 2.690254e-02 32 -2.776679e-03 1.154808e-02 33 8.955993e-03 -2.776679e-03 34 1.516388e-03 8.955993e-03 35 -2.221332e-02 1.516388e-03 36 -6.129165e-03 -2.221332e-02 37 6.854333e-02 -6.129165e-03 38 6.674631e-02 6.854333e-02 39 3.487699e-02 6.674631e-02 40 2.744311e-03 3.487699e-02 41 4.262133e-03 2.744311e-03 42 -3.678243e-02 4.262133e-03 43 -3.738738e-02 -3.678243e-02 44 -1.050422e-02 -3.738738e-02 45 3.980928e-03 -1.050422e-02 46 2.614725e-02 3.980928e-03 47 2.842052e-02 2.614725e-02 48 3.819775e-02 2.842052e-02 49 5.045420e-02 3.819775e-02 50 1.714135e-02 5.045420e-02 51 -1.508141e-02 1.714135e-02 52 -1.495567e-02 -1.508141e-02 53 -1.880519e-02 -1.495567e-02 54 -3.252202e-02 -1.880519e-02 55 -1.303193e-02 -3.252202e-02 56 -2.477946e-02 -1.303193e-02 57 -9.333916e-03 -2.477946e-02 58 -2.084976e-02 -9.333916e-03 59 -3.057451e-02 -2.084976e-02 60 -2.743590e-02 -3.057451e-02 61 -4.391708e-02 -2.743590e-02 62 1.820964e-02 -4.391708e-02 63 1.142847e-02 1.820964e-02 64 1.743318e-03 1.142847e-02 65 6.306688e-03 1.743318e-03 66 5.118561e-03 6.306688e-03 67 4.390835e-03 5.118561e-03 68 -8.108166e-03 4.390835e-03 69 -1.028242e-02 -8.108166e-03 70 -1.073192e-02 -1.028242e-02 71 -4.428953e-03 -1.073192e-02 72 1.258188e-03 -4.428953e-03 73 -7.090322e-03 1.258188e-03 74 -1.231912e-03 -7.090322e-03 75 -5.348741e-03 -1.231912e-03 76 -9.989336e-03 -5.348741e-03 77 4.420565e-03 -9.989336e-03 78 6.047215e-04 4.420565e-03 79 -5.187357e-03 6.047215e-04 80 1.926507e-03 -5.187357e-03 81 4.706707e-03 1.926507e-03 82 6.182945e-03 4.706707e-03 83 1.497106e-02 6.182945e-03 84 5.403735e-03 1.497106e-02 85 7.502754e-04 5.403735e-03 86 -3.210127e-04 7.502754e-04 87 3.195815e-04 -3.210127e-04 88 1.241371e-03 3.195815e-04 89 3.974046e-03 1.241371e-03 90 -4.665478e-04 3.974046e-03 91 -3.268530e-03 -4.665478e-04 92 7.093847e-03 -3.268530e-03 93 8.551277e-03 7.093847e-03 94 7.656231e-03 8.551277e-03 95 -6.091209e-04 7.656231e-03 96 1.886921e-03 -6.091209e-04 97 2.179992e-03 1.886921e-03 98 3.800783e-03 2.179992e-03 99 -2.693667e-05 3.800783e-03 100 1.341377e-03 -2.693667e-05 101 5.820326e-05 1.341377e-03 102 -1.765170e-02 5.820326e-05 103 -1.727744e-02 -1.765170e-02 104 -2.905962e-02 -1.727744e-02 105 NA -2.905962e-02 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 1.353421e-02 -1.099668e-01 [2,] -5.284601e-03 1.353421e-02 [3,] -2.394501e-03 -5.284601e-03 [4,] 6.985770e-05 -2.394501e-03 [5,] -1.368361e-02 6.985770e-05 [6,] -7.364797e-03 -1.368361e-02 [7,] -3.691527e-03 -7.364797e-03 [8,] -2.035191e-02 -3.691527e-03 [9,] -2.458656e-02 -2.035191e-02 [10,] -2.360239e-02 -2.458656e-02 [11,] -3.381626e-02 -2.360239e-02 [12,] -1.567269e-02 -3.381626e-02 [13,] -7.843978e-03 -1.567269e-02 [14,] -7.984570e-03 -7.843978e-03 [15,] 1.322434e-02 -7.984570e-03 [16,] 1.486393e-02 1.322434e-02 [17,] 2.039561e-02 1.486393e-02 [18,] 8.648091e-03 2.039561e-02 [19,] 2.672829e-02 8.648091e-03 [20,] 1.642136e-02 2.672829e-02 [21,] 1.835799e-02 1.642136e-02 [22,] 1.180255e-02 1.835799e-02 [23,] 6.692643e-03 1.180255e-02 [24,] 1.486789e-02 6.692643e-03 [25,] 1.152929e-02 1.486789e-02 [26,] 1.075404e-02 1.152929e-02 [27,] 2.329166e-02 1.075404e-02 [28,] 2.169859e-02 2.329166e-02 [29,] 2.555997e-02 2.169859e-02 [30,] 2.690254e-02 2.555997e-02 [31,] 1.154808e-02 2.690254e-02 [32,] -2.776679e-03 1.154808e-02 [33,] 8.955993e-03 -2.776679e-03 [34,] 1.516388e-03 8.955993e-03 [35,] -2.221332e-02 1.516388e-03 [36,] -6.129165e-03 -2.221332e-02 [37,] 6.854333e-02 -6.129165e-03 [38,] 6.674631e-02 6.854333e-02 [39,] 3.487699e-02 6.674631e-02 [40,] 2.744311e-03 3.487699e-02 [41,] 4.262133e-03 2.744311e-03 [42,] -3.678243e-02 4.262133e-03 [43,] -3.738738e-02 -3.678243e-02 [44,] -1.050422e-02 -3.738738e-02 [45,] 3.980928e-03 -1.050422e-02 [46,] 2.614725e-02 3.980928e-03 [47,] 2.842052e-02 2.614725e-02 [48,] 3.819775e-02 2.842052e-02 [49,] 5.045420e-02 3.819775e-02 [50,] 1.714135e-02 5.045420e-02 [51,] -1.508141e-02 1.714135e-02 [52,] -1.495567e-02 -1.508141e-02 [53,] -1.880519e-02 -1.495567e-02 [54,] -3.252202e-02 -1.880519e-02 [55,] -1.303193e-02 -3.252202e-02 [56,] -2.477946e-02 -1.303193e-02 [57,] -9.333916e-03 -2.477946e-02 [58,] -2.084976e-02 -9.333916e-03 [59,] -3.057451e-02 -2.084976e-02 [60,] -2.743590e-02 -3.057451e-02 [61,] -4.391708e-02 -2.743590e-02 [62,] 1.820964e-02 -4.391708e-02 [63,] 1.142847e-02 1.820964e-02 [64,] 1.743318e-03 1.142847e-02 [65,] 6.306688e-03 1.743318e-03 [66,] 5.118561e-03 6.306688e-03 [67,] 4.390835e-03 5.118561e-03 [68,] -8.108166e-03 4.390835e-03 [69,] -1.028242e-02 -8.108166e-03 [70,] -1.073192e-02 -1.028242e-02 [71,] -4.428953e-03 -1.073192e-02 [72,] 1.258188e-03 -4.428953e-03 [73,] -7.090322e-03 1.258188e-03 [74,] -1.231912e-03 -7.090322e-03 [75,] -5.348741e-03 -1.231912e-03 [76,] -9.989336e-03 -5.348741e-03 [77,] 4.420565e-03 -9.989336e-03 [78,] 6.047215e-04 4.420565e-03 [79,] -5.187357e-03 6.047215e-04 [80,] 1.926507e-03 -5.187357e-03 [81,] 4.706707e-03 1.926507e-03 [82,] 6.182945e-03 4.706707e-03 [83,] 1.497106e-02 6.182945e-03 [84,] 5.403735e-03 1.497106e-02 [85,] 7.502754e-04 5.403735e-03 [86,] -3.210127e-04 7.502754e-04 [87,] 3.195815e-04 -3.210127e-04 [88,] 1.241371e-03 3.195815e-04 [89,] 3.974046e-03 1.241371e-03 [90,] -4.665478e-04 3.974046e-03 [91,] -3.268530e-03 -4.665478e-04 [92,] 7.093847e-03 -3.268530e-03 [93,] 8.551277e-03 7.093847e-03 [94,] 7.656231e-03 8.551277e-03 [95,] -6.091209e-04 7.656231e-03 [96,] 1.886921e-03 -6.091209e-04 [97,] 2.179992e-03 1.886921e-03 [98,] 3.800783e-03 2.179992e-03 [99,] -2.693667e-05 3.800783e-03 [100,] 1.341377e-03 -2.693667e-05 [101,] 5.820326e-05 1.341377e-03 [102,] -1.765170e-02 5.820326e-05 [103,] -1.727744e-02 -1.765170e-02 [104,] -2.905962e-02 -1.727744e-02 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 1.353421e-02 -1.099668e-01 2 -5.284601e-03 1.353421e-02 3 -2.394501e-03 -5.284601e-03 4 6.985770e-05 -2.394501e-03 5 -1.368361e-02 6.985770e-05 6 -7.364797e-03 -1.368361e-02 7 -3.691527e-03 -7.364797e-03 8 -2.035191e-02 -3.691527e-03 9 -2.458656e-02 -2.035191e-02 10 -2.360239e-02 -2.458656e-02 11 -3.381626e-02 -2.360239e-02 12 -1.567269e-02 -3.381626e-02 13 -7.843978e-03 -1.567269e-02 14 -7.984570e-03 -7.843978e-03 15 1.322434e-02 -7.984570e-03 16 1.486393e-02 1.322434e-02 17 2.039561e-02 1.486393e-02 18 8.648091e-03 2.039561e-02 19 2.672829e-02 8.648091e-03 20 1.642136e-02 2.672829e-02 21 1.835799e-02 1.642136e-02 22 1.180255e-02 1.835799e-02 23 6.692643e-03 1.180255e-02 24 1.486789e-02 6.692643e-03 25 1.152929e-02 1.486789e-02 26 1.075404e-02 1.152929e-02 27 2.329166e-02 1.075404e-02 28 2.169859e-02 2.329166e-02 29 2.555997e-02 2.169859e-02 30 2.690254e-02 2.555997e-02 31 1.154808e-02 2.690254e-02 32 -2.776679e-03 1.154808e-02 33 8.955993e-03 -2.776679e-03 34 1.516388e-03 8.955993e-03 35 -2.221332e-02 1.516388e-03 36 -6.129165e-03 -2.221332e-02 37 6.854333e-02 -6.129165e-03 38 6.674631e-02 6.854333e-02 39 3.487699e-02 6.674631e-02 40 2.744311e-03 3.487699e-02 41 4.262133e-03 2.744311e-03 42 -3.678243e-02 4.262133e-03 43 -3.738738e-02 -3.678243e-02 44 -1.050422e-02 -3.738738e-02 45 3.980928e-03 -1.050422e-02 46 2.614725e-02 3.980928e-03 47 2.842052e-02 2.614725e-02 48 3.819775e-02 2.842052e-02 49 5.045420e-02 3.819775e-02 50 1.714135e-02 5.045420e-02 51 -1.508141e-02 1.714135e-02 52 -1.495567e-02 -1.508141e-02 53 -1.880519e-02 -1.495567e-02 54 -3.252202e-02 -1.880519e-02 55 -1.303193e-02 -3.252202e-02 56 -2.477946e-02 -1.303193e-02 57 -9.333916e-03 -2.477946e-02 58 -2.084976e-02 -9.333916e-03 59 -3.057451e-02 -2.084976e-02 60 -2.743590e-02 -3.057451e-02 61 -4.391708e-02 -2.743590e-02 62 1.820964e-02 -4.391708e-02 63 1.142847e-02 1.820964e-02 64 1.743318e-03 1.142847e-02 65 6.306688e-03 1.743318e-03 66 5.118561e-03 6.306688e-03 67 4.390835e-03 5.118561e-03 68 -8.108166e-03 4.390835e-03 69 -1.028242e-02 -8.108166e-03 70 -1.073192e-02 -1.028242e-02 71 -4.428953e-03 -1.073192e-02 72 1.258188e-03 -4.428953e-03 73 -7.090322e-03 1.258188e-03 74 -1.231912e-03 -7.090322e-03 75 -5.348741e-03 -1.231912e-03 76 -9.989336e-03 -5.348741e-03 77 4.420565e-03 -9.989336e-03 78 6.047215e-04 4.420565e-03 79 -5.187357e-03 6.047215e-04 80 1.926507e-03 -5.187357e-03 81 4.706707e-03 1.926507e-03 82 6.182945e-03 4.706707e-03 83 1.497106e-02 6.182945e-03 84 5.403735e-03 1.497106e-02 85 7.502754e-04 5.403735e-03 86 -3.210127e-04 7.502754e-04 87 3.195815e-04 -3.210127e-04 88 1.241371e-03 3.195815e-04 89 3.974046e-03 1.241371e-03 90 -4.665478e-04 3.974046e-03 91 -3.268530e-03 -4.665478e-04 92 7.093847e-03 -3.268530e-03 93 8.551277e-03 7.093847e-03 94 7.656231e-03 8.551277e-03 95 -6.091209e-04 7.656231e-03 96 1.886921e-03 -6.091209e-04 97 2.179992e-03 1.886921e-03 98 3.800783e-03 2.179992e-03 99 -2.693667e-05 3.800783e-03 100 1.341377e-03 -2.693667e-05 101 5.820326e-05 1.341377e-03 102 -1.765170e-02 5.820326e-05 103 -1.727744e-02 -1.765170e-02 104 -2.905962e-02 -1.727744e-02 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/7cyem1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/858e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/958e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/1058e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/111hcg1290506277.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/1250a41290506277.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/1319qc1290506277.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/14ma6i1290506277.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/15pbno1290506277.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/16bt3c1290506277.tab") + } > > try(system("convert tmp/19ggy1290506277.ps tmp/19ggy1290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/29ggy1290506277.ps tmp/29ggy1290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/39ggy1290506277.ps tmp/39ggy1290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/42pf11290506277.ps tmp/42pf11290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/52pf11290506277.ps tmp/52pf11290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/62pf11290506277.ps tmp/62pf11290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/7cyem1290506277.ps tmp/7cyem1290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/858e71290506277.ps tmp/858e71290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/958e71290506277.ps tmp/958e71290506277.png",intern=TRUE)) character(0) > try(system("convert tmp/1058e71290506277.ps tmp/1058e71290506277.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.492 2.545 5.233