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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 = '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 > 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 t 1 1.3954 0 1.0685 1 2 1.4790 0 1.1010 2 3 1.4619 0 1.0996 3 4 1.4670 0 1.0978 4 5 1.4799 0 1.0893 5 6 1.4508 0 1.1018 6 7 1.4678 0 1.0931 7 8 1.4824 0 1.0842 8 9 1.5189 0 1.0409 9 10 1.5348 0 1.0245 10 11 1.5666 0 0.9994 11 12 1.5446 0 1.0090 12 13 1.5803 0 0.9947 13 14 1.5718 0 1.0080 14 15 1.5832 0 0.9986 15 16 1.5801 0 1.0184 16 17 1.5605 0 1.0357 17 18 1.5416 0 1.0556 18 19 1.5479 0 1.0409 19 20 1.5580 0 1.0474 20 21 1.5790 0 1.0219 21 22 1.5554 0 1.0427 22 23 1.5761 0 1.0205 23 24 1.5360 0 1.0490 24 25 1.5621 0 1.0344 25 26 1.5773 0 1.0193 26 27 1.5710 0 1.0238 27 28 1.5925 0 1.0165 28 29 1.5844 0 1.0218 29 30 1.5696 0 1.0370 30 31 1.5540 0 1.0508 31 32 1.5012 0 1.0813 32 33 1.4676 0 1.0970 33 34 1.4770 0 1.0989 34 35 1.4660 0 1.1018 35 36 1.4241 0 1.1166 36 37 1.4214 0 1.1319 37 38 1.4469 1 1.1020 38 39 1.4618 1 1.0884 39 40 1.3834 1 1.1263 40 41 1.3412 1 1.1345 41 42 1.3437 1 1.1337 42 43 1.2630 1 1.1660 43 44 1.2759 1 1.1550 44 45 1.2743 1 1.1782 45 46 1.2797 1 1.1856 46 47 1.2573 1 1.2219 47 48 1.2705 1 1.2130 48 49 1.2680 1 1.2230 49 50 1.3371 1 1.1767 50 51 1.3885 1 1.1077 51 52 1.4060 1 1.0672 52 53 1.3855 1 1.0840 53 54 1.3431 1 1.1154 54 55 1.3257 1 1.1184 55 56 1.2978 1 1.1570 56 57 1.2793 1 1.1625 57 58 1.2945 1 1.1627 58 59 1.2890 1 1.1578 59 60 1.2848 1 1.1533 60 61 1.2694 1 1.1684 61 62 1.2636 1 1.1597 62 63 1.2900 1 1.1888 63 64 1.3559 1 1.1296 64 65 1.3305 1 1.1424 65 66 1.3482 1 1.1317 66 67 1.3146 1 1.1581 67 68 1.3027 1 1.1672 68 69 1.3247 1 1.1391 69 70 1.3267 1 1.1357 70 71 1.3621 1 1.1065 71 72 1.3479 1 1.1232 72 73 1.4011 1 1.0845 73 74 1.4135 1 1.0676 74 75 1.3964 1 1.0863 75 76 1.4010 1 1.0792 76 77 1.3955 1 1.0799 77 78 1.4077 1 1.0817 78 79 1.3975 1 1.0869 79 80 1.3949 1 1.0843 80 81 1.4138 1 1.0747 81 82 1.4210 1 1.0711 82 83 1.4253 1 1.0688 83 84 1.4169 1 1.0828 84 85 1.4174 1 1.0746 85 86 1.4346 1 1.0568 86 87 1.4296 1 1.0600 87 88 1.4311 1 1.0593 88 89 1.4594 1 1.0370 89 90 1.4722 1 1.0288 90 91 1.4669 1 1.0295 91 92 1.4571 1 1.0352 92 93 1.4709 1 1.0324 93 94 1.4893 1 1.0186 94 95 1.4997 1 1.0094 95 96 1.4713 1 1.0258 96 97 1.4846 1 1.0170 97 98 1.4914 1 1.0117 98 99 1.4859 1 1.0175 99 100 1.4957 1 1.0064 100 101 1.4843 1 1.0168 101 102 1.4619 1 1.0340 102 103 1.4340 1 1.0423 103 104 1.4426 1 1.0356 104 105 1.4318 1 1.0348 105 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Crisis `us/ch` t 2.827e+00 -8.354e-02 -1.236e+00 -3.731e-05 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.110513 -0.009947 0.001190 0.010808 0.067313 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.827e+00 6.246e-02 45.252 < 2e-16 *** Crisis -8.354e-02 1.201e-02 -6.955 3.58e-10 *** `us/ch` -1.236e+00 5.702e-02 -21.675 < 2e-16 *** t -3.731e-05 1.743e-04 -0.214 0.831 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.02238 on 101 degrees of freedom Multiple R-squared: 0.9477, Adjusted R-squared: 0.9461 F-statistic: 609.8 on 3 and 101 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,] 0.7743834 4.512332e-01 2.256166e-01 [2,] 0.7579992 4.840015e-01 2.420008e-01 [3,] 0.9463346 1.073308e-01 5.366539e-02 [4,] 0.9387089 1.225822e-01 6.129110e-02 [5,] 0.9400037 1.199927e-01 5.999635e-02 [6,] 0.9339673 1.320655e-01 6.603274e-02 [7,] 0.9209803 1.580395e-01 7.901974e-02 [8,] 0.8932884 2.134232e-01 1.067116e-01 [9,] 0.8651373 2.697255e-01 1.348627e-01 [10,] 0.8183423 3.633154e-01 1.816577e-01 [11,] 0.8125168 3.749664e-01 1.874832e-01 [12,] 0.8256482 3.487035e-01 1.743518e-01 [13,] 0.8299120 3.401759e-01 1.700880e-01 [14,] 0.7875241 4.249517e-01 2.124759e-01 [15,] 0.7367594 5.264811e-01 2.632406e-01 [16,] 0.7150721 5.698559e-01 2.849279e-01 [17,] 0.6796747 6.406507e-01 3.203253e-01 [18,] 0.7362779 5.274443e-01 2.637221e-01 [19,] 0.7034149 5.931702e-01 2.965851e-01 [20,] 0.6653109 6.693782e-01 3.346891e-01 [21,] 0.6374504 7.250993e-01 3.625496e-01 [22,] 0.5739932 8.520135e-01 4.260068e-01 [23,] 0.5170343 9.659313e-01 4.829657e-01 [24,] 0.4722268 9.444535e-01 5.277732e-01 [25,] 0.4481024 8.962048e-01 5.518976e-01 [26,] 0.5320366 9.359267e-01 4.679634e-01 [27,] 0.6580660 6.838680e-01 3.419340e-01 [28,] 0.6583201 6.833599e-01 3.416799e-01 [29,] 0.6682808 6.634385e-01 3.317192e-01 [30,] 0.7656706 4.686589e-01 2.343294e-01 [31,] 0.7464380 5.071241e-01 2.535620e-01 [32,] 0.8278318 3.443364e-01 1.721682e-01 [33,] 0.9313940 1.372120e-01 6.860598e-02 [34,] 0.9640678 7.186446e-02 3.593223e-02 [35,] 0.9810772 3.784552e-02 1.892276e-02 [36,] 0.9855378 2.892441e-02 1.446221e-02 [37,] 0.9975567 4.886603e-03 2.443302e-03 [38,] 0.9994971 1.005767e-03 5.028835e-04 [39,] 0.9993225 1.354904e-03 6.774518e-04 [40,] 0.9988987 2.202600e-03 1.101300e-03 [41,] 0.9991032 1.793574e-03 8.967868e-04 [42,] 0.9993880 1.223987e-03 6.119936e-04 [43,] 0.9998743 2.514110e-04 1.257055e-04 [44,] 0.9999991 1.831881e-06 9.159407e-07 [45,] 0.9999996 7.209271e-07 3.604636e-07 [46,] 0.9999998 4.911790e-07 2.455895e-07 [47,] 0.9999998 4.814651e-07 2.407325e-07 [48,] 0.9999998 4.405329e-07 2.202664e-07 [49,] 1.0000000 6.361077e-08 3.180538e-08 [50,] 0.9999999 1.001756e-07 5.008780e-08 [51,] 1.0000000 6.250867e-08 3.125434e-08 [52,] 0.9999999 1.243125e-07 6.215627e-08 [53,] 0.9999999 1.149144e-07 5.745722e-08 [54,] 1.0000000 2.172678e-08 1.086339e-08 [55,] 1.0000000 6.507588e-09 3.253794e-09 [56,] 1.0000000 1.232907e-12 6.164537e-13 [57,] 1.0000000 2.082063e-13 1.041032e-13 [58,] 1.0000000 4.394774e-13 2.197387e-13 [59,] 1.0000000 1.563997e-12 7.819983e-13 [60,] 1.0000000 4.364771e-12 2.182386e-12 [61,] 1.0000000 6.641537e-12 3.320769e-12 [62,] 1.0000000 3.069310e-12 1.534655e-12 [63,] 1.0000000 1.092652e-11 5.463258e-12 [64,] 1.0000000 3.653641e-11 1.826820e-11 [65,] 1.0000000 5.554407e-11 2.777203e-11 [66,] 1.0000000 1.986375e-10 9.931874e-11 [67,] 1.0000000 6.649547e-10 3.324773e-10 [68,] 1.0000000 2.923059e-10 1.461529e-10 [69,] 1.0000000 8.310722e-10 4.155361e-10 [70,] 1.0000000 8.899629e-10 4.449815e-10 [71,] 1.0000000 1.708075e-10 8.540377e-11 [72,] 1.0000000 6.712442e-10 3.356221e-10 [73,] 1.0000000 2.391363e-09 1.195682e-09 [74,] 1.0000000 3.227667e-09 1.613833e-09 [75,] 1.0000000 9.306036e-09 4.653018e-09 [76,] 1.0000000 3.367737e-08 1.683868e-08 [77,] 0.9999999 1.298024e-07 6.490118e-08 [78,] 1.0000000 3.197538e-08 1.598769e-08 [79,] 1.0000000 4.729814e-08 2.364907e-08 [80,] 0.9999999 2.139938e-07 1.069969e-07 [81,] 0.9999996 8.899940e-07 4.449970e-07 [82,] 0.9999987 2.546400e-06 1.273200e-06 [83,] 0.9999949 1.019757e-05 5.098784e-06 [84,] 0.9999809 3.823272e-05 1.911636e-05 [85,] 0.9999535 9.292987e-05 4.646494e-05 [86,] 0.9999184 1.631090e-04 8.155450e-05 [87,] 0.9996773 6.453565e-04 3.226782e-04 [88,] 0.9987891 2.421831e-03 1.210916e-03 [89,] 0.9960489 7.902281e-03 3.951141e-03 [90,] 0.9902768 1.944649e-02 9.723246e-03 [91,] 0.9801831 3.963389e-02 1.981694e-02 [92,] 0.9626864 7.462727e-02 3.731364e-02 > postscript(file="/var/www/rcomp/tmp/1kque1290506793.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/2kque1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3kque1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4czby1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5czby1290506793.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 -1.105131e-01 1.329367e-02 -5.499394e-03 -2.586855e-03 -1.554074e-04 6 7 8 9 10 -1.376830e-02 -7.484049e-03 -3.846995e-03 -2.082778e-02 -2.516061e-02 11 12 13 14 15 -2.434649e-02 -3.444374e-02 -1.638099e-02 -8.405101e-03 -8.586038e-03 16 17 18 19 20 1.282375e-02 1.464358e-02 2.037697e-02 8.545315e-03 2.671652e-02 21 22 23 24 25 1.623624e-02 1.838202e-02 1.168049e-02 6.843333e-03 1.493528e-02 26 27 28 29 30 1.150923e-02 1.080847e-02 2.332310e-02 2.181112e-02 2.583539e-02 31 32 33 34 35 2.732927e-02 1.226409e-02 -1.893656e-03 9.892023e-03 2.513686e-03 36 37 38 39 40 -2.105644e-02 -4.808583e-03 6.731337e-02 6.544131e-02 3.392240e-02 41 42 43 44 45 1.894778e-03 3.443300e-03 -3.729711e-02 -3.795563e-02 -1.084349e-02 46 47 48 49 50 3.740098e-03 2.624362e-02 2.848067e-02 3.837782e-02 5.028908e-02 51 52 53 54 55 1.644351e-02 -1.607652e-02 -1.577469e-02 -1.932748e-02 -3.298222e-02 56 57 58 59 60 -1.313594e-02 -2.480072e-02 -9.316212e-03 -2.083522e-02 -3.055984e-02 61 62 63 64 65 -2.725917e-02 -4.377492e-02 1.862951e-02 1.139658e-02 1.854486e-03 66 67 68 69 70 6.366769e-03 5.434051e-03 4.818814e-03 -7.875021e-03 -1.004006e-02 71 72 73 74 75 -1.069347e-02 -4.215234e-03 1.189504e-03 -7.261313e-03 -1.211106e-03 76 77 78 79 80 -5.349281e-03 -9.946783e-03 4.515298e-03 7.797237e-04 -4.996524e-03 81 82 83 84 85 2.075341e-03 4.863109e-03 6.357657e-03 1.529874e-02 5.700982e-03 86 87 88 89 90 9.377807e-04 -6.976135e-05 6.023599e-04 1.377231e-03 4.079474e-03 91 92 93 94 95 -3.180275e-04 -3.035610e-03 7.340945e-03 8.721679e-03 7.787938e-03 96 97 98 99 100 -3.046182e-04 2.156034e-03 2.442630e-03 4.148646e-03 2.665357e-04 101 102 103 104 105 1.758077e-03 6.543080e-04 -1.694972e-02 -1.659350e-02 -2.834498e-02 > postscript(file="/var/www/rcomp/tmp/6czby1290506793.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 -1.105131e-01 NA 1 1.329367e-02 -1.105131e-01 2 -5.499394e-03 1.329367e-02 3 -2.586855e-03 -5.499394e-03 4 -1.554074e-04 -2.586855e-03 5 -1.376830e-02 -1.554074e-04 6 -7.484049e-03 -1.376830e-02 7 -3.846995e-03 -7.484049e-03 8 -2.082778e-02 -3.846995e-03 9 -2.516061e-02 -2.082778e-02 10 -2.434649e-02 -2.516061e-02 11 -3.444374e-02 -2.434649e-02 12 -1.638099e-02 -3.444374e-02 13 -8.405101e-03 -1.638099e-02 14 -8.586038e-03 -8.405101e-03 15 1.282375e-02 -8.586038e-03 16 1.464358e-02 1.282375e-02 17 2.037697e-02 1.464358e-02 18 8.545315e-03 2.037697e-02 19 2.671652e-02 8.545315e-03 20 1.623624e-02 2.671652e-02 21 1.838202e-02 1.623624e-02 22 1.168049e-02 1.838202e-02 23 6.843333e-03 1.168049e-02 24 1.493528e-02 6.843333e-03 25 1.150923e-02 1.493528e-02 26 1.080847e-02 1.150923e-02 27 2.332310e-02 1.080847e-02 28 2.181112e-02 2.332310e-02 29 2.583539e-02 2.181112e-02 30 2.732927e-02 2.583539e-02 31 1.226409e-02 2.732927e-02 32 -1.893656e-03 1.226409e-02 33 9.892023e-03 -1.893656e-03 34 2.513686e-03 9.892023e-03 35 -2.105644e-02 2.513686e-03 36 -4.808583e-03 -2.105644e-02 37 6.731337e-02 -4.808583e-03 38 6.544131e-02 6.731337e-02 39 3.392240e-02 6.544131e-02 40 1.894778e-03 3.392240e-02 41 3.443300e-03 1.894778e-03 42 -3.729711e-02 3.443300e-03 43 -3.795563e-02 -3.729711e-02 44 -1.084349e-02 -3.795563e-02 45 3.740098e-03 -1.084349e-02 46 2.624362e-02 3.740098e-03 47 2.848067e-02 2.624362e-02 48 3.837782e-02 2.848067e-02 49 5.028908e-02 3.837782e-02 50 1.644351e-02 5.028908e-02 51 -1.607652e-02 1.644351e-02 52 -1.577469e-02 -1.607652e-02 53 -1.932748e-02 -1.577469e-02 54 -3.298222e-02 -1.932748e-02 55 -1.313594e-02 -3.298222e-02 56 -2.480072e-02 -1.313594e-02 57 -9.316212e-03 -2.480072e-02 58 -2.083522e-02 -9.316212e-03 59 -3.055984e-02 -2.083522e-02 60 -2.725917e-02 -3.055984e-02 61 -4.377492e-02 -2.725917e-02 62 1.862951e-02 -4.377492e-02 63 1.139658e-02 1.862951e-02 64 1.854486e-03 1.139658e-02 65 6.366769e-03 1.854486e-03 66 5.434051e-03 6.366769e-03 67 4.818814e-03 5.434051e-03 68 -7.875021e-03 4.818814e-03 69 -1.004006e-02 -7.875021e-03 70 -1.069347e-02 -1.004006e-02 71 -4.215234e-03 -1.069347e-02 72 1.189504e-03 -4.215234e-03 73 -7.261313e-03 1.189504e-03 74 -1.211106e-03 -7.261313e-03 75 -5.349281e-03 -1.211106e-03 76 -9.946783e-03 -5.349281e-03 77 4.515298e-03 -9.946783e-03 78 7.797237e-04 4.515298e-03 79 -4.996524e-03 7.797237e-04 80 2.075341e-03 -4.996524e-03 81 4.863109e-03 2.075341e-03 82 6.357657e-03 4.863109e-03 83 1.529874e-02 6.357657e-03 84 5.700982e-03 1.529874e-02 85 9.377807e-04 5.700982e-03 86 -6.976135e-05 9.377807e-04 87 6.023599e-04 -6.976135e-05 88 1.377231e-03 6.023599e-04 89 4.079474e-03 1.377231e-03 90 -3.180275e-04 4.079474e-03 91 -3.035610e-03 -3.180275e-04 92 7.340945e-03 -3.035610e-03 93 8.721679e-03 7.340945e-03 94 7.787938e-03 8.721679e-03 95 -3.046182e-04 7.787938e-03 96 2.156034e-03 -3.046182e-04 97 2.442630e-03 2.156034e-03 98 4.148646e-03 2.442630e-03 99 2.665357e-04 4.148646e-03 100 1.758077e-03 2.665357e-04 101 6.543080e-04 1.758077e-03 102 -1.694972e-02 6.543080e-04 103 -1.659350e-02 -1.694972e-02 104 -2.834498e-02 -1.659350e-02 105 NA -2.834498e-02 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 1.329367e-02 -1.105131e-01 [2,] -5.499394e-03 1.329367e-02 [3,] -2.586855e-03 -5.499394e-03 [4,] -1.554074e-04 -2.586855e-03 [5,] -1.376830e-02 -1.554074e-04 [6,] -7.484049e-03 -1.376830e-02 [7,] -3.846995e-03 -7.484049e-03 [8,] -2.082778e-02 -3.846995e-03 [9,] -2.516061e-02 -2.082778e-02 [10,] -2.434649e-02 -2.516061e-02 [11,] -3.444374e-02 -2.434649e-02 [12,] -1.638099e-02 -3.444374e-02 [13,] -8.405101e-03 -1.638099e-02 [14,] -8.586038e-03 -8.405101e-03 [15,] 1.282375e-02 -8.586038e-03 [16,] 1.464358e-02 1.282375e-02 [17,] 2.037697e-02 1.464358e-02 [18,] 8.545315e-03 2.037697e-02 [19,] 2.671652e-02 8.545315e-03 [20,] 1.623624e-02 2.671652e-02 [21,] 1.838202e-02 1.623624e-02 [22,] 1.168049e-02 1.838202e-02 [23,] 6.843333e-03 1.168049e-02 [24,] 1.493528e-02 6.843333e-03 [25,] 1.150923e-02 1.493528e-02 [26,] 1.080847e-02 1.150923e-02 [27,] 2.332310e-02 1.080847e-02 [28,] 2.181112e-02 2.332310e-02 [29,] 2.583539e-02 2.181112e-02 [30,] 2.732927e-02 2.583539e-02 [31,] 1.226409e-02 2.732927e-02 [32,] -1.893656e-03 1.226409e-02 [33,] 9.892023e-03 -1.893656e-03 [34,] 2.513686e-03 9.892023e-03 [35,] -2.105644e-02 2.513686e-03 [36,] -4.808583e-03 -2.105644e-02 [37,] 6.731337e-02 -4.808583e-03 [38,] 6.544131e-02 6.731337e-02 [39,] 3.392240e-02 6.544131e-02 [40,] 1.894778e-03 3.392240e-02 [41,] 3.443300e-03 1.894778e-03 [42,] -3.729711e-02 3.443300e-03 [43,] -3.795563e-02 -3.729711e-02 [44,] -1.084349e-02 -3.795563e-02 [45,] 3.740098e-03 -1.084349e-02 [46,] 2.624362e-02 3.740098e-03 [47,] 2.848067e-02 2.624362e-02 [48,] 3.837782e-02 2.848067e-02 [49,] 5.028908e-02 3.837782e-02 [50,] 1.644351e-02 5.028908e-02 [51,] -1.607652e-02 1.644351e-02 [52,] -1.577469e-02 -1.607652e-02 [53,] -1.932748e-02 -1.577469e-02 [54,] -3.298222e-02 -1.932748e-02 [55,] -1.313594e-02 -3.298222e-02 [56,] -2.480072e-02 -1.313594e-02 [57,] -9.316212e-03 -2.480072e-02 [58,] -2.083522e-02 -9.316212e-03 [59,] -3.055984e-02 -2.083522e-02 [60,] -2.725917e-02 -3.055984e-02 [61,] -4.377492e-02 -2.725917e-02 [62,] 1.862951e-02 -4.377492e-02 [63,] 1.139658e-02 1.862951e-02 [64,] 1.854486e-03 1.139658e-02 [65,] 6.366769e-03 1.854486e-03 [66,] 5.434051e-03 6.366769e-03 [67,] 4.818814e-03 5.434051e-03 [68,] -7.875021e-03 4.818814e-03 [69,] -1.004006e-02 -7.875021e-03 [70,] -1.069347e-02 -1.004006e-02 [71,] -4.215234e-03 -1.069347e-02 [72,] 1.189504e-03 -4.215234e-03 [73,] -7.261313e-03 1.189504e-03 [74,] -1.211106e-03 -7.261313e-03 [75,] -5.349281e-03 -1.211106e-03 [76,] -9.946783e-03 -5.349281e-03 [77,] 4.515298e-03 -9.946783e-03 [78,] 7.797237e-04 4.515298e-03 [79,] -4.996524e-03 7.797237e-04 [80,] 2.075341e-03 -4.996524e-03 [81,] 4.863109e-03 2.075341e-03 [82,] 6.357657e-03 4.863109e-03 [83,] 1.529874e-02 6.357657e-03 [84,] 5.700982e-03 1.529874e-02 [85,] 9.377807e-04 5.700982e-03 [86,] -6.976135e-05 9.377807e-04 [87,] 6.023599e-04 -6.976135e-05 [88,] 1.377231e-03 6.023599e-04 [89,] 4.079474e-03 1.377231e-03 [90,] -3.180275e-04 4.079474e-03 [91,] -3.035610e-03 -3.180275e-04 [92,] 7.340945e-03 -3.035610e-03 [93,] 8.721679e-03 7.340945e-03 [94,] 7.787938e-03 8.721679e-03 [95,] -3.046182e-04 7.787938e-03 [96,] 2.156034e-03 -3.046182e-04 [97,] 2.442630e-03 2.156034e-03 [98,] 4.148646e-03 2.442630e-03 [99,] 2.665357e-04 4.148646e-03 [100,] 1.758077e-03 2.665357e-04 [101,] 6.543080e-04 1.758077e-03 [102,] -1.694972e-02 6.543080e-04 [103,] -1.659350e-02 -1.694972e-02 [104,] -2.834498e-02 -1.659350e-02 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 1.329367e-02 -1.105131e-01 2 -5.499394e-03 1.329367e-02 3 -2.586855e-03 -5.499394e-03 4 -1.554074e-04 -2.586855e-03 5 -1.376830e-02 -1.554074e-04 6 -7.484049e-03 -1.376830e-02 7 -3.846995e-03 -7.484049e-03 8 -2.082778e-02 -3.846995e-03 9 -2.516061e-02 -2.082778e-02 10 -2.434649e-02 -2.516061e-02 11 -3.444374e-02 -2.434649e-02 12 -1.638099e-02 -3.444374e-02 13 -8.405101e-03 -1.638099e-02 14 -8.586038e-03 -8.405101e-03 15 1.282375e-02 -8.586038e-03 16 1.464358e-02 1.282375e-02 17 2.037697e-02 1.464358e-02 18 8.545315e-03 2.037697e-02 19 2.671652e-02 8.545315e-03 20 1.623624e-02 2.671652e-02 21 1.838202e-02 1.623624e-02 22 1.168049e-02 1.838202e-02 23 6.843333e-03 1.168049e-02 24 1.493528e-02 6.843333e-03 25 1.150923e-02 1.493528e-02 26 1.080847e-02 1.150923e-02 27 2.332310e-02 1.080847e-02 28 2.181112e-02 2.332310e-02 29 2.583539e-02 2.181112e-02 30 2.732927e-02 2.583539e-02 31 1.226409e-02 2.732927e-02 32 -1.893656e-03 1.226409e-02 33 9.892023e-03 -1.893656e-03 34 2.513686e-03 9.892023e-03 35 -2.105644e-02 2.513686e-03 36 -4.808583e-03 -2.105644e-02 37 6.731337e-02 -4.808583e-03 38 6.544131e-02 6.731337e-02 39 3.392240e-02 6.544131e-02 40 1.894778e-03 3.392240e-02 41 3.443300e-03 1.894778e-03 42 -3.729711e-02 3.443300e-03 43 -3.795563e-02 -3.729711e-02 44 -1.084349e-02 -3.795563e-02 45 3.740098e-03 -1.084349e-02 46 2.624362e-02 3.740098e-03 47 2.848067e-02 2.624362e-02 48 3.837782e-02 2.848067e-02 49 5.028908e-02 3.837782e-02 50 1.644351e-02 5.028908e-02 51 -1.607652e-02 1.644351e-02 52 -1.577469e-02 -1.607652e-02 53 -1.932748e-02 -1.577469e-02 54 -3.298222e-02 -1.932748e-02 55 -1.313594e-02 -3.298222e-02 56 -2.480072e-02 -1.313594e-02 57 -9.316212e-03 -2.480072e-02 58 -2.083522e-02 -9.316212e-03 59 -3.055984e-02 -2.083522e-02 60 -2.725917e-02 -3.055984e-02 61 -4.377492e-02 -2.725917e-02 62 1.862951e-02 -4.377492e-02 63 1.139658e-02 1.862951e-02 64 1.854486e-03 1.139658e-02 65 6.366769e-03 1.854486e-03 66 5.434051e-03 6.366769e-03 67 4.818814e-03 5.434051e-03 68 -7.875021e-03 4.818814e-03 69 -1.004006e-02 -7.875021e-03 70 -1.069347e-02 -1.004006e-02 71 -4.215234e-03 -1.069347e-02 72 1.189504e-03 -4.215234e-03 73 -7.261313e-03 1.189504e-03 74 -1.211106e-03 -7.261313e-03 75 -5.349281e-03 -1.211106e-03 76 -9.946783e-03 -5.349281e-03 77 4.515298e-03 -9.946783e-03 78 7.797237e-04 4.515298e-03 79 -4.996524e-03 7.797237e-04 80 2.075341e-03 -4.996524e-03 81 4.863109e-03 2.075341e-03 82 6.357657e-03 4.863109e-03 83 1.529874e-02 6.357657e-03 84 5.700982e-03 1.529874e-02 85 9.377807e-04 5.700982e-03 86 -6.976135e-05 9.377807e-04 87 6.023599e-04 -6.976135e-05 88 1.377231e-03 6.023599e-04 89 4.079474e-03 1.377231e-03 90 -3.180275e-04 4.079474e-03 91 -3.035610e-03 -3.180275e-04 92 7.340945e-03 -3.035610e-03 93 8.721679e-03 7.340945e-03 94 7.787938e-03 8.721679e-03 95 -3.046182e-04 7.787938e-03 96 2.156034e-03 -3.046182e-04 97 2.442630e-03 2.156034e-03 98 4.148646e-03 2.442630e-03 99 2.665357e-04 4.148646e-03 100 1.758077e-03 2.665357e-04 101 6.543080e-04 1.758077e-03 102 -1.694972e-02 6.543080e-04 103 -1.659350e-02 -1.694972e-02 104 -2.834498e-02 -1.659350e-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/rcomp/tmp/7nqs11290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8yh9m1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/9yh9m1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/10yh9m1290506793.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/11ur7v1290506793.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/rcomp/tmp/12mi6y1290506793.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/rcomp/tmp/13b13a1290506793.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/rcomp/tmp/14xkky1290506793.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/rcomp/tmp/150k0l1290506793.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/rcomp/tmp/163lzr1290506793.tab") + } > > try(system("convert tmp/1kque1290506793.ps tmp/1kque1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/2kque1290506793.ps tmp/2kque1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/3kque1290506793.ps tmp/3kque1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/4czby1290506793.ps tmp/4czby1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/5czby1290506793.ps tmp/5czby1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/6czby1290506793.ps tmp/6czby1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/7nqs11290506793.ps tmp/7nqs11290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/8yh9m1290506793.ps tmp/8yh9m1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/9yh9m1290506793.ps tmp/9yh9m1290506793.png",intern=TRUE)) character(0) > try(system("convert tmp/10yh9m1290506793.ps tmp/10yh9m1290506793.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.370 2.010 6.417