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Type 'q()' to quit R. > x <- array(list(33907 + ,71433 + ,152 + ,74272 + ,99 + ,765 + ,35981 + ,53655 + ,99 + ,78867 + ,128 + ,1371 + ,36588 + ,70556 + ,92 + ,80176 + ,57 + ,1880 + ,16967 + ,74702 + ,138 + ,36541 + ,95 + ,232 + ,25333 + ,61201 + ,106 + ,55107 + ,205 + ,230 + ,21027 + ,686 + ,95 + ,45527 + ,51 + ,828 + ,21114 + ,87586 + ,145 + ,46001 + ,59 + ,1833 + ,28777 + ,6615 + ,181 + ,62854 + ,194 + ,906 + ,35612 + ,89725 + ,190 + ,78112 + ,27 + ,1781 + ,24183 + ,40420 + ,150 + ,52653 + ,9 + ,1264 + ,22262 + ,49569 + ,186 + ,48467 + ,24 + ,1123 + ,20637 + ,13963 + ,174 + ,44873 + ,189 + ,1461 + ,29948 + ,62508 + ,151 + ,65605 + ,37 + ,820 + ,22093 + ,90901 + ,112 + ,48016 + ,81 + ,107 + ,36997 + ,89418 + ,143 + ,81110 + ,72 + ,1349 + ,31089 + ,83237 + ,120 + ,68019 + ,81 + ,870 + ,19477 + ,22183 + ,169 + ,42198 + ,90 + ,1471 + ,31301 + ,24346 + ,135 + ,68531 + ,216 + ,731 + ,18497 + ,74341 + ,161 + ,40071 + ,216 + ,1945 + ,30142 + ,24188 + ,98 + ,65849 + ,13 + ,521 + ,21326 + ,11781 + ,142 + ,46362 + ,153 + ,1920 + ,16779 + ,23072 + ,190 + ,36313 + ,185 + ,1924 + ,38068 + ,49119 + ,169 + ,83521 + ,131 + ,100 + ,29707 + ,67776 + ,130 + ,64932 + ,136 + ,34 + ,35016 + ,86910 + ,160 + ,76730 + ,182 + ,325 + ,26131 + ,69358 + ,176 + ,56982 + ,139 + ,1677 + ,29251 + ,16144 + ,111 + ,63793 + ,42 + ,1779 + ,22855 + ,77863 + ,165 + ,49740 + ,213 + ,477 + ,31806 + ,89070 + ,117 + ,69447 + ,184 + ,1007 + ,34124 + ,34790 + ,122 + ,74708 + ,44 + ,1527) + ,dim=c(6 + ,30) + ,dimnames=list(c('omzet' + ,'uitgaven_voor_promotie' + ,'Prijs_product' + ,'gem_budget' + ,'index_cons_vertriuwen' + ,'uitg_lok_promotie') + ,1:30)) > y <- array(NA,dim=c(6,30),dimnames=list(c('omzet','uitgaven_voor_promotie','Prijs_product','gem_budget','index_cons_vertriuwen','uitg_lok_promotie'),1:30)) > 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 = '5' > 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 index_cons_vertriuwen omzet uitgaven_voor_promotie Prijs_product gem_budget 1 99 33907 71433 152 74272 2 128 35981 53655 99 78867 3 57 36588 70556 92 80176 4 95 16967 74702 138 36541 5 205 25333 61201 106 55107 6 51 21027 686 95 45527 7 59 21114 87586 145 46001 8 194 28777 6615 181 62854 9 27 35612 89725 190 78112 10 9 24183 40420 150 52653 11 24 22262 49569 186 48467 12 189 20637 13963 174 44873 13 37 29948 62508 151 65605 14 81 22093 90901 112 48016 15 72 36997 89418 143 81110 16 81 31089 83237 120 68019 17 90 19477 22183 169 42198 18 216 31301 24346 135 68531 19 216 18497 74341 161 40071 20 13 30142 24188 98 65849 21 153 21326 11781 142 46362 22 185 16779 23072 190 36313 23 131 38068 49119 169 83521 24 136 29707 67776 130 64932 25 182 35016 86910 160 76730 26 139 26131 69358 176 56982 27 42 29251 16144 111 63793 28 213 22855 77863 165 49740 29 184 31806 89070 117 69447 30 44 34124 34790 122 74708 uitg_lok_promotie 1 765 2 1371 3 1880 4 232 5 230 6 828 7 1833 8 906 9 1781 10 1264 11 1123 12 1461 13 820 14 107 15 1349 16 870 17 1471 18 731 19 1945 20 521 21 1920 22 1924 23 100 24 34 25 325 26 1677 27 1779 28 477 29 1007 30 1527 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) omzet uitgaven_voor_promotie -3.372e+01 2.272e-01 -2.101e-05 Prijs_product gem_budget uitg_lok_promotie 6.971e-01 -1.029e-01 -2.109e-02 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -117.22 -44.87 -7.85 54.33 112.74 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -3.372e+01 3.075e+02 -0.110 0.914 omzet 2.272e-01 5.065e-01 0.449 0.658 uitgaven_voor_promotie -2.101e-05 4.803e-04 -0.044 0.965 Prijs_product 6.971e-01 5.515e-01 1.264 0.218 gem_budget -1.029e-01 2.280e-01 -0.451 0.656 uitg_lok_promotie -2.109e-02 2.223e-02 -0.949 0.352 Residual standard error: 70.9 on 24 degrees of freedom Multiple R-squared: 0.1175, Adjusted R-squared: -0.06636 F-statistic: 0.6391 on 5 and 24 DF, p-value: 0.6721 > 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)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.4474551 0.8949101 0.55254494 [2,] 0.4239791 0.8479583 0.57602086 [3,] 0.5278094 0.9443811 0.47219056 [4,] 0.6314176 0.7371648 0.36858240 [5,] 0.7973948 0.4052104 0.20260518 [6,] 0.7580593 0.4838813 0.24194067 [7,] 0.6941274 0.6117452 0.30587258 [8,] 0.7445442 0.5109116 0.25545582 [9,] 0.6273614 0.7452772 0.37263859 [10,] 0.8763622 0.2472757 0.12363783 [11,] 0.9018552 0.1962895 0.09814476 [12,] 0.9025417 0.1949166 0.09745830 [13,] 0.8952475 0.2095050 0.10475252 > postscript(file="/var/wessaorg/rcomp/tmp/1uyyw1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/22phj1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/33fu91323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/46kjd1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5p69i1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 30 Frequency = 1 1 2 3 4 5 6 -15.661554 64.372918 6.148957 -55.347224 86.577747 -56.001641 7 8 9 10 11 12 -30.820011 51.199941 -84.524531 -109.993026 -117.218685 61.856545 13 14 15 16 17 18 -68.461276 -37.209730 -22.013762 -12.160127 -45.015932 112.738310 19 20 21 22 23 24 101.414069 -81.589702 54.499705 52.255777 -3.539301 14.204423 25 26 27 28 29 30 53.802334 14.129195 -44.440389 69.669023 80.003038 -38.875088 > postscript(file="/var/wessaorg/rcomp/tmp/6vcak1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 30 Frequency = 1 lag(myerror, k = 1) myerror 0 -15.661554 NA 1 64.372918 -15.661554 2 6.148957 64.372918 3 -55.347224 6.148957 4 86.577747 -55.347224 5 -56.001641 86.577747 6 -30.820011 -56.001641 7 51.199941 -30.820011 8 -84.524531 51.199941 9 -109.993026 -84.524531 10 -117.218685 -109.993026 11 61.856545 -117.218685 12 -68.461276 61.856545 13 -37.209730 -68.461276 14 -22.013762 -37.209730 15 -12.160127 -22.013762 16 -45.015932 -12.160127 17 112.738310 -45.015932 18 101.414069 112.738310 19 -81.589702 101.414069 20 54.499705 -81.589702 21 52.255777 54.499705 22 -3.539301 52.255777 23 14.204423 -3.539301 24 53.802334 14.204423 25 14.129195 53.802334 26 -44.440389 14.129195 27 69.669023 -44.440389 28 80.003038 69.669023 29 -38.875088 80.003038 30 NA -38.875088 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 64.372918 -15.661554 [2,] 6.148957 64.372918 [3,] -55.347224 6.148957 [4,] 86.577747 -55.347224 [5,] -56.001641 86.577747 [6,] -30.820011 -56.001641 [7,] 51.199941 -30.820011 [8,] -84.524531 51.199941 [9,] -109.993026 -84.524531 [10,] -117.218685 -109.993026 [11,] 61.856545 -117.218685 [12,] -68.461276 61.856545 [13,] -37.209730 -68.461276 [14,] -22.013762 -37.209730 [15,] -12.160127 -22.013762 [16,] -45.015932 -12.160127 [17,] 112.738310 -45.015932 [18,] 101.414069 112.738310 [19,] -81.589702 101.414069 [20,] 54.499705 -81.589702 [21,] 52.255777 54.499705 [22,] -3.539301 52.255777 [23,] 14.204423 -3.539301 [24,] 53.802334 14.204423 [25,] 14.129195 53.802334 [26,] -44.440389 14.129195 [27,] 69.669023 -44.440389 [28,] 80.003038 69.669023 [29,] -38.875088 80.003038 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 64.372918 -15.661554 2 6.148957 64.372918 3 -55.347224 6.148957 4 86.577747 -55.347224 5 -56.001641 86.577747 6 -30.820011 -56.001641 7 51.199941 -30.820011 8 -84.524531 51.199941 9 -109.993026 -84.524531 10 -117.218685 -109.993026 11 61.856545 -117.218685 12 -68.461276 61.856545 13 -37.209730 -68.461276 14 -22.013762 -37.209730 15 -12.160127 -22.013762 16 -45.015932 -12.160127 17 112.738310 -45.015932 18 101.414069 112.738310 19 -81.589702 101.414069 20 54.499705 -81.589702 21 52.255777 54.499705 22 -3.539301 52.255777 23 14.204423 -3.539301 24 53.802334 14.204423 25 14.129195 53.802334 26 -44.440389 14.129195 27 69.669023 -44.440389 28 80.003038 69.669023 29 -38.875088 80.003038 > 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/wessaorg/rcomp/tmp/76fv91323434303.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/8wz5q1323434303.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/9y4n11323434303.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/10t5kx1323434303.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11kf6q1323434303.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12zp4p1323434303.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13we8r1323434303.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14qjcw1323434303.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/wessaorg/rcomp/tmp/15z86v1323434303.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/wessaorg/rcomp/tmp/167cm61323434303.tab") + } > > try(system("convert tmp/1uyyw1323434303.ps tmp/1uyyw1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/22phj1323434303.ps tmp/22phj1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/33fu91323434303.ps tmp/33fu91323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/46kjd1323434303.ps tmp/46kjd1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/5p69i1323434303.ps tmp/5p69i1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/6vcak1323434303.ps tmp/6vcak1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/76fv91323434303.ps tmp/76fv91323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/8wz5q1323434303.ps tmp/8wz5q1323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/9y4n11323434303.ps tmp/9y4n11323434303.png",intern=TRUE)) character(0) > try(system("convert tmp/10t5kx1323434303.ps tmp/10t5kx1323434303.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.010 0.524 3.550