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Type 'q()' to quit R. > x <- array(list(1235,127,13,1651,1080,115,12,1380,845,127,7,889,1522,150,9,1350,1047,156,6,936,1979,182,11,2002,1822,156,12,1872,1253,132,10,1320,1297,137,9,1233,946,113,9,1017,1713,137,15,2055,1024,117,11,1287,1147,137,8,1096,1092,153,6,918,1152,117,13,1521,1336,126,10,1260,2131,170,14,2380,1550,182,8,1456,1884,162,11,1782,2041,184,10,1840,845,143,6,858,1483,159,9,1431,1055,108,14,1512,1545,175,8,1400,729,108,6,648,1792,179,9,1611,1175,111,15,1665,1593,187,8,1496,785,111,7,777,744,115,7,805,1356,194,5,970,1262,168,7,1176),dim=c(4,32),dimnames=list(c('Veilingprijs','Ouderdom','Aanbieders','Interactie'),1:32)) > y <- array(NA,dim=c(4,32),dimnames=list(c('Veilingprijs','Ouderdom','Aanbieders','Interactie'),1:32)) > 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 = '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 > 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 Veilingprijs Ouderdom Aanbieders Interactie 1 1235 127 13 1651 2 1080 115 12 1380 3 845 127 7 889 4 1522 150 9 1350 5 1047 156 6 936 6 1979 182 11 2002 7 1822 156 12 1872 8 1253 132 10 1320 9 1297 137 9 1233 10 946 113 9 1017 11 1713 137 15 2055 12 1024 117 11 1287 13 1147 137 8 1096 14 1092 153 6 918 15 1152 117 13 1521 16 1336 126 10 1260 17 2131 170 14 2380 18 1550 182 8 1456 19 1884 162 11 1782 20 2041 184 10 1840 21 845 143 6 858 22 1483 159 9 1431 23 1055 108 14 1512 24 1545 175 8 1400 25 729 108 6 648 26 1792 179 9 1611 27 1175 111 15 1665 28 1593 187 8 1496 29 785 111 7 777 30 744 115 7 805 31 1356 194 5 970 32 1262 168 7 1176 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Ouderdom Aanbieders Interactie 320.4580 0.8781 -93.2648 1.2978 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -154.995 -70.431 2.069 47.880 202.259 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 320.4580 295.1413 1.086 0.28684 Ouderdom 0.8781 2.0322 0.432 0.66896 Aanbieders -93.2648 29.8916 -3.120 0.00416 ** Interactie 1.2978 0.2123 6.112 1.35e-06 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 88.91 on 28 degrees of freedom Multiple R-squared: 0.9539, Adjusted R-squared: 0.9489 F-statistic: 193 on 3 and 28 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,] 0.9117908 0.1764185 0.08820923 [2,] 0.8505012 0.2989976 0.14949879 [3,] 0.8375126 0.3249749 0.16248743 [4,] 0.7504840 0.4990320 0.24951598 [5,] 0.6365419 0.7269161 0.36345805 [6,] 0.5322141 0.9355718 0.46778590 [7,] 0.4153347 0.8306693 0.58466533 [8,] 0.3021195 0.6042390 0.69788050 [9,] 0.2114831 0.4229663 0.78851685 [10,] 0.5687442 0.8625115 0.43125577 [11,] 0.7293780 0.5412440 0.27062199 [12,] 0.6949949 0.6100103 0.30500513 [13,] 0.7546620 0.4906761 0.24533803 [14,] 0.7684185 0.4631629 0.23158146 [15,] 0.9179555 0.1640891 0.08204454 [16,] 0.8522015 0.2955969 0.14779846 [17,] 0.7455792 0.5088417 0.25442083 [18,] 0.6001594 0.7996813 0.39984064 [19,] 0.4764456 0.9528913 0.52355437 > postscript(file="/var/www/wessaorg/rcomp/tmp/1p1ty1298406496.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/2l7jd1298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/3xo9z1298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/4ksq91298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/5fbd21298406496.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 = 32 Frequency = 1 1 2 3 4 5 -1.272828e+02 -1.329372e+01 -8.791325e+01 1.571122e+02 -6.564296e+01 6 7 8 9 10 -7.365420e+01 5.416229e+01 3.611896e+01 9.537601e+01 4.578612e+01 11 12 13 14 15 4.135685e+00 -4.361517e+01 2.991606e+01 5.352688e+00 -3.278144e+01 16 17 18 19 20 2.022586e+02 -1.219077e+02 -7.382485e+01 1.344347e+02 1.035757e+02 21 22 23 24 25 -1.549951e+02 5.083398e+00 -1.693273e+01 1.515038e-03 3.228747e+01 26 27 28 29 30 6.290830e+01 -4.872739e+00 -8.712939e+01 1.149576e+01 -6.935650e+01 31 32 7.259604e+01 -7.939885e+01 > postscript(file="/var/www/wessaorg/rcomp/tmp/6zocr1298406496.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 = 32 Frequency = 1 lag(myerror, k = 1) myerror 0 -1.272828e+02 NA 1 -1.329372e+01 -1.272828e+02 2 -8.791325e+01 -1.329372e+01 3 1.571122e+02 -8.791325e+01 4 -6.564296e+01 1.571122e+02 5 -7.365420e+01 -6.564296e+01 6 5.416229e+01 -7.365420e+01 7 3.611896e+01 5.416229e+01 8 9.537601e+01 3.611896e+01 9 4.578612e+01 9.537601e+01 10 4.135685e+00 4.578612e+01 11 -4.361517e+01 4.135685e+00 12 2.991606e+01 -4.361517e+01 13 5.352688e+00 2.991606e+01 14 -3.278144e+01 5.352688e+00 15 2.022586e+02 -3.278144e+01 16 -1.219077e+02 2.022586e+02 17 -7.382485e+01 -1.219077e+02 18 1.344347e+02 -7.382485e+01 19 1.035757e+02 1.344347e+02 20 -1.549951e+02 1.035757e+02 21 5.083398e+00 -1.549951e+02 22 -1.693273e+01 5.083398e+00 23 1.515038e-03 -1.693273e+01 24 3.228747e+01 1.515038e-03 25 6.290830e+01 3.228747e+01 26 -4.872739e+00 6.290830e+01 27 -8.712939e+01 -4.872739e+00 28 1.149576e+01 -8.712939e+01 29 -6.935650e+01 1.149576e+01 30 7.259604e+01 -6.935650e+01 31 -7.939885e+01 7.259604e+01 32 NA -7.939885e+01 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1.329372e+01 -1.272828e+02 [2,] -8.791325e+01 -1.329372e+01 [3,] 1.571122e+02 -8.791325e+01 [4,] -6.564296e+01 1.571122e+02 [5,] -7.365420e+01 -6.564296e+01 [6,] 5.416229e+01 -7.365420e+01 [7,] 3.611896e+01 5.416229e+01 [8,] 9.537601e+01 3.611896e+01 [9,] 4.578612e+01 9.537601e+01 [10,] 4.135685e+00 4.578612e+01 [11,] -4.361517e+01 4.135685e+00 [12,] 2.991606e+01 -4.361517e+01 [13,] 5.352688e+00 2.991606e+01 [14,] -3.278144e+01 5.352688e+00 [15,] 2.022586e+02 -3.278144e+01 [16,] -1.219077e+02 2.022586e+02 [17,] -7.382485e+01 -1.219077e+02 [18,] 1.344347e+02 -7.382485e+01 [19,] 1.035757e+02 1.344347e+02 [20,] -1.549951e+02 1.035757e+02 [21,] 5.083398e+00 -1.549951e+02 [22,] -1.693273e+01 5.083398e+00 [23,] 1.515038e-03 -1.693273e+01 [24,] 3.228747e+01 1.515038e-03 [25,] 6.290830e+01 3.228747e+01 [26,] -4.872739e+00 6.290830e+01 [27,] -8.712939e+01 -4.872739e+00 [28,] 1.149576e+01 -8.712939e+01 [29,] -6.935650e+01 1.149576e+01 [30,] 7.259604e+01 -6.935650e+01 [31,] -7.939885e+01 7.259604e+01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1.329372e+01 -1.272828e+02 2 -8.791325e+01 -1.329372e+01 3 1.571122e+02 -8.791325e+01 4 -6.564296e+01 1.571122e+02 5 -7.365420e+01 -6.564296e+01 6 5.416229e+01 -7.365420e+01 7 3.611896e+01 5.416229e+01 8 9.537601e+01 3.611896e+01 9 4.578612e+01 9.537601e+01 10 4.135685e+00 4.578612e+01 11 -4.361517e+01 4.135685e+00 12 2.991606e+01 -4.361517e+01 13 5.352688e+00 2.991606e+01 14 -3.278144e+01 5.352688e+00 15 2.022586e+02 -3.278144e+01 16 -1.219077e+02 2.022586e+02 17 -7.382485e+01 -1.219077e+02 18 1.344347e+02 -7.382485e+01 19 1.035757e+02 1.344347e+02 20 -1.549951e+02 1.035757e+02 21 5.083398e+00 -1.549951e+02 22 -1.693273e+01 5.083398e+00 23 1.515038e-03 -1.693273e+01 24 3.228747e+01 1.515038e-03 25 6.290830e+01 3.228747e+01 26 -4.872739e+00 6.290830e+01 27 -8.712939e+01 -4.872739e+00 28 1.149576e+01 -8.712939e+01 29 -6.935650e+01 1.149576e+01 30 7.259604e+01 -6.935650e+01 31 -7.939885e+01 7.259604e+01 > 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/wessaorg/rcomp/tmp/7sujs1298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/8ld4j1298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/9wv801298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/wessaorg/rcomp/tmp/10bh5o1298406496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/www/wessaorg/rcomp/tmp/11c9t71298406496.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/wessaorg/rcomp/tmp/12lgvo1298406496.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/wessaorg/rcomp/tmp/13a12d1298406496.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/wessaorg/rcomp/tmp/14klof1298406496.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/wessaorg/rcomp/tmp/15bycs1298406496.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/wessaorg/rcomp/tmp/169wph1298406496.tab") + } > > try(system("convert tmp/1p1ty1298406496.ps tmp/1p1ty1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/2l7jd1298406496.ps tmp/2l7jd1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/3xo9z1298406496.ps tmp/3xo9z1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/4ksq91298406496.ps tmp/4ksq91298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/5fbd21298406496.ps tmp/5fbd21298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/6zocr1298406496.ps tmp/6zocr1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/7sujs1298406496.ps tmp/7sujs1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/8ld4j1298406496.ps tmp/8ld4j1298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/9wv801298406496.ps tmp/9wv801298406496.png",intern=TRUE)) character(0) > try(system("convert tmp/10bh5o1298406496.ps tmp/10bh5o1298406496.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.880 0.480 3.608