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Type 'q()' to quit R. > x <- array(list(87.0,0,96.3,0,107.1,0,115.2,0,106.1,1,89.5,1,91.3,1,97.6,1,100.7,1,104.6,1,94.7,1,101.8,1,102.5,1,105.3,1,110.3,1,109.8,1,117.3,1,118.8,1,131.3,1,125.9,1,133.1,1,147.0,1,145.8,1,164.4,1,149.8,1,137.7,1,151.7,1,156.8,1,180.0,1,180.4,1,170.4,1,191.6,1,199.5,1,218.2,1,217.5,1,205.0,1,194.0,1,199.3,1,219.3,1,211.1,1,215.2,1,240.2,1,242.2,1,240.7,1,255.4,1,253.0,1,218.2,1,203.7,1,205.6,1,215.6,1,188.5,1,202.9,1,214.0,1,230.3,1,230.0,1,241.0,1,259.6,1,247.8,1,270.3,1,289.7,1),dim=c(2,60),dimnames=list(c('prijs/olie','war? '),1:60)) > y <- array(NA,dim=c(2,60),dimnames=list(c('prijs/olie','war? '),1:60)) > 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 = 'Include Monthly Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > 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 prijs/olie war?\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1 87.0 0 1 0 0 0 0 0 0 0 0 0 0 2 96.3 0 0 1 0 0 0 0 0 0 0 0 0 3 107.1 0 0 0 1 0 0 0 0 0 0 0 0 4 115.2 0 0 0 0 1 0 0 0 0 0 0 0 5 106.1 1 0 0 0 0 1 0 0 0 0 0 0 6 89.5 1 0 0 0 0 0 1 0 0 0 0 0 7 91.3 1 0 0 0 0 0 0 1 0 0 0 0 8 97.6 1 0 0 0 0 0 0 0 1 0 0 0 9 100.7 1 0 0 0 0 0 0 0 0 1 0 0 10 104.6 1 0 0 0 0 0 0 0 0 0 1 0 11 94.7 1 0 0 0 0 0 0 0 0 0 0 1 12 101.8 1 0 0 0 0 0 0 0 0 0 0 0 13 102.5 1 1 0 0 0 0 0 0 0 0 0 0 14 105.3 1 0 1 0 0 0 0 0 0 0 0 0 15 110.3 1 0 0 1 0 0 0 0 0 0 0 0 16 109.8 1 0 0 0 1 0 0 0 0 0 0 0 17 117.3 1 0 0 0 0 1 0 0 0 0 0 0 18 118.8 1 0 0 0 0 0 1 0 0 0 0 0 19 131.3 1 0 0 0 0 0 0 1 0 0 0 0 20 125.9 1 0 0 0 0 0 0 0 1 0 0 0 21 133.1 1 0 0 0 0 0 0 0 0 1 0 0 22 147.0 1 0 0 0 0 0 0 0 0 0 1 0 23 145.8 1 0 0 0 0 0 0 0 0 0 0 1 24 164.4 1 0 0 0 0 0 0 0 0 0 0 0 25 149.8 1 1 0 0 0 0 0 0 0 0 0 0 26 137.7 1 0 1 0 0 0 0 0 0 0 0 0 27 151.7 1 0 0 1 0 0 0 0 0 0 0 0 28 156.8 1 0 0 0 1 0 0 0 0 0 0 0 29 180.0 1 0 0 0 0 1 0 0 0 0 0 0 30 180.4 1 0 0 0 0 0 1 0 0 0 0 0 31 170.4 1 0 0 0 0 0 0 1 0 0 0 0 32 191.6 1 0 0 0 0 0 0 0 1 0 0 0 33 199.5 1 0 0 0 0 0 0 0 0 1 0 0 34 218.2 1 0 0 0 0 0 0 0 0 0 1 0 35 217.5 1 0 0 0 0 0 0 0 0 0 0 1 36 205.0 1 0 0 0 0 0 0 0 0 0 0 0 37 194.0 1 1 0 0 0 0 0 0 0 0 0 0 38 199.3 1 0 1 0 0 0 0 0 0 0 0 0 39 219.3 1 0 0 1 0 0 0 0 0 0 0 0 40 211.1 1 0 0 0 1 0 0 0 0 0 0 0 41 215.2 1 0 0 0 0 1 0 0 0 0 0 0 42 240.2 1 0 0 0 0 0 1 0 0 0 0 0 43 242.2 1 0 0 0 0 0 0 1 0 0 0 0 44 240.7 1 0 0 0 0 0 0 0 1 0 0 0 45 255.4 1 0 0 0 0 0 0 0 0 1 0 0 46 253.0 1 0 0 0 0 0 0 0 0 0 1 0 47 218.2 1 0 0 0 0 0 0 0 0 0 0 1 48 203.7 1 0 0 0 0 0 0 0 0 0 0 0 49 205.6 1 1 0 0 0 0 0 0 0 0 0 0 50 215.6 1 0 1 0 0 0 0 0 0 0 0 0 51 188.5 1 0 0 1 0 0 0 0 0 0 0 0 52 202.9 1 0 0 0 1 0 0 0 0 0 0 0 53 214.0 1 0 0 0 0 1 0 0 0 0 0 0 54 230.3 1 0 0 0 0 0 1 0 0 0 0 0 55 230.0 1 0 0 0 0 0 0 1 0 0 0 0 56 241.0 1 0 0 0 0 0 0 0 1 0 0 0 57 259.6 1 0 0 0 0 0 0 0 0 1 0 0 58 247.8 1 0 0 0 0 0 0 0 0 0 1 0 59 270.3 1 0 0 0 0 0 0 0 0 0 0 1 60 289.7 1 0 0 0 0 0 0 0 0 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `war?\r` M1 M2 M3 M4 128.06 64.86 -32.17 -29.11 -24.57 -20.79 M5 M6 M7 M8 M9 M10 -26.40 -21.08 -19.88 -13.56 -3.26 1.20 M11 -3.62 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -94.60 -50.17 9.20 47.78 96.78 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 128.06 42.52 3.012 0.00417 ** `war?\r` 64.86 33.20 1.954 0.05671 . M1 -32.17 38.15 -0.843 0.40333 M2 -29.11 38.15 -0.763 0.44923 M3 -24.57 38.15 -0.644 0.52267 M4 -20.79 38.15 -0.545 0.58836 M5 -26.40 37.56 -0.703 0.48563 M6 -21.08 37.56 -0.561 0.57733 M7 -19.88 37.56 -0.529 0.59912 M8 -13.56 37.56 -0.361 0.71972 M9 -3.26 37.56 -0.087 0.93121 M10 1.20 37.56 0.032 0.97465 M11 -3.62 37.56 -0.096 0.92363 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 59.39 on 47 degrees of freedom Multiple R-Squared: 0.1486, Adjusted R-squared: -0.06874 F-statistic: 0.6838 on 12 and 47 DF, p-value: 0.7582 > postscript(file="/var/www/html/rcomp/tmp/1ilip1197025408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2szdd1197025408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3llww1197025408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4ut151197025408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5v1eb1197025408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 60 Frequency = 1 1 2 3 4 5 6 7 8 -8.8900 -2.6500 3.6100 7.9300 -60.4200 -82.3400 -81.7400 -81.7600 9 10 11 12 13 14 15 16 -88.9600 -89.5200 -94.6000 -91.1200 -58.2525 -58.5125 -58.0525 -62.3325 17 18 19 20 21 22 23 24 -49.2200 -53.0400 -41.7400 -53.4600 -56.5600 -47.1200 -43.5000 -28.5200 25 26 27 28 29 30 31 32 -10.9525 -26.1125 -16.6525 -15.3325 13.4800 8.5600 -2.6400 12.2400 33 34 35 36 37 38 39 40 9.8400 24.0800 28.2000 12.0800 33.2475 35.4875 50.9475 38.9675 41 42 43 44 45 46 47 48 48.6800 68.3600 69.1600 61.3400 65.7400 58.8800 28.9000 10.7800 49 50 51 52 53 54 55 56 44.8475 51.7875 20.1475 30.7675 47.4800 58.4600 56.9600 61.6400 57 58 59 60 69.9400 53.6800 81.0000 96.7800 > postscript(file="/var/www/html/rcomp/tmp/6853z1197025409.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 = 60 Frequency = 1 lag(myerror, k = 1) myerror 0 -8.8900 NA 1 -2.6500 -8.8900 2 3.6100 -2.6500 3 7.9300 3.6100 4 -60.4200 7.9300 5 -82.3400 -60.4200 6 -81.7400 -82.3400 7 -81.7600 -81.7400 8 -88.9600 -81.7600 9 -89.5200 -88.9600 10 -94.6000 -89.5200 11 -91.1200 -94.6000 12 -58.2525 -91.1200 13 -58.5125 -58.2525 14 -58.0525 -58.5125 15 -62.3325 -58.0525 16 -49.2200 -62.3325 17 -53.0400 -49.2200 18 -41.7400 -53.0400 19 -53.4600 -41.7400 20 -56.5600 -53.4600 21 -47.1200 -56.5600 22 -43.5000 -47.1200 23 -28.5200 -43.5000 24 -10.9525 -28.5200 25 -26.1125 -10.9525 26 -16.6525 -26.1125 27 -15.3325 -16.6525 28 13.4800 -15.3325 29 8.5600 13.4800 30 -2.6400 8.5600 31 12.2400 -2.6400 32 9.8400 12.2400 33 24.0800 9.8400 34 28.2000 24.0800 35 12.0800 28.2000 36 33.2475 12.0800 37 35.4875 33.2475 38 50.9475 35.4875 39 38.9675 50.9475 40 48.6800 38.9675 41 68.3600 48.6800 42 69.1600 68.3600 43 61.3400 69.1600 44 65.7400 61.3400 45 58.8800 65.7400 46 28.9000 58.8800 47 10.7800 28.9000 48 44.8475 10.7800 49 51.7875 44.8475 50 20.1475 51.7875 51 30.7675 20.1475 52 47.4800 30.7675 53 58.4600 47.4800 54 56.9600 58.4600 55 61.6400 56.9600 56 69.9400 61.6400 57 53.6800 69.9400 58 81.0000 53.6800 59 96.7800 81.0000 60 NA 96.7800 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -2.6500 -8.8900 [2,] 3.6100 -2.6500 [3,] 7.9300 3.6100 [4,] -60.4200 7.9300 [5,] -82.3400 -60.4200 [6,] -81.7400 -82.3400 [7,] -81.7600 -81.7400 [8,] -88.9600 -81.7600 [9,] -89.5200 -88.9600 [10,] -94.6000 -89.5200 [11,] -91.1200 -94.6000 [12,] -58.2525 -91.1200 [13,] -58.5125 -58.2525 [14,] -58.0525 -58.5125 [15,] -62.3325 -58.0525 [16,] -49.2200 -62.3325 [17,] -53.0400 -49.2200 [18,] -41.7400 -53.0400 [19,] -53.4600 -41.7400 [20,] -56.5600 -53.4600 [21,] -47.1200 -56.5600 [22,] -43.5000 -47.1200 [23,] -28.5200 -43.5000 [24,] -10.9525 -28.5200 [25,] -26.1125 -10.9525 [26,] -16.6525 -26.1125 [27,] -15.3325 -16.6525 [28,] 13.4800 -15.3325 [29,] 8.5600 13.4800 [30,] -2.6400 8.5600 [31,] 12.2400 -2.6400 [32,] 9.8400 12.2400 [33,] 24.0800 9.8400 [34,] 28.2000 24.0800 [35,] 12.0800 28.2000 [36,] 33.2475 12.0800 [37,] 35.4875 33.2475 [38,] 50.9475 35.4875 [39,] 38.9675 50.9475 [40,] 48.6800 38.9675 [41,] 68.3600 48.6800 [42,] 69.1600 68.3600 [43,] 61.3400 69.1600 [44,] 65.7400 61.3400 [45,] 58.8800 65.7400 [46,] 28.9000 58.8800 [47,] 10.7800 28.9000 [48,] 44.8475 10.7800 [49,] 51.7875 44.8475 [50,] 20.1475 51.7875 [51,] 30.7675 20.1475 [52,] 47.4800 30.7675 [53,] 58.4600 47.4800 [54,] 56.9600 58.4600 [55,] 61.6400 56.9600 [56,] 69.9400 61.6400 [57,] 53.6800 69.9400 [58,] 81.0000 53.6800 [59,] 96.7800 81.0000 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -2.6500 -8.8900 2 3.6100 -2.6500 3 7.9300 3.6100 4 -60.4200 7.9300 5 -82.3400 -60.4200 6 -81.7400 -82.3400 7 -81.7600 -81.7400 8 -88.9600 -81.7600 9 -89.5200 -88.9600 10 -94.6000 -89.5200 11 -91.1200 -94.6000 12 -58.2525 -91.1200 13 -58.5125 -58.2525 14 -58.0525 -58.5125 15 -62.3325 -58.0525 16 -49.2200 -62.3325 17 -53.0400 -49.2200 18 -41.7400 -53.0400 19 -53.4600 -41.7400 20 -56.5600 -53.4600 21 -47.1200 -56.5600 22 -43.5000 -47.1200 23 -28.5200 -43.5000 24 -10.9525 -28.5200 25 -26.1125 -10.9525 26 -16.6525 -26.1125 27 -15.3325 -16.6525 28 13.4800 -15.3325 29 8.5600 13.4800 30 -2.6400 8.5600 31 12.2400 -2.6400 32 9.8400 12.2400 33 24.0800 9.8400 34 28.2000 24.0800 35 12.0800 28.2000 36 33.2475 12.0800 37 35.4875 33.2475 38 50.9475 35.4875 39 38.9675 50.9475 40 48.6800 38.9675 41 68.3600 48.6800 42 69.1600 68.3600 43 61.3400 69.1600 44 65.7400 61.3400 45 58.8800 65.7400 46 28.9000 58.8800 47 10.7800 28.9000 48 44.8475 10.7800 49 51.7875 44.8475 50 20.1475 51.7875 51 30.7675 20.1475 52 47.4800 30.7675 53 58.4600 47.4800 54 56.9600 58.4600 55 61.6400 56.9600 56 69.9400 61.6400 57 53.6800 69.9400 58 81.0000 53.6800 59 96.7800 81.0000 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/7o5rm1197025409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8pscv1197025409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9abby1197025409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > load(file='/var/www/html/rcomp/createtable') > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/10i5kb1197025409.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11ji9l1197025409.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/12wac71197025409.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/13qvhe1197025409.tab") > > system("convert tmp/1ilip1197025408.ps tmp/1ilip1197025408.png") > system("convert tmp/2szdd1197025408.ps tmp/2szdd1197025408.png") > system("convert tmp/3llww1197025408.ps tmp/3llww1197025408.png") > system("convert tmp/4ut151197025408.ps tmp/4ut151197025408.png") > system("convert tmp/5v1eb1197025408.ps tmp/5v1eb1197025408.png") > system("convert tmp/6853z1197025409.ps tmp/6853z1197025409.png") > system("convert tmp/7o5rm1197025409.ps tmp/7o5rm1197025409.png") > system("convert tmp/8pscv1197025409.ps tmp/8pscv1197025409.png") > system("convert tmp/9abby1197025409.ps tmp/9abby1197025409.png") > > > proc.time() user system elapsed 2.222 1.417 2.671