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Type 'q()' to quit R. > x <- array(list(733.6,0,844.9,0,864.3,0,833.5,0,814.9,0,820.4,0,710.8,0,773.1,0,801.2,0,832.9,0,808.3,0,817.2,0,745.5,0,932.6,0,1057.0,0,879.9,0,1089.5,0,903.0,0,846.1,0,959.1,0,952.0,0,1092.5,0,1188.9,0,996.7,0,1034.3,0,898.2,0,1111.6,0,900.5,0,1049.2,0,1010.9,0,875.9,0,849.9,0,713.4,1,918.6,1,912.5,1,767.0,1,902.2,1,891.9,1,874.0,1,930.9,1,944.2,1,935.9,1,937.1,1,885.1,1,892.4,1,987.3,1,946.3,1,799.6,1,875.4,1,846.2,1,880.6,1,885.7,1,868.9,1,882.5,1,789.6,1,773.3,1,804.3,1,817.8,1,836.7,1,721.8,1),dim=c(2,60),dimnames=list(c('y','x'),1:60)) > y <- array(NA,dim=c(2,60),dimnames=list(c('y','x'),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 = '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 y x M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 733.6 0 1 0 0 0 0 0 0 0 0 0 0 1 2 844.9 0 0 1 0 0 0 0 0 0 0 0 0 2 3 864.3 0 0 0 1 0 0 0 0 0 0 0 0 3 4 833.5 0 0 0 0 1 0 0 0 0 0 0 0 4 5 814.9 0 0 0 0 0 1 0 0 0 0 0 0 5 6 820.4 0 0 0 0 0 0 1 0 0 0 0 0 6 7 710.8 0 0 0 0 0 0 0 1 0 0 0 0 7 8 773.1 0 0 0 0 0 0 0 0 1 0 0 0 8 9 801.2 0 0 0 0 0 0 0 0 0 1 0 0 9 10 832.9 0 0 0 0 0 0 0 0 0 0 1 0 10 11 808.3 0 0 0 0 0 0 0 0 0 0 0 1 11 12 817.2 0 0 0 0 0 0 0 0 0 0 0 0 12 13 745.5 0 1 0 0 0 0 0 0 0 0 0 0 13 14 932.6 0 0 1 0 0 0 0 0 0 0 0 0 14 15 1057.0 0 0 0 1 0 0 0 0 0 0 0 0 15 16 879.9 0 0 0 0 1 0 0 0 0 0 0 0 16 17 1089.5 0 0 0 0 0 1 0 0 0 0 0 0 17 18 903.0 0 0 0 0 0 0 1 0 0 0 0 0 18 19 846.1 0 0 0 0 0 0 0 1 0 0 0 0 19 20 959.1 0 0 0 0 0 0 0 0 1 0 0 0 20 21 952.0 0 0 0 0 0 0 0 0 0 1 0 0 21 22 1092.5 0 0 0 0 0 0 0 0 0 0 1 0 22 23 1188.9 0 0 0 0 0 0 0 0 0 0 0 1 23 24 996.7 0 0 0 0 0 0 0 0 0 0 0 0 24 25 1034.3 0 1 0 0 0 0 0 0 0 0 0 0 25 26 898.2 0 0 1 0 0 0 0 0 0 0 0 0 26 27 1111.6 0 0 0 1 0 0 0 0 0 0 0 0 27 28 900.5 0 0 0 0 1 0 0 0 0 0 0 0 28 29 1049.2 0 0 0 0 0 1 0 0 0 0 0 0 29 30 1010.9 0 0 0 0 0 0 1 0 0 0 0 0 30 31 875.9 0 0 0 0 0 0 0 1 0 0 0 0 31 32 849.9 0 0 0 0 0 0 0 0 1 0 0 0 32 33 713.4 1 0 0 0 0 0 0 0 0 1 0 0 33 34 918.6 1 0 0 0 0 0 0 0 0 0 1 0 34 35 912.5 1 0 0 0 0 0 0 0 0 0 0 1 35 36 767.0 1 0 0 0 0 0 0 0 0 0 0 0 36 37 902.2 1 1 0 0 0 0 0 0 0 0 0 0 37 38 891.9 1 0 1 0 0 0 0 0 0 0 0 0 38 39 874.0 1 0 0 1 0 0 0 0 0 0 0 0 39 40 930.9 1 0 0 0 1 0 0 0 0 0 0 0 40 41 944.2 1 0 0 0 0 1 0 0 0 0 0 0 41 42 935.9 1 0 0 0 0 0 1 0 0 0 0 0 42 43 937.1 1 0 0 0 0 0 0 1 0 0 0 0 43 44 885.1 1 0 0 0 0 0 0 0 1 0 0 0 44 45 892.4 1 0 0 0 0 0 0 0 0 1 0 0 45 46 987.3 1 0 0 0 0 0 0 0 0 0 1 0 46 47 946.3 1 0 0 0 0 0 0 0 0 0 0 1 47 48 799.6 1 0 0 0 0 0 0 0 0 0 0 0 48 49 875.4 1 1 0 0 0 0 0 0 0 0 0 0 49 50 846.2 1 0 1 0 0 0 0 0 0 0 0 0 50 51 880.6 1 0 0 1 0 0 0 0 0 0 0 0 51 52 885.7 1 0 0 0 1 0 0 0 0 0 0 0 52 53 868.9 1 0 0 0 0 1 0 0 0 0 0 0 53 54 882.5 1 0 0 0 0 0 1 0 0 0 0 0 54 55 789.6 1 0 0 0 0 0 0 1 0 0 0 0 55 56 773.3 1 0 0 0 0 0 0 0 1 0 0 0 56 57 804.3 1 0 0 0 0 0 0 0 0 1 0 0 57 58 817.8 1 0 0 0 0 0 0 0 0 0 1 0 58 59 836.7 1 0 0 0 0 0 0 0 0 0 0 1 59 60 721.8 1 0 0 0 0 0 0 0 0 0 0 0 60 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) x M1 M2 M3 M4 773.4750 -161.6583 49.4022 69.9628 140.7033 65.3039 M5 M6 M7 M8 M9 M10 128.5444 81.7450 -0.8944 11.3061 24.1983 117.3589 M11 t 122.0794 3.9994 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -143.343 -59.033 -5.402 71.291 201.358 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 773.4750 49.9164 15.495 < 2e-16 *** x -161.6583 48.0321 -3.366 0.00155 ** M1 49.4022 58.2523 0.848 0.40079 M2 69.9628 58.1036 1.204 0.23471 M3 140.7033 57.9877 2.426 0.01923 * M4 65.3039 57.9047 1.128 0.26526 M5 128.5444 57.8549 2.222 0.03125 * M6 81.7450 57.8383 1.413 0.16429 M7 -0.8944 57.8549 -0.015 0.98773 M8 11.3061 57.9047 0.195 0.84605 M9 24.1983 57.7884 0.419 0.67735 M10 117.3589 57.7052 2.034 0.04777 * M11 122.0794 57.6552 2.117 0.03966 * t 3.9994 1.3866 2.884 0.00595 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 91.13 on 46 degrees of freedom Multiple R-Squared: 0.3758, Adjusted R-squared: 0.1995 F-statistic: 2.131 on 13 and 46 DF, p-value: 0.03013 > postscript(file="/var/www/html/rcomp/tmp/17qit1197027865.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/2mfrn1197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3y2ng1197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4hoj31197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5792o1197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 -93.2766667 -6.5366667 -61.8766667 -21.2766667 -107.1166667 -58.8166667 7 8 9 10 11 12 -89.7766667 -43.6766667 -32.4683333 -97.9283333 -131.2483333 -4.2683333 13 14 15 16 17 18 -129.3700000 33.1700000 82.8300000 -22.8700000 119.4900000 -24.2100000 19 20 21 22 23 24 -2.4700000 94.3300000 70.3383333 113.6783333 201.3583333 127.2383333 25 26 27 28 29 30 111.4366667 -49.2233333 89.4366667 -50.2633333 31.1966667 35.6966667 31 32 33 34 35 36 -20.6633333 -62.8633333 -54.5966667 53.4433333 38.6233333 11.2033333 37 38 39 40 41 42 93.0016667 58.1416667 -34.4983333 93.8016667 39.8616667 74.3616667 43 44 45 46 47 48 154.2016667 86.0016667 76.4100000 74.1500000 24.4300000 -4.1900000 49 50 51 52 53 54 18.2083333 -35.5516667 -75.8916667 0.6083333 -83.4316667 -27.0316667 55 56 57 58 59 60 -41.2916667 -73.7916667 -59.6833333 -143.3433333 -133.1633333 -129.9833333 > postscript(file="/var/www/html/rcomp/tmp/6b4bx1197027865.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 -93.2766667 NA 1 -6.5366667 -93.2766667 2 -61.8766667 -6.5366667 3 -21.2766667 -61.8766667 4 -107.1166667 -21.2766667 5 -58.8166667 -107.1166667 6 -89.7766667 -58.8166667 7 -43.6766667 -89.7766667 8 -32.4683333 -43.6766667 9 -97.9283333 -32.4683333 10 -131.2483333 -97.9283333 11 -4.2683333 -131.2483333 12 -129.3700000 -4.2683333 13 33.1700000 -129.3700000 14 82.8300000 33.1700000 15 -22.8700000 82.8300000 16 119.4900000 -22.8700000 17 -24.2100000 119.4900000 18 -2.4700000 -24.2100000 19 94.3300000 -2.4700000 20 70.3383333 94.3300000 21 113.6783333 70.3383333 22 201.3583333 113.6783333 23 127.2383333 201.3583333 24 111.4366667 127.2383333 25 -49.2233333 111.4366667 26 89.4366667 -49.2233333 27 -50.2633333 89.4366667 28 31.1966667 -50.2633333 29 35.6966667 31.1966667 30 -20.6633333 35.6966667 31 -62.8633333 -20.6633333 32 -54.5966667 -62.8633333 33 53.4433333 -54.5966667 34 38.6233333 53.4433333 35 11.2033333 38.6233333 36 93.0016667 11.2033333 37 58.1416667 93.0016667 38 -34.4983333 58.1416667 39 93.8016667 -34.4983333 40 39.8616667 93.8016667 41 74.3616667 39.8616667 42 154.2016667 74.3616667 43 86.0016667 154.2016667 44 76.4100000 86.0016667 45 74.1500000 76.4100000 46 24.4300000 74.1500000 47 -4.1900000 24.4300000 48 18.2083333 -4.1900000 49 -35.5516667 18.2083333 50 -75.8916667 -35.5516667 51 0.6083333 -75.8916667 52 -83.4316667 0.6083333 53 -27.0316667 -83.4316667 54 -41.2916667 -27.0316667 55 -73.7916667 -41.2916667 56 -59.6833333 -73.7916667 57 -143.3433333 -59.6833333 58 -133.1633333 -143.3433333 59 -129.9833333 -133.1633333 60 NA -129.9833333 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -6.5366667 -93.2766667 [2,] -61.8766667 -6.5366667 [3,] -21.2766667 -61.8766667 [4,] -107.1166667 -21.2766667 [5,] -58.8166667 -107.1166667 [6,] -89.7766667 -58.8166667 [7,] -43.6766667 -89.7766667 [8,] -32.4683333 -43.6766667 [9,] -97.9283333 -32.4683333 [10,] -131.2483333 -97.9283333 [11,] -4.2683333 -131.2483333 [12,] -129.3700000 -4.2683333 [13,] 33.1700000 -129.3700000 [14,] 82.8300000 33.1700000 [15,] -22.8700000 82.8300000 [16,] 119.4900000 -22.8700000 [17,] -24.2100000 119.4900000 [18,] -2.4700000 -24.2100000 [19,] 94.3300000 -2.4700000 [20,] 70.3383333 94.3300000 [21,] 113.6783333 70.3383333 [22,] 201.3583333 113.6783333 [23,] 127.2383333 201.3583333 [24,] 111.4366667 127.2383333 [25,] -49.2233333 111.4366667 [26,] 89.4366667 -49.2233333 [27,] -50.2633333 89.4366667 [28,] 31.1966667 -50.2633333 [29,] 35.6966667 31.1966667 [30,] -20.6633333 35.6966667 [31,] -62.8633333 -20.6633333 [32,] -54.5966667 -62.8633333 [33,] 53.4433333 -54.5966667 [34,] 38.6233333 53.4433333 [35,] 11.2033333 38.6233333 [36,] 93.0016667 11.2033333 [37,] 58.1416667 93.0016667 [38,] -34.4983333 58.1416667 [39,] 93.8016667 -34.4983333 [40,] 39.8616667 93.8016667 [41,] 74.3616667 39.8616667 [42,] 154.2016667 74.3616667 [43,] 86.0016667 154.2016667 [44,] 76.4100000 86.0016667 [45,] 74.1500000 76.4100000 [46,] 24.4300000 74.1500000 [47,] -4.1900000 24.4300000 [48,] 18.2083333 -4.1900000 [49,] -35.5516667 18.2083333 [50,] -75.8916667 -35.5516667 [51,] 0.6083333 -75.8916667 [52,] -83.4316667 0.6083333 [53,] -27.0316667 -83.4316667 [54,] -41.2916667 -27.0316667 [55,] -73.7916667 -41.2916667 [56,] -59.6833333 -73.7916667 [57,] -143.3433333 -59.6833333 [58,] -133.1633333 -143.3433333 [59,] -129.9833333 -133.1633333 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -6.5366667 -93.2766667 2 -61.8766667 -6.5366667 3 -21.2766667 -61.8766667 4 -107.1166667 -21.2766667 5 -58.8166667 -107.1166667 6 -89.7766667 -58.8166667 7 -43.6766667 -89.7766667 8 -32.4683333 -43.6766667 9 -97.9283333 -32.4683333 10 -131.2483333 -97.9283333 11 -4.2683333 -131.2483333 12 -129.3700000 -4.2683333 13 33.1700000 -129.3700000 14 82.8300000 33.1700000 15 -22.8700000 82.8300000 16 119.4900000 -22.8700000 17 -24.2100000 119.4900000 18 -2.4700000 -24.2100000 19 94.3300000 -2.4700000 20 70.3383333 94.3300000 21 113.6783333 70.3383333 22 201.3583333 113.6783333 23 127.2383333 201.3583333 24 111.4366667 127.2383333 25 -49.2233333 111.4366667 26 89.4366667 -49.2233333 27 -50.2633333 89.4366667 28 31.1966667 -50.2633333 29 35.6966667 31.1966667 30 -20.6633333 35.6966667 31 -62.8633333 -20.6633333 32 -54.5966667 -62.8633333 33 53.4433333 -54.5966667 34 38.6233333 53.4433333 35 11.2033333 38.6233333 36 93.0016667 11.2033333 37 58.1416667 93.0016667 38 -34.4983333 58.1416667 39 93.8016667 -34.4983333 40 39.8616667 93.8016667 41 74.3616667 39.8616667 42 154.2016667 74.3616667 43 86.0016667 154.2016667 44 76.4100000 86.0016667 45 74.1500000 76.4100000 46 24.4300000 74.1500000 47 -4.1900000 24.4300000 48 18.2083333 -4.1900000 49 -35.5516667 18.2083333 50 -75.8916667 -35.5516667 51 0.6083333 -75.8916667 52 -83.4316667 0.6083333 53 -27.0316667 -83.4316667 54 -41.2916667 -27.0316667 55 -73.7916667 -41.2916667 56 -59.6833333 -73.7916667 57 -143.3433333 -59.6833333 58 -133.1633333 -143.3433333 59 -129.9833333 -133.1633333 > 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/7zq981197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8d4np1197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9kdd41197027865.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > load(file='/var/www/html/rcomp/createtable') > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/10jlhq1197027865.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/11al6j1197027865.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/121ndn1197027865.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/133aih1197027865.tab") > > system("convert tmp/17qit1197027865.ps tmp/17qit1197027865.png") > system("convert tmp/2mfrn1197027865.ps tmp/2mfrn1197027865.png") > system("convert tmp/3y2ng1197027865.ps tmp/3y2ng1197027865.png") > system("convert tmp/4hoj31197027865.ps tmp/4hoj31197027865.png") > system("convert tmp/5792o1197027865.ps tmp/5792o1197027865.png") > system("convert tmp/6b4bx1197027865.ps tmp/6b4bx1197027865.png") > system("convert tmp/7zq981197027865.ps tmp/7zq981197027865.png") > system("convert tmp/8d4np1197027865.ps tmp/8d4np1197027865.png") > system("convert tmp/9kdd41197027865.ps tmp/9kdd41197027865.png") > > > proc.time() user system elapsed 2.293 1.452 3.096