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Type 'q()' to quit R. > x <- array(list(36409 + ,0 + ,99.25 + ,33163 + ,0 + ,99.36 + ,34122 + ,0 + ,99.34 + ,35225 + ,0 + ,99.36 + ,28249 + ,0 + ,100.85 + ,30374 + ,0 + ,100.86 + ,26311 + ,0 + ,100.93 + ,22069 + ,0 + ,101.25 + ,23651 + ,0 + ,101.72 + ,28628 + ,0 + ,101.54 + ,23187 + ,0 + ,101.35 + ,14727 + ,0 + ,101.42 + ,43080 + ,0 + ,101.57 + ,32519 + ,0 + ,101.76 + ,39657 + ,0 + ,102.05 + ,33614 + ,0 + ,102.05 + ,28671 + ,0 + ,101.89 + ,34243 + ,0 + ,102.06 + ,27336 + ,0 + ,102 + ,22916 + ,0 + ,102.14 + ,24537 + ,0 + ,102.2 + ,26128 + ,0 + ,102.3 + ,22602 + ,0 + ,102.7 + ,15744 + ,0 + ,102.77 + ,41086 + ,0 + ,103.1 + ,39690 + ,0 + ,103.13 + ,43129 + ,0 + ,103.31 + ,37863 + ,0 + ,103.52 + ,35953 + ,0 + ,103.34 + ,29133 + ,0 + ,103.53 + ,24693 + ,0 + ,103.8 + ,22205 + ,0 + ,103.9 + ,21725 + ,0 + ,103.91 + ,27192 + ,0 + ,104.21 + ,21790 + ,0 + ,104.58 + ,13253 + ,0 + ,104.89 + ,37702 + ,0 + ,105.15 + ,30364 + ,0 + ,105.24 + ,32609 + ,0 + ,105.57 + ,30212 + ,0 + ,105.62 + ,29965 + ,0 + ,106.17 + ,28352 + ,0 + ,106.27 + ,25814 + ,0 + ,106.41 + ,22414 + ,0 + ,106.94 + ,20506 + ,0 + ,107.16 + ,28806 + ,0 + ,107.32 + ,22228 + ,0 + ,107.32 + ,13971 + ,0 + ,107.35 + ,36845 + ,0 + ,107.55 + ,35338 + ,0 + ,107.87 + ,35022 + ,0 + ,108.37 + ,34777 + ,0 + ,108.38 + ,26887 + ,0 + ,107.92 + ,23970 + ,0 + ,108.03 + ,22780 + ,0 + ,108.14 + ,17351 + ,0 + ,108.3 + ,21382 + ,0 + ,108.64 + ,24561 + ,0 + ,108.66 + ,17409 + ,0 + ,109.04 + ,11514 + ,0 + ,109.03 + ,31514 + ,0 + ,109.03 + ,27071 + ,0 + ,109.54 + ,29462 + ,0 + ,109.75 + ,26105 + ,0 + ,109.83 + ,22397 + ,0 + ,109.65 + ,23843 + ,0 + ,109.82 + ,21705 + ,0 + ,109.95 + ,18089 + ,0 + ,110.12 + ,20764 + ,0 + ,110.15 + ,25316 + ,0 + ,110.21 + ,17704 + ,0 + ,109.99 + ,15548 + ,0 + ,110.14 + ,28029 + ,0 + ,110.14 + ,29383 + ,0 + ,110.81 + ,36438 + ,0 + ,110.97 + ,32034 + ,0 + ,110.99 + ,22679 + ,0 + ,109.73 + ,24319 + ,0 + ,109.81 + ,18004 + ,0 + ,110.02 + ,17537 + ,0 + ,110.18 + ,20366 + ,0 + ,110.21 + ,22782 + ,0 + ,110.25 + ,19169 + ,0 + ,110.36 + ,13807 + ,0 + ,110.51 + ,29743 + ,0 + ,110.6 + ,25591 + ,0 + ,110.95 + ,29096 + ,1 + ,111.18 + ,26482 + ,1 + ,111.19 + ,22405 + ,1 + ,111.69 + ,27044 + ,1 + ,111.7 + ,17970 + ,1 + ,111.83 + ,18730 + ,1 + ,111.77 + ,19684 + ,1 + ,111.73 + ,19785 + ,1 + ,112.01 + ,18479 + ,1 + ,111.86 + ,10698 + ,1 + ,112.04) + ,dim=c(3 + ,96) + ,dimnames=list(c('Y' + ,'X1' + ,'X2') + ,1:96)) > y <- array(NA,dim=c(3,96),dimnames=list(c('Y','X1','X2'),1:96)) > 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 X1 X2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 36409 0 99.25 1 0 0 0 0 0 0 0 0 0 0 1 2 33163 0 99.36 0 1 0 0 0 0 0 0 0 0 0 2 3 34122 0 99.34 0 0 1 0 0 0 0 0 0 0 0 3 4 35225 0 99.36 0 0 0 1 0 0 0 0 0 0 0 4 5 28249 0 100.85 0 0 0 0 1 0 0 0 0 0 0 5 6 30374 0 100.86 0 0 0 0 0 1 0 0 0 0 0 6 7 26311 0 100.93 0 0 0 0 0 0 1 0 0 0 0 7 8 22069 0 101.25 0 0 0 0 0 0 0 1 0 0 0 8 9 23651 0 101.72 0 0 0 0 0 0 0 0 1 0 0 9 10 28628 0 101.54 0 0 0 0 0 0 0 0 0 1 0 10 11 23187 0 101.35 0 0 0 0 0 0 0 0 0 0 1 11 12 14727 0 101.42 0 0 0 0 0 0 0 0 0 0 0 12 13 43080 0 101.57 1 0 0 0 0 0 0 0 0 0 0 13 14 32519 0 101.76 0 1 0 0 0 0 0 0 0 0 0 14 15 39657 0 102.05 0 0 1 0 0 0 0 0 0 0 0 15 16 33614 0 102.05 0 0 0 1 0 0 0 0 0 0 0 16 17 28671 0 101.89 0 0 0 0 1 0 0 0 0 0 0 17 18 34243 0 102.06 0 0 0 0 0 1 0 0 0 0 0 18 19 27336 0 102.00 0 0 0 0 0 0 1 0 0 0 0 19 20 22916 0 102.14 0 0 0 0 0 0 0 1 0 0 0 20 21 24537 0 102.20 0 0 0 0 0 0 0 0 1 0 0 21 22 26128 0 102.30 0 0 0 0 0 0 0 0 0 1 0 22 23 22602 0 102.70 0 0 0 0 0 0 0 0 0 0 1 23 24 15744 0 102.77 0 0 0 0 0 0 0 0 0 0 0 24 25 41086 0 103.10 1 0 0 0 0 0 0 0 0 0 0 25 26 39690 0 103.13 0 1 0 0 0 0 0 0 0 0 0 26 27 43129 0 103.31 0 0 1 0 0 0 0 0 0 0 0 27 28 37863 0 103.52 0 0 0 1 0 0 0 0 0 0 0 28 29 35953 0 103.34 0 0 0 0 1 0 0 0 0 0 0 29 30 29133 0 103.53 0 0 0 0 0 1 0 0 0 0 0 30 31 24693 0 103.80 0 0 0 0 0 0 1 0 0 0 0 31 32 22205 0 103.90 0 0 0 0 0 0 0 1 0 0 0 32 33 21725 0 103.91 0 0 0 0 0 0 0 0 1 0 0 33 34 27192 0 104.21 0 0 0 0 0 0 0 0 0 1 0 34 35 21790 0 104.58 0 0 0 0 0 0 0 0 0 0 1 35 36 13253 0 104.89 0 0 0 0 0 0 0 0 0 0 0 36 37 37702 0 105.15 1 0 0 0 0 0 0 0 0 0 0 37 38 30364 0 105.24 0 1 0 0 0 0 0 0 0 0 0 38 39 32609 0 105.57 0 0 1 0 0 0 0 0 0 0 0 39 40 30212 0 105.62 0 0 0 1 0 0 0 0 0 0 0 40 41 29965 0 106.17 0 0 0 0 1 0 0 0 0 0 0 41 42 28352 0 106.27 0 0 0 0 0 1 0 0 0 0 0 42 43 25814 0 106.41 0 0 0 0 0 0 1 0 0 0 0 43 44 22414 0 106.94 0 0 0 0 0 0 0 1 0 0 0 44 45 20506 0 107.16 0 0 0 0 0 0 0 0 1 0 0 45 46 28806 0 107.32 0 0 0 0 0 0 0 0 0 1 0 46 47 22228 0 107.32 0 0 0 0 0 0 0 0 0 0 1 47 48 13971 0 107.35 0 0 0 0 0 0 0 0 0 0 0 48 49 36845 0 107.55 1 0 0 0 0 0 0 0 0 0 0 49 50 35338 0 107.87 0 1 0 0 0 0 0 0 0 0 0 50 51 35022 0 108.37 0 0 1 0 0 0 0 0 0 0 0 51 52 34777 0 108.38 0 0 0 1 0 0 0 0 0 0 0 52 53 26887 0 107.92 0 0 0 0 1 0 0 0 0 0 0 53 54 23970 0 108.03 0 0 0 0 0 1 0 0 0 0 0 54 55 22780 0 108.14 0 0 0 0 0 0 1 0 0 0 0 55 56 17351 0 108.30 0 0 0 0 0 0 0 1 0 0 0 56 57 21382 0 108.64 0 0 0 0 0 0 0 0 1 0 0 57 58 24561 0 108.66 0 0 0 0 0 0 0 0 0 1 0 58 59 17409 0 109.04 0 0 0 0 0 0 0 0 0 0 1 59 60 11514 0 109.03 0 0 0 0 0 0 0 0 0 0 0 60 61 31514 0 109.03 1 0 0 0 0 0 0 0 0 0 0 61 62 27071 0 109.54 0 1 0 0 0 0 0 0 0 0 0 62 63 29462 0 109.75 0 0 1 0 0 0 0 0 0 0 0 63 64 26105 0 109.83 0 0 0 1 0 0 0 0 0 0 0 64 65 22397 0 109.65 0 0 0 0 1 0 0 0 0 0 0 65 66 23843 0 109.82 0 0 0 0 0 1 0 0 0 0 0 66 67 21705 0 109.95 0 0 0 0 0 0 1 0 0 0 0 67 68 18089 0 110.12 0 0 0 0 0 0 0 1 0 0 0 68 69 20764 0 110.15 0 0 0 0 0 0 0 0 1 0 0 69 70 25316 0 110.21 0 0 0 0 0 0 0 0 0 1 0 70 71 17704 0 109.99 0 0 0 0 0 0 0 0 0 0 1 71 72 15548 0 110.14 0 0 0 0 0 0 0 0 0 0 0 72 73 28029 0 110.14 1 0 0 0 0 0 0 0 0 0 0 73 74 29383 0 110.81 0 1 0 0 0 0 0 0 0 0 0 74 75 36438 0 110.97 0 0 1 0 0 0 0 0 0 0 0 75 76 32034 0 110.99 0 0 0 1 0 0 0 0 0 0 0 76 77 22679 0 109.73 0 0 0 0 1 0 0 0 0 0 0 77 78 24319 0 109.81 0 0 0 0 0 1 0 0 0 0 0 78 79 18004 0 110.02 0 0 0 0 0 0 1 0 0 0 0 79 80 17537 0 110.18 0 0 0 0 0 0 0 1 0 0 0 80 81 20366 0 110.21 0 0 0 0 0 0 0 0 1 0 0 81 82 22782 0 110.25 0 0 0 0 0 0 0 0 0 1 0 82 83 19169 0 110.36 0 0 0 0 0 0 0 0 0 0 1 83 84 13807 0 110.51 0 0 0 0 0 0 0 0 0 0 0 84 85 29743 0 110.60 1 0 0 0 0 0 0 0 0 0 0 85 86 25591 0 110.95 0 1 0 0 0 0 0 0 0 0 0 86 87 29096 1 111.18 0 0 1 0 0 0 0 0 0 0 0 87 88 26482 1 111.19 0 0 0 1 0 0 0 0 0 0 0 88 89 22405 1 111.69 0 0 0 0 1 0 0 0 0 0 0 89 90 27044 1 111.70 0 0 0 0 0 1 0 0 0 0 0 90 91 17970 1 111.83 0 0 0 0 0 0 1 0 0 0 0 91 92 18730 1 111.77 0 0 0 0 0 0 0 1 0 0 0 92 93 19684 1 111.73 0 0 0 0 0 0 0 0 1 0 0 93 94 19785 1 112.01 0 0 0 0 0 0 0 0 0 1 0 94 95 18479 1 111.86 0 0 0 0 0 0 0 0 0 0 1 95 96 10698 1 112.04 0 0 0 0 0 0 0 0 0 0 0 96 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X1 X2 M1 M2 M3 28380.82 146.76 -99.08 20928.00 17121.16 20504.28 M4 M5 M6 M7 M8 M9 17682.53 12874.18 13469.76 8975.20 6157.45 7660.50 M10 M11 t 11569.21 6575.31 -76.18 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -4806.5 -1997.0 -190.0 1620.6 7145.7 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 28380.82 43551.77 0.652 0.516 X1 146.76 1202.44 0.122 0.903 X2 -99.08 436.91 -0.227 0.821 M1 20928.00 1351.06 15.490 < 2e-16 *** M2 17121.16 1351.13 12.672 < 2e-16 *** M3 20504.28 1357.39 15.106 < 2e-16 *** M4 17682.53 1352.58 13.073 < 2e-16 *** M5 12874.18 1348.84 9.545 6.68e-15 *** M6 13469.76 1347.49 9.996 8.63e-16 *** M7 8975.20 1346.67 6.665 2.97e-09 *** M8 6157.45 1346.92 4.572 1.72e-05 *** M9 7660.50 1346.48 5.689 1.96e-07 *** M10 11569.21 1345.54 8.598 4.95e-13 *** M11 6575.31 1344.95 4.889 5.05e-06 *** t -76.18 64.00 -1.190 0.237 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2690 on 81 degrees of freedom Multiple R-Squared: 0.8847, Adjusted R-squared: 0.8648 F-statistic: 44.41 on 14 and 81 DF, p-value: < 2.2e-16 > postscript(file="/var/www/html/rcomp/tmp/1aark1199525320.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/2e2dk1199525320.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/39ln31199525320.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4m1ni1199525320.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5lu5v1199525320.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 96 Frequency = 1 1 2 3 4 5 6 -2990.297373 -2342.386913 -4692.306860 -689.404154 -2633.245551 -1026.657818 7 8 9 10 11 12 -511.982025 -1828.352081 -1626.656839 -500.025565 -889.769291 -2691.349270 13 14 15 16 17 18 4824.694430 -1834.468991 2025.324775 -1119.754050 -1194.071657 3875.368315 19 20 21 22 23 24 1533.164164 20.960339 221.034220 -2010.593089 -426.881685 -626.461664 25 26 27 28 29 30 3896.415805 6386.400145 6536.295497 4189.022735 7145.723598 -174.854900 31 32 33 34 35 36 -17.363809 398.469307 -1507.410637 156.777353 -138.483539 -1993.285160 37 38 39 40 41 42 1629.656955 -1816.414115 -2845.657290 -2339.782290 2352.244412 229.749029 43 44 45 46 47 48 2276.360176 1822.796183 -1490.277697 2993.039583 1485.120390 -117.422648 49 50 51 52 53 54 1924.574877 4332.291400 758.891228 3412.803169 361.762614 -3063.742003 55 56 57 58 59 60 327.896849 -2191.325445 446.489853 -205.063575 -2249.333702 -1493.839800 61 62 63 64 65 66 -2345.657573 -2855.116517 -3750.248871 -4201.401576 -3042.700713 -2099.260741 67 68 69 70 71 72 346.359641 -358.871888 892.229698 1617.639329 -946.076692 3564.269449 73 74 75 76 77 78 -4806.548325 496.844970 4260.758792 2756.661497 -1838.640251 -710.117163 79 80 81 82 83 84 -2433.570661 9.207044 1414.308630 1.736732 1469.715953 2774.062093 85 86 87 88 89 90 -2132.838796 -2367.149978 -2293.057270 -2008.145330 -1151.072453 2969.515281 91 92 93 94 95 96 -1520.864337 2127.116540 1650.282772 -2053.510768 1695.708565 584.027000 > postscript(file="/var/www/html/rcomp/tmp/66bf81199525320.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 = 96 Frequency = 1 lag(myerror, k = 1) myerror 0 -2990.297373 NA 1 -2342.386913 -2990.297373 2 -4692.306860 -2342.386913 3 -689.404154 -4692.306860 4 -2633.245551 -689.404154 5 -1026.657818 -2633.245551 6 -511.982025 -1026.657818 7 -1828.352081 -511.982025 8 -1626.656839 -1828.352081 9 -500.025565 -1626.656839 10 -889.769291 -500.025565 11 -2691.349270 -889.769291 12 4824.694430 -2691.349270 13 -1834.468991 4824.694430 14 2025.324775 -1834.468991 15 -1119.754050 2025.324775 16 -1194.071657 -1119.754050 17 3875.368315 -1194.071657 18 1533.164164 3875.368315 19 20.960339 1533.164164 20 221.034220 20.960339 21 -2010.593089 221.034220 22 -426.881685 -2010.593089 23 -626.461664 -426.881685 24 3896.415805 -626.461664 25 6386.400145 3896.415805 26 6536.295497 6386.400145 27 4189.022735 6536.295497 28 7145.723598 4189.022735 29 -174.854900 7145.723598 30 -17.363809 -174.854900 31 398.469307 -17.363809 32 -1507.410637 398.469307 33 156.777353 -1507.410637 34 -138.483539 156.777353 35 -1993.285160 -138.483539 36 1629.656955 -1993.285160 37 -1816.414115 1629.656955 38 -2845.657290 -1816.414115 39 -2339.782290 -2845.657290 40 2352.244412 -2339.782290 41 229.749029 2352.244412 42 2276.360176 229.749029 43 1822.796183 2276.360176 44 -1490.277697 1822.796183 45 2993.039583 -1490.277697 46 1485.120390 2993.039583 47 -117.422648 1485.120390 48 1924.574877 -117.422648 49 4332.291400 1924.574877 50 758.891228 4332.291400 51 3412.803169 758.891228 52 361.762614 3412.803169 53 -3063.742003 361.762614 54 327.896849 -3063.742003 55 -2191.325445 327.896849 56 446.489853 -2191.325445 57 -205.063575 446.489853 58 -2249.333702 -205.063575 59 -1493.839800 -2249.333702 60 -2345.657573 -1493.839800 61 -2855.116517 -2345.657573 62 -3750.248871 -2855.116517 63 -4201.401576 -3750.248871 64 -3042.700713 -4201.401576 65 -2099.260741 -3042.700713 66 346.359641 -2099.260741 67 -358.871888 346.359641 68 892.229698 -358.871888 69 1617.639329 892.229698 70 -946.076692 1617.639329 71 3564.269449 -946.076692 72 -4806.548325 3564.269449 73 496.844970 -4806.548325 74 4260.758792 496.844970 75 2756.661497 4260.758792 76 -1838.640251 2756.661497 77 -710.117163 -1838.640251 78 -2433.570661 -710.117163 79 9.207044 -2433.570661 80 1414.308630 9.207044 81 1.736732 1414.308630 82 1469.715953 1.736732 83 2774.062093 1469.715953 84 -2132.838796 2774.062093 85 -2367.149978 -2132.838796 86 -2293.057270 -2367.149978 87 -2008.145330 -2293.057270 88 -1151.072453 -2008.145330 89 2969.515281 -1151.072453 90 -1520.864337 2969.515281 91 2127.116540 -1520.864337 92 1650.282772 2127.116540 93 -2053.510768 1650.282772 94 1695.708565 -2053.510768 95 584.027000 1695.708565 96 NA 584.027000 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -2342.386913 -2990.297373 [2,] -4692.306860 -2342.386913 [3,] -689.404154 -4692.306860 [4,] -2633.245551 -689.404154 [5,] -1026.657818 -2633.245551 [6,] -511.982025 -1026.657818 [7,] -1828.352081 -511.982025 [8,] -1626.656839 -1828.352081 [9,] -500.025565 -1626.656839 [10,] -889.769291 -500.025565 [11,] -2691.349270 -889.769291 [12,] 4824.694430 -2691.349270 [13,] -1834.468991 4824.694430 [14,] 2025.324775 -1834.468991 [15,] -1119.754050 2025.324775 [16,] -1194.071657 -1119.754050 [17,] 3875.368315 -1194.071657 [18,] 1533.164164 3875.368315 [19,] 20.960339 1533.164164 [20,] 221.034220 20.960339 [21,] -2010.593089 221.034220 [22,] -426.881685 -2010.593089 [23,] -626.461664 -426.881685 [24,] 3896.415805 -626.461664 [25,] 6386.400145 3896.415805 [26,] 6536.295497 6386.400145 [27,] 4189.022735 6536.295497 [28,] 7145.723598 4189.022735 [29,] -174.854900 7145.723598 [30,] -17.363809 -174.854900 [31,] 398.469307 -17.363809 [32,] -1507.410637 398.469307 [33,] 156.777353 -1507.410637 [34,] -138.483539 156.777353 [35,] -1993.285160 -138.483539 [36,] 1629.656955 -1993.285160 [37,] -1816.414115 1629.656955 [38,] -2845.657290 -1816.414115 [39,] -2339.782290 -2845.657290 [40,] 2352.244412 -2339.782290 [41,] 229.749029 2352.244412 [42,] 2276.360176 229.749029 [43,] 1822.796183 2276.360176 [44,] -1490.277697 1822.796183 [45,] 2993.039583 -1490.277697 [46,] 1485.120390 2993.039583 [47,] -117.422648 1485.120390 [48,] 1924.574877 -117.422648 [49,] 4332.291400 1924.574877 [50,] 758.891228 4332.291400 [51,] 3412.803169 758.891228 [52,] 361.762614 3412.803169 [53,] -3063.742003 361.762614 [54,] 327.896849 -3063.742003 [55,] -2191.325445 327.896849 [56,] 446.489853 -2191.325445 [57,] -205.063575 446.489853 [58,] -2249.333702 -205.063575 [59,] -1493.839800 -2249.333702 [60,] -2345.657573 -1493.839800 [61,] -2855.116517 -2345.657573 [62,] -3750.248871 -2855.116517 [63,] -4201.401576 -3750.248871 [64,] -3042.700713 -4201.401576 [65,] -2099.260741 -3042.700713 [66,] 346.359641 -2099.260741 [67,] -358.871888 346.359641 [68,] 892.229698 -358.871888 [69,] 1617.639329 892.229698 [70,] -946.076692 1617.639329 [71,] 3564.269449 -946.076692 [72,] -4806.548325 3564.269449 [73,] 496.844970 -4806.548325 [74,] 4260.758792 496.844970 [75,] 2756.661497 4260.758792 [76,] -1838.640251 2756.661497 [77,] -710.117163 -1838.640251 [78,] -2433.570661 -710.117163 [79,] 9.207044 -2433.570661 [80,] 1414.308630 9.207044 [81,] 1.736732 1414.308630 [82,] 1469.715953 1.736732 [83,] 2774.062093 1469.715953 [84,] -2132.838796 2774.062093 [85,] -2367.149978 -2132.838796 [86,] -2293.057270 -2367.149978 [87,] -2008.145330 -2293.057270 [88,] -1151.072453 -2008.145330 [89,] 2969.515281 -1151.072453 [90,] -1520.864337 2969.515281 [91,] 2127.116540 -1520.864337 [92,] 1650.282772 2127.116540 [93,] -2053.510768 1650.282772 [94,] 1695.708565 -2053.510768 [95,] 584.027000 1695.708565 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -2342.386913 -2990.297373 2 -4692.306860 -2342.386913 3 -689.404154 -4692.306860 4 -2633.245551 -689.404154 5 -1026.657818 -2633.245551 6 -511.982025 -1026.657818 7 -1828.352081 -511.982025 8 -1626.656839 -1828.352081 9 -500.025565 -1626.656839 10 -889.769291 -500.025565 11 -2691.349270 -889.769291 12 4824.694430 -2691.349270 13 -1834.468991 4824.694430 14 2025.324775 -1834.468991 15 -1119.754050 2025.324775 16 -1194.071657 -1119.754050 17 3875.368315 -1194.071657 18 1533.164164 3875.368315 19 20.960339 1533.164164 20 221.034220 20.960339 21 -2010.593089 221.034220 22 -426.881685 -2010.593089 23 -626.461664 -426.881685 24 3896.415805 -626.461664 25 6386.400145 3896.415805 26 6536.295497 6386.400145 27 4189.022735 6536.295497 28 7145.723598 4189.022735 29 -174.854900 7145.723598 30 -17.363809 -174.854900 31 398.469307 -17.363809 32 -1507.410637 398.469307 33 156.777353 -1507.410637 34 -138.483539 156.777353 35 -1993.285160 -138.483539 36 1629.656955 -1993.285160 37 -1816.414115 1629.656955 38 -2845.657290 -1816.414115 39 -2339.782290 -2845.657290 40 2352.244412 -2339.782290 41 229.749029 2352.244412 42 2276.360176 229.749029 43 1822.796183 2276.360176 44 -1490.277697 1822.796183 45 2993.039583 -1490.277697 46 1485.120390 2993.039583 47 -117.422648 1485.120390 48 1924.574877 -117.422648 49 4332.291400 1924.574877 50 758.891228 4332.291400 51 3412.803169 758.891228 52 361.762614 3412.803169 53 -3063.742003 361.762614 54 327.896849 -3063.742003 55 -2191.325445 327.896849 56 446.489853 -2191.325445 57 -205.063575 446.489853 58 -2249.333702 -205.063575 59 -1493.839800 -2249.333702 60 -2345.657573 -1493.839800 61 -2855.116517 -2345.657573 62 -3750.248871 -2855.116517 63 -4201.401576 -3750.248871 64 -3042.700713 -4201.401576 65 -2099.260741 -3042.700713 66 346.359641 -2099.260741 67 -358.871888 346.359641 68 892.229698 -358.871888 69 1617.639329 892.229698 70 -946.076692 1617.639329 71 3564.269449 -946.076692 72 -4806.548325 3564.269449 73 496.844970 -4806.548325 74 4260.758792 496.844970 75 2756.661497 4260.758792 76 -1838.640251 2756.661497 77 -710.117163 -1838.640251 78 -2433.570661 -710.117163 79 9.207044 -2433.570661 80 1414.308630 9.207044 81 1.736732 1414.308630 82 1469.715953 1.736732 83 2774.062093 1469.715953 84 -2132.838796 2774.062093 85 -2367.149978 -2132.838796 86 -2293.057270 -2367.149978 87 -2008.145330 -2293.057270 88 -1151.072453 -2008.145330 89 2969.515281 -1151.072453 90 -1520.864337 2969.515281 91 2127.116540 -1520.864337 92 1650.282772 2127.116540 93 -2053.510768 1650.282772 94 1695.708565 -2053.510768 95 584.027000 1695.708565 > 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/7ionq1199525321.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8hx261199525321.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9t6jw1199525321.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > load(file='/var/www/html/rcomp/createtable') > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/10x4r61199525321.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/11f73u1199525321.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/12acwd1199525321.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/13gkma1199525321.tab") > > system("convert tmp/1aark1199525320.ps tmp/1aark1199525320.png") > system("convert tmp/2e2dk1199525320.ps tmp/2e2dk1199525320.png") > system("convert tmp/39ln31199525320.ps tmp/39ln31199525320.png") > system("convert tmp/4m1ni1199525320.ps tmp/4m1ni1199525320.png") > system("convert tmp/5lu5v1199525320.ps tmp/5lu5v1199525320.png") > system("convert tmp/66bf81199525320.ps tmp/66bf81199525320.png") > system("convert tmp/7ionq1199525321.ps tmp/7ionq1199525321.png") > system("convert tmp/8hx261199525321.ps tmp/8hx261199525321.png") > system("convert tmp/9t6jw1199525321.ps tmp/9t6jw1199525321.png") > > > proc.time() user system elapsed 2.459 1.507 3.106