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Type 'q()' to quit R. > x <- array(list(7272.2 + ,0 + ,6680.1 + ,0 + ,8427.6 + ,0 + ,8752.8 + ,0 + ,7952.7 + ,0 + ,8694.3 + ,0 + ,7787 + ,0 + ,8474.2 + ,0 + ,9154.7 + ,0 + ,8557.2 + ,0 + ,7951.1 + ,0 + ,9156.7 + ,0 + ,7865.7 + ,0 + ,7337.4 + ,0 + ,9131.7 + ,0 + ,8814.6 + ,0 + ,8598.8 + ,0 + ,8439.6 + ,0 + ,7451.8 + ,0 + ,8016.2 + ,0 + ,9544.1 + ,0 + ,8270.7 + ,0 + ,8102.2 + ,0 + ,9369 + ,0 + ,7657.7 + ,0 + ,7816.6 + ,0 + ,9391.3 + ,0 + ,9445.4 + ,0 + ,9533.1 + ,0 + ,10068.7 + ,0 + ,8955.5 + ,0 + ,10423.9 + ,0 + ,11617.2 + ,0 + ,9391.1 + ,0 + ,10872 + ,0 + ,10230.4 + ,0 + ,9221 + ,0 + ,9428.6 + ,0 + ,10934.5 + ,0 + ,10986 + ,0 + ,11724.6 + ,0 + ,11180.9 + ,0 + ,11163.2 + ,0 + ,11240.9 + ,0 + ,12107.1 + ,0 + ,10762.3 + ,0 + ,11340.4 + ,0 + ,11266.8 + ,0 + ,9542.7 + ,0 + ,9227.7 + ,0 + ,10571.9 + ,0 + ,10774.4 + ,0 + ,10392.8 + ,0 + ,9920.2 + ,0 + ,9884.9 + ,1 + ,10174.5 + ,1 + ,11395.4 + ,1 + ,10760.2 + ,1 + ,10570.1 + ,1 + ,10536 + ,1 + ,9902.6 + ,1 + ,8889 + ,1 + ,10837.3 + ,1 + ,11624.1 + ,1 + ,10509 + ,1 + ,10984.9 + ,1 + ,10649.1 + ,1 + ,10855.7 + ,1 + ,11677.4 + ,1 + ,10760.2 + ,1 + ,10046.2 + ,1 + ,10772.8 + ,1 + ,9987.7 + ,1 + ,8638.7 + ,1 + ,11063.7 + ,1 + ,11855.7 + ,1 + ,10684.5 + ,1 + ,11337.4 + ,1 + ,10478 + ,1 + ,11123.9 + ,1 + ,12909.3 + ,1 + ,11339.9 + ,1 + ,10462.2 + ,1 + ,12733.5 + ,1 + ,10519.2 + ,1 + ,10414.9 + ,1 + ,12476.8 + ,1 + ,12384.6 + ,1 + ,12266.7 + ,1 + ,12919.9 + ,1 + ,11497.3 + ,1 + ,12142 + ,1 + ,13919.4 + ,1 + ,12656.8 + ,1 + ,12034.1 + ,1 + ,13199.7 + ,1 + ,10881.3 + ,1 + ,11301.2 + ,1 + ,13643.9 + ,1 + ,12517 + ,1 + ,13981.1 + ,1 + ,14275.7 + ,1 + ,13435 + ,1 + ,13565.7 + ,1 + ,16216.3 + ,1 + ,12970 + ,1 + ,14079.9 + ,1 + ,14235 + ,1 + ,12213.4 + ,1 + ,12581 + ,1 + ,14130.4 + ,1 + ,14210.8 + ,1 + ,14378.5 + ,1 + ,13142.8 + ,1 + ,13714.7 + ,1 + ,13621.9 + ,1 + ,15379.8 + ,1 + ,13306.3 + ,1 + ,14391.2 + ,1 + ,14909.9 + ,1 + ,14552.7 + ,1) + ,dim=c(2 + ,121) + ,dimnames=list(c('Invoer' + ,'X') + ,1:121)) > y <- array(NA,dim=c(2,121),dimnames=list(c('Invoer','X'),1:121)) > 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 Invoer X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 7272.2 0 1 0 0 0 0 0 0 0 0 0 0 1 2 6680.1 0 0 1 0 0 0 0 0 0 0 0 0 2 3 8427.6 0 0 0 1 0 0 0 0 0 0 0 0 3 4 8752.8 0 0 0 0 1 0 0 0 0 0 0 0 4 5 7952.7 0 0 0 0 0 1 0 0 0 0 0 0 5 6 8694.3 0 0 0 0 0 0 1 0 0 0 0 0 6 7 7787.0 0 0 0 0 0 0 0 1 0 0 0 0 7 8 8474.2 0 0 0 0 0 0 0 0 1 0 0 0 8 9 9154.7 0 0 0 0 0 0 0 0 0 1 0 0 9 10 8557.2 0 0 0 0 0 0 0 0 0 0 1 0 10 11 7951.1 0 0 0 0 0 0 0 0 0 0 0 1 11 12 9156.7 0 0 0 0 0 0 0 0 0 0 0 0 12 13 7865.7 0 1 0 0 0 0 0 0 0 0 0 0 13 14 7337.4 0 0 1 0 0 0 0 0 0 0 0 0 14 15 9131.7 0 0 0 1 0 0 0 0 0 0 0 0 15 16 8814.6 0 0 0 0 1 0 0 0 0 0 0 0 16 17 8598.8 0 0 0 0 0 1 0 0 0 0 0 0 17 18 8439.6 0 0 0 0 0 0 1 0 0 0 0 0 18 19 7451.8 0 0 0 0 0 0 0 1 0 0 0 0 19 20 8016.2 0 0 0 0 0 0 0 0 1 0 0 0 20 21 9544.1 0 0 0 0 0 0 0 0 0 1 0 0 21 22 8270.7 0 0 0 0 0 0 0 0 0 0 1 0 22 23 8102.2 0 0 0 0 0 0 0 0 0 0 0 1 23 24 9369.0 0 0 0 0 0 0 0 0 0 0 0 0 24 25 7657.7 0 1 0 0 0 0 0 0 0 0 0 0 25 26 7816.6 0 0 1 0 0 0 0 0 0 0 0 0 26 27 9391.3 0 0 0 1 0 0 0 0 0 0 0 0 27 28 9445.4 0 0 0 0 1 0 0 0 0 0 0 0 28 29 9533.1 0 0 0 0 0 1 0 0 0 0 0 0 29 30 10068.7 0 0 0 0 0 0 1 0 0 0 0 0 30 31 8955.5 0 0 0 0 0 0 0 1 0 0 0 0 31 32 10423.9 0 0 0 0 0 0 0 0 1 0 0 0 32 33 11617.2 0 0 0 0 0 0 0 0 0 1 0 0 33 34 9391.1 0 0 0 0 0 0 0 0 0 0 1 0 34 35 10872.0 0 0 0 0 0 0 0 0 0 0 0 1 35 36 10230.4 0 0 0 0 0 0 0 0 0 0 0 0 36 37 9221.0 0 1 0 0 0 0 0 0 0 0 0 0 37 38 9428.6 0 0 1 0 0 0 0 0 0 0 0 0 38 39 10934.5 0 0 0 1 0 0 0 0 0 0 0 0 39 40 10986.0 0 0 0 0 1 0 0 0 0 0 0 0 40 41 11724.6 0 0 0 0 0 1 0 0 0 0 0 0 41 42 11180.9 0 0 0 0 0 0 1 0 0 0 0 0 42 43 11163.2 0 0 0 0 0 0 0 1 0 0 0 0 43 44 11240.9 0 0 0 0 0 0 0 0 1 0 0 0 44 45 12107.1 0 0 0 0 0 0 0 0 0 1 0 0 45 46 10762.3 0 0 0 0 0 0 0 0 0 0 1 0 46 47 11340.4 0 0 0 0 0 0 0 0 0 0 0 1 47 48 11266.8 0 0 0 0 0 0 0 0 0 0 0 0 48 49 9542.7 0 1 0 0 0 0 0 0 0 0 0 0 49 50 9227.7 0 0 1 0 0 0 0 0 0 0 0 0 50 51 10571.9 0 0 0 1 0 0 0 0 0 0 0 0 51 52 10774.4 0 0 0 0 1 0 0 0 0 0 0 0 52 53 10392.8 0 0 0 0 0 1 0 0 0 0 0 0 53 54 9920.2 0 0 0 0 0 0 1 0 0 0 0 0 54 55 9884.9 1 0 0 0 0 0 0 1 0 0 0 0 55 56 10174.5 1 0 0 0 0 0 0 0 1 0 0 0 56 57 11395.4 1 0 0 0 0 0 0 0 0 1 0 0 57 58 10760.2 1 0 0 0 0 0 0 0 0 0 1 0 58 59 10570.1 1 0 0 0 0 0 0 0 0 0 0 1 59 60 10536.0 1 0 0 0 0 0 0 0 0 0 0 0 60 61 9902.6 1 1 0 0 0 0 0 0 0 0 0 0 61 62 8889.0 1 0 1 0 0 0 0 0 0 0 0 0 62 63 10837.3 1 0 0 1 0 0 0 0 0 0 0 0 63 64 11624.1 1 0 0 0 1 0 0 0 0 0 0 0 64 65 10509.0 1 0 0 0 0 1 0 0 0 0 0 0 65 66 10984.9 1 0 0 0 0 0 1 0 0 0 0 0 66 67 10649.1 1 0 0 0 0 0 0 1 0 0 0 0 67 68 10855.7 1 0 0 0 0 0 0 0 1 0 0 0 68 69 11677.4 1 0 0 0 0 0 0 0 0 1 0 0 69 70 10760.2 1 0 0 0 0 0 0 0 0 0 1 0 70 71 10046.2 1 0 0 0 0 0 0 0 0 0 0 1 71 72 10772.8 1 0 0 0 0 0 0 0 0 0 0 0 72 73 9987.7 1 1 0 0 0 0 0 0 0 0 0 0 73 74 8638.7 1 0 1 0 0 0 0 0 0 0 0 0 74 75 11063.7 1 0 0 1 0 0 0 0 0 0 0 0 75 76 11855.7 1 0 0 0 1 0 0 0 0 0 0 0 76 77 10684.5 1 0 0 0 0 1 0 0 0 0 0 0 77 78 11337.4 1 0 0 0 0 0 1 0 0 0 0 0 78 79 10478.0 1 0 0 0 0 0 0 1 0 0 0 0 79 80 11123.9 1 0 0 0 0 0 0 0 1 0 0 0 80 81 12909.3 1 0 0 0 0 0 0 0 0 1 0 0 81 82 11339.9 1 0 0 0 0 0 0 0 0 0 1 0 82 83 10462.2 1 0 0 0 0 0 0 0 0 0 0 1 83 84 12733.5 1 0 0 0 0 0 0 0 0 0 0 0 84 85 10519.2 1 1 0 0 0 0 0 0 0 0 0 0 85 86 10414.9 1 0 1 0 0 0 0 0 0 0 0 0 86 87 12476.8 1 0 0 1 0 0 0 0 0 0 0 0 87 88 12384.6 1 0 0 0 1 0 0 0 0 0 0 0 88 89 12266.7 1 0 0 0 0 1 0 0 0 0 0 0 89 90 12919.9 1 0 0 0 0 0 1 0 0 0 0 0 90 91 11497.3 1 0 0 0 0 0 0 1 0 0 0 0 91 92 12142.0 1 0 0 0 0 0 0 0 1 0 0 0 92 93 13919.4 1 0 0 0 0 0 0 0 0 1 0 0 93 94 12656.8 1 0 0 0 0 0 0 0 0 0 1 0 94 95 12034.1 1 0 0 0 0 0 0 0 0 0 0 1 95 96 13199.7 1 0 0 0 0 0 0 0 0 0 0 0 96 97 10881.3 1 1 0 0 0 0 0 0 0 0 0 0 97 98 11301.2 1 0 1 0 0 0 0 0 0 0 0 0 98 99 13643.9 1 0 0 1 0 0 0 0 0 0 0 0 99 100 12517.0 1 0 0 0 1 0 0 0 0 0 0 0 100 101 13981.1 1 0 0 0 0 1 0 0 0 0 0 0 101 102 14275.7 1 0 0 0 0 0 1 0 0 0 0 0 102 103 13435.0 1 0 0 0 0 0 0 1 0 0 0 0 103 104 13565.7 1 0 0 0 0 0 0 0 1 0 0 0 104 105 16216.3 1 0 0 0 0 0 0 0 0 1 0 0 105 106 12970.0 1 0 0 0 0 0 0 0 0 0 1 0 106 107 14079.9 1 0 0 0 0 0 0 0 0 0 0 1 107 108 14235.0 1 0 0 0 0 0 0 0 0 0 0 0 108 109 12213.4 1 1 0 0 0 0 0 0 0 0 0 0 109 110 12581.0 1 0 1 0 0 0 0 0 0 0 0 0 110 111 14130.4 1 0 0 1 0 0 0 0 0 0 0 0 111 112 14210.8 1 0 0 0 1 0 0 0 0 0 0 0 112 113 14378.5 1 0 0 0 0 1 0 0 0 0 0 0 113 114 13142.8 1 0 0 0 0 0 1 0 0 0 0 0 114 115 13714.7 1 0 0 0 0 0 0 1 0 0 0 0 115 116 13621.9 1 0 0 0 0 0 0 0 1 0 0 0 116 117 15379.8 1 0 0 0 0 0 0 0 0 1 0 0 117 118 13306.3 1 0 0 0 0 0 0 0 0 0 1 0 118 119 14391.2 1 0 0 0 0 0 0 0 0 0 0 1 119 120 14909.9 1 0 0 0 0 0 0 0 0 0 0 0 120 121 14552.7 1 1 0 0 0 0 0 0 0 0 0 0 121 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X M1 M2 M3 M4 7993.75 -1443.30 -1412.69 -1869.97 -108.96 -101.71 M5 M6 M7 M8 M9 M10 -304.46 -278.58 -797.42 -403.56 956.24 -626.75 M11 t -587.66 68.38 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1487.60 -378.00 49.76 378.50 1529.51 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 7993.749 220.327 36.281 < 2e-16 *** X -1443.303 216.338 -6.672 1.15e-09 *** M1 -1412.686 261.758 -5.397 4.11e-07 *** M2 -1869.970 268.295 -6.970 2.71e-10 *** M3 -108.962 268.173 -0.406 0.685325 M4 -101.714 268.087 -0.379 0.705137 M5 -304.456 268.036 -1.136 0.258546 M6 -278.578 268.020 -1.039 0.300966 M7 -797.420 268.236 -2.973 0.003646 ** M8 -403.562 268.077 -1.505 0.135169 M9 956.236 267.954 3.569 0.000539 *** M10 -626.746 267.865 -2.340 0.021151 * M11 -587.658 267.812 -2.194 0.030377 * t 68.382 3.076 22.229 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 598.8 on 107 degrees of freedom Multiple R-Squared: 0.9232, Adjusted R-squared: 0.9138 F-statistic: 98.89 on 13 and 107 DF, p-value: < 2.2e-16 > postscript(file="/var/www/html/rcomp/tmp/190h11198247559.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/2p0px1198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3fsey1198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4mpku1198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5xnko1198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 121 Frequency = 1 1 2 3 4 5 6 622.755354 419.557064 337.667064 587.237064 -78.502936 568.837064 7 8 9 10 11 12 111.996767 336.956767 -410.723233 506.376767 -207.193233 342.366767 13 14 15 16 17 18 395.671231 256.272942 221.182942 -171.547058 -252.987058 -506.447058 19 20 21 22 23 24 -1043.787356 -941.627356 -841.907356 -600.707356 -876.677356 -265.917356 25 26 27 28 29 30 -632.912891 -85.111181 -339.801181 -361.331181 -139.271181 302.068819 31 32 33 34 35 36 -360.671479 645.488521 410.608521 -300.891479 1072.538521 -225.101479 37 38 39 40 41 42 109.802986 706.304696 382.814696 358.684696 1231.644696 593.684696 43 44 45 46 47 48 1026.444399 641.904399 79.924399 249.724399 720.354399 -9.285601 49 50 51 52 53 54 -389.081137 -315.179427 -800.369427 -673.499427 -920.739427 -1487.599427 55 56 57 58 59 60 370.863252 198.223252 -9.056748 870.343252 572.773252 -117.366748 61 62 63 64 65 66 593.537716 -31.160573 87.749427 798.919427 -181.820573 199.819427 67 68 69 70 71 72 314.479129 58.839129 -547.640871 49.759129 -771.710871 -701.150871 73 74 75 76 77 78 -141.946406 -1102.044696 -506.434696 209.935304 -826.904696 -268.264696 79 80 81 82 83 84 -677.204994 -493.544994 -136.324994 -191.124994 -1176.294994 438.965006 85 86 87 88 89 90 -431.030529 -146.428819 86.081181 -81.748819 -65.288819 493.651181 91 92 93 94 95 96 -478.489117 -296.029117 53.190883 305.190883 -424.979117 84.580883 97 98 99 100 101 102 -889.514652 -80.712942 432.597058 -769.932942 828.527058 1028.867058 103 104 105 106 107 108 638.626761 307.086761 1529.506761 -202.193239 800.236761 299.296761 109 110 111 112 113 114 -377.998775 378.502936 98.512936 103.282936 405.342936 -924.617064 115 116 117 118 119 120 97.742638 -457.297362 -127.577362 -686.477362 290.952638 153.612638 121 1140.717103 > postscript(file="/var/www/html/rcomp/tmp/60mn11198247559.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 = 121 Frequency = 1 lag(myerror, k = 1) myerror 0 622.755354 NA 1 419.557064 622.755354 2 337.667064 419.557064 3 587.237064 337.667064 4 -78.502936 587.237064 5 568.837064 -78.502936 6 111.996767 568.837064 7 336.956767 111.996767 8 -410.723233 336.956767 9 506.376767 -410.723233 10 -207.193233 506.376767 11 342.366767 -207.193233 12 395.671231 342.366767 13 256.272942 395.671231 14 221.182942 256.272942 15 -171.547058 221.182942 16 -252.987058 -171.547058 17 -506.447058 -252.987058 18 -1043.787356 -506.447058 19 -941.627356 -1043.787356 20 -841.907356 -941.627356 21 -600.707356 -841.907356 22 -876.677356 -600.707356 23 -265.917356 -876.677356 24 -632.912891 -265.917356 25 -85.111181 -632.912891 26 -339.801181 -85.111181 27 -361.331181 -339.801181 28 -139.271181 -361.331181 29 302.068819 -139.271181 30 -360.671479 302.068819 31 645.488521 -360.671479 32 410.608521 645.488521 33 -300.891479 410.608521 34 1072.538521 -300.891479 35 -225.101479 1072.538521 36 109.802986 -225.101479 37 706.304696 109.802986 38 382.814696 706.304696 39 358.684696 382.814696 40 1231.644696 358.684696 41 593.684696 1231.644696 42 1026.444399 593.684696 43 641.904399 1026.444399 44 79.924399 641.904399 45 249.724399 79.924399 46 720.354399 249.724399 47 -9.285601 720.354399 48 -389.081137 -9.285601 49 -315.179427 -389.081137 50 -800.369427 -315.179427 51 -673.499427 -800.369427 52 -920.739427 -673.499427 53 -1487.599427 -920.739427 54 370.863252 -1487.599427 55 198.223252 370.863252 56 -9.056748 198.223252 57 870.343252 -9.056748 58 572.773252 870.343252 59 -117.366748 572.773252 60 593.537716 -117.366748 61 -31.160573 593.537716 62 87.749427 -31.160573 63 798.919427 87.749427 64 -181.820573 798.919427 65 199.819427 -181.820573 66 314.479129 199.819427 67 58.839129 314.479129 68 -547.640871 58.839129 69 49.759129 -547.640871 70 -771.710871 49.759129 71 -701.150871 -771.710871 72 -141.946406 -701.150871 73 -1102.044696 -141.946406 74 -506.434696 -1102.044696 75 209.935304 -506.434696 76 -826.904696 209.935304 77 -268.264696 -826.904696 78 -677.204994 -268.264696 79 -493.544994 -677.204994 80 -136.324994 -493.544994 81 -191.124994 -136.324994 82 -1176.294994 -191.124994 83 438.965006 -1176.294994 84 -431.030529 438.965006 85 -146.428819 -431.030529 86 86.081181 -146.428819 87 -81.748819 86.081181 88 -65.288819 -81.748819 89 493.651181 -65.288819 90 -478.489117 493.651181 91 -296.029117 -478.489117 92 53.190883 -296.029117 93 305.190883 53.190883 94 -424.979117 305.190883 95 84.580883 -424.979117 96 -889.514652 84.580883 97 -80.712942 -889.514652 98 432.597058 -80.712942 99 -769.932942 432.597058 100 828.527058 -769.932942 101 1028.867058 828.527058 102 638.626761 1028.867058 103 307.086761 638.626761 104 1529.506761 307.086761 105 -202.193239 1529.506761 106 800.236761 -202.193239 107 299.296761 800.236761 108 -377.998775 299.296761 109 378.502936 -377.998775 110 98.512936 378.502936 111 103.282936 98.512936 112 405.342936 103.282936 113 -924.617064 405.342936 114 97.742638 -924.617064 115 -457.297362 97.742638 116 -127.577362 -457.297362 117 -686.477362 -127.577362 118 290.952638 -686.477362 119 153.612638 290.952638 120 1140.717103 153.612638 121 NA 1140.717103 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 419.557064 622.755354 [2,] 337.667064 419.557064 [3,] 587.237064 337.667064 [4,] -78.502936 587.237064 [5,] 568.837064 -78.502936 [6,] 111.996767 568.837064 [7,] 336.956767 111.996767 [8,] -410.723233 336.956767 [9,] 506.376767 -410.723233 [10,] -207.193233 506.376767 [11,] 342.366767 -207.193233 [12,] 395.671231 342.366767 [13,] 256.272942 395.671231 [14,] 221.182942 256.272942 [15,] -171.547058 221.182942 [16,] -252.987058 -171.547058 [17,] -506.447058 -252.987058 [18,] -1043.787356 -506.447058 [19,] -941.627356 -1043.787356 [20,] -841.907356 -941.627356 [21,] -600.707356 -841.907356 [22,] -876.677356 -600.707356 [23,] -265.917356 -876.677356 [24,] -632.912891 -265.917356 [25,] -85.111181 -632.912891 [26,] -339.801181 -85.111181 [27,] -361.331181 -339.801181 [28,] -139.271181 -361.331181 [29,] 302.068819 -139.271181 [30,] -360.671479 302.068819 [31,] 645.488521 -360.671479 [32,] 410.608521 645.488521 [33,] -300.891479 410.608521 [34,] 1072.538521 -300.891479 [35,] -225.101479 1072.538521 [36,] 109.802986 -225.101479 [37,] 706.304696 109.802986 [38,] 382.814696 706.304696 [39,] 358.684696 382.814696 [40,] 1231.644696 358.684696 [41,] 593.684696 1231.644696 [42,] 1026.444399 593.684696 [43,] 641.904399 1026.444399 [44,] 79.924399 641.904399 [45,] 249.724399 79.924399 [46,] 720.354399 249.724399 [47,] -9.285601 720.354399 [48,] -389.081137 -9.285601 [49,] -315.179427 -389.081137 [50,] -800.369427 -315.179427 [51,] -673.499427 -800.369427 [52,] -920.739427 -673.499427 [53,] -1487.599427 -920.739427 [54,] 370.863252 -1487.599427 [55,] 198.223252 370.863252 [56,] -9.056748 198.223252 [57,] 870.343252 -9.056748 [58,] 572.773252 870.343252 [59,] -117.366748 572.773252 [60,] 593.537716 -117.366748 [61,] -31.160573 593.537716 [62,] 87.749427 -31.160573 [63,] 798.919427 87.749427 [64,] -181.820573 798.919427 [65,] 199.819427 -181.820573 [66,] 314.479129 199.819427 [67,] 58.839129 314.479129 [68,] -547.640871 58.839129 [69,] 49.759129 -547.640871 [70,] -771.710871 49.759129 [71,] -701.150871 -771.710871 [72,] -141.946406 -701.150871 [73,] -1102.044696 -141.946406 [74,] -506.434696 -1102.044696 [75,] 209.935304 -506.434696 [76,] -826.904696 209.935304 [77,] -268.264696 -826.904696 [78,] -677.204994 -268.264696 [79,] -493.544994 -677.204994 [80,] -136.324994 -493.544994 [81,] -191.124994 -136.324994 [82,] -1176.294994 -191.124994 [83,] 438.965006 -1176.294994 [84,] -431.030529 438.965006 [85,] -146.428819 -431.030529 [86,] 86.081181 -146.428819 [87,] -81.748819 86.081181 [88,] -65.288819 -81.748819 [89,] 493.651181 -65.288819 [90,] -478.489117 493.651181 [91,] -296.029117 -478.489117 [92,] 53.190883 -296.029117 [93,] 305.190883 53.190883 [94,] -424.979117 305.190883 [95,] 84.580883 -424.979117 [96,] -889.514652 84.580883 [97,] -80.712942 -889.514652 [98,] 432.597058 -80.712942 [99,] -769.932942 432.597058 [100,] 828.527058 -769.932942 [101,] 1028.867058 828.527058 [102,] 638.626761 1028.867058 [103,] 307.086761 638.626761 [104,] 1529.506761 307.086761 [105,] -202.193239 1529.506761 [106,] 800.236761 -202.193239 [107,] 299.296761 800.236761 [108,] -377.998775 299.296761 [109,] 378.502936 -377.998775 [110,] 98.512936 378.502936 [111,] 103.282936 98.512936 [112,] 405.342936 103.282936 [113,] -924.617064 405.342936 [114,] 97.742638 -924.617064 [115,] -457.297362 97.742638 [116,] -127.577362 -457.297362 [117,] -686.477362 -127.577362 [118,] 290.952638 -686.477362 [119,] 153.612638 290.952638 [120,] 1140.717103 153.612638 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 419.557064 622.755354 2 337.667064 419.557064 3 587.237064 337.667064 4 -78.502936 587.237064 5 568.837064 -78.502936 6 111.996767 568.837064 7 336.956767 111.996767 8 -410.723233 336.956767 9 506.376767 -410.723233 10 -207.193233 506.376767 11 342.366767 -207.193233 12 395.671231 342.366767 13 256.272942 395.671231 14 221.182942 256.272942 15 -171.547058 221.182942 16 -252.987058 -171.547058 17 -506.447058 -252.987058 18 -1043.787356 -506.447058 19 -941.627356 -1043.787356 20 -841.907356 -941.627356 21 -600.707356 -841.907356 22 -876.677356 -600.707356 23 -265.917356 -876.677356 24 -632.912891 -265.917356 25 -85.111181 -632.912891 26 -339.801181 -85.111181 27 -361.331181 -339.801181 28 -139.271181 -361.331181 29 302.068819 -139.271181 30 -360.671479 302.068819 31 645.488521 -360.671479 32 410.608521 645.488521 33 -300.891479 410.608521 34 1072.538521 -300.891479 35 -225.101479 1072.538521 36 109.802986 -225.101479 37 706.304696 109.802986 38 382.814696 706.304696 39 358.684696 382.814696 40 1231.644696 358.684696 41 593.684696 1231.644696 42 1026.444399 593.684696 43 641.904399 1026.444399 44 79.924399 641.904399 45 249.724399 79.924399 46 720.354399 249.724399 47 -9.285601 720.354399 48 -389.081137 -9.285601 49 -315.179427 -389.081137 50 -800.369427 -315.179427 51 -673.499427 -800.369427 52 -920.739427 -673.499427 53 -1487.599427 -920.739427 54 370.863252 -1487.599427 55 198.223252 370.863252 56 -9.056748 198.223252 57 870.343252 -9.056748 58 572.773252 870.343252 59 -117.366748 572.773252 60 593.537716 -117.366748 61 -31.160573 593.537716 62 87.749427 -31.160573 63 798.919427 87.749427 64 -181.820573 798.919427 65 199.819427 -181.820573 66 314.479129 199.819427 67 58.839129 314.479129 68 -547.640871 58.839129 69 49.759129 -547.640871 70 -771.710871 49.759129 71 -701.150871 -771.710871 72 -141.946406 -701.150871 73 -1102.044696 -141.946406 74 -506.434696 -1102.044696 75 209.935304 -506.434696 76 -826.904696 209.935304 77 -268.264696 -826.904696 78 -677.204994 -268.264696 79 -493.544994 -677.204994 80 -136.324994 -493.544994 81 -191.124994 -136.324994 82 -1176.294994 -191.124994 83 438.965006 -1176.294994 84 -431.030529 438.965006 85 -146.428819 -431.030529 86 86.081181 -146.428819 87 -81.748819 86.081181 88 -65.288819 -81.748819 89 493.651181 -65.288819 90 -478.489117 493.651181 91 -296.029117 -478.489117 92 53.190883 -296.029117 93 305.190883 53.190883 94 -424.979117 305.190883 95 84.580883 -424.979117 96 -889.514652 84.580883 97 -80.712942 -889.514652 98 432.597058 -80.712942 99 -769.932942 432.597058 100 828.527058 -769.932942 101 1028.867058 828.527058 102 638.626761 1028.867058 103 307.086761 638.626761 104 1529.506761 307.086761 105 -202.193239 1529.506761 106 800.236761 -202.193239 107 299.296761 800.236761 108 -377.998775 299.296761 109 378.502936 -377.998775 110 98.512936 378.502936 111 103.282936 98.512936 112 405.342936 103.282936 113 -924.617064 405.342936 114 97.742638 -924.617064 115 -457.297362 97.742638 116 -127.577362 -457.297362 117 -686.477362 -127.577362 118 290.952638 -686.477362 119 153.612638 290.952638 120 1140.717103 153.612638 > 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/77yi21198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8emvd1198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/99e181198247559.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > load(file='/var/www/html/rcomp/createtable') > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/105zpz1198247559.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/11g3ex1198247559.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/12hfm81198247560.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/13niav1198247560.tab") > > system("convert tmp/190h11198247559.ps tmp/190h11198247559.png") > system("convert tmp/2p0px1198247559.ps tmp/2p0px1198247559.png") > system("convert tmp/3fsey1198247559.ps tmp/3fsey1198247559.png") > system("convert tmp/4mpku1198247559.ps tmp/4mpku1198247559.png") > system("convert tmp/5xnko1198247559.ps tmp/5xnko1198247559.png") > system("convert tmp/60mn11198247559.ps tmp/60mn11198247559.png") > system("convert tmp/77yi21198247559.ps tmp/77yi21198247559.png") > system("convert tmp/8emvd1198247559.ps tmp/8emvd1198247559.png") > system("convert tmp/99e181198247559.ps tmp/99e181198247559.png") > > > proc.time() user system elapsed 2.550 1.517 2.885