R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1.1608 + ,0 + ,1.1208 + ,0 + ,1.0883 + ,0 + ,1.0704 + ,0 + ,1.0628 + ,0 + ,1.0378 + ,0 + ,1.0353 + ,0 + ,1.0604 + ,0 + ,1.0501 + ,0 + ,1.0706 + ,0 + ,1.0338 + ,0 + ,1.011 + ,0 + ,1.0137 + ,0 + ,0.9834 + ,0 + ,0.9643 + ,0 + ,0.947 + ,0 + ,0.906 + ,0 + ,0.9492 + ,0 + ,0.9397 + ,0 + ,0.9041 + ,0 + ,0.8721 + ,0 + ,0.8552 + ,0 + ,0.8564 + ,0 + ,0.8973 + ,0 + ,0.9383 + ,0 + ,0.9217 + ,0 + ,0.9095 + ,0 + ,0.892 + ,0 + ,0.8742 + ,0 + ,0.8532 + ,0 + ,0.8607 + ,0 + ,0.9005 + ,0 + ,0.9111 + ,0 + ,0.9059 + ,0 + ,0.8883 + ,0 + ,0.8924 + ,0 + ,0.8833 + ,0 + ,0.87 + ,0 + ,0.8758 + ,0 + ,0.8858 + ,0 + ,0.917 + ,0 + ,0.9554 + ,0 + ,0.9922 + ,0 + ,0.9778 + ,0 + ,0.9808 + ,0 + ,0.9811 + ,0 + ,1.0014 + ,0 + ,1.0183 + ,0 + ,1.0622 + ,0 + ,1.0773 + ,0 + ,1.0807 + ,0 + ,1.0848 + ,0 + ,1.1582 + ,0 + ,1.1663 + ,0 + ,1.1372 + ,0 + ,1.1139 + ,0 + ,1.1222 + ,0 + ,1.1692 + ,0 + ,1.1702 + ,0 + ,1.2286 + ,0 + ,1.2613 + ,0 + ,1.2646 + ,0 + ,1.2262 + ,0 + ,1.1985 + ,0 + ,1.2007 + ,0 + ,1.2138 + ,0 + ,1.2266 + ,0 + ,1.2176 + ,0 + ,1.2218 + ,0 + ,1.249 + ,0 + ,1.2991 + ,0 + ,1.3408 + ,0 + ,1.3119 + ,0 + ,1.3014 + ,0 + ,1.3201 + ,0 + ,1.2938 + ,0 + ,1.2694 + ,0 + ,1.2165 + ,0 + ,1.2037 + ,0 + ,1.2292 + ,0 + ,1.2256 + ,0 + ,1.2015 + ,0 + ,1.1786 + ,0 + ,1.1856 + ,0 + ,1.2103 + ,0 + ,1.1938 + ,0 + ,1.202 + ,0 + ,1.2271 + ,0 + ,1.277 + ,0 + ,1.265 + ,0 + ,1.2684 + ,0 + ,1.2811 + ,0 + ,1.2727 + ,0 + ,1.2611 + ,0 + ,1.2881 + ,0 + ,1.3213 + ,0 + ,1.2999 + ,0 + ,1.3074 + ,0 + ,1.3242 + ,0 + ,1.3516 + ,0 + ,1.3511 + ,0 + ,1.3419 + ,1 + ,1.3716 + ,1 + ,1.3622 + ,1 + ,1.3896 + ,1 + ,1.4227 + ,1 + ,1.4684 + ,1 + ,1.457 + ,1 + ,1.4718 + ,1 + ,1.4748 + ,1 + ,1.5527 + ,1 + ,1.5751 + ,1 + ,1.5557 + ,1 + ,1.5553 + ,1 + ,1.577 + ,1) + ,dim=c(2 + ,115) + ,dimnames=list(c('y' + ,'x') + ,1:115)) > y <- array(NA,dim=c(2,115),dimnames=list(c('y','x'),1:115)) > 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 1.1608 0 1 0 0 0 0 0 0 0 0 0 0 1 2 1.1208 0 0 1 0 0 0 0 0 0 0 0 0 2 3 1.0883 0 0 0 1 0 0 0 0 0 0 0 0 3 4 1.0704 0 0 0 0 1 0 0 0 0 0 0 0 4 5 1.0628 0 0 0 0 0 1 0 0 0 0 0 0 5 6 1.0378 0 0 0 0 0 0 1 0 0 0 0 0 6 7 1.0353 0 0 0 0 0 0 0 1 0 0 0 0 7 8 1.0604 0 0 0 0 0 0 0 0 1 0 0 0 8 9 1.0501 0 0 0 0 0 0 0 0 0 1 0 0 9 10 1.0706 0 0 0 0 0 0 0 0 0 0 1 0 10 11 1.0338 0 0 0 0 0 0 0 0 0 0 0 1 11 12 1.0110 0 0 0 0 0 0 0 0 0 0 0 0 12 13 1.0137 0 1 0 0 0 0 0 0 0 0 0 0 13 14 0.9834 0 0 1 0 0 0 0 0 0 0 0 0 14 15 0.9643 0 0 0 1 0 0 0 0 0 0 0 0 15 16 0.9470 0 0 0 0 1 0 0 0 0 0 0 0 16 17 0.9060 0 0 0 0 0 1 0 0 0 0 0 0 17 18 0.9492 0 0 0 0 0 0 1 0 0 0 0 0 18 19 0.9397 0 0 0 0 0 0 0 1 0 0 0 0 19 20 0.9041 0 0 0 0 0 0 0 0 1 0 0 0 20 21 0.8721 0 0 0 0 0 0 0 0 0 1 0 0 21 22 0.8552 0 0 0 0 0 0 0 0 0 0 1 0 22 23 0.8564 0 0 0 0 0 0 0 0 0 0 0 1 23 24 0.8973 0 0 0 0 0 0 0 0 0 0 0 0 24 25 0.9383 0 1 0 0 0 0 0 0 0 0 0 0 25 26 0.9217 0 0 1 0 0 0 0 0 0 0 0 0 26 27 0.9095 0 0 0 1 0 0 0 0 0 0 0 0 27 28 0.8920 0 0 0 0 1 0 0 0 0 0 0 0 28 29 0.8742 0 0 0 0 0 1 0 0 0 0 0 0 29 30 0.8532 0 0 0 0 0 0 1 0 0 0 0 0 30 31 0.8607 0 0 0 0 0 0 0 1 0 0 0 0 31 32 0.9005 0 0 0 0 0 0 0 0 1 0 0 0 32 33 0.9111 0 0 0 0 0 0 0 0 0 1 0 0 33 34 0.9059 0 0 0 0 0 0 0 0 0 0 1 0 34 35 0.8883 0 0 0 0 0 0 0 0 0 0 0 1 35 36 0.8924 0 0 0 0 0 0 0 0 0 0 0 0 36 37 0.8833 0 1 0 0 0 0 0 0 0 0 0 0 37 38 0.8700 0 0 1 0 0 0 0 0 0 0 0 0 38 39 0.8758 0 0 0 1 0 0 0 0 0 0 0 0 39 40 0.8858 0 0 0 0 1 0 0 0 0 0 0 0 40 41 0.9170 0 0 0 0 0 1 0 0 0 0 0 0 41 42 0.9554 0 0 0 0 0 0 1 0 0 0 0 0 42 43 0.9922 0 0 0 0 0 0 0 1 0 0 0 0 43 44 0.9778 0 0 0 0 0 0 0 0 1 0 0 0 44 45 0.9808 0 0 0 0 0 0 0 0 0 1 0 0 45 46 0.9811 0 0 0 0 0 0 0 0 0 0 1 0 46 47 1.0014 0 0 0 0 0 0 0 0 0 0 0 1 47 48 1.0183 0 0 0 0 0 0 0 0 0 0 0 0 48 49 1.0622 0 1 0 0 0 0 0 0 0 0 0 0 49 50 1.0773 0 0 1 0 0 0 0 0 0 0 0 0 50 51 1.0807 0 0 0 1 0 0 0 0 0 0 0 0 51 52 1.0848 0 0 0 0 1 0 0 0 0 0 0 0 52 53 1.1582 0 0 0 0 0 1 0 0 0 0 0 0 53 54 1.1663 0 0 0 0 0 0 1 0 0 0 0 0 54 55 1.1372 0 0 0 0 0 0 0 1 0 0 0 0 55 56 1.1139 0 0 0 0 0 0 0 0 1 0 0 0 56 57 1.1222 0 0 0 0 0 0 0 0 0 1 0 0 57 58 1.1692 0 0 0 0 0 0 0 0 0 0 1 0 58 59 1.1702 0 0 0 0 0 0 0 0 0 0 0 1 59 60 1.2286 0 0 0 0 0 0 0 0 0 0 0 0 60 61 1.2613 0 1 0 0 0 0 0 0 0 0 0 0 61 62 1.2646 0 0 1 0 0 0 0 0 0 0 0 0 62 63 1.2262 0 0 0 1 0 0 0 0 0 0 0 0 63 64 1.1985 0 0 0 0 1 0 0 0 0 0 0 0 64 65 1.2007 0 0 0 0 0 1 0 0 0 0 0 0 65 66 1.2138 0 0 0 0 0 0 1 0 0 0 0 0 66 67 1.2266 0 0 0 0 0 0 0 1 0 0 0 0 67 68 1.2176 0 0 0 0 0 0 0 0 1 0 0 0 68 69 1.2218 0 0 0 0 0 0 0 0 0 1 0 0 69 70 1.2490 0 0 0 0 0 0 0 0 0 0 1 0 70 71 1.2991 0 0 0 0 0 0 0 0 0 0 0 1 71 72 1.3408 0 0 0 0 0 0 0 0 0 0 0 0 72 73 1.3119 0 1 0 0 0 0 0 0 0 0 0 0 73 74 1.3014 0 0 1 0 0 0 0 0 0 0 0 0 74 75 1.3201 0 0 0 1 0 0 0 0 0 0 0 0 75 76 1.2938 0 0 0 0 1 0 0 0 0 0 0 0 76 77 1.2694 0 0 0 0 0 1 0 0 0 0 0 0 77 78 1.2165 0 0 0 0 0 0 1 0 0 0 0 0 78 79 1.2037 0 0 0 0 0 0 0 1 0 0 0 0 79 80 1.2292 0 0 0 0 0 0 0 0 1 0 0 0 80 81 1.2256 0 0 0 0 0 0 0 0 0 1 0 0 81 82 1.2015 0 0 0 0 0 0 0 0 0 0 1 0 82 83 1.1786 0 0 0 0 0 0 0 0 0 0 0 1 83 84 1.1856 0 0 0 0 0 0 0 0 0 0 0 0 84 85 1.2103 0 1 0 0 0 0 0 0 0 0 0 0 85 86 1.1938 0 0 1 0 0 0 0 0 0 0 0 0 86 87 1.2020 0 0 0 1 0 0 0 0 0 0 0 0 87 88 1.2271 0 0 0 0 1 0 0 0 0 0 0 0 88 89 1.2770 0 0 0 0 0 1 0 0 0 0 0 0 89 90 1.2650 0 0 0 0 0 0 1 0 0 0 0 0 90 91 1.2684 0 0 0 0 0 0 0 1 0 0 0 0 91 92 1.2811 0 0 0 0 0 0 0 0 1 0 0 0 92 93 1.2727 0 0 0 0 0 0 0 0 0 1 0 0 93 94 1.2611 0 0 0 0 0 0 0 0 0 0 1 0 94 95 1.2881 0 0 0 0 0 0 0 0 0 0 0 1 95 96 1.3213 0 0 0 0 0 0 0 0 0 0 0 0 96 97 1.2999 0 1 0 0 0 0 0 0 0 0 0 0 97 98 1.3074 0 0 1 0 0 0 0 0 0 0 0 0 98 99 1.3242 0 0 0 1 0 0 0 0 0 0 0 0 99 100 1.3516 0 0 0 0 1 0 0 0 0 0 0 0 100 101 1.3511 0 0 0 0 0 1 0 0 0 0 0 0 101 102 1.3419 1 0 0 0 0 0 1 0 0 0 0 0 102 103 1.3716 1 0 0 0 0 0 0 1 0 0 0 0 103 104 1.3622 1 0 0 0 0 0 0 0 1 0 0 0 104 105 1.3896 1 0 0 0 0 0 0 0 0 1 0 0 105 106 1.4227 1 0 0 0 0 0 0 0 0 0 1 0 106 107 1.4684 1 0 0 0 0 0 0 0 0 0 0 1 107 108 1.4570 1 0 0 0 0 0 0 0 0 0 0 0 108 109 1.4718 1 1 0 0 0 0 0 0 0 0 0 0 109 110 1.4748 1 0 1 0 0 0 0 0 0 0 0 0 110 111 1.5527 1 0 0 1 0 0 0 0 0 0 0 0 111 112 1.5751 1 0 0 0 1 0 0 0 0 0 0 0 112 113 1.5557 1 0 0 0 0 1 0 0 0 0 0 0 113 114 1.5553 1 0 0 0 0 0 1 0 0 0 0 0 114 115 1.5770 1 0 0 0 0 0 0 1 0 0 0 0 115 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) x M1 M2 M3 M4 0.883859 0.130031 0.033535 0.019506 0.018167 0.012198 M5 M6 M7 M8 M9 M10 0.012598 -0.006374 -0.004773 -0.017148 -0.021436 -0.017824 M11 t -0.014468 0.004199 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.192932 -0.068739 0.006459 0.060845 0.239207 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.8838588 0.0370742 23.840 < 2e-16 *** x 0.1300313 0.0338395 3.843 0.000213 *** M1 0.0335350 0.0446681 0.751 0.454544 M2 0.0195058 0.0446586 0.437 0.663206 M3 0.0181667 0.0446516 0.407 0.684976 M4 0.0121975 0.0446470 0.273 0.785258 M5 0.0125984 0.0446449 0.282 0.778375 M6 -0.0063739 0.0447449 -0.142 0.887009 M7 -0.0047730 0.0447335 -0.107 0.915239 M8 -0.0171479 0.0458227 -0.374 0.709023 M9 -0.0214359 0.0458142 -0.468 0.640873 M10 -0.0178239 0.0458082 -0.389 0.698022 M11 -0.0144675 0.0458046 -0.316 0.752766 t 0.0041991 0.0003317 12.658 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.09716 on 101 degrees of freedom Multiple R-squared: 0.7721, Adjusted R-squared: 0.7428 F-statistic: 26.32 on 13 and 101 DF, p-value: < 2.2e-16 > postscript(file="/var/www/html/freestat/rcomp/tmp/1qqwj1227972271.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/freestat/rcomp/tmp/29v1i1227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3an581227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4oxok1227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/575gm1227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 115 Frequency = 1 1 2 3 4 5 0.2392070800 0.2090370800 0.1736770800 0.1575470800 0.1453470800 6 7 8 9 10 0.1351202066 0.1268202066 0.1600958770 0.1498847659 0.1625736548 11 12 13 14 15 0.1182180992 0.0767514326 0.0417173126 0.0212473126 -0.0007126874 16 17 18 19 20 -0.0162426874 -0.0618426874 -0.0038695607 -0.0191695607 -0.0465938904 21 22 23 24 25 -0.0785050015 -0.1032161126 -0.1095716682 -0.0873383348 -0.0840724548 26 27 28 29 30 -0.0908424548 -0.1059024548 -0.1216324548 -0.1440324548 -0.1502593281 31 32 33 34 35 -0.1485593281 -0.1005836578 -0.0898947689 -0.1029058800 -0.1280614356 36 37 38 39 40 -0.1426281022 -0.1894622222 -0.1929322222 -0.1899922222 -0.1782222222 41 42 43 44 45 -0.1516222222 -0.0984490955 -0.0674490955 -0.0736734252 -0.0705845363 46 47 48 49 50 -0.0780956474 -0.0653512030 -0.0671178696 -0.0609519896 -0.0360219896 51 52 53 54 55 -0.0354819896 -0.0296119896 0.0391880104 0.0620611371 0.0271611371 56 57 58 59 60 0.0120368074 0.0204256963 0.0596145852 0.0530590296 0.0927923630 61 62 63 64 65 0.0877582430 0.1008882430 0.0596282430 0.0336982430 0.0312982430 66 67 68 69 70 0.0591713697 0.0661713697 0.0653470400 0.0696359289 0.0890248178 71 72 73 74 75 0.1315692623 0.1546025956 0.0879684756 0.0872984756 0.1031384756 76 77 78 79 80 0.0786084756 0.0496084756 0.0114816023 -0.0071183977 0.0265572726 81 82 83 84 85 0.0230461615 -0.0088649496 -0.0393205051 -0.0509871718 -0.0640212918 86 87 88 89 90 -0.0706912918 -0.0653512918 -0.0384812918 0.0068187082 0.0095918349 91 92 93 94 95 0.0071918349 0.0280675052 0.0197563941 0.0003452830 0.0197897275 96 97 98 99 100 0.0343230608 -0.0248110592 -0.0074810592 0.0064589408 0.0356289408 101 102 103 104 105 0.0305289408 -0.0939291994 -0.0700291994 -0.0712535290 -0.0437646401 106 107 108 109 110 -0.0184757512 0.0196686932 -0.0103979734 -0.0333320934 -0.0205020934 111 112 113 114 115 0.0545379066 0.0787079066 0.0547079066 0.0690810332 0.0849810332 > postscript(file="/var/www/html/freestat/rcomp/tmp/6q73c1227972271.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 = 115 Frequency = 1 lag(myerror, k = 1) myerror 0 0.2392070800 NA 1 0.2090370800 0.2392070800 2 0.1736770800 0.2090370800 3 0.1575470800 0.1736770800 4 0.1453470800 0.1575470800 5 0.1351202066 0.1453470800 6 0.1268202066 0.1351202066 7 0.1600958770 0.1268202066 8 0.1498847659 0.1600958770 9 0.1625736548 0.1498847659 10 0.1182180992 0.1625736548 11 0.0767514326 0.1182180992 12 0.0417173126 0.0767514326 13 0.0212473126 0.0417173126 14 -0.0007126874 0.0212473126 15 -0.0162426874 -0.0007126874 16 -0.0618426874 -0.0162426874 17 -0.0038695607 -0.0618426874 18 -0.0191695607 -0.0038695607 19 -0.0465938904 -0.0191695607 20 -0.0785050015 -0.0465938904 21 -0.1032161126 -0.0785050015 22 -0.1095716682 -0.1032161126 23 -0.0873383348 -0.1095716682 24 -0.0840724548 -0.0873383348 25 -0.0908424548 -0.0840724548 26 -0.1059024548 -0.0908424548 27 -0.1216324548 -0.1059024548 28 -0.1440324548 -0.1216324548 29 -0.1502593281 -0.1440324548 30 -0.1485593281 -0.1502593281 31 -0.1005836578 -0.1485593281 32 -0.0898947689 -0.1005836578 33 -0.1029058800 -0.0898947689 34 -0.1280614356 -0.1029058800 35 -0.1426281022 -0.1280614356 36 -0.1894622222 -0.1426281022 37 -0.1929322222 -0.1894622222 38 -0.1899922222 -0.1929322222 39 -0.1782222222 -0.1899922222 40 -0.1516222222 -0.1782222222 41 -0.0984490955 -0.1516222222 42 -0.0674490955 -0.0984490955 43 -0.0736734252 -0.0674490955 44 -0.0705845363 -0.0736734252 45 -0.0780956474 -0.0705845363 46 -0.0653512030 -0.0780956474 47 -0.0671178696 -0.0653512030 48 -0.0609519896 -0.0671178696 49 -0.0360219896 -0.0609519896 50 -0.0354819896 -0.0360219896 51 -0.0296119896 -0.0354819896 52 0.0391880104 -0.0296119896 53 0.0620611371 0.0391880104 54 0.0271611371 0.0620611371 55 0.0120368074 0.0271611371 56 0.0204256963 0.0120368074 57 0.0596145852 0.0204256963 58 0.0530590296 0.0596145852 59 0.0927923630 0.0530590296 60 0.0877582430 0.0927923630 61 0.1008882430 0.0877582430 62 0.0596282430 0.1008882430 63 0.0336982430 0.0596282430 64 0.0312982430 0.0336982430 65 0.0591713697 0.0312982430 66 0.0661713697 0.0591713697 67 0.0653470400 0.0661713697 68 0.0696359289 0.0653470400 69 0.0890248178 0.0696359289 70 0.1315692623 0.0890248178 71 0.1546025956 0.1315692623 72 0.0879684756 0.1546025956 73 0.0872984756 0.0879684756 74 0.1031384756 0.0872984756 75 0.0786084756 0.1031384756 76 0.0496084756 0.0786084756 77 0.0114816023 0.0496084756 78 -0.0071183977 0.0114816023 79 0.0265572726 -0.0071183977 80 0.0230461615 0.0265572726 81 -0.0088649496 0.0230461615 82 -0.0393205051 -0.0088649496 83 -0.0509871718 -0.0393205051 84 -0.0640212918 -0.0509871718 85 -0.0706912918 -0.0640212918 86 -0.0653512918 -0.0706912918 87 -0.0384812918 -0.0653512918 88 0.0068187082 -0.0384812918 89 0.0095918349 0.0068187082 90 0.0071918349 0.0095918349 91 0.0280675052 0.0071918349 92 0.0197563941 0.0280675052 93 0.0003452830 0.0197563941 94 0.0197897275 0.0003452830 95 0.0343230608 0.0197897275 96 -0.0248110592 0.0343230608 97 -0.0074810592 -0.0248110592 98 0.0064589408 -0.0074810592 99 0.0356289408 0.0064589408 100 0.0305289408 0.0356289408 101 -0.0939291994 0.0305289408 102 -0.0700291994 -0.0939291994 103 -0.0712535290 -0.0700291994 104 -0.0437646401 -0.0712535290 105 -0.0184757512 -0.0437646401 106 0.0196686932 -0.0184757512 107 -0.0103979734 0.0196686932 108 -0.0333320934 -0.0103979734 109 -0.0205020934 -0.0333320934 110 0.0545379066 -0.0205020934 111 0.0787079066 0.0545379066 112 0.0547079066 0.0787079066 113 0.0690810332 0.0547079066 114 0.0849810332 0.0690810332 115 NA 0.0849810332 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.2090370800 0.2392070800 [2,] 0.1736770800 0.2090370800 [3,] 0.1575470800 0.1736770800 [4,] 0.1453470800 0.1575470800 [5,] 0.1351202066 0.1453470800 [6,] 0.1268202066 0.1351202066 [7,] 0.1600958770 0.1268202066 [8,] 0.1498847659 0.1600958770 [9,] 0.1625736548 0.1498847659 [10,] 0.1182180992 0.1625736548 [11,] 0.0767514326 0.1182180992 [12,] 0.0417173126 0.0767514326 [13,] 0.0212473126 0.0417173126 [14,] -0.0007126874 0.0212473126 [15,] -0.0162426874 -0.0007126874 [16,] -0.0618426874 -0.0162426874 [17,] -0.0038695607 -0.0618426874 [18,] -0.0191695607 -0.0038695607 [19,] -0.0465938904 -0.0191695607 [20,] -0.0785050015 -0.0465938904 [21,] -0.1032161126 -0.0785050015 [22,] -0.1095716682 -0.1032161126 [23,] -0.0873383348 -0.1095716682 [24,] -0.0840724548 -0.0873383348 [25,] -0.0908424548 -0.0840724548 [26,] -0.1059024548 -0.0908424548 [27,] -0.1216324548 -0.1059024548 [28,] -0.1440324548 -0.1216324548 [29,] -0.1502593281 -0.1440324548 [30,] -0.1485593281 -0.1502593281 [31,] -0.1005836578 -0.1485593281 [32,] -0.0898947689 -0.1005836578 [33,] -0.1029058800 -0.0898947689 [34,] -0.1280614356 -0.1029058800 [35,] -0.1426281022 -0.1280614356 [36,] -0.1894622222 -0.1426281022 [37,] -0.1929322222 -0.1894622222 [38,] -0.1899922222 -0.1929322222 [39,] -0.1782222222 -0.1899922222 [40,] -0.1516222222 -0.1782222222 [41,] -0.0984490955 -0.1516222222 [42,] -0.0674490955 -0.0984490955 [43,] -0.0736734252 -0.0674490955 [44,] -0.0705845363 -0.0736734252 [45,] -0.0780956474 -0.0705845363 [46,] -0.0653512030 -0.0780956474 [47,] -0.0671178696 -0.0653512030 [48,] -0.0609519896 -0.0671178696 [49,] -0.0360219896 -0.0609519896 [50,] -0.0354819896 -0.0360219896 [51,] -0.0296119896 -0.0354819896 [52,] 0.0391880104 -0.0296119896 [53,] 0.0620611371 0.0391880104 [54,] 0.0271611371 0.0620611371 [55,] 0.0120368074 0.0271611371 [56,] 0.0204256963 0.0120368074 [57,] 0.0596145852 0.0204256963 [58,] 0.0530590296 0.0596145852 [59,] 0.0927923630 0.0530590296 [60,] 0.0877582430 0.0927923630 [61,] 0.1008882430 0.0877582430 [62,] 0.0596282430 0.1008882430 [63,] 0.0336982430 0.0596282430 [64,] 0.0312982430 0.0336982430 [65,] 0.0591713697 0.0312982430 [66,] 0.0661713697 0.0591713697 [67,] 0.0653470400 0.0661713697 [68,] 0.0696359289 0.0653470400 [69,] 0.0890248178 0.0696359289 [70,] 0.1315692623 0.0890248178 [71,] 0.1546025956 0.1315692623 [72,] 0.0879684756 0.1546025956 [73,] 0.0872984756 0.0879684756 [74,] 0.1031384756 0.0872984756 [75,] 0.0786084756 0.1031384756 [76,] 0.0496084756 0.0786084756 [77,] 0.0114816023 0.0496084756 [78,] -0.0071183977 0.0114816023 [79,] 0.0265572726 -0.0071183977 [80,] 0.0230461615 0.0265572726 [81,] -0.0088649496 0.0230461615 [82,] -0.0393205051 -0.0088649496 [83,] -0.0509871718 -0.0393205051 [84,] -0.0640212918 -0.0509871718 [85,] -0.0706912918 -0.0640212918 [86,] -0.0653512918 -0.0706912918 [87,] -0.0384812918 -0.0653512918 [88,] 0.0068187082 -0.0384812918 [89,] 0.0095918349 0.0068187082 [90,] 0.0071918349 0.0095918349 [91,] 0.0280675052 0.0071918349 [92,] 0.0197563941 0.0280675052 [93,] 0.0003452830 0.0197563941 [94,] 0.0197897275 0.0003452830 [95,] 0.0343230608 0.0197897275 [96,] -0.0248110592 0.0343230608 [97,] -0.0074810592 -0.0248110592 [98,] 0.0064589408 -0.0074810592 [99,] 0.0356289408 0.0064589408 [100,] 0.0305289408 0.0356289408 [101,] -0.0939291994 0.0305289408 [102,] -0.0700291994 -0.0939291994 [103,] -0.0712535290 -0.0700291994 [104,] -0.0437646401 -0.0712535290 [105,] -0.0184757512 -0.0437646401 [106,] 0.0196686932 -0.0184757512 [107,] -0.0103979734 0.0196686932 [108,] -0.0333320934 -0.0103979734 [109,] -0.0205020934 -0.0333320934 [110,] 0.0545379066 -0.0205020934 [111,] 0.0787079066 0.0545379066 [112,] 0.0547079066 0.0787079066 [113,] 0.0690810332 0.0547079066 [114,] 0.0849810332 0.0690810332 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.2090370800 0.2392070800 2 0.1736770800 0.2090370800 3 0.1575470800 0.1736770800 4 0.1453470800 0.1575470800 5 0.1351202066 0.1453470800 6 0.1268202066 0.1351202066 7 0.1600958770 0.1268202066 8 0.1498847659 0.1600958770 9 0.1625736548 0.1498847659 10 0.1182180992 0.1625736548 11 0.0767514326 0.1182180992 12 0.0417173126 0.0767514326 13 0.0212473126 0.0417173126 14 -0.0007126874 0.0212473126 15 -0.0162426874 -0.0007126874 16 -0.0618426874 -0.0162426874 17 -0.0038695607 -0.0618426874 18 -0.0191695607 -0.0038695607 19 -0.0465938904 -0.0191695607 20 -0.0785050015 -0.0465938904 21 -0.1032161126 -0.0785050015 22 -0.1095716682 -0.1032161126 23 -0.0873383348 -0.1095716682 24 -0.0840724548 -0.0873383348 25 -0.0908424548 -0.0840724548 26 -0.1059024548 -0.0908424548 27 -0.1216324548 -0.1059024548 28 -0.1440324548 -0.1216324548 29 -0.1502593281 -0.1440324548 30 -0.1485593281 -0.1502593281 31 -0.1005836578 -0.1485593281 32 -0.0898947689 -0.1005836578 33 -0.1029058800 -0.0898947689 34 -0.1280614356 -0.1029058800 35 -0.1426281022 -0.1280614356 36 -0.1894622222 -0.1426281022 37 -0.1929322222 -0.1894622222 38 -0.1899922222 -0.1929322222 39 -0.1782222222 -0.1899922222 40 -0.1516222222 -0.1782222222 41 -0.0984490955 -0.1516222222 42 -0.0674490955 -0.0984490955 43 -0.0736734252 -0.0674490955 44 -0.0705845363 -0.0736734252 45 -0.0780956474 -0.0705845363 46 -0.0653512030 -0.0780956474 47 -0.0671178696 -0.0653512030 48 -0.0609519896 -0.0671178696 49 -0.0360219896 -0.0609519896 50 -0.0354819896 -0.0360219896 51 -0.0296119896 -0.0354819896 52 0.0391880104 -0.0296119896 53 0.0620611371 0.0391880104 54 0.0271611371 0.0620611371 55 0.0120368074 0.0271611371 56 0.0204256963 0.0120368074 57 0.0596145852 0.0204256963 58 0.0530590296 0.0596145852 59 0.0927923630 0.0530590296 60 0.0877582430 0.0927923630 61 0.1008882430 0.0877582430 62 0.0596282430 0.1008882430 63 0.0336982430 0.0596282430 64 0.0312982430 0.0336982430 65 0.0591713697 0.0312982430 66 0.0661713697 0.0591713697 67 0.0653470400 0.0661713697 68 0.0696359289 0.0653470400 69 0.0890248178 0.0696359289 70 0.1315692623 0.0890248178 71 0.1546025956 0.1315692623 72 0.0879684756 0.1546025956 73 0.0872984756 0.0879684756 74 0.1031384756 0.0872984756 75 0.0786084756 0.1031384756 76 0.0496084756 0.0786084756 77 0.0114816023 0.0496084756 78 -0.0071183977 0.0114816023 79 0.0265572726 -0.0071183977 80 0.0230461615 0.0265572726 81 -0.0088649496 0.0230461615 82 -0.0393205051 -0.0088649496 83 -0.0509871718 -0.0393205051 84 -0.0640212918 -0.0509871718 85 -0.0706912918 -0.0640212918 86 -0.0653512918 -0.0706912918 87 -0.0384812918 -0.0653512918 88 0.0068187082 -0.0384812918 89 0.0095918349 0.0068187082 90 0.0071918349 0.0095918349 91 0.0280675052 0.0071918349 92 0.0197563941 0.0280675052 93 0.0003452830 0.0197563941 94 0.0197897275 0.0003452830 95 0.0343230608 0.0197897275 96 -0.0248110592 0.0343230608 97 -0.0074810592 -0.0248110592 98 0.0064589408 -0.0074810592 99 0.0356289408 0.0064589408 100 0.0305289408 0.0356289408 101 -0.0939291994 0.0305289408 102 -0.0700291994 -0.0939291994 103 -0.0712535290 -0.0700291994 104 -0.0437646401 -0.0712535290 105 -0.0184757512 -0.0437646401 106 0.0196686932 -0.0184757512 107 -0.0103979734 0.0196686932 108 -0.0333320934 -0.0103979734 109 -0.0205020934 -0.0333320934 110 0.0545379066 -0.0205020934 111 0.0787079066 0.0545379066 112 0.0547079066 0.0787079066 113 0.0690810332 0.0547079066 114 0.0849810332 0.0690810332 > 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/freestat/rcomp/tmp/7yxty1227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8s8a61227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9y7ay1227972271.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/10zf9g1227972271.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/freestat/rcomp/tmp/11kpn61227972271.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/freestat/rcomp/tmp/12t0or1227972271.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/freestat/rcomp/tmp/13crts1227972271.tab") > > system("convert tmp/1qqwj1227972271.ps tmp/1qqwj1227972271.png") > system("convert tmp/29v1i1227972271.ps tmp/29v1i1227972271.png") > system("convert tmp/3an581227972271.ps tmp/3an581227972271.png") > system("convert tmp/4oxok1227972271.ps tmp/4oxok1227972271.png") > system("convert tmp/575gm1227972271.ps tmp/575gm1227972271.png") > system("convert tmp/6q73c1227972271.ps tmp/6q73c1227972271.png") > system("convert tmp/7yxty1227972271.ps tmp/7yxty1227972271.png") > system("convert tmp/8s8a61227972271.ps tmp/8s8a61227972271.png") > system("convert tmp/9y7ay1227972271.ps tmp/9y7ay1227972271.png") > > > proc.time() user system elapsed 3.132 2.258 3.468