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Type 'q()' to quit R. > x <- array(list(121.6 + ,0 + ,97.2 + ,111.5 + ,114.0 + ,118.8 + ,118.8 + ,0 + ,102.5 + ,97.2 + ,111.5 + ,114.0 + ,114.0 + ,1 + ,113.4 + ,102.5 + ,97.2 + ,111.5 + ,111.5 + ,1 + ,109.8 + ,113.4 + ,102.5 + ,97.2 + ,97.2 + ,1 + ,104.9 + ,109.8 + ,113.4 + ,102.5 + ,102.5 + ,1 + ,126.1 + ,104.9 + ,109.8 + ,113.4 + ,113.4 + ,1 + ,80.0 + ,126.1 + ,104.9 + ,109.8 + ,109.8 + ,1 + ,96.8 + ,80.0 + ,126.1 + ,104.9 + ,104.9 + ,1 + ,117.2 + ,96.8 + ,80.0 + ,126.1 + ,126.1 + ,1 + ,112.3 + ,117.2 + ,96.8 + ,80.0 + ,80.0 + ,1 + ,117.3 + ,112.3 + ,117.2 + ,96.8 + ,96.8 + ,1 + ,111.1 + ,117.3 + ,112.3 + ,117.2 + ,117.2 + ,1 + ,102.2 + ,111.1 + ,117.3 + ,112.3 + ,112.3 + ,1 + ,104.3 + ,102.2 + ,111.1 + ,117.3 + ,117.3 + ,1 + ,122.9 + ,104.3 + ,102.2 + ,111.1 + ,111.1 + ,0 + ,107.6 + ,122.9 + ,104.3 + ,102.2 + ,102.2 + ,0 + ,121.3 + ,107.6 + ,122.9 + ,104.3 + ,104.3 + ,0 + ,131.5 + ,121.3 + ,107.6 + ,122.9 + ,122.9 + ,0 + ,89.0 + ,131.5 + ,121.3 + ,107.6 + ,107.6 + ,0 + ,104.4 + ,89.0 + ,131.5 + ,121.3 + ,121.3 + ,0 + ,128.9 + ,104.4 + ,89.0 + ,131.5 + ,131.5 + ,0 + ,135.9 + ,128.9 + ,104.4 + ,89.0 + ,89.0 + ,0 + ,133.3 + ,135.9 + ,128.9 + ,104.4 + ,104.4 + ,0 + ,121.3 + ,133.3 + ,135.9 + ,128.9 + ,128.9 + ,0 + ,120.5 + ,121.3 + ,133.3 + ,135.9 + ,135.9 + ,0 + ,120.4 + ,120.5 + ,121.3 + ,133.3 + ,133.3 + ,0 + ,137.9 + ,120.4 + ,120.5 + ,121.3 + ,121.3 + ,0 + ,126.1 + ,137.9 + ,120.4 + ,120.5 + ,120.5 + ,0 + ,133.2 + ,126.1 + ,137.9 + ,120.4 + ,120.4 + ,0 + ,151.1 + ,133.2 + ,126.1 + ,137.9 + ,137.9 + ,0 + ,105.0 + ,151.1 + ,133.2 + ,126.1 + ,126.1 + ,0 + ,119.0 + ,105.0 + ,151.1 + ,133.2 + ,133.2 + ,0 + ,140.4 + ,119.0 + ,105.0 + ,151.1 + ,151.1 + ,0 + ,156.6 + ,140.4 + ,119.0 + ,105.0 + ,105.0 + ,0 + ,137.1 + ,156.6 + ,140.4 + ,119.0 + ,119.0 + ,0 + ,122.7 + ,137.1 + ,156.6 + ,140.4 + ,140.4 + ,0 + ,125.8 + ,122.7 + ,137.1 + ,156.6 + ,156.6 + ,0 + ,139.3 + ,125.8 + ,122.7 + ,137.1 + ,137.1 + ,0 + ,134.9 + ,139.3 + ,125.8 + ,122.7 + ,122.7 + ,0 + ,149.2 + ,134.9 + ,139.3 + ,125.8 + ,125.8 + ,0 + ,132.3 + ,149.2 + ,134.9 + ,139.3 + ,139.3 + ,0 + ,149.0 + ,132.3 + ,149.2 + ,134.9 + ,134.9 + ,0 + ,117.2 + ,149.0 + ,132.3 + ,149.2 + ,149.2 + ,1 + ,119.6 + ,117.2 + ,149.0 + ,132.3 + ,132.3 + ,0 + ,152.0 + ,119.6 + ,117.2 + ,149.0 + ,149.0 + ,1 + ,149.4 + ,152.0 + ,119.6 + ,117.2 + ,117.2 + ,1 + ,127.3 + ,149.4 + ,152.0 + ,119.6 + ,119.6 + ,1 + ,114.1 + ,127.3 + ,149.4 + ,152.0 + ,152.0 + ,1 + ,102.1 + ,114.1 + ,127.3 + ,149.4 + ,149.4 + ,1 + ,107.7 + ,102.1 + ,114.1 + ,127.3 + ,127.3 + ,1 + ,104.4 + ,107.7 + ,102.1 + ,114.1 + ,114.1 + ,1 + ,102.1 + ,104.4 + ,107.7 + ,102.1 + ,102.1 + ,1 + ,96.0 + ,102.1 + ,104.4 + ,107.7 + ,107.7 + ,1 + ,109.3 + ,96.0 + ,102.1 + ,104.4 + ,104.4 + ,1 + ,90.0 + ,109.3 + ,96.0 + ,102.1 + ,102.1 + ,1 + ,83.9 + ,90.0 + ,109.3 + ,96.0) + ,dim=c(6 + ,56) + ,dimnames=list(c('X' + ,'Y' + ,'y(t)' + ,'y(t-1)' + ,'y(t-2)' + ,'y(t-3)') + ,1:56)) > y <- array(NA,dim=c(6,56),dimnames=list(c('X','Y','y(t)','y(t-1)','y(t-2)','y(t-3)'),1:56)) > 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) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > 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 X Y y(t) y(t-1) y(t-2) y(t-3) M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 121.6 0 97.2 111.5 114.0 118.8 1 0 0 0 0 0 0 0 0 0 0 1 2 118.8 0 102.5 97.2 111.5 114.0 0 1 0 0 0 0 0 0 0 0 0 2 3 114.0 1 113.4 102.5 97.2 111.5 0 0 1 0 0 0 0 0 0 0 0 3 4 111.5 1 109.8 113.4 102.5 97.2 0 0 0 1 0 0 0 0 0 0 0 4 5 97.2 1 104.9 109.8 113.4 102.5 0 0 0 0 1 0 0 0 0 0 0 5 6 102.5 1 126.1 104.9 109.8 113.4 0 0 0 0 0 1 0 0 0 0 0 6 7 113.4 1 80.0 126.1 104.9 109.8 0 0 0 0 0 0 1 0 0 0 0 7 8 109.8 1 96.8 80.0 126.1 104.9 0 0 0 0 0 0 0 1 0 0 0 8 9 104.9 1 117.2 96.8 80.0 126.1 0 0 0 0 0 0 0 0 1 0 0 9 10 126.1 1 112.3 117.2 96.8 80.0 0 0 0 0 0 0 0 0 0 1 0 10 11 80.0 1 117.3 112.3 117.2 96.8 0 0 0 0 0 0 0 0 0 0 1 11 12 96.8 1 111.1 117.3 112.3 117.2 0 0 0 0 0 0 0 0 0 0 0 12 13 117.2 1 102.2 111.1 117.3 112.3 1 0 0 0 0 0 0 0 0 0 0 13 14 112.3 1 104.3 102.2 111.1 117.3 0 1 0 0 0 0 0 0 0 0 0 14 15 117.3 1 122.9 104.3 102.2 111.1 0 0 1 0 0 0 0 0 0 0 0 15 16 111.1 0 107.6 122.9 104.3 102.2 0 0 0 1 0 0 0 0 0 0 0 16 17 102.2 0 121.3 107.6 122.9 104.3 0 0 0 0 1 0 0 0 0 0 0 17 18 104.3 0 131.5 121.3 107.6 122.9 0 0 0 0 0 1 0 0 0 0 0 18 19 122.9 0 89.0 131.5 121.3 107.6 0 0 0 0 0 0 1 0 0 0 0 19 20 107.6 0 104.4 89.0 131.5 121.3 0 0 0 0 0 0 0 1 0 0 0 20 21 121.3 0 128.9 104.4 89.0 131.5 0 0 0 0 0 0 0 0 1 0 0 21 22 131.5 0 135.9 128.9 104.4 89.0 0 0 0 0 0 0 0 0 0 1 0 22 23 89.0 0 133.3 135.9 128.9 104.4 0 0 0 0 0 0 0 0 0 0 1 23 24 104.4 0 121.3 133.3 135.9 128.9 0 0 0 0 0 0 0 0 0 0 0 24 25 128.9 0 120.5 121.3 133.3 135.9 1 0 0 0 0 0 0 0 0 0 0 25 26 135.9 0 120.4 120.5 121.3 133.3 0 1 0 0 0 0 0 0 0 0 0 26 27 133.3 0 137.9 120.4 120.5 121.3 0 0 1 0 0 0 0 0 0 0 0 27 28 121.3 0 126.1 137.9 120.4 120.5 0 0 0 1 0 0 0 0 0 0 0 28 29 120.5 0 133.2 126.1 137.9 120.4 0 0 0 0 1 0 0 0 0 0 0 29 30 120.4 0 151.1 133.2 126.1 137.9 0 0 0 0 0 1 0 0 0 0 0 30 31 137.9 0 105.0 151.1 133.2 126.1 0 0 0 0 0 0 1 0 0 0 0 31 32 126.1 0 119.0 105.0 151.1 133.2 0 0 0 0 0 0 0 1 0 0 0 32 33 133.2 0 140.4 119.0 105.0 151.1 0 0 0 0 0 0 0 0 1 0 0 33 34 151.1 0 156.6 140.4 119.0 105.0 0 0 0 0 0 0 0 0 0 1 0 34 35 105.0 0 137.1 156.6 140.4 119.0 0 0 0 0 0 0 0 0 0 0 1 35 36 119.0 0 122.7 137.1 156.6 140.4 0 0 0 0 0 0 0 0 0 0 0 36 37 140.4 0 125.8 122.7 137.1 156.6 1 0 0 0 0 0 0 0 0 0 0 37 38 156.6 0 139.3 125.8 122.7 137.1 0 1 0 0 0 0 0 0 0 0 0 38 39 137.1 0 134.9 139.3 125.8 122.7 0 0 1 0 0 0 0 0 0 0 0 39 40 122.7 0 149.2 134.9 139.3 125.8 0 0 0 1 0 0 0 0 0 0 0 40 41 125.8 0 132.3 149.2 134.9 139.3 0 0 0 0 1 0 0 0 0 0 0 41 42 139.3 0 149.0 132.3 149.2 134.9 0 0 0 0 0 1 0 0 0 0 0 42 43 134.9 0 117.2 149.0 132.3 149.2 0 0 0 0 0 0 1 0 0 0 0 43 44 149.2 1 119.6 117.2 149.0 132.3 0 0 0 0 0 0 0 1 0 0 0 44 45 132.3 0 152.0 119.6 117.2 149.0 0 0 0 0 0 0 0 0 1 0 0 45 46 149.0 1 149.4 152.0 119.6 117.2 0 0 0 0 0 0 0 0 0 1 0 46 47 117.2 1 127.3 149.4 152.0 119.6 0 0 0 0 0 0 0 0 0 0 1 47 48 119.6 1 114.1 127.3 149.4 152.0 0 0 0 0 0 0 0 0 0 0 0 48 49 152.0 1 102.1 114.1 127.3 149.4 1 0 0 0 0 0 0 0 0 0 0 49 50 149.4 1 107.7 102.1 114.1 127.3 0 1 0 0 0 0 0 0 0 0 0 50 51 127.3 1 104.4 107.7 102.1 114.1 0 0 1 0 0 0 0 0 0 0 0 51 52 114.1 1 102.1 104.4 107.7 102.1 0 0 0 1 0 0 0 0 0 0 0 52 53 102.1 1 96.0 102.1 104.4 107.7 0 0 0 0 1 0 0 0 0 0 0 53 54 107.7 1 109.3 96.0 102.1 104.4 0 0 0 0 0 1 0 0 0 0 0 54 55 104.4 1 90.0 109.3 96.0 102.1 0 0 0 0 0 0 1 0 0 0 0 55 56 102.1 1 83.9 90.0 109.3 96.0 0 0 0 0 0 0 0 1 0 0 0 56 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Y `y(t)` `y(t-1)` `y(t-2)` `y(t-3)` -14.58669 3.81450 -0.06149 0.29835 0.44321 0.18274 M1 M2 M3 M4 M5 M6 32.29672 42.87337 36.71937 23.92885 13.74819 20.46761 M7 M8 M9 M10 M11 t 22.44288 22.59901 38.32861 48.79545 -7.94034 0.18070 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -17.0854 -3.1291 -0.7408 3.5476 13.0437 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -14.58669 14.15494 -1.031 0.309289 Y 3.81450 2.59774 1.468 0.150228 `y(t)` -0.06149 0.14179 -0.434 0.666990 `y(t-1)` 0.29835 0.13699 2.178 0.035682 * `y(t-2)` 0.44321 0.14282 3.103 0.003604 ** `y(t-3)` 0.18274 0.15041 1.215 0.231876 M1 32.29672 4.90681 6.582 9.09e-08 *** M2 42.87337 5.30026 8.089 8.71e-10 *** M3 36.71937 6.06347 6.056 4.77e-07 *** M4 23.92885 5.85319 4.088 0.000217 *** M5 13.74819 5.13766 2.676 0.010934 * M6 20.46761 6.18625 3.309 0.002059 ** M7 22.44288 5.62810 3.988 0.000293 *** M8 22.59901 5.64127 4.006 0.000277 *** M9 38.32861 8.76751 4.372 9.24e-05 *** M10 48.79545 9.17732 5.317 4.91e-06 *** M11 -7.94034 6.75937 -1.175 0.247417 t 0.18070 0.06585 2.744 0.009215 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 6.556 on 38 degrees of freedom Multiple R-squared: 0.8944, Adjusted R-squared: 0.8472 F-statistic: 18.94 on 17 and 38 DF, p-value: 1.548e-13 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.20262049 0.40524098 0.7973795 [2,] 0.15980078 0.31960156 0.8401992 [3,] 0.07832361 0.15664722 0.9216764 [4,] 0.03459187 0.06918373 0.9654081 [5,] 0.03648995 0.07297989 0.9635101 [6,] 0.36632033 0.73264066 0.6336797 [7,] 0.26977225 0.53954450 0.7302277 [8,] 0.17632954 0.35265907 0.8236705 [9,] 0.15207570 0.30415139 0.8479243 [10,] 0.12144586 0.24289171 0.8785541 [11,] 0.08215135 0.16430270 0.9178487 [12,] 0.12234733 0.24469465 0.8776527 [13,] 0.15640554 0.31281107 0.8435945 [14,] 0.41917318 0.83834636 0.5808268 [15,] 0.27002990 0.54005980 0.7299701 > postscript(file="/var/www/html/rcomp/tmp/1dxph1258623266.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/222ei1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ylix1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4z2jh1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/52i941258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 56 Frequency = 1 1 2 3 4 5 6 4.1841261 -2.7956867 0.4467929 7.3474168 -1.9793407 -1.2103027 7 8 9 10 11 12 1.2035481 3.5533143 -4.4572471 0.6860578 0.7990311 6.0487422 13 14 15 16 17 18 -6.0467361 -17.0854407 -0.5174281 3.9123955 1.7921660 -3.0861603 19 20 21 22 23 24 4.4253858 -4.6087478 7.0651200 0.6795144 -1.1865527 -1.4494016 25 26 27 28 29 30 -6.0226295 -3.7538300 3.2728544 -1.8735826 3.5456808 -2.4402483 31 32 33 34 35 36 3.7381772 -3.0145589 2.4748118 6.5581711 -1.0621421 -1.3413875 37 38 39 40 41 42 -2.2497921 13.0437370 -3.5237361 -9.6716610 -2.3942504 4.7408912 43 44 45 46 47 48 -3.8759790 11.5947241 -5.0826847 -7.9237432 1.4496637 -3.2579531 49 50 51 52 53 54 10.1350316 10.5912204 0.3215169 0.2854313 -0.9642558 1.9958201 55 56 -5.4911320 -7.5247318 > postscript(file="/var/www/html/rcomp/tmp/6bpkp1258623266.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 = 56 Frequency = 1 lag(myerror, k = 1) myerror 0 4.1841261 NA 1 -2.7956867 4.1841261 2 0.4467929 -2.7956867 3 7.3474168 0.4467929 4 -1.9793407 7.3474168 5 -1.2103027 -1.9793407 6 1.2035481 -1.2103027 7 3.5533143 1.2035481 8 -4.4572471 3.5533143 9 0.6860578 -4.4572471 10 0.7990311 0.6860578 11 6.0487422 0.7990311 12 -6.0467361 6.0487422 13 -17.0854407 -6.0467361 14 -0.5174281 -17.0854407 15 3.9123955 -0.5174281 16 1.7921660 3.9123955 17 -3.0861603 1.7921660 18 4.4253858 -3.0861603 19 -4.6087478 4.4253858 20 7.0651200 -4.6087478 21 0.6795144 7.0651200 22 -1.1865527 0.6795144 23 -1.4494016 -1.1865527 24 -6.0226295 -1.4494016 25 -3.7538300 -6.0226295 26 3.2728544 -3.7538300 27 -1.8735826 3.2728544 28 3.5456808 -1.8735826 29 -2.4402483 3.5456808 30 3.7381772 -2.4402483 31 -3.0145589 3.7381772 32 2.4748118 -3.0145589 33 6.5581711 2.4748118 34 -1.0621421 6.5581711 35 -1.3413875 -1.0621421 36 -2.2497921 -1.3413875 37 13.0437370 -2.2497921 38 -3.5237361 13.0437370 39 -9.6716610 -3.5237361 40 -2.3942504 -9.6716610 41 4.7408912 -2.3942504 42 -3.8759790 4.7408912 43 11.5947241 -3.8759790 44 -5.0826847 11.5947241 45 -7.9237432 -5.0826847 46 1.4496637 -7.9237432 47 -3.2579531 1.4496637 48 10.1350316 -3.2579531 49 10.5912204 10.1350316 50 0.3215169 10.5912204 51 0.2854313 0.3215169 52 -0.9642558 0.2854313 53 1.9958201 -0.9642558 54 -5.4911320 1.9958201 55 -7.5247318 -5.4911320 56 NA -7.5247318 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -2.7956867 4.1841261 [2,] 0.4467929 -2.7956867 [3,] 7.3474168 0.4467929 [4,] -1.9793407 7.3474168 [5,] -1.2103027 -1.9793407 [6,] 1.2035481 -1.2103027 [7,] 3.5533143 1.2035481 [8,] -4.4572471 3.5533143 [9,] 0.6860578 -4.4572471 [10,] 0.7990311 0.6860578 [11,] 6.0487422 0.7990311 [12,] -6.0467361 6.0487422 [13,] -17.0854407 -6.0467361 [14,] -0.5174281 -17.0854407 [15,] 3.9123955 -0.5174281 [16,] 1.7921660 3.9123955 [17,] -3.0861603 1.7921660 [18,] 4.4253858 -3.0861603 [19,] -4.6087478 4.4253858 [20,] 7.0651200 -4.6087478 [21,] 0.6795144 7.0651200 [22,] -1.1865527 0.6795144 [23,] -1.4494016 -1.1865527 [24,] -6.0226295 -1.4494016 [25,] -3.7538300 -6.0226295 [26,] 3.2728544 -3.7538300 [27,] -1.8735826 3.2728544 [28,] 3.5456808 -1.8735826 [29,] -2.4402483 3.5456808 [30,] 3.7381772 -2.4402483 [31,] -3.0145589 3.7381772 [32,] 2.4748118 -3.0145589 [33,] 6.5581711 2.4748118 [34,] -1.0621421 6.5581711 [35,] -1.3413875 -1.0621421 [36,] -2.2497921 -1.3413875 [37,] 13.0437370 -2.2497921 [38,] -3.5237361 13.0437370 [39,] -9.6716610 -3.5237361 [40,] -2.3942504 -9.6716610 [41,] 4.7408912 -2.3942504 [42,] -3.8759790 4.7408912 [43,] 11.5947241 -3.8759790 [44,] -5.0826847 11.5947241 [45,] -7.9237432 -5.0826847 [46,] 1.4496637 -7.9237432 [47,] -3.2579531 1.4496637 [48,] 10.1350316 -3.2579531 [49,] 10.5912204 10.1350316 [50,] 0.3215169 10.5912204 [51,] 0.2854313 0.3215169 [52,] -0.9642558 0.2854313 [53,] 1.9958201 -0.9642558 [54,] -5.4911320 1.9958201 [55,] -7.5247318 -5.4911320 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -2.7956867 4.1841261 2 0.4467929 -2.7956867 3 7.3474168 0.4467929 4 -1.9793407 7.3474168 5 -1.2103027 -1.9793407 6 1.2035481 -1.2103027 7 3.5533143 1.2035481 8 -4.4572471 3.5533143 9 0.6860578 -4.4572471 10 0.7990311 0.6860578 11 6.0487422 0.7990311 12 -6.0467361 6.0487422 13 -17.0854407 -6.0467361 14 -0.5174281 -17.0854407 15 3.9123955 -0.5174281 16 1.7921660 3.9123955 17 -3.0861603 1.7921660 18 4.4253858 -3.0861603 19 -4.6087478 4.4253858 20 7.0651200 -4.6087478 21 0.6795144 7.0651200 22 -1.1865527 0.6795144 23 -1.4494016 -1.1865527 24 -6.0226295 -1.4494016 25 -3.7538300 -6.0226295 26 3.2728544 -3.7538300 27 -1.8735826 3.2728544 28 3.5456808 -1.8735826 29 -2.4402483 3.5456808 30 3.7381772 -2.4402483 31 -3.0145589 3.7381772 32 2.4748118 -3.0145589 33 6.5581711 2.4748118 34 -1.0621421 6.5581711 35 -1.3413875 -1.0621421 36 -2.2497921 -1.3413875 37 13.0437370 -2.2497921 38 -3.5237361 13.0437370 39 -9.6716610 -3.5237361 40 -2.3942504 -9.6716610 41 4.7408912 -2.3942504 42 -3.8759790 4.7408912 43 11.5947241 -3.8759790 44 -5.0826847 11.5947241 45 -7.9237432 -5.0826847 46 1.4496637 -7.9237432 47 -3.2579531 1.4496637 48 10.1350316 -3.2579531 49 10.5912204 10.1350316 50 0.3215169 10.5912204 51 0.2854313 0.3215169 52 -0.9642558 0.2854313 53 1.9958201 -0.9642558 54 -5.4911320 1.9958201 55 -7.5247318 -5.4911320 > 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/7h6lz1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8x0w41258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9lyid1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/101izy1258623266.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11v7cs1258623266.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/12mad61258623266.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/138uz81258623267.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/143e691258623267.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/15ez5i1258623267.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/163w291258623267.tab") + } > > system("convert tmp/1dxph1258623266.ps tmp/1dxph1258623266.png") > system("convert tmp/222ei1258623266.ps tmp/222ei1258623266.png") > system("convert tmp/3ylix1258623266.ps tmp/3ylix1258623266.png") > system("convert tmp/4z2jh1258623266.ps tmp/4z2jh1258623266.png") > system("convert tmp/52i941258623266.ps tmp/52i941258623266.png") > system("convert tmp/6bpkp1258623266.ps tmp/6bpkp1258623266.png") > system("convert tmp/7h6lz1258623266.ps tmp/7h6lz1258623266.png") > system("convert tmp/8x0w41258623266.ps tmp/8x0w41258623266.png") > system("convert tmp/9lyid1258623266.ps tmp/9lyid1258623266.png") > system("convert tmp/101izy1258623266.ps tmp/101izy1258623266.png") > > > proc.time() user system elapsed 2.310 1.547 2.827