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Type 'q()' to quit R. > x <- array(list(127 + ,2.75 + ,123 + ,127 + ,2.75 + ,118 + ,123 + ,127 + ,2.55 + ,114 + ,118 + ,123 + ,2.5 + ,108 + ,114 + ,118 + ,2.5 + ,111 + ,108 + ,114 + ,2.1 + ,151 + ,111 + ,108 + ,2 + ,159 + ,151 + ,111 + ,2 + ,158 + ,159 + ,151 + ,2 + ,148 + ,158 + ,159 + ,2 + ,138 + ,148 + ,158 + ,2 + ,137 + ,138 + ,148 + ,2 + ,136 + ,137 + ,138 + ,2 + ,133 + ,136 + ,137 + ,2 + ,126 + ,133 + ,136 + ,2 + ,120 + ,126 + ,133 + ,2 + ,114 + ,120 + ,126 + ,2 + ,116 + ,114 + ,120 + ,2 + ,153 + ,116 + ,114 + ,2 + ,162 + ,153 + ,116 + ,2 + ,161 + ,162 + ,153 + ,2 + ,149 + ,161 + ,162 + ,2 + ,139 + ,149 + ,161 + ,2 + ,135 + ,139 + ,149 + ,2 + ,130 + ,135 + ,139 + ,2 + ,127 + ,130 + ,135 + ,2 + ,122 + ,127 + ,130 + ,2 + ,117 + ,122 + ,127 + ,2 + ,112 + ,117 + ,122 + ,2 + ,113 + ,112 + ,117 + ,2 + ,149 + ,113 + ,112 + ,2 + ,157 + ,149 + ,113 + ,2 + ,157 + ,157 + ,149 + ,2 + ,147 + ,157 + ,157 + ,2 + ,137 + ,147 + ,157 + ,2 + ,132 + ,137 + ,147 + ,2.21 + ,125 + ,132 + ,137 + ,2.25 + ,123 + ,125 + ,132 + ,2.25 + ,117 + ,123 + ,125 + ,2.45 + ,114 + ,117 + ,123 + ,2.5 + ,111 + ,114 + ,117 + ,2.5 + ,112 + ,111 + ,114 + ,2.64 + ,144 + ,112 + ,111 + ,2.75 + ,150 + ,144 + ,112 + ,2.93 + ,149 + ,150 + ,144 + ,3 + ,134 + ,149 + ,150 + ,3.17 + ,123 + ,134 + ,149 + ,3.25 + ,116 + ,123 + ,134 + ,3.39 + ,117 + ,116 + ,123 + ,3.5 + ,111 + ,117 + ,116 + ,3.5 + ,105 + ,111 + ,117 + ,3.65 + ,102 + ,105 + ,111 + ,3.75 + ,95 + ,102 + ,105 + ,3.75 + ,93 + ,95 + ,102 + ,3.9 + ,124 + ,93 + ,95 + ,4 + ,130 + ,124 + ,93 + ,4 + ,124 + ,130 + ,124 + ,4 + ,115 + ,124 + ,130 + ,4 + ,106 + ,115 + ,124 + ,4 + ,105 + ,106 + ,115 + ,4 + ,105 + ,105 + ,106 + ,4 + ,101 + ,105 + ,105 + ,4 + ,95 + ,101 + ,105 + ,4 + ,93 + ,95 + ,101 + ,4 + ,84 + ,93 + ,95 + ,4 + ,87 + ,84 + ,93 + ,4 + ,116 + ,87 + ,84 + ,4.18 + ,120 + ,116 + ,87 + ,4.25 + ,117 + ,120 + ,116 + ,4.25 + ,109 + ,117 + ,120 + ,3.97 + ,105 + ,109 + ,117 + ,3.42 + ,107 + ,105 + ,109 + ,2.75) + ,dim=c(2 + ,72) + ,dimnames=list(c('Werkloosheid' + ,'Rente') + ,1:72)) > y <- array(NA,dim=c(2,72),dimnames=list(c('Werkloosheid','Rente'),1:72)) > 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 Werkloosheid Rente M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 127.00 2.75 1 0 0 0 0 0 0 0 0 0 0 1 2 123.00 127.00 0 1 0 0 0 0 0 0 0 0 0 2 3 2.75 118.00 0 0 1 0 0 0 0 0 0 0 0 3 4 123.00 127.00 0 0 0 1 0 0 0 0 0 0 0 4 5 2.55 114.00 0 0 0 0 1 0 0 0 0 0 0 5 6 118.00 123.00 0 0 0 0 0 1 0 0 0 0 0 6 7 2.50 108.00 0 0 0 0 0 0 1 0 0 0 0 7 8 114.00 118.00 0 0 0 0 0 0 0 1 0 0 0 8 9 2.50 111.00 0 0 0 0 0 0 0 0 1 0 0 9 10 108.00 114.00 0 0 0 0 0 0 0 0 0 1 0 10 11 2.10 151.00 0 0 0 0 0 0 0 0 0 0 1 11 12 111.00 108.00 0 0 0 0 0 0 0 0 0 0 0 12 13 2.00 159.00 1 0 0 0 0 0 0 0 0 0 0 13 14 151.00 111.00 0 1 0 0 0 0 0 0 0 0 0 14 15 2.00 158.00 0 0 1 0 0 0 0 0 0 0 0 15 16 159.00 151.00 0 0 0 1 0 0 0 0 0 0 0 16 17 2.00 148.00 0 0 0 0 1 0 0 0 0 0 0 17 18 158.00 159.00 0 0 0 0 0 1 0 0 0 0 0 18 19 2.00 138.00 0 0 0 0 0 0 1 0 0 0 0 19 20 148.00 158.00 0 0 0 0 0 0 0 1 0 0 0 20 21 2.00 137.00 0 0 0 0 0 0 0 0 1 0 0 21 22 138.00 148.00 0 0 0 0 0 0 0 0 0 1 0 22 23 2.00 136.00 0 0 0 0 0 0 0 0 0 0 1 23 24 137.00 138.00 0 0 0 0 0 0 0 0 0 0 0 24 25 2.00 133.00 1 0 0 0 0 0 0 0 0 0 0 25 26 136.00 137.00 0 1 0 0 0 0 0 0 0 0 0 26 27 2.00 126.00 0 0 1 0 0 0 0 0 0 0 0 27 28 133.00 136.00 0 0 0 1 0 0 0 0 0 0 0 28 29 2.00 120.00 0 0 0 0 1 0 0 0 0 0 0 29 30 126.00 133.00 0 0 0 0 0 1 0 0 0 0 0 30 31 2.00 114.00 0 0 0 0 0 0 1 0 0 0 0 31 32 120.00 126.00 0 0 0 0 0 0 0 1 0 0 0 32 33 2.00 116.00 0 0 0 0 0 0 0 0 1 0 0 33 34 114.00 120.00 0 0 0 0 0 0 0 0 0 1 0 34 35 2.00 153.00 0 0 0 0 0 0 0 0 0 0 1 35 36 116.00 114.00 0 0 0 0 0 0 0 0 0 0 0 36 37 2.00 162.00 1 0 0 0 0 0 0 0 0 0 0 37 38 153.00 116.00 0 1 0 0 0 0 0 0 0 0 0 38 39 2.00 161.00 0 0 1 0 0 0 0 0 0 0 0 39 40 162.00 153.00 0 0 0 1 0 0 0 0 0 0 0 40 41 2.00 149.00 0 0 0 0 1 0 0 0 0 0 0 41 42 161.00 162.00 0 0 0 0 0 1 0 0 0 0 0 42 43 2.00 139.00 0 0 0 0 0 0 1 0 0 0 0 43 44 149.00 161.00 0 0 0 0 0 0 0 1 0 0 0 44 45 2.00 135.00 0 0 0 0 0 0 0 0 1 0 0 45 46 139.00 149.00 0 0 0 0 0 0 0 0 0 1 0 46 47 2.00 130.00 0 0 0 0 0 0 0 0 0 0 1 47 48 135.00 139.00 0 0 0 0 0 0 0 0 0 0 0 48 49 2.00 127.00 1 0 0 0 0 0 0 0 0 0 0 49 50 130.00 135.00 0 1 0 0 0 0 0 0 0 0 0 50 51 2.00 122.00 0 0 1 0 0 0 0 0 0 0 0 51 52 127.00 130.00 0 0 0 1 0 0 0 0 0 0 0 52 53 2.00 117.00 0 0 0 0 1 0 0 0 0 0 0 53 54 122.00 127.00 0 0 0 0 0 1 0 0 0 0 0 54 55 2.00 112.00 0 0 0 0 0 0 1 0 0 0 0 55 56 117.00 122.00 0 0 0 0 0 0 0 1 0 0 0 56 57 2.00 113.00 0 0 0 0 0 0 0 0 1 0 0 57 58 112.00 117.00 0 0 0 0 0 0 0 0 0 1 0 58 59 2.00 149.00 0 0 0 0 0 0 0 0 0 0 1 59 60 113.00 112.00 0 0 0 0 0 0 0 0 0 0 0 60 61 2.00 157.00 1 0 0 0 0 0 0 0 0 0 0 61 62 149.00 113.00 0 1 0 0 0 0 0 0 0 0 0 62 63 2.00 157.00 0 0 1 0 0 0 0 0 0 0 0 63 64 157.00 149.00 0 0 0 1 0 0 0 0 0 0 0 64 65 2.00 147.00 0 0 0 0 1 0 0 0 0 0 0 65 66 157.00 157.00 0 0 0 0 0 1 0 0 0 0 0 66 67 2.00 137.00 0 0 0 0 0 0 1 0 0 0 0 67 68 147.00 157.00 0 0 0 0 0 0 0 1 0 0 0 68 69 2.00 132.00 0 0 0 0 0 0 0 0 1 0 0 69 70 137.00 147.00 0 0 0 0 0 0 0 0 0 1 0 70 71 2.21 125.00 0 0 0 0 0 0 0 0 0 0 1 71 72 132.00 137.00 0 0 0 0 0 0 0 0 0 0 0 72 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Rente M1 M2 M3 M4 158.51930 -0.29988 -100.77832 16.56597 -116.56259 24.94409 M5 M6 M7 M8 M9 M10 -119.08151 22.39064 -121.57544 13.47118 -121.91185 3.15226 M11 t -117.08193 0.06825 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -26.4336 -10.9895 -0.8286 6.8627 70.0155 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 158.51930 14.25391 11.121 5.23e-16 *** Rente -0.29988 0.10234 -2.930 0.00484 ** M1 -100.77832 10.23514 -9.846 5.49e-14 *** M2 16.56597 10.22366 1.620 0.11058 M3 -116.56259 10.38171 -11.228 3.57e-16 *** M4 24.94409 10.38045 2.403 0.01948 * M5 -119.08151 10.24638 -11.622 < 2e-16 *** M6 22.39064 10.40478 2.152 0.03558 * M7 -121.57544 10.18606 -11.935 < 2e-16 *** M8 13.47118 10.32455 1.305 0.19712 M9 -121.91185 10.17699 -11.979 < 2e-16 *** M10 3.15226 10.21067 0.309 0.75864 M11 -117.08193 10.30849 -11.358 2.25e-16 *** t 0.06825 0.10534 0.648 0.51964 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 17.62 on 58 degrees of freedom Multiple R-squared: 0.9443, Adjusted R-squared: 0.9318 F-statistic: 75.58 on 13 and 58 DF, p-value: < 2.2e-16 > 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,] 0.9223422 1.553155e-01 7.765777e-02 [2,] 0.9923620 1.527593e-02 7.637967e-03 [3,] 0.9865429 2.691429e-02 1.345714e-02 [4,] 0.9952074 9.585300e-03 4.792650e-03 [5,] 0.9936976 1.260478e-02 6.302388e-03 [6,] 0.9934975 1.300493e-02 6.502466e-03 [7,] 0.9995000 1.000015e-03 5.000075e-04 [8,] 0.9993234 1.353140e-03 6.765698e-04 [9,] 0.9999891 2.170225e-05 1.085112e-05 [10,] 0.9999872 2.563268e-05 1.281634e-05 [11,] 0.9999921 1.588567e-05 7.942837e-06 [12,] 0.9999921 1.579527e-05 7.897637e-06 [13,] 0.9999881 2.386457e-05 1.193229e-05 [14,] 0.9999881 2.386576e-05 1.193288e-05 [15,] 0.9999764 4.716911e-05 2.358456e-05 [16,] 0.9999636 7.289218e-05 3.644609e-05 [17,] 0.9999203 1.594920e-04 7.974602e-05 [18,] 0.9998569 2.861150e-04 1.430575e-04 [19,] 0.9997046 5.907126e-04 2.953563e-04 [20,] 0.9994260 1.147996e-03 5.739982e-04 [21,] 0.9990092 1.981598e-03 9.907989e-04 [22,] 0.9988932 2.213553e-03 1.106777e-03 [23,] 0.9981586 3.682818e-03 1.841409e-03 [24,] 0.9982203 3.559329e-03 1.779664e-03 [25,] 0.9966519 6.696143e-03 3.348071e-03 [26,] 0.9969175 6.164901e-03 3.082451e-03 [27,] 0.9938666 1.226680e-02 6.133398e-03 [28,] 0.9920155 1.596891e-02 7.984453e-03 [29,] 0.9843637 3.127268e-02 1.563634e-02 [30,] 0.9795031 4.099383e-02 2.049691e-02 [31,] 0.9681663 6.366740e-02 3.183370e-02 [32,] 0.9746798 5.064046e-02 2.532023e-02 [33,] 0.9728208 5.435834e-02 2.717917e-02 [34,] 0.9596212 8.075756e-02 4.037878e-02 [35,] 0.9568137 8.637269e-02 4.318634e-02 [36,] 0.9489842 1.020317e-01 5.101584e-02 [37,] 0.9454378 1.091243e-01 5.456216e-02 [38,] 0.9367270 1.265460e-01 6.327302e-02 [39,] 0.9298628 1.402744e-01 7.013720e-02 > postscript(file="/var/www/html/rcomp/tmp/10l5v1258711900.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2p7ap1258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/36qx21258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4vh171258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/58d441258711900.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 = 72 Frequency = 1 1 2 3 4 5 6 70.0154549 -14.1363850 -4.0250388 -22.6509983 -3.0421468 -26.4335832 7 8 9 10 11 12 -2.5340246 -23.1500388 -1.4344468 -20.1671468 5.1945332 -15.9506913 13 14 15 16 17 18 -8.9464918 8.2465014 6.4013996 19.7272824 5.7849825 23.5433158 19 20 21 22 23 24 5.1435653 22.0263996 5.0436036 19.2099825 -0.2226955 18.2268986 25 26 27 28 29 30 -17.5624540 0.2245518 -4.0138717 -11.5899464 -3.4307495 -17.0726464 31 32 33 34 35 36 -2.8726272 -16.3888717 -2.0729343 -14.0057495 4.0563912 -10.7892939 37 38 39 40 41 42 -9.6847490 10.1080139 5.6631425 21.6891404 4.4469556 25.8050586 43 44 45 46 47 48 3.8055384 22.2881425 2.8059222 18.8719556 -3.6599164 14.8888717 49 50 51 52 53 54 -20.9996749 -8.0131297 -6.8513229 -21.0271673 -5.9683158 -24.5098673 55 56 57 58 59 60 -5.1103087 -22.2263229 -4.6105006 -18.5433158 1.2189400 -16.0269754 61 62 63 64 65 66 -12.8220851 3.5704476 2.8256913 13.8516892 2.2092741 18.6677226 67 68 69 70 71 72 1.5678569 17.4506913 0.2683558 14.6342741 -6.5872525 9.6511902 > postscript(file="/var/www/html/rcomp/tmp/68bvi1258711900.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 = 72 Frequency = 1 lag(myerror, k = 1) myerror 0 70.0154549 NA 1 -14.1363850 70.0154549 2 -4.0250388 -14.1363850 3 -22.6509983 -4.0250388 4 -3.0421468 -22.6509983 5 -26.4335832 -3.0421468 6 -2.5340246 -26.4335832 7 -23.1500388 -2.5340246 8 -1.4344468 -23.1500388 9 -20.1671468 -1.4344468 10 5.1945332 -20.1671468 11 -15.9506913 5.1945332 12 -8.9464918 -15.9506913 13 8.2465014 -8.9464918 14 6.4013996 8.2465014 15 19.7272824 6.4013996 16 5.7849825 19.7272824 17 23.5433158 5.7849825 18 5.1435653 23.5433158 19 22.0263996 5.1435653 20 5.0436036 22.0263996 21 19.2099825 5.0436036 22 -0.2226955 19.2099825 23 18.2268986 -0.2226955 24 -17.5624540 18.2268986 25 0.2245518 -17.5624540 26 -4.0138717 0.2245518 27 -11.5899464 -4.0138717 28 -3.4307495 -11.5899464 29 -17.0726464 -3.4307495 30 -2.8726272 -17.0726464 31 -16.3888717 -2.8726272 32 -2.0729343 -16.3888717 33 -14.0057495 -2.0729343 34 4.0563912 -14.0057495 35 -10.7892939 4.0563912 36 -9.6847490 -10.7892939 37 10.1080139 -9.6847490 38 5.6631425 10.1080139 39 21.6891404 5.6631425 40 4.4469556 21.6891404 41 25.8050586 4.4469556 42 3.8055384 25.8050586 43 22.2881425 3.8055384 44 2.8059222 22.2881425 45 18.8719556 2.8059222 46 -3.6599164 18.8719556 47 14.8888717 -3.6599164 48 -20.9996749 14.8888717 49 -8.0131297 -20.9996749 50 -6.8513229 -8.0131297 51 -21.0271673 -6.8513229 52 -5.9683158 -21.0271673 53 -24.5098673 -5.9683158 54 -5.1103087 -24.5098673 55 -22.2263229 -5.1103087 56 -4.6105006 -22.2263229 57 -18.5433158 -4.6105006 58 1.2189400 -18.5433158 59 -16.0269754 1.2189400 60 -12.8220851 -16.0269754 61 3.5704476 -12.8220851 62 2.8256913 3.5704476 63 13.8516892 2.8256913 64 2.2092741 13.8516892 65 18.6677226 2.2092741 66 1.5678569 18.6677226 67 17.4506913 1.5678569 68 0.2683558 17.4506913 69 14.6342741 0.2683558 70 -6.5872525 14.6342741 71 9.6511902 -6.5872525 72 NA 9.6511902 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -14.1363850 70.0154549 [2,] -4.0250388 -14.1363850 [3,] -22.6509983 -4.0250388 [4,] -3.0421468 -22.6509983 [5,] -26.4335832 -3.0421468 [6,] -2.5340246 -26.4335832 [7,] -23.1500388 -2.5340246 [8,] -1.4344468 -23.1500388 [9,] -20.1671468 -1.4344468 [10,] 5.1945332 -20.1671468 [11,] -15.9506913 5.1945332 [12,] -8.9464918 -15.9506913 [13,] 8.2465014 -8.9464918 [14,] 6.4013996 8.2465014 [15,] 19.7272824 6.4013996 [16,] 5.7849825 19.7272824 [17,] 23.5433158 5.7849825 [18,] 5.1435653 23.5433158 [19,] 22.0263996 5.1435653 [20,] 5.0436036 22.0263996 [21,] 19.2099825 5.0436036 [22,] -0.2226955 19.2099825 [23,] 18.2268986 -0.2226955 [24,] -17.5624540 18.2268986 [25,] 0.2245518 -17.5624540 [26,] -4.0138717 0.2245518 [27,] -11.5899464 -4.0138717 [28,] -3.4307495 -11.5899464 [29,] -17.0726464 -3.4307495 [30,] -2.8726272 -17.0726464 [31,] -16.3888717 -2.8726272 [32,] -2.0729343 -16.3888717 [33,] -14.0057495 -2.0729343 [34,] 4.0563912 -14.0057495 [35,] -10.7892939 4.0563912 [36,] -9.6847490 -10.7892939 [37,] 10.1080139 -9.6847490 [38,] 5.6631425 10.1080139 [39,] 21.6891404 5.6631425 [40,] 4.4469556 21.6891404 [41,] 25.8050586 4.4469556 [42,] 3.8055384 25.8050586 [43,] 22.2881425 3.8055384 [44,] 2.8059222 22.2881425 [45,] 18.8719556 2.8059222 [46,] -3.6599164 18.8719556 [47,] 14.8888717 -3.6599164 [48,] -20.9996749 14.8888717 [49,] -8.0131297 -20.9996749 [50,] -6.8513229 -8.0131297 [51,] -21.0271673 -6.8513229 [52,] -5.9683158 -21.0271673 [53,] -24.5098673 -5.9683158 [54,] -5.1103087 -24.5098673 [55,] -22.2263229 -5.1103087 [56,] -4.6105006 -22.2263229 [57,] -18.5433158 -4.6105006 [58,] 1.2189400 -18.5433158 [59,] -16.0269754 1.2189400 [60,] -12.8220851 -16.0269754 [61,] 3.5704476 -12.8220851 [62,] 2.8256913 3.5704476 [63,] 13.8516892 2.8256913 [64,] 2.2092741 13.8516892 [65,] 18.6677226 2.2092741 [66,] 1.5678569 18.6677226 [67,] 17.4506913 1.5678569 [68,] 0.2683558 17.4506913 [69,] 14.6342741 0.2683558 [70,] -6.5872525 14.6342741 [71,] 9.6511902 -6.5872525 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -14.1363850 70.0154549 2 -4.0250388 -14.1363850 3 -22.6509983 -4.0250388 4 -3.0421468 -22.6509983 5 -26.4335832 -3.0421468 6 -2.5340246 -26.4335832 7 -23.1500388 -2.5340246 8 -1.4344468 -23.1500388 9 -20.1671468 -1.4344468 10 5.1945332 -20.1671468 11 -15.9506913 5.1945332 12 -8.9464918 -15.9506913 13 8.2465014 -8.9464918 14 6.4013996 8.2465014 15 19.7272824 6.4013996 16 5.7849825 19.7272824 17 23.5433158 5.7849825 18 5.1435653 23.5433158 19 22.0263996 5.1435653 20 5.0436036 22.0263996 21 19.2099825 5.0436036 22 -0.2226955 19.2099825 23 18.2268986 -0.2226955 24 -17.5624540 18.2268986 25 0.2245518 -17.5624540 26 -4.0138717 0.2245518 27 -11.5899464 -4.0138717 28 -3.4307495 -11.5899464 29 -17.0726464 -3.4307495 30 -2.8726272 -17.0726464 31 -16.3888717 -2.8726272 32 -2.0729343 -16.3888717 33 -14.0057495 -2.0729343 34 4.0563912 -14.0057495 35 -10.7892939 4.0563912 36 -9.6847490 -10.7892939 37 10.1080139 -9.6847490 38 5.6631425 10.1080139 39 21.6891404 5.6631425 40 4.4469556 21.6891404 41 25.8050586 4.4469556 42 3.8055384 25.8050586 43 22.2881425 3.8055384 44 2.8059222 22.2881425 45 18.8719556 2.8059222 46 -3.6599164 18.8719556 47 14.8888717 -3.6599164 48 -20.9996749 14.8888717 49 -8.0131297 -20.9996749 50 -6.8513229 -8.0131297 51 -21.0271673 -6.8513229 52 -5.9683158 -21.0271673 53 -24.5098673 -5.9683158 54 -5.1103087 -24.5098673 55 -22.2263229 -5.1103087 56 -4.6105006 -22.2263229 57 -18.5433158 -4.6105006 58 1.2189400 -18.5433158 59 -16.0269754 1.2189400 60 -12.8220851 -16.0269754 61 3.5704476 -12.8220851 62 2.8256913 3.5704476 63 13.8516892 2.8256913 64 2.2092741 13.8516892 65 18.6677226 2.2092741 66 1.5678569 18.6677226 67 17.4506913 1.5678569 68 0.2683558 17.4506913 69 14.6342741 0.2683558 70 -6.5872525 14.6342741 71 9.6511902 -6.5872525 > 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/7mubj1258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8gbec1258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9zhp01258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10x8jv1258711900.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11h63j1258711900.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/12dt551258711900.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/13ux3w1258711901.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/14tcfj1258711901.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/156heo1258711901.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/16p0s91258711901.tab") + } > > system("convert tmp/10l5v1258711900.ps tmp/10l5v1258711900.png") > system("convert tmp/2p7ap1258711900.ps tmp/2p7ap1258711900.png") > system("convert tmp/36qx21258711900.ps tmp/36qx21258711900.png") > system("convert tmp/4vh171258711900.ps tmp/4vh171258711900.png") > system("convert tmp/58d441258711900.ps tmp/58d441258711900.png") > system("convert tmp/68bvi1258711900.ps tmp/68bvi1258711900.png") > system("convert tmp/7mubj1258711900.ps tmp/7mubj1258711900.png") > system("convert tmp/8gbec1258711900.ps tmp/8gbec1258711900.png") > system("convert tmp/9zhp01258711900.ps tmp/9zhp01258711900.png") > system("convert tmp/10x8jv1258711900.ps tmp/10x8jv1258711900.png") > > > proc.time() user system elapsed 2.505 1.541 3.053