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Type 'q()' to quit R. > x <- array(list(112.3 + ,0 + ,117.2 + ,96.8 + ,117.3 + ,0 + ,112.3 + ,117.2 + ,111.1 + ,1 + ,117.3 + ,112.3 + ,102.2 + ,1 + ,111.1 + ,117.3 + ,104.3 + ,1 + ,102.2 + ,111.1 + ,122.9 + ,1 + ,104.3 + ,102.2 + ,107.6 + ,1 + ,122.9 + ,104.3 + ,121.3 + ,1 + ,107.6 + ,122.9 + ,131.5 + ,1 + ,121.3 + ,107.6 + ,89 + ,1 + ,131.5 + ,121.3 + ,104.4 + ,1 + ,89 + ,131.5 + ,128.9 + ,1 + ,104.4 + ,89 + ,135.9 + ,1 + ,128.9 + ,104.4 + ,133.3 + ,1 + ,135.9 + ,128.9 + ,121.3 + ,1 + ,133.3 + ,135.9 + ,120.5 + ,0 + ,121.3 + ,133.3 + ,120.4 + ,0 + ,120.5 + ,121.3 + ,137.9 + ,0 + ,120.4 + ,120.5 + ,126.1 + ,0 + ,137.9 + ,120.4 + ,133.2 + ,0 + ,126.1 + ,137.9 + ,151.1 + ,0 + ,133.2 + ,126.1 + ,105 + ,0 + ,151.1 + ,133.2 + ,119 + ,0 + ,105 + ,151.1 + ,140.4 + ,0 + ,119 + ,105 + ,156.6 + ,0 + ,140.4 + ,119 + ,137.1 + ,0 + ,156.6 + ,140.4 + ,122.7 + ,0 + ,137.1 + ,156.6 + ,125.8 + ,0 + ,122.7 + ,137.1 + ,139.3 + ,0 + ,125.8 + ,122.7 + ,134.9 + ,0 + ,139.3 + ,125.8 + ,149.2 + ,0 + ,134.9 + ,139.3 + ,132.3 + ,0 + ,149.2 + ,134.9 + ,149 + ,0 + ,132.3 + ,149.2 + ,117.2 + ,0 + ,149 + ,132.3 + ,119.6 + ,0 + ,117.2 + ,149 + ,152 + ,0 + ,119.6 + ,117.2 + ,149.4 + ,0 + ,152 + ,119.6 + ,127.3 + ,0 + ,149.4 + ,152 + ,114.1 + ,0 + ,127.3 + ,149.4 + ,102.1 + ,0 + ,114.1 + ,127.3 + ,107.7 + ,0 + ,102.1 + ,114.1 + ,104.4 + ,0 + ,107.7 + ,102.1 + ,102.1 + ,0 + ,104.4 + ,107.7 + ,96 + ,1 + ,102.1 + ,104.4 + ,109.3 + ,0 + ,96 + ,102.1 + ,90 + ,1 + ,109.3 + ,96 + ,83.9 + ,1 + ,90 + ,109.3 + ,112 + ,1 + ,83.9 + ,90 + ,114.3 + ,1 + ,112 + ,83.9 + ,103.6 + ,1 + ,114.3 + ,112 + ,91.7 + ,1 + ,103.6 + ,114.3 + ,80.8 + ,1 + ,91.7 + ,103.6 + ,87.2 + ,1 + ,80.8 + ,91.7 + ,109.2 + ,1 + ,87.2 + ,80.8 + ,102.7 + ,1 + ,109.2 + ,87.2 + ,95.1 + ,1 + ,102.7 + ,109.2 + ,117.5 + ,1 + ,95.1 + ,102.7 + ,85.1 + ,1 + ,117.5 + ,95.1 + ,92.1 + ,1 + ,85.1 + ,117.5 + ,113.5 + ,1 + ,92.1 + ,85.1) + ,dim=c(4 + ,60) + ,dimnames=list(c('X' + ,'Y' + ,'y(t)' + ,'y(t-1)') + ,1:60)) > y <- array(NA,dim=c(4,60),dimnames=list(c('X','Y','y(t)','y(t-1)'),1:60)) > 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' > library(lattice) > library(lmtest) Loading required package: zoo > 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) M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 112.3 0 117.2 96.8 1 0 0 0 0 0 0 0 0 0 0 1 2 117.3 0 112.3 117.2 0 1 0 0 0 0 0 0 0 0 0 2 3 111.1 1 117.3 112.3 0 0 1 0 0 0 0 0 0 0 0 3 4 102.2 1 111.1 117.3 0 0 0 1 0 0 0 0 0 0 0 4 5 104.3 1 102.2 111.1 0 0 0 0 1 0 0 0 0 0 0 5 6 122.9 1 104.3 102.2 0 0 0 0 0 1 0 0 0 0 0 6 7 107.6 1 122.9 104.3 0 0 0 0 0 0 1 0 0 0 0 7 8 121.3 1 107.6 122.9 0 0 0 0 0 0 0 1 0 0 0 8 9 131.5 1 121.3 107.6 0 0 0 0 0 0 0 0 1 0 0 9 10 89.0 1 131.5 121.3 0 0 0 0 0 0 0 0 0 1 0 10 11 104.4 1 89.0 131.5 0 0 0 0 0 0 0 0 0 0 1 11 12 128.9 1 104.4 89.0 0 0 0 0 0 0 0 0 0 0 0 12 13 135.9 1 128.9 104.4 1 0 0 0 0 0 0 0 0 0 0 13 14 133.3 1 135.9 128.9 0 1 0 0 0 0 0 0 0 0 0 14 15 121.3 1 133.3 135.9 0 0 1 0 0 0 0 0 0 0 0 15 16 120.5 0 121.3 133.3 0 0 0 1 0 0 0 0 0 0 0 16 17 120.4 0 120.5 121.3 0 0 0 0 1 0 0 0 0 0 0 17 18 137.9 0 120.4 120.5 0 0 0 0 0 1 0 0 0 0 0 18 19 126.1 0 137.9 120.4 0 0 0 0 0 0 1 0 0 0 0 19 20 133.2 0 126.1 137.9 0 0 0 0 0 0 0 1 0 0 0 20 21 151.1 0 133.2 126.1 0 0 0 0 0 0 0 0 1 0 0 21 22 105.0 0 151.1 133.2 0 0 0 0 0 0 0 0 0 1 0 22 23 119.0 0 105.0 151.1 0 0 0 0 0 0 0 0 0 0 1 23 24 140.4 0 119.0 105.0 0 0 0 0 0 0 0 0 0 0 0 24 25 156.6 0 140.4 119.0 1 0 0 0 0 0 0 0 0 0 0 25 26 137.1 0 156.6 140.4 0 1 0 0 0 0 0 0 0 0 0 26 27 122.7 0 137.1 156.6 0 0 1 0 0 0 0 0 0 0 0 27 28 125.8 0 122.7 137.1 0 0 0 1 0 0 0 0 0 0 0 28 29 139.3 0 125.8 122.7 0 0 0 0 1 0 0 0 0 0 0 29 30 134.9 0 139.3 125.8 0 0 0 0 0 1 0 0 0 0 0 30 31 149.2 0 134.9 139.3 0 0 0 0 0 0 1 0 0 0 0 31 32 132.3 0 149.2 134.9 0 0 0 0 0 0 0 1 0 0 0 32 33 149.0 0 132.3 149.2 0 0 0 0 0 0 0 0 1 0 0 33 34 117.2 0 149.0 132.3 0 0 0 0 0 0 0 0 0 1 0 34 35 119.6 0 117.2 149.0 0 0 0 0 0 0 0 0 0 0 1 35 36 152.0 0 119.6 117.2 0 0 0 0 0 0 0 0 0 0 0 36 37 149.4 0 152.0 119.6 1 0 0 0 0 0 0 0 0 0 0 37 38 127.3 0 149.4 152.0 0 1 0 0 0 0 0 0 0 0 0 38 39 114.1 0 127.3 149.4 0 0 1 0 0 0 0 0 0 0 0 39 40 102.1 0 114.1 127.3 0 0 0 1 0 0 0 0 0 0 0 40 41 107.7 0 102.1 114.1 0 0 0 0 1 0 0 0 0 0 0 41 42 104.4 0 107.7 102.1 0 0 0 0 0 1 0 0 0 0 0 42 43 102.1 0 104.4 107.7 0 0 0 0 0 0 1 0 0 0 0 43 44 96.0 1 102.1 104.4 0 0 0 0 0 0 0 1 0 0 0 44 45 109.3 0 96.0 102.1 0 0 0 0 0 0 0 0 1 0 0 45 46 90.0 1 109.3 96.0 0 0 0 0 0 0 0 0 0 1 0 46 47 83.9 1 90.0 109.3 0 0 0 0 0 0 0 0 0 0 1 47 48 112.0 1 83.9 90.0 0 0 0 0 0 0 0 0 0 0 0 48 49 114.3 1 112.0 83.9 1 0 0 0 0 0 0 0 0 0 0 49 50 103.6 1 114.3 112.0 0 1 0 0 0 0 0 0 0 0 0 50 51 91.7 1 103.6 114.3 0 0 1 0 0 0 0 0 0 0 0 51 52 80.8 1 91.7 103.6 0 0 0 1 0 0 0 0 0 0 0 52 53 87.2 1 80.8 91.7 0 0 0 0 1 0 0 0 0 0 0 53 54 109.2 1 87.2 80.8 0 0 0 0 0 1 0 0 0 0 0 54 55 102.7 1 109.2 87.2 0 0 0 0 0 0 1 0 0 0 0 55 56 95.1 1 102.7 109.2 0 0 0 0 0 0 0 1 0 0 0 56 57 117.5 1 95.1 102.7 0 0 0 0 0 0 0 0 1 0 0 57 58 85.1 1 117.5 95.1 0 0 0 0 0 0 0 0 0 1 0 58 59 92.1 1 85.1 117.5 0 0 0 0 0 0 0 0 0 0 1 59 60 113.5 1 92.1 85.1 0 0 0 0 0 0 0 0 0 0 0 60 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Y `y(t)` `y(t-1)` M1 M2 39.57185 1.44282 0.46265 0.45684 -12.03576 -35.16856 M3 M4 M5 M6 M7 M8 -43.92633 -39.54141 -25.94174 -15.61285 -27.01085 -31.76754 M9 M10 M11 t -12.40052 -53.56424 -38.35671 -0.09813 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -13.7221 -4.3546 -0.5014 5.0563 14.2602 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 39.57185 14.91699 2.653 0.01106 * Y 1.44282 3.35206 0.430 0.66899 `y(t)` 0.46265 0.13452 3.439 0.00129 ** `y(t-1)` 0.45684 0.15540 2.940 0.00522 ** M1 -12.03576 5.67362 -2.121 0.03956 * M2 -35.16856 5.87623 -5.985 3.55e-07 *** M3 -43.92633 6.51312 -6.744 2.71e-08 *** M4 -39.54141 5.82835 -6.784 2.37e-08 *** M5 -25.94174 5.31775 -4.878 1.44e-05 *** M6 -15.61285 5.04665 -3.094 0.00343 ** M7 -27.01085 5.19111 -5.203 4.91e-06 *** M8 -31.76754 5.75193 -5.523 1.69e-06 *** M9 -12.40052 5.35011 -2.318 0.02517 * M10 -53.56424 5.69895 -9.399 4.36e-12 *** M11 -38.35671 7.79401 -4.921 1.25e-05 *** t -0.09813 0.06734 -1.457 0.15212 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 7.917 on 44 degrees of freedom Multiple R-squared: 0.8701, Adjusted R-squared: 0.8258 F-statistic: 19.65 on 15 and 44 DF, p-value: 1.038e-14 > 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)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.0103166246 0.0206332492 0.98968338 [2,] 0.0043575352 0.0087150703 0.99564246 [3,] 0.0020285676 0.0040571352 0.99797143 [4,] 0.0009449645 0.0018899289 0.99905504 [5,] 0.0002091860 0.0004183721 0.99979081 [6,] 0.0003681085 0.0007362169 0.99963189 [7,] 0.0001345388 0.0002690776 0.99986546 [8,] 0.0011168879 0.0022337759 0.99888311 [9,] 0.0781291570 0.1562583140 0.92187084 [10,] 0.2216972725 0.4433945450 0.77830273 [11,] 0.2372747286 0.4745494572 0.76272527 [12,] 0.5147635554 0.9704728893 0.48523644 [13,] 0.6017481221 0.7965037557 0.39825188 [14,] 0.5741346903 0.8517306194 0.42586531 [15,] 0.6680146331 0.6639707338 0.33198537 [16,] 0.5762489459 0.8475021082 0.42375105 [17,] 0.5133391396 0.9733217208 0.48666086 [18,] 0.6556826876 0.6886346249 0.34431731 [19,] 0.6341537401 0.7316925198 0.36584626 [20,] 0.7139558512 0.5720882975 0.28604415 [21,] 0.6656465654 0.6687068693 0.33435343 [22,] 0.6565966518 0.6868066963 0.34340335 [23,] 0.9487824658 0.1024350685 0.05121753 > postscript(file="/var/wessaorg/rcomp/tmp/1y08f1322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2viks1322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3yzp41322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4vqq11322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5xla51322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 60 Frequency = 1 1 2 3 4 5 6 -13.58253732 7.59591276 8.73424179 -3.86829598 -8.31984807 3.14367797 7 8 9 10 11 12 -10.22487101 6.91136245 -1.50626343 -13.72211467 1.57144807 0.10359285 13 14 15 16 17 18 0.86723436 7.06709767 1.92804726 5.02367085 -2.72570857 4.95527485 19 20 21 22 23 24 -3.39931657 6.02015581 6.75710376 -9.60604478 2.43542253 0.15989168 25 26 27 28 29 30 12.19732509 -1.34301479 -5.26614639 9.11755792 14.26024429 -8.03249982 31 32 33 34 35 36 13.63200554 -3.01901255 -4.30185675 5.15425576 -0.47199398 7.08647260 37 38 39 40 41 42 0.53404081 -11.93364773 -4.86535616 -4.94905882 -1.26853394 -11.90809575 43 44 45 46 47 48 -3.74349809 -3.85983881 -4.51301225 12.63945844 -5.71669451 -4.23614522 49 50 51 52 53 54 -0.01606294 -1.38634791 -0.53078650 -5.32387398 -1.94615371 11.84164275 55 56 57 58 59 60 3.73568013 -6.05266691 3.56402867 5.53444526 2.18181788 -3.11381192 > postscript(file="/var/wessaorg/rcomp/tmp/65jn81322332338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 60 Frequency = 1 lag(myerror, k = 1) myerror 0 -13.58253732 NA 1 7.59591276 -13.58253732 2 8.73424179 7.59591276 3 -3.86829598 8.73424179 4 -8.31984807 -3.86829598 5 3.14367797 -8.31984807 6 -10.22487101 3.14367797 7 6.91136245 -10.22487101 8 -1.50626343 6.91136245 9 -13.72211467 -1.50626343 10 1.57144807 -13.72211467 11 0.10359285 1.57144807 12 0.86723436 0.10359285 13 7.06709767 0.86723436 14 1.92804726 7.06709767 15 5.02367085 1.92804726 16 -2.72570857 5.02367085 17 4.95527485 -2.72570857 18 -3.39931657 4.95527485 19 6.02015581 -3.39931657 20 6.75710376 6.02015581 21 -9.60604478 6.75710376 22 2.43542253 -9.60604478 23 0.15989168 2.43542253 24 12.19732509 0.15989168 25 -1.34301479 12.19732509 26 -5.26614639 -1.34301479 27 9.11755792 -5.26614639 28 14.26024429 9.11755792 29 -8.03249982 14.26024429 30 13.63200554 -8.03249982 31 -3.01901255 13.63200554 32 -4.30185675 -3.01901255 33 5.15425576 -4.30185675 34 -0.47199398 5.15425576 35 7.08647260 -0.47199398 36 0.53404081 7.08647260 37 -11.93364773 0.53404081 38 -4.86535616 -11.93364773 39 -4.94905882 -4.86535616 40 -1.26853394 -4.94905882 41 -11.90809575 -1.26853394 42 -3.74349809 -11.90809575 43 -3.85983881 -3.74349809 44 -4.51301225 -3.85983881 45 12.63945844 -4.51301225 46 -5.71669451 12.63945844 47 -4.23614522 -5.71669451 48 -0.01606294 -4.23614522 49 -1.38634791 -0.01606294 50 -0.53078650 -1.38634791 51 -5.32387398 -0.53078650 52 -1.94615371 -5.32387398 53 11.84164275 -1.94615371 54 3.73568013 11.84164275 55 -6.05266691 3.73568013 56 3.56402867 -6.05266691 57 5.53444526 3.56402867 58 2.18181788 5.53444526 59 -3.11381192 2.18181788 60 NA -3.11381192 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 7.59591276 -13.58253732 [2,] 8.73424179 7.59591276 [3,] -3.86829598 8.73424179 [4,] -8.31984807 -3.86829598 [5,] 3.14367797 -8.31984807 [6,] -10.22487101 3.14367797 [7,] 6.91136245 -10.22487101 [8,] -1.50626343 6.91136245 [9,] -13.72211467 -1.50626343 [10,] 1.57144807 -13.72211467 [11,] 0.10359285 1.57144807 [12,] 0.86723436 0.10359285 [13,] 7.06709767 0.86723436 [14,] 1.92804726 7.06709767 [15,] 5.02367085 1.92804726 [16,] -2.72570857 5.02367085 [17,] 4.95527485 -2.72570857 [18,] -3.39931657 4.95527485 [19,] 6.02015581 -3.39931657 [20,] 6.75710376 6.02015581 [21,] -9.60604478 6.75710376 [22,] 2.43542253 -9.60604478 [23,] 0.15989168 2.43542253 [24,] 12.19732509 0.15989168 [25,] -1.34301479 12.19732509 [26,] -5.26614639 -1.34301479 [27,] 9.11755792 -5.26614639 [28,] 14.26024429 9.11755792 [29,] -8.03249982 14.26024429 [30,] 13.63200554 -8.03249982 [31,] -3.01901255 13.63200554 [32,] -4.30185675 -3.01901255 [33,] 5.15425576 -4.30185675 [34,] -0.47199398 5.15425576 [35,] 7.08647260 -0.47199398 [36,] 0.53404081 7.08647260 [37,] -11.93364773 0.53404081 [38,] -4.86535616 -11.93364773 [39,] -4.94905882 -4.86535616 [40,] -1.26853394 -4.94905882 [41,] -11.90809575 -1.26853394 [42,] -3.74349809 -11.90809575 [43,] -3.85983881 -3.74349809 [44,] -4.51301225 -3.85983881 [45,] 12.63945844 -4.51301225 [46,] -5.71669451 12.63945844 [47,] -4.23614522 -5.71669451 [48,] -0.01606294 -4.23614522 [49,] -1.38634791 -0.01606294 [50,] -0.53078650 -1.38634791 [51,] -5.32387398 -0.53078650 [52,] -1.94615371 -5.32387398 [53,] 11.84164275 -1.94615371 [54,] 3.73568013 11.84164275 [55,] -6.05266691 3.73568013 [56,] 3.56402867 -6.05266691 [57,] 5.53444526 3.56402867 [58,] 2.18181788 5.53444526 [59,] -3.11381192 2.18181788 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 7.59591276 -13.58253732 2 8.73424179 7.59591276 3 -3.86829598 8.73424179 4 -8.31984807 -3.86829598 5 3.14367797 -8.31984807 6 -10.22487101 3.14367797 7 6.91136245 -10.22487101 8 -1.50626343 6.91136245 9 -13.72211467 -1.50626343 10 1.57144807 -13.72211467 11 0.10359285 1.57144807 12 0.86723436 0.10359285 13 7.06709767 0.86723436 14 1.92804726 7.06709767 15 5.02367085 1.92804726 16 -2.72570857 5.02367085 17 4.95527485 -2.72570857 18 -3.39931657 4.95527485 19 6.02015581 -3.39931657 20 6.75710376 6.02015581 21 -9.60604478 6.75710376 22 2.43542253 -9.60604478 23 0.15989168 2.43542253 24 12.19732509 0.15989168 25 -1.34301479 12.19732509 26 -5.26614639 -1.34301479 27 9.11755792 -5.26614639 28 14.26024429 9.11755792 29 -8.03249982 14.26024429 30 13.63200554 -8.03249982 31 -3.01901255 13.63200554 32 -4.30185675 -3.01901255 33 5.15425576 -4.30185675 34 -0.47199398 5.15425576 35 7.08647260 -0.47199398 36 0.53404081 7.08647260 37 -11.93364773 0.53404081 38 -4.86535616 -11.93364773 39 -4.94905882 -4.86535616 40 -1.26853394 -4.94905882 41 -11.90809575 -1.26853394 42 -3.74349809 -11.90809575 43 -3.85983881 -3.74349809 44 -4.51301225 -3.85983881 45 12.63945844 -4.51301225 46 -5.71669451 12.63945844 47 -4.23614522 -5.71669451 48 -0.01606294 -4.23614522 49 -1.38634791 -0.01606294 50 -0.53078650 -1.38634791 51 -5.32387398 -0.53078650 52 -1.94615371 -5.32387398 53 11.84164275 -1.94615371 54 3.73568013 11.84164275 55 -6.05266691 3.73568013 56 3.56402867 -6.05266691 57 5.53444526 3.56402867 58 2.18181788 5.53444526 59 -3.11381192 2.18181788 > 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/wessaorg/rcomp/tmp/7vbfn1322332338.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/8kasj1322332338.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/9b0y61322332338.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/10ijyh1322332338.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11inle1322332338.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12ebfb1322332338.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13xqg21322332338.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14a4b61322332338.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/wessaorg/rcomp/tmp/15fruz1322332338.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/wessaorg/rcomp/tmp/162mid1322332338.tab") + } > > try(system("convert tmp/1y08f1322332338.ps tmp/1y08f1322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/2viks1322332338.ps tmp/2viks1322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/3yzp41322332338.ps tmp/3yzp41322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/4vqq11322332338.ps tmp/4vqq11322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/5xla51322332338.ps tmp/5xla51322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/65jn81322332338.ps tmp/65jn81322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/7vbfn1322332338.ps tmp/7vbfn1322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/8kasj1322332338.ps tmp/8kasj1322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/9b0y61322332338.ps tmp/9b0y61322332338.png",intern=TRUE)) character(0) > try(system("convert tmp/10ijyh1322332338.ps tmp/10ijyh1322332338.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.150 0.499 3.692