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Type 'q()' to quit R. > x <- array(list(37,30,47,35,30,43,82,40,47,19,52,136,80,42,54,66,81,63,137,72,107,58,36,52,79,77,54,84,48,96,83,66,61,53,30,74,69,59,42,65,70,100,63,105,82,81,75,102,121,98,76,77,63,37,35,23,40,29,37,51,20,28,13,22,25,13,16,13,16,17,9,17,25,14,8,7,10,7,10,3),dim=c(1,80),dimnames=list(c('Death'),1:80)) > y <- array(NA,dim=c(1,80),dimnames=list(c('Death'),1:80)) > 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 > 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 Death M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 37 1 0 0 0 0 0 0 0 0 0 0 1 2 30 0 1 0 0 0 0 0 0 0 0 0 2 3 47 0 0 1 0 0 0 0 0 0 0 0 3 4 35 0 0 0 1 0 0 0 0 0 0 0 4 5 30 0 0 0 0 1 0 0 0 0 0 0 5 6 43 0 0 0 0 0 1 0 0 0 0 0 6 7 82 0 0 0 0 0 0 1 0 0 0 0 7 8 40 0 0 0 0 0 0 0 1 0 0 0 8 9 47 0 0 0 0 0 0 0 0 1 0 0 9 10 19 0 0 0 0 0 0 0 0 0 1 0 10 11 52 0 0 0 0 0 0 0 0 0 0 1 11 12 136 0 0 0 0 0 0 0 0 0 0 0 12 13 80 1 0 0 0 0 0 0 0 0 0 0 13 14 42 0 1 0 0 0 0 0 0 0 0 0 14 15 54 0 0 1 0 0 0 0 0 0 0 0 15 16 66 0 0 0 1 0 0 0 0 0 0 0 16 17 81 0 0 0 0 1 0 0 0 0 0 0 17 18 63 0 0 0 0 0 1 0 0 0 0 0 18 19 137 0 0 0 0 0 0 1 0 0 0 0 19 20 72 0 0 0 0 0 0 0 1 0 0 0 20 21 107 0 0 0 0 0 0 0 0 1 0 0 21 22 58 0 0 0 0 0 0 0 0 0 1 0 22 23 36 0 0 0 0 0 0 0 0 0 0 1 23 24 52 0 0 0 0 0 0 0 0 0 0 0 24 25 79 1 0 0 0 0 0 0 0 0 0 0 25 26 77 0 1 0 0 0 0 0 0 0 0 0 26 27 54 0 0 1 0 0 0 0 0 0 0 0 27 28 84 0 0 0 1 0 0 0 0 0 0 0 28 29 48 0 0 0 0 1 0 0 0 0 0 0 29 30 96 0 0 0 0 0 1 0 0 0 0 0 30 31 83 0 0 0 0 0 0 1 0 0 0 0 31 32 66 0 0 0 0 0 0 0 1 0 0 0 32 33 61 0 0 0 0 0 0 0 0 1 0 0 33 34 53 0 0 0 0 0 0 0 0 0 1 0 34 35 30 0 0 0 0 0 0 0 0 0 0 1 35 36 74 0 0 0 0 0 0 0 0 0 0 0 36 37 69 1 0 0 0 0 0 0 0 0 0 0 37 38 59 0 1 0 0 0 0 0 0 0 0 0 38 39 42 0 0 1 0 0 0 0 0 0 0 0 39 40 65 0 0 0 1 0 0 0 0 0 0 0 40 41 70 0 0 0 0 1 0 0 0 0 0 0 41 42 100 0 0 0 0 0 1 0 0 0 0 0 42 43 63 0 0 0 0 0 0 1 0 0 0 0 43 44 105 0 0 0 0 0 0 0 1 0 0 0 44 45 82 0 0 0 0 0 0 0 0 1 0 0 45 46 81 0 0 0 0 0 0 0 0 0 1 0 46 47 75 0 0 0 0 0 0 0 0 0 0 1 47 48 102 0 0 0 0 0 0 0 0 0 0 0 48 49 121 1 0 0 0 0 0 0 0 0 0 0 49 50 98 0 1 0 0 0 0 0 0 0 0 0 50 51 76 0 0 1 0 0 0 0 0 0 0 0 51 52 77 0 0 0 1 0 0 0 0 0 0 0 52 53 63 0 0 0 0 1 0 0 0 0 0 0 53 54 37 0 0 0 0 0 1 0 0 0 0 0 54 55 35 0 0 0 0 0 0 1 0 0 0 0 55 56 23 0 0 0 0 0 0 0 1 0 0 0 56 57 40 0 0 0 0 0 0 0 0 1 0 0 57 58 29 0 0 0 0 0 0 0 0 0 1 0 58 59 37 0 0 0 0 0 0 0 0 0 0 1 59 60 51 0 0 0 0 0 0 0 0 0 0 0 60 61 20 1 0 0 0 0 0 0 0 0 0 0 61 62 28 0 1 0 0 0 0 0 0 0 0 0 62 63 13 0 0 1 0 0 0 0 0 0 0 0 63 64 22 0 0 0 1 0 0 0 0 0 0 0 64 65 25 0 0 0 0 1 0 0 0 0 0 0 65 66 13 0 0 0 0 0 1 0 0 0 0 0 66 67 16 0 0 0 0 0 0 1 0 0 0 0 67 68 13 0 0 0 0 0 0 0 1 0 0 0 68 69 16 0 0 0 0 0 0 0 0 1 0 0 69 70 17 0 0 0 0 0 0 0 0 0 1 0 70 71 9 0 0 0 0 0 0 0 0 0 0 1 71 72 17 0 0 0 0 0 0 0 0 0 0 0 72 73 25 1 0 0 0 0 0 0 0 0 0 0 73 74 14 0 1 0 0 0 0 0 0 0 0 0 74 75 8 0 0 1 0 0 0 0 0 0 0 0 75 76 7 0 0 0 1 0 0 0 0 0 0 0 76 77 10 0 0 0 0 1 0 0 0 0 0 0 77 78 7 0 0 0 0 0 1 0 0 0 0 0 78 79 10 0 0 0 0 0 0 1 0 0 0 0 79 80 3 0 0 0 0 0 0 0 1 0 0 0 80 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) M1 M2 M3 M4 M5 99.3512 -13.6847 -24.8906 -31.9537 -22.4453 -25.9369 M6 M7 M8 M9 M10 M11 -20.7143 -10.4916 -24.6976 -15.1203 -30.4691 -32.8179 t -0.6512 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -48.02 -18.14 -5.00 14.19 67.24 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 99.3512 13.2048 7.524 1.74e-10 *** M1 -13.6847 16.1106 -0.849 0.3987 M2 -24.8906 16.1051 -1.546 0.1269 M3 -31.9537 16.1008 -1.985 0.0513 . M4 -22.4453 16.0977 -1.394 0.1678 M5 -25.9369 16.0959 -1.611 0.1118 M6 -20.7143 16.0953 -1.287 0.2025 M7 -10.4916 16.0959 -0.652 0.5167 M8 -24.6976 16.0977 -1.534 0.1297 M9 -15.1203 16.7082 -0.905 0.3687 M10 -30.4691 16.7052 -1.824 0.0726 . M11 -32.8179 16.7035 -1.965 0.0536 . t -0.6512 0.1406 -4.632 1.72e-05 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 28.93 on 67 degrees of freedom Multiple R-squared: 0.3033, Adjusted R-squared: 0.1785 F-statistic: 2.431 on 12 and 67 DF, p-value: 0.01096 > 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,] 0.13616995 2.723399e-01 8.638301e-01 [2,] 0.13275338 2.655068e-01 8.672466e-01 [3,] 0.07087295 1.417459e-01 9.291270e-01 [4,] 0.08484731 1.696946e-01 9.151527e-01 [5,] 0.04272494 8.544988e-02 9.572751e-01 [6,] 0.04882668 9.765335e-02 9.511733e-01 [7,] 0.02676174 5.352347e-02 9.732383e-01 [8,] 0.11529154 2.305831e-01 8.847085e-01 [9,] 0.85970358 2.805928e-01 1.402964e-01 [10,] 0.81951903 3.609619e-01 1.804810e-01 [11,] 0.76947399 4.610520e-01 2.305260e-01 [12,] 0.75731081 4.853784e-01 2.426892e-01 [13,] 0.68791046 6.241791e-01 3.120895e-01 [14,] 0.74235924 5.152815e-01 2.576408e-01 [15,] 0.69018731 6.196254e-01 3.098127e-01 [16,] 0.74602277 5.079545e-01 2.539772e-01 [17,] 0.69968645 6.006271e-01 3.003135e-01 [18,] 0.71418399 5.716320e-01 2.858160e-01 [19,] 0.68809436 6.238113e-01 3.119056e-01 [20,] 0.79171068 4.165786e-01 2.082893e-01 [21,] 0.81607657 3.678469e-01 1.839234e-01 [22,] 0.82597053 3.480589e-01 1.740295e-01 [23,] 0.84906902 3.018620e-01 1.509310e-01 [24,] 0.90885183 1.822963e-01 9.114817e-02 [25,] 0.91054577 1.789085e-01 8.945423e-02 [26,] 0.90180443 1.963911e-01 9.819557e-02 [27,] 0.88852366 2.229527e-01 1.114763e-01 [28,] 0.92019974 1.596005e-01 7.980026e-02 [29,] 0.93890497 1.221901e-01 6.109503e-02 [30,] 0.91325365 1.734927e-01 8.674635e-02 [31,] 0.89587861 2.082428e-01 1.041214e-01 [32,] 0.86677042 2.664592e-01 1.332296e-01 [33,] 0.85511785 2.897643e-01 1.448822e-01 [34,] 0.97710322 4.579356e-02 2.289678e-02 [35,] 0.99489909 1.020182e-02 5.100911e-03 [36,] 0.99868694 2.626119e-03 1.313059e-03 [37,] 0.99992496 1.500895e-04 7.504473e-05 [38,] 0.99998379 3.241584e-05 1.620792e-05 [39,] 0.99998011 3.978018e-05 1.989009e-05 [40,] 0.99997351 5.298509e-05 2.649255e-05 [41,] 0.99995023 9.953407e-05 4.976703e-05 [42,] 0.99990831 1.833845e-04 9.169224e-05 [43,] 0.99969943 6.011424e-04 3.005712e-04 [44,] 0.99959060 8.187933e-04 4.093967e-04 [45,] 0.99995923 8.153551e-05 4.076776e-05 [46,] 0.99998919 2.161274e-05 1.080637e-05 [47,] 0.99993599 1.280151e-04 6.400754e-05 [48,] 0.99967408 6.518421e-04 3.259210e-04 [49,] 0.99835519 3.289626e-03 1.644813e-03 > postscript(file="/var/wessaorg/rcomp/tmp/1di5t1322324163.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/20y551322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3limt1322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4epom1322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5kggo1322324163.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 = 80 Frequency = 1 1 2 3 4 5 -4.801531e+01 -4.315816e+01 -1.844388e+01 -3.930102e+01 -4.015816e+01 6 7 8 9 10 -3.172959e+01 -2.301020e+00 -2.944388e+01 -3.136990e+01 -4.336990e+01 11 12 13 14 15 -7.369898e+00 4.446344e+01 2.799320e+00 -2.334354e+01 -3.629252e+00 16 17 18 19 20 -4.863946e-01 1.865646e+01 -3.914966e+00 6.051361e+01 1.037075e+01 21 22 23 24 25 3.644473e+01 3.444728e+00 -1.555527e+01 -3.172194e+01 9.613946e+00 26 27 28 29 30 1.947109e+01 4.185374e+00 2.532823e+01 -6.528912e+00 3.689966e+01 31 32 33 34 35 1.432823e+01 1.218537e+01 -1.740646e+00 6.259354e+00 -1.374065e+01 36 37 38 39 40 -1.907313e+00 7.428571e+00 9.285714e+00 6.986599e-15 1.414286e+01 41 42 43 44 45 2.328571e+01 4.871429e+01 2.142857e+00 5.900000e+01 2.707398e+01 46 47 48 49 50 4.207398e+01 3.907398e+01 3.390731e+01 6.724320e+01 5.610034e+01 51 52 53 54 55 4.181463e+01 3.395748e+01 2.410034e+01 -6.471088e+00 -1.804252e+01 56 57 58 59 60 -1.518537e+01 -7.111395e+00 -2.111395e+00 8.888605e+00 -9.278061e+00 61 62 63 64 65 -2.594218e+01 -6.085034e+00 -1.337075e+01 -1.322789e+01 -6.085034e+00 66 67 68 69 70 -2.265646e+01 -2.922789e+01 -1.737075e+01 -2.329677e+01 -6.296769e+00 71 72 73 74 75 -1.129677e+01 -3.546344e+01 -1.312755e+01 -1.227041e+01 -1.055612e+01 76 77 78 79 80 -2.041327e+01 -1.327041e+01 -2.084184e+01 -2.741327e+01 -1.955612e+01 > postscript(file="/var/wessaorg/rcomp/tmp/68l691322324163.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 = 80 Frequency = 1 lag(myerror, k = 1) myerror 0 -4.801531e+01 NA 1 -4.315816e+01 -4.801531e+01 2 -1.844388e+01 -4.315816e+01 3 -3.930102e+01 -1.844388e+01 4 -4.015816e+01 -3.930102e+01 5 -3.172959e+01 -4.015816e+01 6 -2.301020e+00 -3.172959e+01 7 -2.944388e+01 -2.301020e+00 8 -3.136990e+01 -2.944388e+01 9 -4.336990e+01 -3.136990e+01 10 -7.369898e+00 -4.336990e+01 11 4.446344e+01 -7.369898e+00 12 2.799320e+00 4.446344e+01 13 -2.334354e+01 2.799320e+00 14 -3.629252e+00 -2.334354e+01 15 -4.863946e-01 -3.629252e+00 16 1.865646e+01 -4.863946e-01 17 -3.914966e+00 1.865646e+01 18 6.051361e+01 -3.914966e+00 19 1.037075e+01 6.051361e+01 20 3.644473e+01 1.037075e+01 21 3.444728e+00 3.644473e+01 22 -1.555527e+01 3.444728e+00 23 -3.172194e+01 -1.555527e+01 24 9.613946e+00 -3.172194e+01 25 1.947109e+01 9.613946e+00 26 4.185374e+00 1.947109e+01 27 2.532823e+01 4.185374e+00 28 -6.528912e+00 2.532823e+01 29 3.689966e+01 -6.528912e+00 30 1.432823e+01 3.689966e+01 31 1.218537e+01 1.432823e+01 32 -1.740646e+00 1.218537e+01 33 6.259354e+00 -1.740646e+00 34 -1.374065e+01 6.259354e+00 35 -1.907313e+00 -1.374065e+01 36 7.428571e+00 -1.907313e+00 37 9.285714e+00 7.428571e+00 38 6.986599e-15 9.285714e+00 39 1.414286e+01 6.986599e-15 40 2.328571e+01 1.414286e+01 41 4.871429e+01 2.328571e+01 42 2.142857e+00 4.871429e+01 43 5.900000e+01 2.142857e+00 44 2.707398e+01 5.900000e+01 45 4.207398e+01 2.707398e+01 46 3.907398e+01 4.207398e+01 47 3.390731e+01 3.907398e+01 48 6.724320e+01 3.390731e+01 49 5.610034e+01 6.724320e+01 50 4.181463e+01 5.610034e+01 51 3.395748e+01 4.181463e+01 52 2.410034e+01 3.395748e+01 53 -6.471088e+00 2.410034e+01 54 -1.804252e+01 -6.471088e+00 55 -1.518537e+01 -1.804252e+01 56 -7.111395e+00 -1.518537e+01 57 -2.111395e+00 -7.111395e+00 58 8.888605e+00 -2.111395e+00 59 -9.278061e+00 8.888605e+00 60 -2.594218e+01 -9.278061e+00 61 -6.085034e+00 -2.594218e+01 62 -1.337075e+01 -6.085034e+00 63 -1.322789e+01 -1.337075e+01 64 -6.085034e+00 -1.322789e+01 65 -2.265646e+01 -6.085034e+00 66 -2.922789e+01 -2.265646e+01 67 -1.737075e+01 -2.922789e+01 68 -2.329677e+01 -1.737075e+01 69 -6.296769e+00 -2.329677e+01 70 -1.129677e+01 -6.296769e+00 71 -3.546344e+01 -1.129677e+01 72 -1.312755e+01 -3.546344e+01 73 -1.227041e+01 -1.312755e+01 74 -1.055612e+01 -1.227041e+01 75 -2.041327e+01 -1.055612e+01 76 -1.327041e+01 -2.041327e+01 77 -2.084184e+01 -1.327041e+01 78 -2.741327e+01 -2.084184e+01 79 -1.955612e+01 -2.741327e+01 80 NA -1.955612e+01 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -4.315816e+01 -4.801531e+01 [2,] -1.844388e+01 -4.315816e+01 [3,] -3.930102e+01 -1.844388e+01 [4,] -4.015816e+01 -3.930102e+01 [5,] -3.172959e+01 -4.015816e+01 [6,] -2.301020e+00 -3.172959e+01 [7,] -2.944388e+01 -2.301020e+00 [8,] -3.136990e+01 -2.944388e+01 [9,] -4.336990e+01 -3.136990e+01 [10,] -7.369898e+00 -4.336990e+01 [11,] 4.446344e+01 -7.369898e+00 [12,] 2.799320e+00 4.446344e+01 [13,] -2.334354e+01 2.799320e+00 [14,] -3.629252e+00 -2.334354e+01 [15,] -4.863946e-01 -3.629252e+00 [16,] 1.865646e+01 -4.863946e-01 [17,] -3.914966e+00 1.865646e+01 [18,] 6.051361e+01 -3.914966e+00 [19,] 1.037075e+01 6.051361e+01 [20,] 3.644473e+01 1.037075e+01 [21,] 3.444728e+00 3.644473e+01 [22,] -1.555527e+01 3.444728e+00 [23,] -3.172194e+01 -1.555527e+01 [24,] 9.613946e+00 -3.172194e+01 [25,] 1.947109e+01 9.613946e+00 [26,] 4.185374e+00 1.947109e+01 [27,] 2.532823e+01 4.185374e+00 [28,] -6.528912e+00 2.532823e+01 [29,] 3.689966e+01 -6.528912e+00 [30,] 1.432823e+01 3.689966e+01 [31,] 1.218537e+01 1.432823e+01 [32,] -1.740646e+00 1.218537e+01 [33,] 6.259354e+00 -1.740646e+00 [34,] -1.374065e+01 6.259354e+00 [35,] -1.907313e+00 -1.374065e+01 [36,] 7.428571e+00 -1.907313e+00 [37,] 9.285714e+00 7.428571e+00 [38,] 6.986599e-15 9.285714e+00 [39,] 1.414286e+01 6.986599e-15 [40,] 2.328571e+01 1.414286e+01 [41,] 4.871429e+01 2.328571e+01 [42,] 2.142857e+00 4.871429e+01 [43,] 5.900000e+01 2.142857e+00 [44,] 2.707398e+01 5.900000e+01 [45,] 4.207398e+01 2.707398e+01 [46,] 3.907398e+01 4.207398e+01 [47,] 3.390731e+01 3.907398e+01 [48,] 6.724320e+01 3.390731e+01 [49,] 5.610034e+01 6.724320e+01 [50,] 4.181463e+01 5.610034e+01 [51,] 3.395748e+01 4.181463e+01 [52,] 2.410034e+01 3.395748e+01 [53,] -6.471088e+00 2.410034e+01 [54,] -1.804252e+01 -6.471088e+00 [55,] -1.518537e+01 -1.804252e+01 [56,] -7.111395e+00 -1.518537e+01 [57,] -2.111395e+00 -7.111395e+00 [58,] 8.888605e+00 -2.111395e+00 [59,] -9.278061e+00 8.888605e+00 [60,] -2.594218e+01 -9.278061e+00 [61,] -6.085034e+00 -2.594218e+01 [62,] -1.337075e+01 -6.085034e+00 [63,] -1.322789e+01 -1.337075e+01 [64,] -6.085034e+00 -1.322789e+01 [65,] -2.265646e+01 -6.085034e+00 [66,] -2.922789e+01 -2.265646e+01 [67,] -1.737075e+01 -2.922789e+01 [68,] -2.329677e+01 -1.737075e+01 [69,] -6.296769e+00 -2.329677e+01 [70,] -1.129677e+01 -6.296769e+00 [71,] -3.546344e+01 -1.129677e+01 [72,] -1.312755e+01 -3.546344e+01 [73,] -1.227041e+01 -1.312755e+01 [74,] -1.055612e+01 -1.227041e+01 [75,] -2.041327e+01 -1.055612e+01 [76,] -1.327041e+01 -2.041327e+01 [77,] -2.084184e+01 -1.327041e+01 [78,] -2.741327e+01 -2.084184e+01 [79,] -1.955612e+01 -2.741327e+01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -4.315816e+01 -4.801531e+01 2 -1.844388e+01 -4.315816e+01 3 -3.930102e+01 -1.844388e+01 4 -4.015816e+01 -3.930102e+01 5 -3.172959e+01 -4.015816e+01 6 -2.301020e+00 -3.172959e+01 7 -2.944388e+01 -2.301020e+00 8 -3.136990e+01 -2.944388e+01 9 -4.336990e+01 -3.136990e+01 10 -7.369898e+00 -4.336990e+01 11 4.446344e+01 -7.369898e+00 12 2.799320e+00 4.446344e+01 13 -2.334354e+01 2.799320e+00 14 -3.629252e+00 -2.334354e+01 15 -4.863946e-01 -3.629252e+00 16 1.865646e+01 -4.863946e-01 17 -3.914966e+00 1.865646e+01 18 6.051361e+01 -3.914966e+00 19 1.037075e+01 6.051361e+01 20 3.644473e+01 1.037075e+01 21 3.444728e+00 3.644473e+01 22 -1.555527e+01 3.444728e+00 23 -3.172194e+01 -1.555527e+01 24 9.613946e+00 -3.172194e+01 25 1.947109e+01 9.613946e+00 26 4.185374e+00 1.947109e+01 27 2.532823e+01 4.185374e+00 28 -6.528912e+00 2.532823e+01 29 3.689966e+01 -6.528912e+00 30 1.432823e+01 3.689966e+01 31 1.218537e+01 1.432823e+01 32 -1.740646e+00 1.218537e+01 33 6.259354e+00 -1.740646e+00 34 -1.374065e+01 6.259354e+00 35 -1.907313e+00 -1.374065e+01 36 7.428571e+00 -1.907313e+00 37 9.285714e+00 7.428571e+00 38 6.986599e-15 9.285714e+00 39 1.414286e+01 6.986599e-15 40 2.328571e+01 1.414286e+01 41 4.871429e+01 2.328571e+01 42 2.142857e+00 4.871429e+01 43 5.900000e+01 2.142857e+00 44 2.707398e+01 5.900000e+01 45 4.207398e+01 2.707398e+01 46 3.907398e+01 4.207398e+01 47 3.390731e+01 3.907398e+01 48 6.724320e+01 3.390731e+01 49 5.610034e+01 6.724320e+01 50 4.181463e+01 5.610034e+01 51 3.395748e+01 4.181463e+01 52 2.410034e+01 3.395748e+01 53 -6.471088e+00 2.410034e+01 54 -1.804252e+01 -6.471088e+00 55 -1.518537e+01 -1.804252e+01 56 -7.111395e+00 -1.518537e+01 57 -2.111395e+00 -7.111395e+00 58 8.888605e+00 -2.111395e+00 59 -9.278061e+00 8.888605e+00 60 -2.594218e+01 -9.278061e+00 61 -6.085034e+00 -2.594218e+01 62 -1.337075e+01 -6.085034e+00 63 -1.322789e+01 -1.337075e+01 64 -6.085034e+00 -1.322789e+01 65 -2.265646e+01 -6.085034e+00 66 -2.922789e+01 -2.265646e+01 67 -1.737075e+01 -2.922789e+01 68 -2.329677e+01 -1.737075e+01 69 -6.296769e+00 -2.329677e+01 70 -1.129677e+01 -6.296769e+00 71 -3.546344e+01 -1.129677e+01 72 -1.312755e+01 -3.546344e+01 73 -1.227041e+01 -1.312755e+01 74 -1.055612e+01 -1.227041e+01 75 -2.041327e+01 -1.055612e+01 76 -1.327041e+01 -2.041327e+01 77 -2.084184e+01 -1.327041e+01 78 -2.741327e+01 -2.084184e+01 79 -1.955612e+01 -2.741327e+01 > 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/7x7ka1322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8sm161322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/946z51322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/1045bq1322324163.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11nyj21322324163.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/12n8o71322324163.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/13p5wx1322324163.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/14r27o1322324163.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/159ry21322324163.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/16ez8i1322324164.tab") + } > > try(system("convert tmp/1di5t1322324163.ps tmp/1di5t1322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/20y551322324163.ps tmp/20y551322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/3limt1322324163.ps tmp/3limt1322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/4epom1322324163.ps tmp/4epom1322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/5kggo1322324163.ps tmp/5kggo1322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/68l691322324163.ps tmp/68l691322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/7x7ka1322324163.ps tmp/7x7ka1322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/8sm161322324163.ps tmp/8sm161322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/946z51322324163.ps tmp/946z51322324163.png",intern=TRUE)) character(0) > try(system("convert tmp/1045bq1322324163.ps tmp/1045bq1322324163.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.497 0.518 4.087