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Type 'q()' to quit R. > x <- array(list(9.829,9.125,9.782,9.441,9.162,9.915,10.444,10.209,9.985,9.842,9.429,10.132,9.849,9.172,10.313,9.819,9.955,10.048,10.082,10.541,10.208,10.233,9.439,9.963,10.158,9.225,10.474,9.757,10.490,10.281,10.444,10.640,10.695,10.786,9.832,9.747,10.411,9.511,10.402,9.701,10.540,10.112,10.915,11.183,10.384,10.834,9.886,10.216,10.943,9.867,10.203,10.837,10.573,10.647,11.502,10.656,10.866,10.835,9.945,10.331),dim=c(1,60),dimnames=list(c('Births'),1:60)) > y <- array(NA,dim=c(1,60),dimnames=list(c('Births'),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' > #'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 Births M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 9.829 1 0 0 0 0 0 0 0 0 0 0 1 2 9.125 0 1 0 0 0 0 0 0 0 0 0 2 3 9.782 0 0 1 0 0 0 0 0 0 0 0 3 4 9.441 0 0 0 1 0 0 0 0 0 0 0 4 5 9.162 0 0 0 0 1 0 0 0 0 0 0 5 6 9.915 0 0 0 0 0 1 0 0 0 0 0 6 7 10.444 0 0 0 0 0 0 1 0 0 0 0 7 8 10.209 0 0 0 0 0 0 0 1 0 0 0 8 9 9.985 0 0 0 0 0 0 0 0 1 0 0 9 10 9.842 0 0 0 0 0 0 0 0 0 1 0 10 11 9.429 0 0 0 0 0 0 0 0 0 0 1 11 12 10.132 0 0 0 0 0 0 0 0 0 0 0 12 13 9.849 1 0 0 0 0 0 0 0 0 0 0 13 14 9.172 0 1 0 0 0 0 0 0 0 0 0 14 15 10.313 0 0 1 0 0 0 0 0 0 0 0 15 16 9.819 0 0 0 1 0 0 0 0 0 0 0 16 17 9.955 0 0 0 0 1 0 0 0 0 0 0 17 18 10.048 0 0 0 0 0 1 0 0 0 0 0 18 19 10.082 0 0 0 0 0 0 1 0 0 0 0 19 20 10.541 0 0 0 0 0 0 0 1 0 0 0 20 21 10.208 0 0 0 0 0 0 0 0 1 0 0 21 22 10.233 0 0 0 0 0 0 0 0 0 1 0 22 23 9.439 0 0 0 0 0 0 0 0 0 0 1 23 24 9.963 0 0 0 0 0 0 0 0 0 0 0 24 25 10.158 1 0 0 0 0 0 0 0 0 0 0 25 26 9.225 0 1 0 0 0 0 0 0 0 0 0 26 27 10.474 0 0 1 0 0 0 0 0 0 0 0 27 28 9.757 0 0 0 1 0 0 0 0 0 0 0 28 29 10.490 0 0 0 0 1 0 0 0 0 0 0 29 30 10.281 0 0 0 0 0 1 0 0 0 0 0 30 31 10.444 0 0 0 0 0 0 1 0 0 0 0 31 32 10.640 0 0 0 0 0 0 0 1 0 0 0 32 33 10.695 0 0 0 0 0 0 0 0 1 0 0 33 34 10.786 0 0 0 0 0 0 0 0 0 1 0 34 35 9.832 0 0 0 0 0 0 0 0 0 0 1 35 36 9.747 0 0 0 0 0 0 0 0 0 0 0 36 37 10.411 1 0 0 0 0 0 0 0 0 0 0 37 38 9.511 0 1 0 0 0 0 0 0 0 0 0 38 39 10.402 0 0 1 0 0 0 0 0 0 0 0 39 40 9.701 0 0 0 1 0 0 0 0 0 0 0 40 41 10.540 0 0 0 0 1 0 0 0 0 0 0 41 42 10.112 0 0 0 0 0 1 0 0 0 0 0 42 43 10.915 0 0 0 0 0 0 1 0 0 0 0 43 44 11.183 0 0 0 0 0 0 0 1 0 0 0 44 45 10.384 0 0 0 0 0 0 0 0 1 0 0 45 46 10.834 0 0 0 0 0 0 0 0 0 1 0 46 47 9.886 0 0 0 0 0 0 0 0 0 0 1 47 48 10.216 0 0 0 0 0 0 0 0 0 0 0 48 49 10.943 1 0 0 0 0 0 0 0 0 0 0 49 50 9.867 0 1 0 0 0 0 0 0 0 0 0 50 51 10.203 0 0 1 0 0 0 0 0 0 0 0 51 52 10.837 0 0 0 1 0 0 0 0 0 0 0 52 53 10.573 0 0 0 0 1 0 0 0 0 0 0 53 54 10.647 0 0 0 0 0 1 0 0 0 0 0 54 55 11.502 0 0 0 0 0 0 1 0 0 0 0 55 56 10.656 0 0 0 0 0 0 0 1 0 0 0 56 57 10.866 0 0 0 0 0 0 0 0 1 0 0 57 58 10.835 0 0 0 0 0 0 0 0 0 1 0 58 59 9.945 0 0 0 0 0 0 0 0 0 0 1 59 60 10.331 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) M1 M2 M3 M4 M5 9.47047 0.34577 -0.52910 0.30883 -0.03184 0.18429 M6 M7 M8 M9 M10 M11 0.22402 0.68395 0.63548 0.40041 0.46194 -0.35473 t 0.01687 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.57712 -0.09792 -0.00568 0.12562 0.52112 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 9.470475 0.133009 71.202 < 2e-16 *** M1 0.345772 0.161813 2.137 0.037845 * M2 -0.529099 0.161571 -3.275 0.001990 ** M3 0.308831 0.161352 1.914 0.061718 . M4 -0.031839 0.161156 -0.198 0.844237 M5 0.184291 0.160983 1.145 0.258094 M6 0.224021 0.160832 1.393 0.170209 M7 0.683951 0.160705 4.256 9.86e-05 *** M8 0.635481 0.160601 3.957 0.000255 *** M9 0.400410 0.160520 2.494 0.016188 * M10 0.461940 0.160462 2.879 0.005990 ** M11 -0.354730 0.160427 -2.211 0.031925 * t 0.016870 0.001929 8.743 2.03e-11 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2536 on 47 degrees of freedom Multiple R-squared: 0.8096, Adjusted R-squared: 0.761 F-statistic: 16.65 on 12 and 47 DF, p-value: 4.677e-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,] 0.30998885 0.6199777 0.6900111 [2,] 0.47794872 0.9558974 0.5220513 [3,] 0.37110004 0.7422001 0.6289000 [4,] 0.62839748 0.7432050 0.3716025 [5,] 0.51332256 0.9733549 0.4866774 [6,] 0.39233465 0.7846693 0.6076653 [7,] 0.30908114 0.6181623 0.6909189 [8,] 0.24651445 0.4930289 0.7534856 [9,] 0.25103494 0.5020699 0.7489651 [10,] 0.18362648 0.3672530 0.8163735 [11,] 0.14648188 0.2929638 0.8535181 [12,] 0.13590450 0.2718090 0.8640955 [13,] 0.10246665 0.2049333 0.8975333 [14,] 0.22171031 0.4434206 0.7782897 [15,] 0.16521595 0.3304319 0.8347840 [16,] 0.16658505 0.3331701 0.8334149 [17,] 0.11267081 0.2253416 0.8873292 [18,] 0.11352484 0.2270497 0.8864752 [19,] 0.12592727 0.2518545 0.8740727 [20,] 0.09961009 0.1992202 0.9003899 [21,] 0.14817483 0.2963497 0.8518252 [22,] 0.10979757 0.2195951 0.8902024 [23,] 0.07094476 0.1418895 0.9290552 [24,] 0.06731526 0.1346305 0.9326847 [25,] 0.30758339 0.6151668 0.6924166 [26,] 0.23717111 0.4743422 0.7628289 [27,] 0.24971139 0.4994228 0.7502886 [28,] 0.33493977 0.6698795 0.6650602 [29,] 0.73807174 0.5238565 0.2619283 > postscript(file="/var/wessaorg/rcomp/tmp/1hyti1322252532.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2qi1r1322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/31rsa1322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4gjz51322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5e01v1322252532.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 -0.004116667 0.149883333 -0.047916667 -0.065116667 -0.577116667 0.119283333 7 8 9 10 11 12 0.171483333 -0.031916667 -0.037716667 -0.259116667 0.127683333 0.459083333 13 14 15 16 17 18 -0.186558333 -0.005558333 0.280641667 0.110441667 0.013441667 0.049841667 19 20 21 22 23 24 -0.392958333 0.097641667 -0.017158333 -0.070558333 -0.064758333 0.087641667 25 26 27 28 29 30 -0.080000000 -0.155000000 0.239200000 -0.154000000 0.346000000 0.080400000 31 32 33 34 35 36 -0.233400000 -0.005800000 0.267400000 0.280000000 0.125800000 -0.330800000 37 38 39 40 41 42 -0.029441667 -0.071441667 -0.035241667 -0.412441667 0.193558333 -0.291041667 43 44 45 46 47 48 0.035158333 0.334758333 -0.246041667 0.125558333 -0.022641667 -0.064241667 49 50 51 52 53 54 0.300116667 0.082116667 -0.436683333 0.521116667 0.024116667 0.041516667 55 56 57 58 59 60 0.419716667 -0.394683333 0.033516667 -0.075883333 -0.166083333 -0.151683333 > postscript(file="/var/wessaorg/rcomp/tmp/6w3z71322252532.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 -0.004116667 NA 1 0.149883333 -0.004116667 2 -0.047916667 0.149883333 3 -0.065116667 -0.047916667 4 -0.577116667 -0.065116667 5 0.119283333 -0.577116667 6 0.171483333 0.119283333 7 -0.031916667 0.171483333 8 -0.037716667 -0.031916667 9 -0.259116667 -0.037716667 10 0.127683333 -0.259116667 11 0.459083333 0.127683333 12 -0.186558333 0.459083333 13 -0.005558333 -0.186558333 14 0.280641667 -0.005558333 15 0.110441667 0.280641667 16 0.013441667 0.110441667 17 0.049841667 0.013441667 18 -0.392958333 0.049841667 19 0.097641667 -0.392958333 20 -0.017158333 0.097641667 21 -0.070558333 -0.017158333 22 -0.064758333 -0.070558333 23 0.087641667 -0.064758333 24 -0.080000000 0.087641667 25 -0.155000000 -0.080000000 26 0.239200000 -0.155000000 27 -0.154000000 0.239200000 28 0.346000000 -0.154000000 29 0.080400000 0.346000000 30 -0.233400000 0.080400000 31 -0.005800000 -0.233400000 32 0.267400000 -0.005800000 33 0.280000000 0.267400000 34 0.125800000 0.280000000 35 -0.330800000 0.125800000 36 -0.029441667 -0.330800000 37 -0.071441667 -0.029441667 38 -0.035241667 -0.071441667 39 -0.412441667 -0.035241667 40 0.193558333 -0.412441667 41 -0.291041667 0.193558333 42 0.035158333 -0.291041667 43 0.334758333 0.035158333 44 -0.246041667 0.334758333 45 0.125558333 -0.246041667 46 -0.022641667 0.125558333 47 -0.064241667 -0.022641667 48 0.300116667 -0.064241667 49 0.082116667 0.300116667 50 -0.436683333 0.082116667 51 0.521116667 -0.436683333 52 0.024116667 0.521116667 53 0.041516667 0.024116667 54 0.419716667 0.041516667 55 -0.394683333 0.419716667 56 0.033516667 -0.394683333 57 -0.075883333 0.033516667 58 -0.166083333 -0.075883333 59 -0.151683333 -0.166083333 60 NA -0.151683333 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.149883333 -0.004116667 [2,] -0.047916667 0.149883333 [3,] -0.065116667 -0.047916667 [4,] -0.577116667 -0.065116667 [5,] 0.119283333 -0.577116667 [6,] 0.171483333 0.119283333 [7,] -0.031916667 0.171483333 [8,] -0.037716667 -0.031916667 [9,] -0.259116667 -0.037716667 [10,] 0.127683333 -0.259116667 [11,] 0.459083333 0.127683333 [12,] -0.186558333 0.459083333 [13,] -0.005558333 -0.186558333 [14,] 0.280641667 -0.005558333 [15,] 0.110441667 0.280641667 [16,] 0.013441667 0.110441667 [17,] 0.049841667 0.013441667 [18,] -0.392958333 0.049841667 [19,] 0.097641667 -0.392958333 [20,] -0.017158333 0.097641667 [21,] -0.070558333 -0.017158333 [22,] -0.064758333 -0.070558333 [23,] 0.087641667 -0.064758333 [24,] -0.080000000 0.087641667 [25,] -0.155000000 -0.080000000 [26,] 0.239200000 -0.155000000 [27,] -0.154000000 0.239200000 [28,] 0.346000000 -0.154000000 [29,] 0.080400000 0.346000000 [30,] -0.233400000 0.080400000 [31,] -0.005800000 -0.233400000 [32,] 0.267400000 -0.005800000 [33,] 0.280000000 0.267400000 [34,] 0.125800000 0.280000000 [35,] -0.330800000 0.125800000 [36,] -0.029441667 -0.330800000 [37,] -0.071441667 -0.029441667 [38,] -0.035241667 -0.071441667 [39,] -0.412441667 -0.035241667 [40,] 0.193558333 -0.412441667 [41,] -0.291041667 0.193558333 [42,] 0.035158333 -0.291041667 [43,] 0.334758333 0.035158333 [44,] -0.246041667 0.334758333 [45,] 0.125558333 -0.246041667 [46,] -0.022641667 0.125558333 [47,] -0.064241667 -0.022641667 [48,] 0.300116667 -0.064241667 [49,] 0.082116667 0.300116667 [50,] -0.436683333 0.082116667 [51,] 0.521116667 -0.436683333 [52,] 0.024116667 0.521116667 [53,] 0.041516667 0.024116667 [54,] 0.419716667 0.041516667 [55,] -0.394683333 0.419716667 [56,] 0.033516667 -0.394683333 [57,] -0.075883333 0.033516667 [58,] -0.166083333 -0.075883333 [59,] -0.151683333 -0.166083333 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.149883333 -0.004116667 2 -0.047916667 0.149883333 3 -0.065116667 -0.047916667 4 -0.577116667 -0.065116667 5 0.119283333 -0.577116667 6 0.171483333 0.119283333 7 -0.031916667 0.171483333 8 -0.037716667 -0.031916667 9 -0.259116667 -0.037716667 10 0.127683333 -0.259116667 11 0.459083333 0.127683333 12 -0.186558333 0.459083333 13 -0.005558333 -0.186558333 14 0.280641667 -0.005558333 15 0.110441667 0.280641667 16 0.013441667 0.110441667 17 0.049841667 0.013441667 18 -0.392958333 0.049841667 19 0.097641667 -0.392958333 20 -0.017158333 0.097641667 21 -0.070558333 -0.017158333 22 -0.064758333 -0.070558333 23 0.087641667 -0.064758333 24 -0.080000000 0.087641667 25 -0.155000000 -0.080000000 26 0.239200000 -0.155000000 27 -0.154000000 0.239200000 28 0.346000000 -0.154000000 29 0.080400000 0.346000000 30 -0.233400000 0.080400000 31 -0.005800000 -0.233400000 32 0.267400000 -0.005800000 33 0.280000000 0.267400000 34 0.125800000 0.280000000 35 -0.330800000 0.125800000 36 -0.029441667 -0.330800000 37 -0.071441667 -0.029441667 38 -0.035241667 -0.071441667 39 -0.412441667 -0.035241667 40 0.193558333 -0.412441667 41 -0.291041667 0.193558333 42 0.035158333 -0.291041667 43 0.334758333 0.035158333 44 -0.246041667 0.334758333 45 0.125558333 -0.246041667 46 -0.022641667 0.125558333 47 -0.064241667 -0.022641667 48 0.300116667 -0.064241667 49 0.082116667 0.300116667 50 -0.436683333 0.082116667 51 0.521116667 -0.436683333 52 0.024116667 0.521116667 53 0.041516667 0.024116667 54 0.419716667 0.041516667 55 -0.394683333 0.419716667 56 0.033516667 -0.394683333 57 -0.075883333 0.033516667 58 -0.166083333 -0.075883333 59 -0.151683333 -0.166083333 > 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/718e01322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8593m1322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/97w5y1322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10f6ph1322252532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11xire1322252532.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/121rkf1322252532.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/13rlbo1322252532.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/14obvq1322252532.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/15k9qp1322252533.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/16iucq1322252533.tab") + } > > try(system("convert tmp/1hyti1322252532.ps tmp/1hyti1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/2qi1r1322252532.ps tmp/2qi1r1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/31rsa1322252532.ps tmp/31rsa1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/4gjz51322252532.ps tmp/4gjz51322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/5e01v1322252532.ps tmp/5e01v1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/6w3z71322252532.ps tmp/6w3z71322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/718e01322252532.ps tmp/718e01322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/8593m1322252532.ps tmp/8593m1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/97w5y1322252532.ps tmp/97w5y1322252532.png",intern=TRUE)) character(0) > try(system("convert tmp/10f6ph1322252532.ps tmp/10f6ph1322252532.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.173 0.487 3.672