R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1 + ,162556 + ,807 + ,213118 + ,1 + ,29790 + ,444 + ,81767 + ,1 + ,87550 + ,412 + ,153198 + ,0 + ,84738 + ,428 + ,-26007 + ,1 + ,54660 + ,315 + ,126942 + ,1 + ,42634 + ,168 + ,157214 + ,0 + ,40949 + ,263 + ,129352 + ,1 + ,45187 + ,267 + ,234817 + ,1 + ,37704 + ,228 + ,60448 + ,1 + ,16275 + ,129 + ,47818 + ,0 + ,25830 + ,104 + ,245546 + ,0 + ,12679 + ,122 + ,48020 + ,1 + ,18014 + ,393 + ,-1710 + ,0 + ,43556 + ,190 + ,32648 + ,1 + ,24811 + ,280 + ,95350 + ,0 + ,6575 + ,63 + ,151352 + ,0 + ,7123 + ,102 + ,288170 + ,1 + ,21950 + ,265 + ,114337 + ,1 + ,37597 + ,234 + ,37884 + ,0 + ,17821 + ,277 + ,122844 + ,1 + ,12988 + ,73 + ,82340 + ,1 + ,22330 + ,67 + ,79801 + ,0 + ,13326 + ,103 + ,165548 + ,0 + ,16189 + ,290 + ,116384 + ,0 + ,7146 + ,83 + ,134028 + ,0 + ,15824 + ,56 + ,63838 + ,1 + ,27664 + ,236 + ,74996 + ,0 + ,11920 + ,73 + ,31080 + ,0 + ,8568 + ,34 + ,32168 + ,0 + ,14416 + ,139 + ,49857 + ,1 + ,3369 + ,26 + ,87161 + ,1 + ,11819 + ,70 + ,106113 + ,1 + ,6984 + ,40 + ,80570 + ,1 + ,4519 + ,42 + ,102129 + ,0 + ,2220 + ,12 + ,301670 + ,0 + ,18562 + ,211 + ,102313 + ,0 + ,10327 + ,74 + ,88577 + ,1 + ,5336 + ,80 + ,112477 + ,1 + ,2365 + ,83 + ,191778 + ,0 + ,4069 + ,131 + ,79804 + ,0 + ,8636 + ,203 + ,128294 + ,0 + ,13718 + ,56 + ,96448 + ,0 + ,4525 + ,89 + ,93811 + ,0 + ,6869 + ,88 + ,117520 + ,0 + ,4628 + ,39 + ,69159 + ,1 + ,3689 + ,25 + ,101792 + ,1 + ,4891 + ,49 + ,210568 + ,1 + ,7489 + ,149 + ,136996 + ,0 + ,4901 + ,58 + ,121920 + ,0 + ,2284 + ,41 + ,76403 + ,1 + ,3160 + ,90 + ,108094 + ,1 + ,4150 + ,136 + ,134759 + ,1 + ,7285 + ,97 + ,188873 + ,1 + ,1134 + ,63 + ,146216 + ,1 + ,4658 + ,114 + ,156608 + ,0 + ,2384 + ,77 + ,61348 + ,0 + ,3748 + ,6 + ,50350 + ,0 + ,5371 + ,47 + ,87720 + ,0 + ,1285 + ,51 + ,99489 + ,1 + ,9327 + ,85 + ,87419 + ,1 + ,5565 + ,43 + ,94355 + ,0 + ,1528 + ,32 + ,60326 + ,1 + ,3122 + ,25 + ,94670 + ,1 + ,7561 + ,77 + ,82425 + ,0 + ,2675 + ,54 + ,59017 + ,0 + ,13253 + ,251 + ,90829 + ,0 + ,880 + ,15 + ,80791 + ,1 + ,2053 + ,44 + ,100423 + ,0 + ,1424 + ,73 + ,131116 + ,1 + ,4036 + ,85 + ,100269 + ,1 + ,3045 + ,49 + ,27330 + ,0 + ,5119 + ,38 + ,39039 + ,0 + ,1431 + ,35 + ,106885 + ,0 + ,554 + ,9 + ,79285 + ,0 + ,1975 + ,34 + ,118881 + ,1 + ,1765 + ,20 + ,77623 + ,0 + ,1012 + ,29 + ,114768 + ,0 + ,810 + ,11 + ,74015 + ,0 + ,1280 + ,52 + ,69465 + ,1 + ,666 + ,13 + ,117869 + ,0 + ,1380 + ,29 + ,60982 + ,1 + ,4677 + ,66 + ,90131 + ,0 + ,876 + ,33 + ,138971 + ,0 + ,814 + ,15 + ,39625 + ,0 + ,514 + ,15 + ,102725 + ,1 + ,5692 + ,68 + ,64239 + ,0 + ,3642 + ,100 + ,90262 + ,0 + ,540 + ,13 + ,103960 + ,0 + ,2099 + ,45 + ,106611 + ,0 + ,567 + ,14 + ,103345 + ,0 + ,2001 + ,36 + ,95551 + ,1 + ,2949 + ,40 + ,82903 + ,0 + ,2253 + ,68 + ,63593 + ,1 + ,6533 + ,29 + ,126910 + ,0 + ,1889 + ,43 + ,37527 + ,1 + ,3055 + ,30 + ,60247 + ,0 + ,272 + ,9 + ,112995 + ,1 + ,1414 + ,22 + ,70184 + ,0 + ,2564 + ,19 + ,130140 + ,1 + ,1383 + ,9 + ,73221) + ,dim=c(4 + ,100) + ,dimnames=list(c('Group' + ,'Costs' + ,'Orders' + ,'Dividends') + ,1:100)) > y <- array(NA,dim=c(4,100),dimnames=list(c('Group','Costs','Orders','Dividends'),1:100)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '3' > #'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 Orders Group Costs Dividends 1 807 1 162556 213118 2 444 1 29790 81767 3 412 1 87550 153198 4 428 0 84738 -26007 5 315 1 54660 126942 6 168 1 42634 157214 7 263 0 40949 129352 8 267 1 45187 234817 9 228 1 37704 60448 10 129 1 16275 47818 11 104 0 25830 245546 12 122 0 12679 48020 13 393 1 18014 -1710 14 190 0 43556 32648 15 280 1 24811 95350 16 63 0 6575 151352 17 102 0 7123 288170 18 265 1 21950 114337 19 234 1 37597 37884 20 277 0 17821 122844 21 73 1 12988 82340 22 67 1 22330 79801 23 103 0 13326 165548 24 290 0 16189 116384 25 83 0 7146 134028 26 56 0 15824 63838 27 236 1 27664 74996 28 73 0 11920 31080 29 34 0 8568 32168 30 139 0 14416 49857 31 26 1 3369 87161 32 70 1 11819 106113 33 40 1 6984 80570 34 42 1 4519 102129 35 12 0 2220 301670 36 211 0 18562 102313 37 74 0 10327 88577 38 80 1 5336 112477 39 83 1 2365 191778 40 131 0 4069 79804 41 203 0 8636 128294 42 56 0 13718 96448 43 89 0 4525 93811 44 88 0 6869 117520 45 39 0 4628 69159 46 25 1 3689 101792 47 49 1 4891 210568 48 149 1 7489 136996 49 58 0 4901 121920 50 41 0 2284 76403 51 90 1 3160 108094 52 136 1 4150 134759 53 97 1 7285 188873 54 63 1 1134 146216 55 114 1 4658 156608 56 77 0 2384 61348 57 6 0 3748 50350 58 47 0 5371 87720 59 51 0 1285 99489 60 85 1 9327 87419 61 43 1 5565 94355 62 32 0 1528 60326 63 25 1 3122 94670 64 77 1 7561 82425 65 54 0 2675 59017 66 251 0 13253 90829 67 15 0 880 80791 68 44 1 2053 100423 69 73 0 1424 131116 70 85 1 4036 100269 71 49 1 3045 27330 72 38 0 5119 39039 73 35 0 1431 106885 74 9 0 554 79285 75 34 0 1975 118881 76 20 1 1765 77623 77 29 0 1012 114768 78 11 0 810 74015 79 52 0 1280 69465 80 13 1 666 117869 81 29 0 1380 60982 82 66 1 4677 90131 83 33 0 876 138971 84 15 0 814 39625 85 15 0 514 102725 86 68 1 5692 64239 87 100 0 3642 90262 88 13 0 540 103960 89 45 0 2099 106611 90 14 0 567 103345 91 36 0 2001 95551 92 40 1 2949 82903 93 68 0 2253 63593 94 29 1 6533 126910 95 43 0 1889 37527 96 30 1 3055 60247 97 9 0 272 112995 98 22 1 1414 70184 99 19 0 2564 130140 100 9 1 1383 73221 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Group Costs Dividends 4.579e+01 1.010e+01 4.878e-03 -4.408e-05 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -94.29 -33.25 -12.94 13.93 249.16 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 4.579e+01 1.385e+01 3.306 0.00133 ** Group 1.010e+01 1.242e+01 0.813 0.41821 Costs 4.878e-03 2.856e-04 17.081 < 2e-16 *** Dividends -4.408e-05 1.149e-04 -0.384 0.70207 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 60.48 on 96 degrees of freedom Multiple R-squared: 0.7651, Adjusted R-squared: 0.7578 F-statistic: 104.2 on 3 and 96 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,] 0.9993803 1.239397e-03 6.196986e-04 [2,] 0.9983580 3.283984e-03 1.641992e-03 [3,] 0.9981051 3.789855e-03 1.894927e-03 [4,] 0.9972015 5.596974e-03 2.798487e-03 [5,] 0.9962515 7.497003e-03 3.748502e-03 [6,] 0.9925740 1.485200e-02 7.426002e-03 [7,] 0.9999549 9.013038e-05 4.506519e-05 [8,] 0.9999877 2.452518e-05 1.226259e-05 [9,] 0.9999841 3.171414e-05 1.585707e-05 [10,] 0.9999668 6.641407e-05 3.320703e-05 [11,] 0.9999720 5.590913e-05 2.795456e-05 [12,] 0.9999693 6.133100e-05 3.066550e-05 [13,] 0.9999753 4.932030e-05 2.466015e-05 [14,] 0.9999984 3.248316e-06 1.624158e-06 [15,] 0.9999994 1.104936e-06 5.524681e-07 [16,] 1.0000000 2.237241e-08 1.118620e-08 [17,] 1.0000000 3.823168e-08 1.911584e-08 [18,] 1.0000000 4.073508e-10 2.036754e-10 [19,] 1.0000000 1.015765e-09 5.078824e-10 [20,] 1.0000000 1.490747e-10 7.453735e-11 [21,] 1.0000000 3.948052e-10 1.974026e-10 [22,] 1.0000000 4.444512e-10 2.222256e-10 [23,] 1.0000000 2.768040e-10 1.384020e-10 [24,] 1.0000000 7.147707e-10 3.573853e-10 [25,] 1.0000000 6.905850e-10 3.452925e-10 [26,] 1.0000000 4.028974e-10 2.014487e-10 [27,] 1.0000000 3.385988e-10 1.692994e-10 [28,] 1.0000000 5.707004e-10 2.853502e-10 [29,] 1.0000000 4.183891e-10 2.091946e-10 [30,] 1.0000000 7.324472e-10 3.662236e-10 [31,] 1.0000000 8.320268e-10 4.160134e-10 [32,] 1.0000000 2.057341e-09 1.028671e-09 [33,] 1.0000000 4.538981e-09 2.269491e-09 [34,] 1.0000000 2.215938e-09 1.107969e-09 [35,] 1.0000000 1.676306e-10 8.381528e-11 [36,] 1.0000000 2.092142e-12 1.046071e-12 [37,] 1.0000000 5.385114e-12 2.692557e-12 [38,] 1.0000000 1.397479e-11 6.987397e-12 [39,] 1.0000000 2.206494e-11 1.103247e-11 [40,] 1.0000000 3.089009e-11 1.544504e-11 [41,] 1.0000000 3.201753e-11 1.600877e-11 [42,] 1.0000000 3.952888e-11 1.976444e-11 [43,] 1.0000000 7.757441e-11 3.878721e-11 [44,] 1.0000000 2.070058e-10 1.035029e-10 [45,] 1.0000000 2.456057e-10 1.228029e-10 [46,] 1.0000000 3.306720e-11 1.653360e-11 [47,] 1.0000000 8.594485e-11 4.297242e-11 [48,] 1.0000000 9.768460e-11 4.884230e-11 [49,] 1.0000000 5.361826e-11 2.680913e-11 [50,] 1.0000000 7.445674e-11 3.722837e-11 [51,] 1.0000000 1.698065e-11 8.490324e-12 [52,] 1.0000000 1.313074e-11 6.565368e-12 [53,] 1.0000000 3.255383e-11 1.627692e-11 [54,] 1.0000000 2.928400e-11 1.464200e-11 [55,] 1.0000000 3.761371e-11 1.880686e-11 [56,] 1.0000000 1.188709e-10 5.943543e-11 [57,] 1.0000000 2.842452e-10 1.421226e-10 [58,] 1.0000000 4.063593e-10 2.031796e-10 [59,] 1.0000000 1.305428e-09 6.527141e-10 [60,] 1.0000000 6.646889e-11 3.323444e-11 [61,] 1.0000000 1.874980e-10 9.374899e-11 [62,] 1.0000000 5.014853e-10 2.507426e-10 [63,] 1.0000000 2.157230e-10 1.078615e-10 [64,] 1.0000000 7.728921e-11 3.864460e-11 [65,] 1.0000000 2.507362e-10 1.253681e-10 [66,] 1.0000000 9.569850e-11 4.784925e-11 [67,] 1.0000000 3.839132e-10 1.919566e-10 [68,] 1.0000000 9.864776e-10 4.932388e-10 [69,] 1.0000000 4.029839e-09 2.014920e-09 [70,] 1.0000000 1.499045e-08 7.495226e-09 [71,] 1.0000000 5.584652e-08 2.792326e-08 [72,] 0.9999999 1.220530e-07 6.102649e-08 [73,] 0.9999998 3.318007e-07 1.659004e-07 [74,] 0.9999996 7.685796e-07 3.842898e-07 [75,] 0.9999988 2.393849e-06 1.196924e-06 [76,] 0.9999974 5.193268e-06 2.596634e-06 [77,] 0.9999950 1.004255e-05 5.021274e-06 [78,] 0.9999967 6.558805e-06 3.279403e-06 [79,] 0.9999868 2.645540e-05 1.322770e-05 [80,] 0.9999474 1.051035e-04 5.255177e-05 [81,] 0.9999957 8.556326e-06 4.278163e-06 [82,] 0.9999787 4.253140e-05 2.126570e-05 [83,] 0.9999442 1.116141e-04 5.580704e-05 [84,] 0.9997077 5.846585e-04 2.923293e-04 [85,] 0.9985139 2.972259e-03 1.486130e-03 [86,] 0.9964060 7.188069e-03 3.594034e-03 [87,] 0.9993082 1.383571e-03 6.917854e-04 > postscript(file="/var/www/html/freestat/rcomp/tmp/10k2o1291209396.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/20k2o1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/30k2o1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4ab1r1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5ab1r1291209396.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 = 100 Frequency = 1 1 2 3 4 5 6 -32.3975016 246.4042470 -64.1825875 -32.2668349 -1.9126527 -88.9191456 7 8 9 10 11 12 23.1706089 1.0488270 -9.1375442 -4.1702078 -56.9617626 16.4778703 13 14 15 16 17 18 249.1643041 -66.8082221 107.2890111 -8.1938490 34.1640783 107.0810302 19 20 21 22 23 24 -3.6102466 149.6950004 -42.6155129 -94.2948308 -0.4973922 170.3706387 25 26 27 28 29 30 8.2573513 -64.1652179 48.4757564 -29.5666723 -52.1686897 25.0862936 31 32 33 34 35 36 -42.4844843 -38.8655831 -46.4078708 -31.4340446 -31.3255209 79.1756293 37 38 39 40 41 42 -18.2620557 3.0370182 24.0242092 68.8758297 120.7368368 -52.4553579 43 44 45 46 47 48 25.2690271 13.8808036 -26.3200290 -44.4004150 -21.4685826 62.6161384 49 50 51 52 53 54 -6.3259475 -12.5674051 23.4576746 65.8041459 13.8979125 8.0202868 55 56 57 58 59 60 42.2893766 22.2812051 -55.8567559 -21.1259901 3.3230343 -12.5344012 61 62 63 64 65 66 -35.8787864 -18.5885400 -41.9486996 -12.1405312 -2.2409532 144.5650848 67 68 69 70 71 72 -31.5257035 -17.4808560 26.0391452 13.8398924 -20.5414473 -31.0426578 73 74 75 76 77 78 -13.0630950 -36.0019600 -16.1877789 -41.0810988 -16.6718614 -35.4829494 79 80 81 82 83 84 3.0239725 -40.9464818 -20.8377252 -8.7335887 -10.9416332 -33.0183626 85 86 87 88 89 90 -28.7736231 -12.8257589 40.4195902 -30.8460046 -6.3334711 -30.0048113 91 92 93 94 95 96 -15.3429793 -26.6235452 14.0191418 -53.1653763 -10.3543609 -38.1392513 97 98 99 100 -33.1405226 -37.6969381 -33.5644456 -50.4118595 > postscript(file="/var/www/html/freestat/rcomp/tmp/6ab1r1291209396.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 = 100 Frequency = 1 lag(myerror, k = 1) myerror 0 -32.3975016 NA 1 246.4042470 -32.3975016 2 -64.1825875 246.4042470 3 -32.2668349 -64.1825875 4 -1.9126527 -32.2668349 5 -88.9191456 -1.9126527 6 23.1706089 -88.9191456 7 1.0488270 23.1706089 8 -9.1375442 1.0488270 9 -4.1702078 -9.1375442 10 -56.9617626 -4.1702078 11 16.4778703 -56.9617626 12 249.1643041 16.4778703 13 -66.8082221 249.1643041 14 107.2890111 -66.8082221 15 -8.1938490 107.2890111 16 34.1640783 -8.1938490 17 107.0810302 34.1640783 18 -3.6102466 107.0810302 19 149.6950004 -3.6102466 20 -42.6155129 149.6950004 21 -94.2948308 -42.6155129 22 -0.4973922 -94.2948308 23 170.3706387 -0.4973922 24 8.2573513 170.3706387 25 -64.1652179 8.2573513 26 48.4757564 -64.1652179 27 -29.5666723 48.4757564 28 -52.1686897 -29.5666723 29 25.0862936 -52.1686897 30 -42.4844843 25.0862936 31 -38.8655831 -42.4844843 32 -46.4078708 -38.8655831 33 -31.4340446 -46.4078708 34 -31.3255209 -31.4340446 35 79.1756293 -31.3255209 36 -18.2620557 79.1756293 37 3.0370182 -18.2620557 38 24.0242092 3.0370182 39 68.8758297 24.0242092 40 120.7368368 68.8758297 41 -52.4553579 120.7368368 42 25.2690271 -52.4553579 43 13.8808036 25.2690271 44 -26.3200290 13.8808036 45 -44.4004150 -26.3200290 46 -21.4685826 -44.4004150 47 62.6161384 -21.4685826 48 -6.3259475 62.6161384 49 -12.5674051 -6.3259475 50 23.4576746 -12.5674051 51 65.8041459 23.4576746 52 13.8979125 65.8041459 53 8.0202868 13.8979125 54 42.2893766 8.0202868 55 22.2812051 42.2893766 56 -55.8567559 22.2812051 57 -21.1259901 -55.8567559 58 3.3230343 -21.1259901 59 -12.5344012 3.3230343 60 -35.8787864 -12.5344012 61 -18.5885400 -35.8787864 62 -41.9486996 -18.5885400 63 -12.1405312 -41.9486996 64 -2.2409532 -12.1405312 65 144.5650848 -2.2409532 66 -31.5257035 144.5650848 67 -17.4808560 -31.5257035 68 26.0391452 -17.4808560 69 13.8398924 26.0391452 70 -20.5414473 13.8398924 71 -31.0426578 -20.5414473 72 -13.0630950 -31.0426578 73 -36.0019600 -13.0630950 74 -16.1877789 -36.0019600 75 -41.0810988 -16.1877789 76 -16.6718614 -41.0810988 77 -35.4829494 -16.6718614 78 3.0239725 -35.4829494 79 -40.9464818 3.0239725 80 -20.8377252 -40.9464818 81 -8.7335887 -20.8377252 82 -10.9416332 -8.7335887 83 -33.0183626 -10.9416332 84 -28.7736231 -33.0183626 85 -12.8257589 -28.7736231 86 40.4195902 -12.8257589 87 -30.8460046 40.4195902 88 -6.3334711 -30.8460046 89 -30.0048113 -6.3334711 90 -15.3429793 -30.0048113 91 -26.6235452 -15.3429793 92 14.0191418 -26.6235452 93 -53.1653763 14.0191418 94 -10.3543609 -53.1653763 95 -38.1392513 -10.3543609 96 -33.1405226 -38.1392513 97 -37.6969381 -33.1405226 98 -33.5644456 -37.6969381 99 -50.4118595 -33.5644456 100 NA -50.4118595 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 246.4042470 -32.3975016 [2,] -64.1825875 246.4042470 [3,] -32.2668349 -64.1825875 [4,] -1.9126527 -32.2668349 [5,] -88.9191456 -1.9126527 [6,] 23.1706089 -88.9191456 [7,] 1.0488270 23.1706089 [8,] -9.1375442 1.0488270 [9,] -4.1702078 -9.1375442 [10,] -56.9617626 -4.1702078 [11,] 16.4778703 -56.9617626 [12,] 249.1643041 16.4778703 [13,] -66.8082221 249.1643041 [14,] 107.2890111 -66.8082221 [15,] -8.1938490 107.2890111 [16,] 34.1640783 -8.1938490 [17,] 107.0810302 34.1640783 [18,] -3.6102466 107.0810302 [19,] 149.6950004 -3.6102466 [20,] -42.6155129 149.6950004 [21,] -94.2948308 -42.6155129 [22,] -0.4973922 -94.2948308 [23,] 170.3706387 -0.4973922 [24,] 8.2573513 170.3706387 [25,] -64.1652179 8.2573513 [26,] 48.4757564 -64.1652179 [27,] -29.5666723 48.4757564 [28,] -52.1686897 -29.5666723 [29,] 25.0862936 -52.1686897 [30,] -42.4844843 25.0862936 [31,] -38.8655831 -42.4844843 [32,] -46.4078708 -38.8655831 [33,] -31.4340446 -46.4078708 [34,] -31.3255209 -31.4340446 [35,] 79.1756293 -31.3255209 [36,] -18.2620557 79.1756293 [37,] 3.0370182 -18.2620557 [38,] 24.0242092 3.0370182 [39,] 68.8758297 24.0242092 [40,] 120.7368368 68.8758297 [41,] -52.4553579 120.7368368 [42,] 25.2690271 -52.4553579 [43,] 13.8808036 25.2690271 [44,] -26.3200290 13.8808036 [45,] -44.4004150 -26.3200290 [46,] -21.4685826 -44.4004150 [47,] 62.6161384 -21.4685826 [48,] -6.3259475 62.6161384 [49,] -12.5674051 -6.3259475 [50,] 23.4576746 -12.5674051 [51,] 65.8041459 23.4576746 [52,] 13.8979125 65.8041459 [53,] 8.0202868 13.8979125 [54,] 42.2893766 8.0202868 [55,] 22.2812051 42.2893766 [56,] -55.8567559 22.2812051 [57,] -21.1259901 -55.8567559 [58,] 3.3230343 -21.1259901 [59,] -12.5344012 3.3230343 [60,] -35.8787864 -12.5344012 [61,] -18.5885400 -35.8787864 [62,] -41.9486996 -18.5885400 [63,] -12.1405312 -41.9486996 [64,] -2.2409532 -12.1405312 [65,] 144.5650848 -2.2409532 [66,] -31.5257035 144.5650848 [67,] -17.4808560 -31.5257035 [68,] 26.0391452 -17.4808560 [69,] 13.8398924 26.0391452 [70,] -20.5414473 13.8398924 [71,] -31.0426578 -20.5414473 [72,] -13.0630950 -31.0426578 [73,] -36.0019600 -13.0630950 [74,] -16.1877789 -36.0019600 [75,] -41.0810988 -16.1877789 [76,] -16.6718614 -41.0810988 [77,] -35.4829494 -16.6718614 [78,] 3.0239725 -35.4829494 [79,] -40.9464818 3.0239725 [80,] -20.8377252 -40.9464818 [81,] -8.7335887 -20.8377252 [82,] -10.9416332 -8.7335887 [83,] -33.0183626 -10.9416332 [84,] -28.7736231 -33.0183626 [85,] -12.8257589 -28.7736231 [86,] 40.4195902 -12.8257589 [87,] -30.8460046 40.4195902 [88,] -6.3334711 -30.8460046 [89,] -30.0048113 -6.3334711 [90,] -15.3429793 -30.0048113 [91,] -26.6235452 -15.3429793 [92,] 14.0191418 -26.6235452 [93,] -53.1653763 14.0191418 [94,] -10.3543609 -53.1653763 [95,] -38.1392513 -10.3543609 [96,] -33.1405226 -38.1392513 [97,] -37.6969381 -33.1405226 [98,] -33.5644456 -37.6969381 [99,] -50.4118595 -33.5644456 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 246.4042470 -32.3975016 2 -64.1825875 246.4042470 3 -32.2668349 -64.1825875 4 -1.9126527 -32.2668349 5 -88.9191456 -1.9126527 6 23.1706089 -88.9191456 7 1.0488270 23.1706089 8 -9.1375442 1.0488270 9 -4.1702078 -9.1375442 10 -56.9617626 -4.1702078 11 16.4778703 -56.9617626 12 249.1643041 16.4778703 13 -66.8082221 249.1643041 14 107.2890111 -66.8082221 15 -8.1938490 107.2890111 16 34.1640783 -8.1938490 17 107.0810302 34.1640783 18 -3.6102466 107.0810302 19 149.6950004 -3.6102466 20 -42.6155129 149.6950004 21 -94.2948308 -42.6155129 22 -0.4973922 -94.2948308 23 170.3706387 -0.4973922 24 8.2573513 170.3706387 25 -64.1652179 8.2573513 26 48.4757564 -64.1652179 27 -29.5666723 48.4757564 28 -52.1686897 -29.5666723 29 25.0862936 -52.1686897 30 -42.4844843 25.0862936 31 -38.8655831 -42.4844843 32 -46.4078708 -38.8655831 33 -31.4340446 -46.4078708 34 -31.3255209 -31.4340446 35 79.1756293 -31.3255209 36 -18.2620557 79.1756293 37 3.0370182 -18.2620557 38 24.0242092 3.0370182 39 68.8758297 24.0242092 40 120.7368368 68.8758297 41 -52.4553579 120.7368368 42 25.2690271 -52.4553579 43 13.8808036 25.2690271 44 -26.3200290 13.8808036 45 -44.4004150 -26.3200290 46 -21.4685826 -44.4004150 47 62.6161384 -21.4685826 48 -6.3259475 62.6161384 49 -12.5674051 -6.3259475 50 23.4576746 -12.5674051 51 65.8041459 23.4576746 52 13.8979125 65.8041459 53 8.0202868 13.8979125 54 42.2893766 8.0202868 55 22.2812051 42.2893766 56 -55.8567559 22.2812051 57 -21.1259901 -55.8567559 58 3.3230343 -21.1259901 59 -12.5344012 3.3230343 60 -35.8787864 -12.5344012 61 -18.5885400 -35.8787864 62 -41.9486996 -18.5885400 63 -12.1405312 -41.9486996 64 -2.2409532 -12.1405312 65 144.5650848 -2.2409532 66 -31.5257035 144.5650848 67 -17.4808560 -31.5257035 68 26.0391452 -17.4808560 69 13.8398924 26.0391452 70 -20.5414473 13.8398924 71 -31.0426578 -20.5414473 72 -13.0630950 -31.0426578 73 -36.0019600 -13.0630950 74 -16.1877789 -36.0019600 75 -41.0810988 -16.1877789 76 -16.6718614 -41.0810988 77 -35.4829494 -16.6718614 78 3.0239725 -35.4829494 79 -40.9464818 3.0239725 80 -20.8377252 -40.9464818 81 -8.7335887 -20.8377252 82 -10.9416332 -8.7335887 83 -33.0183626 -10.9416332 84 -28.7736231 -33.0183626 85 -12.8257589 -28.7736231 86 40.4195902 -12.8257589 87 -30.8460046 40.4195902 88 -6.3334711 -30.8460046 89 -30.0048113 -6.3334711 90 -15.3429793 -30.0048113 91 -26.6235452 -15.3429793 92 14.0191418 -26.6235452 93 -53.1653763 14.0191418 94 -10.3543609 -53.1653763 95 -38.1392513 -10.3543609 96 -33.1405226 -38.1392513 97 -37.6969381 -33.1405226 98 -33.5644456 -37.6969381 99 -50.4118595 -33.5644456 > 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/freestat/rcomp/tmp/7lk1u1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8ebif1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9ebif1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10ebif1291209396.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/11a3go1291209396.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/freestat/rcomp/tmp/12luxr1291209396.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/freestat/rcomp/tmp/13rdc31291209396.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/freestat/rcomp/tmp/14kntn1291209396.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/freestat/rcomp/tmp/1555st1291209396.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/freestat/rcomp/tmp/162x721291209396.tab") + } > > try(system("convert tmp/10k2o1291209396.ps tmp/10k2o1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/20k2o1291209396.ps tmp/20k2o1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/30k2o1291209396.ps tmp/30k2o1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/4ab1r1291209396.ps tmp/4ab1r1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/5ab1r1291209396.ps tmp/5ab1r1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/6ab1r1291209396.ps tmp/6ab1r1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/7lk1u1291209396.ps tmp/7lk1u1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/8ebif1291209396.ps tmp/8ebif1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/9ebif1291209396.ps tmp/9ebif1291209396.png",intern=TRUE)) character(0) > try(system("convert tmp/10ebif1291209396.ps tmp/10ebif1291209396.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.454 2.567 4.769