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(0 + ,162556 + ,1081 + ,213118 + ,6282154 + ,0 + ,29790 + ,309 + ,81767 + ,4321023 + ,0 + ,87550 + ,458 + ,153198 + ,4111912 + ,1 + ,84738 + ,588 + ,-26007 + ,223193 + ,0 + ,54660 + ,302 + ,126942 + ,1491348 + ,0 + ,42634 + ,156 + ,157214 + ,1629616 + ,1 + ,40949 + ,481 + ,129352 + ,1398893 + ,0 + ,45187 + ,353 + ,234817 + ,1926517 + ,0 + ,37704 + ,452 + ,60448 + ,983660 + ,0 + ,16275 + ,109 + ,47818 + ,1443586 + ,1 + ,25830 + ,115 + ,245546 + ,1073089 + ,1 + ,12679 + ,110 + ,48020 + ,984885 + ,0 + ,18014 + ,239 + ,-1710 + ,1405225 + ,1 + ,43556 + ,247 + ,32648 + ,227132 + ,0 + ,24811 + ,505 + ,95350 + ,929118 + ,1 + ,6575 + ,159 + ,151352 + ,1071292 + ,1 + ,7123 + ,109 + ,288170 + ,638830 + ,0 + ,21950 + ,519 + ,114337 + ,856956 + ,0 + ,37597 + ,248 + ,37884 + ,992426 + ,1 + ,17821 + ,373 + ,122844 + ,444477 + ,0 + ,12988 + ,119 + ,82340 + ,857217 + ,0 + ,22330 + ,84 + ,79801 + ,711969 + ,1 + ,13326 + ,102 + ,165548 + ,702380 + ,1 + ,16189 + ,295 + ,116384 + ,358589 + ,1 + ,7146 + ,105 + ,134028 + ,297978 + ,1 + ,15824 + ,64 + ,63838 + ,585715 + ,0 + ,27664 + ,282 + ,74996 + ,657954 + ,1 + ,11920 + ,182 + ,31080 + ,209458 + ,1 + ,8568 + ,37 + ,32168 + ,786690 + ,1 + ,14416 + ,361 + ,49857 + ,439798 + ,0 + ,3369 + ,28 + ,87161 + ,688779 + ,0 + ,11819 + ,85 + ,106113 + ,574339 + ,0 + ,6984 + ,45 + ,80570 + ,741409 + ,0 + ,4519 + ,49 + ,102129 + ,597793 + ,1 + ,2220 + ,22 + ,301670 + ,644190 + ,1 + ,18562 + ,155 + ,102313 + ,377934 + ,1 + ,10327 + ,91 + ,88577 + ,640273 + ,0 + ,5336 + ,81 + ,112477 + ,697458 + ,0 + ,2365 + ,79 + ,191778 + ,550608 + ,1 + ,4069 + ,145 + ,79804 + ,207393 + ,1 + ,8636 + ,855 + ,128294 + ,301607 + ,1 + ,13718 + ,61 + ,96448 + ,345783 + ,1 + ,4525 + ,226 + ,93811 + ,501749 + ,1 + ,6869 + ,105 + ,117520 + ,379983 + ,1 + ,4628 + ,62 + ,69159 + ,387475 + ,0 + ,3689 + ,25 + ,101792 + ,377305 + ,0 + ,4891 + ,217 + ,210568 + ,370837 + ,0 + ,7489 + ,322 + ,136996 + ,430866 + ,1 + ,4901 + ,84 + ,121920 + ,469107 + ,1 + ,2284 + ,33 + ,76403 + ,194493 + ,0 + ,3160 + ,108 + ,108094 + ,530670 + ,0 + ,4150 + ,150 + ,134759 + ,518365 + ,0 + ,7285 + ,115 + ,188873 + ,491303 + ,0 + ,1134 + ,162 + ,146216 + ,527021 + ,0 + ,4658 + ,158 + ,156608 + ,233773 + ,1 + ,2384 + ,97 + ,61348 + ,405972 + ,1 + ,3748 + ,9 + ,50350 + ,652925 + ,1 + ,5371 + ,66 + ,87720 + ,446211 + ,1 + ,1285 + ,107 + ,99489 + ,341340 + ,0 + ,9327 + ,101 + ,87419 + ,387699 + ,0 + ,5565 + ,47 + ,94355 + ,493408 + ,1 + ,1528 + ,38 + ,60326 + ,146494 + ,0 + ,3122 + ,34 + ,94670 + ,414462 + ,0 + ,7561 + ,87 + ,82425 + ,364304 + ,1 + ,2675 + ,79 + ,59017 + ,355178 + ,1 + ,13253 + ,947 + ,90829 + ,357760 + ,1 + ,880 + ,74 + ,80791 + ,261216 + ,0 + ,2053 + ,53 + ,100423 + ,397144 + ,1 + ,1424 + ,94 + ,131116 + ,374943 + ,0 + ,4036 + ,63 + ,100269 + ,424898 + ,0 + ,3045 + ,58 + ,27330 + ,202055 + ,1 + ,5119 + ,49 + ,39039 + ,378525 + ,1 + ,1431 + ,34 + ,106885 + ,310768 + ,1 + ,554 + ,11 + ,79285 + ,325738 + ,1 + ,1975 + ,35 + ,118881 + ,394510 + ,0 + ,1765 + ,20 + ,77623 + ,247060 + ,1 + ,1012 + ,47 + ,114768 + ,368078 + ,1 + ,810 + ,43 + ,74015 + ,236761 + ,1 + ,1280 + ,117 + ,69465 + ,312378 + ,0 + ,666 + ,171 + ,117869 + ,339836 + ,1 + ,1380 + ,26 + ,60982 + ,347385 + ,0 + ,4677 + ,75 + ,90131 + ,426280 + ,1 + ,876 + ,59 + ,138971 + ,352850 + ,1 + ,814 + ,18 + ,39625 + ,301881 + ,1 + ,514 + ,15 + ,102725 + ,377516 + ,0 + ,5692 + ,72 + ,64239 + ,357312 + ,1 + ,3642 + ,86 + ,90262 + ,458343 + ,1 + ,540 + ,14 + ,103960 + ,354228 + ,1 + ,2099 + ,64 + ,106611 + ,308636 + ,1 + ,567 + ,11 + ,103345 + ,386212 + ,1 + ,2001 + ,52 + ,95551 + ,393343 + ,0 + ,2949 + ,41 + ,82903 + ,378509 + ,1 + ,2253 + ,99 + ,63593 + ,452469 + ,0 + ,6533 + ,75 + ,126910 + ,364839 + ,1 + ,1889 + ,45 + ,37527 + ,358649 + ,0 + ,3055 + ,43 + ,60247 + ,376641 + ,1 + ,272 + ,8 + ,112995 + ,429112 + ,0 + ,1414 + ,198 + ,70184 + ,330546 + ,1 + ,2564 + ,22 + ,130140 + ,403560 + ,0 + ,1383 + ,11 + ,73221 + ,317892) + ,dim=c(5 + ,100) + ,dimnames=list(c('Group' + ,'Costs' + ,'Trades' + ,'Dividends' + ,'Wealth') + ,1:100)) > y <- array(NA,dim=c(5,100),dimnames=list(c('Group','Costs','Trades','Dividends','Wealth'),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 = '5' > #'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 Wealth Group Costs Trades Dividends 1 6282154 0 162556 1081 213118 2 4321023 0 29790 309 81767 3 4111912 0 87550 458 153198 4 223193 1 84738 588 -26007 5 1491348 0 54660 302 126942 6 1629616 0 42634 156 157214 7 1398893 1 40949 481 129352 8 1926517 0 45187 353 234817 9 983660 0 37704 452 60448 10 1443586 0 16275 109 47818 11 1073089 1 25830 115 245546 12 984885 1 12679 110 48020 13 1405225 0 18014 239 -1710 14 227132 1 43556 247 32648 15 929118 0 24811 505 95350 16 1071292 1 6575 159 151352 17 638830 1 7123 109 288170 18 856956 0 21950 519 114337 19 992426 0 37597 248 37884 20 444477 1 17821 373 122844 21 857217 0 12988 119 82340 22 711969 0 22330 84 79801 23 702380 1 13326 102 165548 24 358589 1 16189 295 116384 25 297978 1 7146 105 134028 26 585715 1 15824 64 63838 27 657954 0 27664 282 74996 28 209458 1 11920 182 31080 29 786690 1 8568 37 32168 30 439798 1 14416 361 49857 31 688779 0 3369 28 87161 32 574339 0 11819 85 106113 33 741409 0 6984 45 80570 34 597793 0 4519 49 102129 35 644190 1 2220 22 301670 36 377934 1 18562 155 102313 37 640273 1 10327 91 88577 38 697458 0 5336 81 112477 39 550608 0 2365 79 191778 40 207393 1 4069 145 79804 41 301607 1 8636 855 128294 42 345783 1 13718 61 96448 43 501749 1 4525 226 93811 44 379983 1 6869 105 117520 45 387475 1 4628 62 69159 46 377305 0 3689 25 101792 47 370837 0 4891 217 210568 48 430866 0 7489 322 136996 49 469107 1 4901 84 121920 50 194493 1 2284 33 76403 51 530670 0 3160 108 108094 52 518365 0 4150 150 134759 53 491303 0 7285 115 188873 54 527021 0 1134 162 146216 55 233773 0 4658 158 156608 56 405972 1 2384 97 61348 57 652925 1 3748 9 50350 58 446211 1 5371 66 87720 59 341340 1 1285 107 99489 60 387699 0 9327 101 87419 61 493408 0 5565 47 94355 62 146494 1 1528 38 60326 63 414462 0 3122 34 94670 64 364304 0 7561 87 82425 65 355178 1 2675 79 59017 66 357760 1 13253 947 90829 67 261216 1 880 74 80791 68 397144 0 2053 53 100423 69 374943 1 1424 94 131116 70 424898 0 4036 63 100269 71 202055 0 3045 58 27330 72 378525 1 5119 49 39039 73 310768 1 1431 34 106885 74 325738 1 554 11 79285 75 394510 1 1975 35 118881 76 247060 0 1765 20 77623 77 368078 1 1012 47 114768 78 236761 1 810 43 74015 79 312378 1 1280 117 69465 80 339836 0 666 171 117869 81 347385 1 1380 26 60982 82 426280 0 4677 75 90131 83 352850 1 876 59 138971 84 301881 1 814 18 39625 85 377516 1 514 15 102725 86 357312 0 5692 72 64239 87 458343 1 3642 86 90262 88 354228 1 540 14 103960 89 308636 1 2099 64 106611 90 386212 1 567 11 103345 91 393343 1 2001 52 95551 92 378509 0 2949 41 82903 93 452469 1 2253 99 63593 94 364839 0 6533 75 126910 95 358649 1 1889 45 37527 96 376641 0 3055 43 60247 97 429112 1 272 8 112995 98 330546 0 1414 198 70184 99 403560 1 2564 22 130140 100 317892 0 1383 11 73221 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Group Costs Trades Dividends 2.052e+05 -2.103e+05 3.068e+01 -3.246e+02 2.373e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -2118699 -167993 -13843 128253 3108199 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.052e+05 1.266e+05 1.620 0.1084 Group -2.103e+05 1.002e+05 -2.098 0.0386 * Costs 3.068e+01 3.191e+00 9.615 1.1e-15 *** Trades -3.246e+02 3.586e+02 -0.905 0.3677 Dividends 2.373e+00 9.269e-01 2.560 0.0120 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 487500 on 95 degrees of freedom Multiple R-squared: 0.674, Adjusted R-squared: 0.6603 F-statistic: 49.11 on 4 and 95 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,] 1.0000000 1.149510e-15 5.747548e-16 [2,] 1.0000000 6.501924e-24 3.250962e-24 [3,] 1.0000000 9.838985e-26 4.919492e-26 [4,] 1.0000000 1.093317e-25 5.466584e-26 [5,] 1.0000000 5.569551e-28 2.784775e-28 [6,] 1.0000000 1.199069e-31 5.995345e-32 [7,] 1.0000000 6.145062e-34 3.072531e-34 [8,] 1.0000000 6.804677e-35 3.402339e-35 [9,] 1.0000000 1.813588e-38 9.067940e-39 [10,] 1.0000000 1.006113e-37 5.030564e-38 [11,] 1.0000000 4.146459e-38 2.073229e-38 [12,] 1.0000000 6.457182e-38 3.228591e-38 [13,] 1.0000000 4.805932e-37 2.402966e-37 [14,] 1.0000000 1.287432e-37 6.437162e-38 [15,] 1.0000000 3.965084e-37 1.982542e-37 [16,] 1.0000000 1.390437e-36 6.952183e-37 [17,] 1.0000000 6.303613e-36 3.151807e-36 [18,] 1.0000000 2.304466e-35 1.152233e-35 [19,] 1.0000000 1.072559e-34 5.362794e-35 [20,] 1.0000000 2.822984e-34 1.411492e-34 [21,] 1.0000000 4.275950e-34 2.137975e-34 [22,] 1.0000000 5.710565e-36 2.855282e-36 [23,] 1.0000000 3.735881e-35 1.867940e-35 [24,] 1.0000000 1.524535e-35 7.622677e-36 [25,] 1.0000000 6.170279e-35 3.085139e-35 [26,] 1.0000000 6.030711e-36 3.015355e-36 [27,] 1.0000000 8.718315e-36 4.359157e-36 [28,] 1.0000000 4.625266e-35 2.312633e-35 [29,] 1.0000000 1.460461e-34 7.302307e-35 [30,] 1.0000000 1.126734e-34 5.633670e-35 [31,] 1.0000000 8.826448e-36 4.413224e-36 [32,] 1.0000000 2.496123e-35 1.248061e-35 [33,] 1.0000000 4.685161e-35 2.342581e-35 [34,] 1.0000000 3.159456e-34 1.579728e-34 [35,] 1.0000000 8.850116e-34 4.425058e-34 [36,] 1.0000000 2.131976e-33 1.065988e-33 [37,] 1.0000000 1.455305e-32 7.276523e-33 [38,] 1.0000000 1.084196e-31 5.420979e-32 [39,] 1.0000000 7.412173e-31 3.706087e-31 [40,] 1.0000000 2.027283e-30 1.013641e-30 [41,] 1.0000000 1.330207e-29 6.651035e-30 [42,] 1.0000000 8.833899e-29 4.416949e-29 [43,] 1.0000000 1.098503e-28 5.492516e-29 [44,] 1.0000000 1.660361e-28 8.301805e-29 [45,] 1.0000000 4.020852e-28 2.010426e-28 [46,] 1.0000000 2.465482e-27 1.232741e-27 [47,] 1.0000000 8.748733e-28 4.374366e-28 [48,] 1.0000000 8.178200e-28 4.089100e-28 [49,] 1.0000000 4.680325e-27 2.340163e-27 [50,] 1.0000000 5.301790e-30 2.650895e-30 [51,] 1.0000000 4.019791e-29 2.009895e-29 [52,] 1.0000000 4.113444e-28 2.056722e-28 [53,] 1.0000000 2.737689e-27 1.368844e-27 [54,] 1.0000000 9.166718e-27 4.583359e-27 [55,] 1.0000000 5.886556e-28 2.943278e-28 [56,] 1.0000000 4.196695e-27 2.098347e-27 [57,] 1.0000000 3.585171e-26 1.792585e-26 [58,] 1.0000000 3.887099e-25 1.943549e-25 [59,] 1.0000000 2.634617e-24 1.317308e-24 [60,] 1.0000000 9.038535e-24 4.519267e-24 [61,] 1.0000000 5.550277e-23 2.775138e-23 [62,] 1.0000000 5.822142e-22 2.911071e-22 [63,] 1.0000000 3.457048e-21 1.728524e-21 [64,] 1.0000000 4.960305e-21 2.480152e-21 [65,] 1.0000000 5.302941e-20 2.651471e-20 [66,] 1.0000000 3.137319e-19 1.568660e-19 [67,] 1.0000000 3.363604e-18 1.681802e-18 [68,] 1.0000000 3.714660e-17 1.857330e-17 [69,] 1.0000000 1.167859e-16 5.839297e-17 [70,] 1.0000000 1.312036e-15 6.560181e-16 [71,] 1.0000000 6.973451e-16 3.486726e-16 [72,] 1.0000000 3.744969e-15 1.872485e-15 [73,] 1.0000000 4.758931e-14 2.379466e-14 [74,] 1.0000000 5.093667e-13 2.546834e-13 [75,] 1.0000000 3.142222e-12 1.571111e-12 [76,] 1.0000000 2.826536e-11 1.413268e-11 [77,] 1.0000000 9.543906e-11 4.771953e-11 [78,] 1.0000000 1.208650e-09 6.043251e-10 [79,] 1.0000000 1.319321e-08 6.596604e-09 [80,] 1.0000000 8.340256e-08 4.170128e-08 [81,] 0.9999996 8.184116e-07 4.092058e-07 [82,] 0.9999995 1.040498e-06 5.202489e-07 [83,] 0.9999928 1.435868e-05 7.179340e-06 [84,] 0.9999081 1.838548e-04 9.192742e-05 [85,] 0.9990223 1.955347e-03 9.776735e-04 > postscript(file="/var/www/html/freestat/rcomp/tmp/1y4381291392198.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2rwks1291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3rwks1291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4rwks1291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5252d1291392198.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 935301.699 3108199.099 1006023.279 -2118698.544 -593892.459 -205923.000 7 8 9 10 11 12 -3072.106 -107555.022 -374939.913 661013.370 -259589.926 522753.913 13 14 15 16 17 18 729029.653 -1101276.542 -99581.379 567109.219 -223064.876 -124488.452 19 20 21 22 23 24 -375558.353 -267594.388 96804.587 -340365.032 -61092.721 -313403.670 25 26 27 28 29 30 -200137.866 -25362.669 -482345.650 -165821.120 464596.823 1487.822 31 32 33 34 35 36 182475.008 -217660.947 145365.018 27506.656 -127567.573 -378904.444 37 38 39 40 41 42 147885.227 87938.450 -156601.856 -54671.337 14814.867 -279046.440 43 44 45 46 47 48 218746.871 -70461.368 106583.801 -174509.148 -413662.363 -224665.013 49 50 51 52 53 54 61778.221 -41093.392 7068.445 -85251.898 -348260.836 -7366.253 55 56 57 58 59 60 -434679.626 223816.123 426461.914 99779.156 105634.541 -278298.824 61 62 63 64 65 66 -91167.984 -26126.426 -100136.351 -240210.865 163784.343 48096.647 67 68 69 70 71 72 71594.913 -92145.597 55702.352 -121613.456 -142592.054 149827.410 73 74 75 76 77 78 29339.313 129243.696 68250.647 -190000.314 85015.905 55305.336 79 80 81 82 83 84 151319.316 -110005.043 173853.288 -111943.028 20420.495 193796.768 85 86 87 88 89 90 127923.346 -151579.769 165411.246 100582.483 17102.157 132223.904 91 92 93 94 95 96 127166.372 -100586.824 269653.536 -317598.497 231328.665 -51294.217 97 98 99 100 160300.295 -20320.583 28294.474 -99924.659 > postscript(file="/var/www/html/freestat/rcomp/tmp/6252d1291392198.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 935301.699 NA 1 3108199.099 935301.699 2 1006023.279 3108199.099 3 -2118698.544 1006023.279 4 -593892.459 -2118698.544 5 -205923.000 -593892.459 6 -3072.106 -205923.000 7 -107555.022 -3072.106 8 -374939.913 -107555.022 9 661013.370 -374939.913 10 -259589.926 661013.370 11 522753.913 -259589.926 12 729029.653 522753.913 13 -1101276.542 729029.653 14 -99581.379 -1101276.542 15 567109.219 -99581.379 16 -223064.876 567109.219 17 -124488.452 -223064.876 18 -375558.353 -124488.452 19 -267594.388 -375558.353 20 96804.587 -267594.388 21 -340365.032 96804.587 22 -61092.721 -340365.032 23 -313403.670 -61092.721 24 -200137.866 -313403.670 25 -25362.669 -200137.866 26 -482345.650 -25362.669 27 -165821.120 -482345.650 28 464596.823 -165821.120 29 1487.822 464596.823 30 182475.008 1487.822 31 -217660.947 182475.008 32 145365.018 -217660.947 33 27506.656 145365.018 34 -127567.573 27506.656 35 -378904.444 -127567.573 36 147885.227 -378904.444 37 87938.450 147885.227 38 -156601.856 87938.450 39 -54671.337 -156601.856 40 14814.867 -54671.337 41 -279046.440 14814.867 42 218746.871 -279046.440 43 -70461.368 218746.871 44 106583.801 -70461.368 45 -174509.148 106583.801 46 -413662.363 -174509.148 47 -224665.013 -413662.363 48 61778.221 -224665.013 49 -41093.392 61778.221 50 7068.445 -41093.392 51 -85251.898 7068.445 52 -348260.836 -85251.898 53 -7366.253 -348260.836 54 -434679.626 -7366.253 55 223816.123 -434679.626 56 426461.914 223816.123 57 99779.156 426461.914 58 105634.541 99779.156 59 -278298.824 105634.541 60 -91167.984 -278298.824 61 -26126.426 -91167.984 62 -100136.351 -26126.426 63 -240210.865 -100136.351 64 163784.343 -240210.865 65 48096.647 163784.343 66 71594.913 48096.647 67 -92145.597 71594.913 68 55702.352 -92145.597 69 -121613.456 55702.352 70 -142592.054 -121613.456 71 149827.410 -142592.054 72 29339.313 149827.410 73 129243.696 29339.313 74 68250.647 129243.696 75 -190000.314 68250.647 76 85015.905 -190000.314 77 55305.336 85015.905 78 151319.316 55305.336 79 -110005.043 151319.316 80 173853.288 -110005.043 81 -111943.028 173853.288 82 20420.495 -111943.028 83 193796.768 20420.495 84 127923.346 193796.768 85 -151579.769 127923.346 86 165411.246 -151579.769 87 100582.483 165411.246 88 17102.157 100582.483 89 132223.904 17102.157 90 127166.372 132223.904 91 -100586.824 127166.372 92 269653.536 -100586.824 93 -317598.497 269653.536 94 231328.665 -317598.497 95 -51294.217 231328.665 96 160300.295 -51294.217 97 -20320.583 160300.295 98 28294.474 -20320.583 99 -99924.659 28294.474 100 NA -99924.659 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 3108199.099 935301.699 [2,] 1006023.279 3108199.099 [3,] -2118698.544 1006023.279 [4,] -593892.459 -2118698.544 [5,] -205923.000 -593892.459 [6,] -3072.106 -205923.000 [7,] -107555.022 -3072.106 [8,] -374939.913 -107555.022 [9,] 661013.370 -374939.913 [10,] -259589.926 661013.370 [11,] 522753.913 -259589.926 [12,] 729029.653 522753.913 [13,] -1101276.542 729029.653 [14,] -99581.379 -1101276.542 [15,] 567109.219 -99581.379 [16,] -223064.876 567109.219 [17,] -124488.452 -223064.876 [18,] -375558.353 -124488.452 [19,] -267594.388 -375558.353 [20,] 96804.587 -267594.388 [21,] -340365.032 96804.587 [22,] -61092.721 -340365.032 [23,] -313403.670 -61092.721 [24,] -200137.866 -313403.670 [25,] -25362.669 -200137.866 [26,] -482345.650 -25362.669 [27,] -165821.120 -482345.650 [28,] 464596.823 -165821.120 [29,] 1487.822 464596.823 [30,] 182475.008 1487.822 [31,] -217660.947 182475.008 [32,] 145365.018 -217660.947 [33,] 27506.656 145365.018 [34,] -127567.573 27506.656 [35,] -378904.444 -127567.573 [36,] 147885.227 -378904.444 [37,] 87938.450 147885.227 [38,] -156601.856 87938.450 [39,] -54671.337 -156601.856 [40,] 14814.867 -54671.337 [41,] -279046.440 14814.867 [42,] 218746.871 -279046.440 [43,] -70461.368 218746.871 [44,] 106583.801 -70461.368 [45,] -174509.148 106583.801 [46,] -413662.363 -174509.148 [47,] -224665.013 -413662.363 [48,] 61778.221 -224665.013 [49,] -41093.392 61778.221 [50,] 7068.445 -41093.392 [51,] -85251.898 7068.445 [52,] -348260.836 -85251.898 [53,] -7366.253 -348260.836 [54,] -434679.626 -7366.253 [55,] 223816.123 -434679.626 [56,] 426461.914 223816.123 [57,] 99779.156 426461.914 [58,] 105634.541 99779.156 [59,] -278298.824 105634.541 [60,] -91167.984 -278298.824 [61,] -26126.426 -91167.984 [62,] -100136.351 -26126.426 [63,] -240210.865 -100136.351 [64,] 163784.343 -240210.865 [65,] 48096.647 163784.343 [66,] 71594.913 48096.647 [67,] -92145.597 71594.913 [68,] 55702.352 -92145.597 [69,] -121613.456 55702.352 [70,] -142592.054 -121613.456 [71,] 149827.410 -142592.054 [72,] 29339.313 149827.410 [73,] 129243.696 29339.313 [74,] 68250.647 129243.696 [75,] -190000.314 68250.647 [76,] 85015.905 -190000.314 [77,] 55305.336 85015.905 [78,] 151319.316 55305.336 [79,] -110005.043 151319.316 [80,] 173853.288 -110005.043 [81,] -111943.028 173853.288 [82,] 20420.495 -111943.028 [83,] 193796.768 20420.495 [84,] 127923.346 193796.768 [85,] -151579.769 127923.346 [86,] 165411.246 -151579.769 [87,] 100582.483 165411.246 [88,] 17102.157 100582.483 [89,] 132223.904 17102.157 [90,] 127166.372 132223.904 [91,] -100586.824 127166.372 [92,] 269653.536 -100586.824 [93,] -317598.497 269653.536 [94,] 231328.665 -317598.497 [95,] -51294.217 231328.665 [96,] 160300.295 -51294.217 [97,] -20320.583 160300.295 [98,] 28294.474 -20320.583 [99,] -99924.659 28294.474 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 3108199.099 935301.699 2 1006023.279 3108199.099 3 -2118698.544 1006023.279 4 -593892.459 -2118698.544 5 -205923.000 -593892.459 6 -3072.106 -205923.000 7 -107555.022 -3072.106 8 -374939.913 -107555.022 9 661013.370 -374939.913 10 -259589.926 661013.370 11 522753.913 -259589.926 12 729029.653 522753.913 13 -1101276.542 729029.653 14 -99581.379 -1101276.542 15 567109.219 -99581.379 16 -223064.876 567109.219 17 -124488.452 -223064.876 18 -375558.353 -124488.452 19 -267594.388 -375558.353 20 96804.587 -267594.388 21 -340365.032 96804.587 22 -61092.721 -340365.032 23 -313403.670 -61092.721 24 -200137.866 -313403.670 25 -25362.669 -200137.866 26 -482345.650 -25362.669 27 -165821.120 -482345.650 28 464596.823 -165821.120 29 1487.822 464596.823 30 182475.008 1487.822 31 -217660.947 182475.008 32 145365.018 -217660.947 33 27506.656 145365.018 34 -127567.573 27506.656 35 -378904.444 -127567.573 36 147885.227 -378904.444 37 87938.450 147885.227 38 -156601.856 87938.450 39 -54671.337 -156601.856 40 14814.867 -54671.337 41 -279046.440 14814.867 42 218746.871 -279046.440 43 -70461.368 218746.871 44 106583.801 -70461.368 45 -174509.148 106583.801 46 -413662.363 -174509.148 47 -224665.013 -413662.363 48 61778.221 -224665.013 49 -41093.392 61778.221 50 7068.445 -41093.392 51 -85251.898 7068.445 52 -348260.836 -85251.898 53 -7366.253 -348260.836 54 -434679.626 -7366.253 55 223816.123 -434679.626 56 426461.914 223816.123 57 99779.156 426461.914 58 105634.541 99779.156 59 -278298.824 105634.541 60 -91167.984 -278298.824 61 -26126.426 -91167.984 62 -100136.351 -26126.426 63 -240210.865 -100136.351 64 163784.343 -240210.865 65 48096.647 163784.343 66 71594.913 48096.647 67 -92145.597 71594.913 68 55702.352 -92145.597 69 -121613.456 55702.352 70 -142592.054 -121613.456 71 149827.410 -142592.054 72 29339.313 149827.410 73 129243.696 29339.313 74 68250.647 129243.696 75 -190000.314 68250.647 76 85015.905 -190000.314 77 55305.336 85015.905 78 151319.316 55305.336 79 -110005.043 151319.316 80 173853.288 -110005.043 81 -111943.028 173853.288 82 20420.495 -111943.028 83 193796.768 20420.495 84 127923.346 193796.768 85 -151579.769 127923.346 86 165411.246 -151579.769 87 100582.483 165411.246 88 17102.157 100582.483 89 132223.904 17102.157 90 127166.372 132223.904 91 -100586.824 127166.372 92 269653.536 -100586.824 93 -317598.497 269653.536 94 231328.665 -317598.497 95 -51294.217 231328.665 96 160300.295 -51294.217 97 -20320.583 160300.295 98 28294.474 -20320.583 99 -99924.659 28294.474 > 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/7cejg1291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8cejg1291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9nn011291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10nn011291392198.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/1186hp1291392198.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/12coxd1291392198.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/131qcp1291392198.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/14thtr1291392198.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/15ezaf1291392198.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/16t98o1291392198.tab") + } > > try(system("convert tmp/1y4381291392198.ps tmp/1y4381291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/2rwks1291392198.ps tmp/2rwks1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/3rwks1291392198.ps tmp/3rwks1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/4rwks1291392198.ps tmp/4rwks1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/5252d1291392198.ps tmp/5252d1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/6252d1291392198.ps tmp/6252d1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/7cejg1291392198.ps tmp/7cejg1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/8cejg1291392198.ps tmp/8cejg1291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/9nn011291392198.ps tmp/9nn011291392198.png",intern=TRUE)) character(0) > try(system("convert tmp/10nn011291392198.ps tmp/10nn011291392198.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.589 2.671 5.066