R version 2.9.0 (2009-04-17) Copyright (C) 2009 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. 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 + ,162556 + ,1081 + ,1081 + ,213118 + ,213118 + ,6282929 + ,1 + ,29790 + ,29790 + ,309 + ,309 + ,81767 + ,81767 + ,4324047 + ,1 + ,87550 + ,87550 + ,458 + ,458 + ,153198 + ,153198 + ,4108272 + ,0 + ,84738 + ,0 + ,588 + ,0 + ,-26007 + ,0 + ,-1212617 + ,1 + ,54660 + ,54660 + ,299 + ,299 + ,126942 + ,126942 + ,1485329 + ,1 + ,42634 + ,42634 + ,156 + ,156 + ,157214 + ,157214 + ,1779876 + ,0 + ,40949 + ,0 + ,481 + ,0 + ,129352 + ,0 + ,1367203 + ,1 + ,42312 + ,42312 + ,323 + ,323 + ,234817 + ,234817 + ,2519076 + ,1 + ,37704 + ,37704 + ,452 + ,452 + ,60448 + ,60448 + ,912684 + ,1 + ,16275 + ,16275 + ,109 + ,109 + ,47818 + ,47818 + ,1443586 + ,0 + ,25830 + ,0 + ,115 + ,0 + ,245546 + ,0 + ,1220017 + ,0 + ,12679 + ,0 + ,110 + ,0 + ,48020 + ,0 + ,984885 + ,1 + ,18014 + ,18014 + ,239 + ,239 + ,-1710 + ,-1710 + ,1457425 + ,0 + ,43556 + ,0 + ,247 + ,0 + ,32648 + ,0 + ,-572920 + ,1 + ,24524 + ,24524 + ,497 + ,497 + ,95350 + ,95350 + ,929144 + ,0 + ,6532 + ,0 + ,103 + ,0 + ,151352 + ,0 + ,1151176 + ,0 + ,7123 + ,0 + ,109 + ,0 + ,288170 + ,0 + ,790090 + ,1 + ,20813 + ,20813 + ,502 + ,502 + ,114337 + ,114337 + ,774497 + ,1 + ,37597 + ,37597 + ,248 + ,248 + ,37884 + ,37884 + ,990576 + ,0 + ,17821 + ,0 + ,373 + ,0 + ,122844 + ,0 + ,454195 + ,1 + ,12988 + ,12988 + ,119 + ,119 + ,82340 + ,82340 + ,876607 + ,1 + ,22330 + ,22330 + ,84 + ,84 + ,79801 + ,79801 + ,711969 + ,0 + ,13326 + ,0 + ,102 + ,0 + ,165548 + ,0 + ,702380 + ,0 + ,16189 + ,0 + ,295 + ,0 + ,116384 + ,0 + ,264449 + ,0 + ,7146 + ,0 + ,105 + ,0 + ,134028 + ,0 + ,450033 + ,0 + ,15824 + ,0 + ,64 + ,0 + ,63838 + ,0 + ,541063 + ,1 + ,26088 + ,26088 + ,267 + ,267 + ,74996 + ,74996 + ,588864 + ,0 + ,11326 + ,0 + ,129 + ,0 + ,31080 + ,0 + ,-37216 + ,0 + ,8568 + ,0 + ,37 + ,0 + ,32168 + ,0 + ,783310 + ,0 + ,14416 + ,0 + ,361 + ,0 + ,49857 + ,0 + ,467359 + ,1 + ,3369 + ,3369 + ,28 + ,28 + ,87161 + ,87161 + ,688779 + ,1 + ,11819 + ,11819 + ,85 + ,85 + ,106113 + ,106113 + ,608419 + ,1 + ,6620 + ,6620 + ,44 + ,44 + ,80570 + ,80570 + ,696348 + ,1 + ,4519 + ,4519 + ,49 + ,49 + ,102129 + ,102129 + ,597793 + ,0 + ,2220 + ,0 + ,22 + ,0 + ,301670 + ,0 + ,821730 + ,0 + ,18562 + ,0 + ,155 + ,0 + ,102313 + ,0 + ,377934 + ,0 + ,10327 + ,0 + ,91 + ,0 + ,88577 + ,0 + ,651939 + ,1 + ,5336 + ,5336 + ,81 + ,81 + ,112477 + ,112477 + ,697458 + ,1 + ,2365 + ,2365 + ,79 + ,79 + ,191778 + ,191778 + ,700368 + ,0 + ,4069 + ,0 + ,145 + ,0 + ,79804 + ,0 + ,225986 + ,0 + ,7710 + ,0 + ,816 + ,0 + ,128294 + ,0 + ,348695 + ,0 + ,13718 + ,0 + ,61 + ,0 + ,96448 + ,0 + ,373683 + ,0 + ,4525 + ,0 + ,226 + ,0 + ,93811 + ,0 + ,501709 + ,0 + ,6869 + ,0 + ,105 + ,0 + ,117520 + ,0 + ,413743 + ,0 + ,4628 + ,0 + ,62 + ,0 + ,69159 + ,0 + ,379825 + ,1 + ,3653 + ,3653 + ,24 + ,24 + ,101792 + ,101792 + ,336260 + ,1 + ,1265 + ,1265 + ,26 + ,26 + ,210568 + ,210568 + ,636765 + ,1 + ,7489 + ,7489 + ,322 + ,322 + ,136996 + ,136996 + ,481231 + ,0 + ,4901 + ,0 + ,84 + ,0 + ,121920 + ,0 + ,469107 + ,0 + ,2284 + ,0 + ,33 + ,0 + ,76403 + ,0 + ,211928 + ,1 + ,3160 + ,3160 + ,108 + ,108 + ,108094 + ,108094 + ,563925 + ,1 + ,4150 + ,4150 + ,150 + ,150 + ,134759 + ,134759 + ,511939 + ,1 + ,7285 + ,7285 + ,115 + ,115 + ,188873 + ,188873 + ,521016 + ,1 + ,1134 + ,1134 + ,162 + ,162 + ,146216 + ,146216 + ,543856 + ,1 + ,4658 + ,4658 + ,158 + ,158 + ,156608 + ,156608 + ,329304 + ,0 + ,2384 + ,0 + ,97 + ,0 + ,61348 + ,0 + ,423262 + ,0 + ,3748 + ,0 + ,9 + ,0 + ,50350 + ,0 + ,509665 + ,0 + ,5371 + ,0 + ,66 + ,0 + ,87720 + ,0 + ,455881 + ,0 + ,1285 + ,0 + ,107 + ,0 + ,99489 + ,0 + ,367772 + ,1 + ,9327 + ,9327 + ,101 + ,101 + ,87419 + ,87419 + ,406339 + ,1 + ,5565 + ,5565 + ,47 + ,47 + ,94355 + ,94355 + ,493408 + ,0 + ,1528 + ,0 + ,38 + ,0 + ,60326 + ,0 + ,232942 + ,1 + ,3122 + ,3122 + ,34 + ,34 + ,94670 + ,94670 + ,416002 + ,1 + ,7317 + ,7317 + ,84 + ,84 + ,82425 + ,82425 + ,337430 + ,0 + ,2675 + ,0 + ,79 + ,0 + ,59017 + ,0 + ,361517 + ,0 + ,13253 + ,0 + ,947 + ,0 + ,90829 + ,0 + ,360962 + ,0 + ,880 + ,0 + ,74 + ,0 + ,80791 + ,0 + ,235561 + ,1 + ,2053 + ,2053 + ,53 + ,53 + ,100423 + ,100423 + ,408247 + ,0 + ,1424 + ,0 + ,94 + ,0 + ,131116 + ,0 + ,450296 + ,1 + ,4036 + ,4036 + ,63 + ,63 + ,100269 + ,100269 + ,418799 + ,1 + ,3045 + ,3045 + ,58 + ,58 + ,27330 + ,27330 + ,247405 + ,0 + ,5119 + ,0 + ,49 + ,0 + ,39039 + ,0 + ,378519 + ,0 + ,1431 + ,0 + ,34 + ,0 + ,106885 + ,0 + ,326638 + ,0 + ,554 + ,0 + ,11 + ,0 + ,79285 + ,0 + ,328233 + ,0 + ,1975 + ,0 + ,35 + ,0 + ,118881 + ,0 + ,386225 + ,1 + ,1286 + ,1286 + ,17 + ,17 + ,77623 + ,77623 + ,283662 + ,0 + ,1012 + ,0 + ,47 + ,0 + ,114768 + ,0 + ,370225 + ,0 + ,810 + ,0 + ,43 + ,0 + ,74015 + ,0 + ,269236 + ,0 + ,1280 + ,0 + ,117 + ,0 + ,69465 + ,0 + ,365732 + ,1 + ,666 + ,666 + ,171 + ,171 + ,117869 + ,117869 + ,420383 + ,0 + ,1380 + ,0 + ,26 + ,0 + ,60982 + ,0 + ,345811 + ,1 + ,4608 + ,4608 + ,73 + ,73 + ,90131 + ,90131 + ,431809 + ,0 + ,876 + ,0 + ,59 + ,0 + ,138971 + ,0 + ,418876 + ,0 + ,814 + ,0 + ,18 + ,0 + ,39625 + ,0 + ,297476 + ,0 + ,514 + ,0 + ,15 + ,0 + ,102725 + ,0 + ,416776 + ,1 + ,5692 + ,5692 + ,72 + ,72 + ,64239 + ,64239 + ,357257 + ,0 + ,3642 + ,0 + ,86 + ,0 + ,90262 + ,0 + ,458343 + ,0 + ,540 + ,0 + ,14 + ,0 + ,103960 + ,0 + ,388386 + ,0 + ,2099 + ,0 + ,64 + ,0 + ,106611 + ,0 + ,358934 + ,0 + ,567 + ,0 + ,11 + ,0 + ,103345 + ,0 + ,407560 + ,0 + ,2001 + ,0 + ,52 + ,0 + ,95551 + ,0 + ,392558 + ,1 + ,2949 + ,2949 + ,41 + ,41 + ,82903 + ,82903 + ,373177 + ,0 + ,2253 + ,0 + ,99 + ,0 + ,63593 + ,0 + ,428370 + ,1 + ,6533 + ,6533 + ,75 + ,75 + ,126910 + ,126910 + ,369419 + ,0 + ,1889 + ,0 + ,45 + ,0 + ,37527 + ,0 + ,358649 + ,1 + ,3055 + ,3055 + ,43 + ,43 + ,60247 + ,60247 + ,376641 + ,0 + ,272 + ,0 + ,8 + ,0 + ,112995 + ,0 + ,467427 + ,1 + ,1414 + ,1414 + ,198 + ,198 + ,70184 + ,70184 + ,364885 + ,0 + ,2564 + ,0 + ,22 + ,0 + ,130140 + ,0 + ,436230 + ,1 + ,1383 + ,1383 + ,11 + ,11 + ,73221 + ,73221 + ,329118) + ,dim=c(8 + ,100) + ,dimnames=list(c('Group' + ,'Costs' + ,'GrCosts' + ,'Trades' + ,'GrTrades' + ,'Dividends' + ,'GrDiv' + ,'Wealth') + ,1:100)) > y <- array(NA,dim=c(8,100),dimnames=list(c('Group','Costs','GrCosts','Trades','GrTrades','Dividends','GrDiv','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 = '8' > #'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 GrCosts Trades GrTrades Dividends GrDiv 1 6282929 1 162556 162556 1081 1081 213118 213118 2 4324047 1 29790 29790 309 309 81767 81767 3 4108272 1 87550 87550 458 458 153198 153198 4 -1212617 0 84738 0 588 0 -26007 0 5 1485329 1 54660 54660 299 299 126942 126942 6 1779876 1 42634 42634 156 156 157214 157214 7 1367203 0 40949 0 481 0 129352 0 8 2519076 1 42312 42312 323 323 234817 234817 9 912684 1 37704 37704 452 452 60448 60448 10 1443586 1 16275 16275 109 109 47818 47818 11 1220017 0 25830 0 115 0 245546 0 12 984885 0 12679 0 110 0 48020 0 13 1457425 1 18014 18014 239 239 -1710 -1710 14 -572920 0 43556 0 247 0 32648 0 15 929144 1 24524 24524 497 497 95350 95350 16 1151176 0 6532 0 103 0 151352 0 17 790090 0 7123 0 109 0 288170 0 18 774497 1 20813 20813 502 502 114337 114337 19 990576 1 37597 37597 248 248 37884 37884 20 454195 0 17821 0 373 0 122844 0 21 876607 1 12988 12988 119 119 82340 82340 22 711969 1 22330 22330 84 84 79801 79801 23 702380 0 13326 0 102 0 165548 0 24 264449 0 16189 0 295 0 116384 0 25 450033 0 7146 0 105 0 134028 0 26 541063 0 15824 0 64 0 63838 0 27 588864 1 26088 26088 267 267 74996 74996 28 -37216 0 11326 0 129 0 31080 0 29 783310 0 8568 0 37 0 32168 0 30 467359 0 14416 0 361 0 49857 0 31 688779 1 3369 3369 28 28 87161 87161 32 608419 1 11819 11819 85 85 106113 106113 33 696348 1 6620 6620 44 44 80570 80570 34 597793 1 4519 4519 49 49 102129 102129 35 821730 0 2220 0 22 0 301670 0 36 377934 0 18562 0 155 0 102313 0 37 651939 0 10327 0 91 0 88577 0 38 697458 1 5336 5336 81 81 112477 112477 39 700368 1 2365 2365 79 79 191778 191778 40 225986 0 4069 0 145 0 79804 0 41 348695 0 7710 0 816 0 128294 0 42 373683 0 13718 0 61 0 96448 0 43 501709 0 4525 0 226 0 93811 0 44 413743 0 6869 0 105 0 117520 0 45 379825 0 4628 0 62 0 69159 0 46 336260 1 3653 3653 24 24 101792 101792 47 636765 1 1265 1265 26 26 210568 210568 48 481231 1 7489 7489 322 322 136996 136996 49 469107 0 4901 0 84 0 121920 0 50 211928 0 2284 0 33 0 76403 0 51 563925 1 3160 3160 108 108 108094 108094 52 511939 1 4150 4150 150 150 134759 134759 53 521016 1 7285 7285 115 115 188873 188873 54 543856 1 1134 1134 162 162 146216 146216 55 329304 1 4658 4658 158 158 156608 156608 56 423262 0 2384 0 97 0 61348 0 57 509665 0 3748 0 9 0 50350 0 58 455881 0 5371 0 66 0 87720 0 59 367772 0 1285 0 107 0 99489 0 60 406339 1 9327 9327 101 101 87419 87419 61 493408 1 5565 5565 47 47 94355 94355 62 232942 0 1528 0 38 0 60326 0 63 416002 1 3122 3122 34 34 94670 94670 64 337430 1 7317 7317 84 84 82425 82425 65 361517 0 2675 0 79 0 59017 0 66 360962 0 13253 0 947 0 90829 0 67 235561 0 880 0 74 0 80791 0 68 408247 1 2053 2053 53 53 100423 100423 69 450296 0 1424 0 94 0 131116 0 70 418799 1 4036 4036 63 63 100269 100269 71 247405 1 3045 3045 58 58 27330 27330 72 378519 0 5119 0 49 0 39039 0 73 326638 0 1431 0 34 0 106885 0 74 328233 0 554 0 11 0 79285 0 75 386225 0 1975 0 35 0 118881 0 76 283662 1 1286 1286 17 17 77623 77623 77 370225 0 1012 0 47 0 114768 0 78 269236 0 810 0 43 0 74015 0 79 365732 0 1280 0 117 0 69465 0 80 420383 1 666 666 171 171 117869 117869 81 345811 0 1380 0 26 0 60982 0 82 431809 1 4608 4608 73 73 90131 90131 83 418876 0 876 0 59 0 138971 0 84 297476 0 814 0 18 0 39625 0 85 416776 0 514 0 15 0 102725 0 86 357257 1 5692 5692 72 72 64239 64239 87 458343 0 3642 0 86 0 90262 0 88 388386 0 540 0 14 0 103960 0 89 358934 0 2099 0 64 0 106611 0 90 407560 0 567 0 11 0 103345 0 91 392558 0 2001 0 52 0 95551 0 92 373177 1 2949 2949 41 41 82903 82903 93 428370 0 2253 0 99 0 63593 0 94 369419 1 6533 6533 75 75 126910 126910 95 358649 0 1889 0 45 0 37527 0 96 376641 1 3055 3055 43 43 60247 60247 97 467427 0 272 0 8 0 112995 0 98 364885 1 1414 1414 198 198 70184 70184 99 436230 0 2564 0 22 0 130140 0 100 329118 1 1383 1383 11 11 73221 73221 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Group Costs GrCosts Trades GrTrades 169088.919 44386.189 -7.976 44.982 20.889 -124.124 Dividends GrDiv 3.244 -1.982 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -880218 -164971 -58294 84173 2936875 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 169088.919 131306.033 1.288 0.20106 Group 44386.189 208024.502 0.213 0.83151 Costs -7.976 5.115 -1.559 0.12234 GrCosts 44.982 6.917 6.503 4.01e-09 *** Trades 20.889 371.116 0.056 0.95524 GrTrades -124.124 767.621 -0.162 0.87190 Dividends 3.244 1.053 3.082 0.00271 ** GrDiv -1.982 1.760 -1.126 0.26300 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 431900 on 92 degrees of freedom Multiple R-squared: 0.7737, Adjusted R-squared: 0.7565 F-statistic: 44.94 on 7 and 92 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 1.190379e-22 5.951896e-23 [2,] 1.0000000 7.096225e-24 3.548113e-24 [3,] 1.0000000 1.752406e-26 8.762028e-27 [4,] 1.0000000 8.647713e-30 4.323857e-30 [5,] 1.0000000 3.484822e-30 1.742411e-30 [6,] 1.0000000 1.549031e-33 7.745156e-34 [7,] 1.0000000 5.028888e-34 2.514444e-34 [8,] 1.0000000 1.792619e-33 8.963094e-34 [9,] 1.0000000 5.797992e-34 2.898996e-34 [10,] 1.0000000 8.329440e-34 4.164720e-34 [11,] 1.0000000 2.121156e-34 1.060578e-34 [12,] 1.0000000 5.132892e-34 2.566446e-34 [13,] 1.0000000 2.201123e-33 1.100561e-33 [14,] 1.0000000 1.923062e-33 9.615310e-34 [15,] 1.0000000 1.115834e-32 5.579170e-33 [16,] 1.0000000 6.119109e-32 3.059554e-32 [17,] 1.0000000 1.289984e-31 6.449919e-32 [18,] 1.0000000 2.084033e-33 1.042016e-33 [19,] 1.0000000 9.709997e-36 4.854999e-36 [20,] 1.0000000 5.242918e-35 2.621459e-35 [21,] 1.0000000 1.714046e-35 8.570230e-36 [22,] 1.0000000 8.169510e-35 4.084755e-35 [23,] 1.0000000 7.538136e-36 3.769068e-36 [24,] 1.0000000 1.153997e-35 5.769983e-36 [25,] 1.0000000 1.421873e-35 7.109365e-36 [26,] 1.0000000 3.082032e-35 1.541016e-35 [27,] 1.0000000 1.416904e-35 7.084521e-36 [28,] 1.0000000 4.309244e-37 2.154622e-37 [29,] 1.0000000 9.504762e-37 4.752381e-37 [30,] 1.0000000 8.310026e-37 4.155013e-37 [31,] 1.0000000 6.099214e-36 3.049607e-36 [32,] 1.0000000 9.236479e-36 4.618240e-36 [33,] 1.0000000 2.298622e-35 1.149311e-35 [34,] 1.0000000 1.105845e-34 5.529227e-35 [35,] 1.0000000 9.334162e-34 4.667081e-34 [36,] 1.0000000 4.847147e-33 2.423573e-33 [37,] 1.0000000 3.138925e-32 1.569463e-32 [38,] 1.0000000 2.872243e-31 1.436121e-31 [39,] 1.0000000 2.593747e-30 1.296874e-30 [40,] 1.0000000 7.222995e-31 3.611497e-31 [41,] 1.0000000 4.096923e-31 2.048462e-31 [42,] 1.0000000 2.256225e-30 1.128113e-30 [43,] 1.0000000 2.076865e-29 1.038433e-29 [44,] 1.0000000 3.244515e-29 1.622258e-29 [45,] 1.0000000 2.635715e-29 1.317857e-29 [46,] 1.0000000 1.146314e-28 5.731569e-29 [47,] 1.0000000 1.209813e-28 6.049063e-29 [48,] 1.0000000 1.357057e-27 6.785287e-28 [49,] 1.0000000 1.427485e-26 7.137427e-27 [50,] 1.0000000 1.405641e-25 7.028206e-26 [51,] 1.0000000 1.982275e-25 9.911375e-26 [52,] 1.0000000 2.158152e-25 1.079076e-25 [53,] 1.0000000 1.756903e-24 8.784516e-25 [54,] 1.0000000 1.472448e-23 7.362241e-24 [55,] 1.0000000 1.655217e-22 8.276087e-23 [56,] 1.0000000 1.455170e-21 7.275848e-22 [57,] 1.0000000 5.470071e-22 2.735036e-22 [58,] 1.0000000 5.209189e-21 2.604594e-21 [59,] 1.0000000 5.413749e-20 2.706875e-20 [60,] 1.0000000 4.575651e-19 2.287825e-19 [61,] 1.0000000 1.866055e-18 9.330277e-19 [62,] 1.0000000 2.132988e-17 1.066494e-17 [63,] 1.0000000 7.315406e-17 3.657703e-17 [64,] 1.0000000 6.997643e-16 3.498821e-16 [65,] 1.0000000 5.493112e-15 2.746556e-15 [66,] 1.0000000 2.449696e-14 1.224848e-14 [67,] 1.0000000 1.997491e-13 9.987453e-14 [68,] 1.0000000 1.678485e-13 8.392425e-14 [69,] 1.0000000 1.955483e-12 9.777413e-13 [70,] 1.0000000 1.919404e-11 9.597020e-12 [71,] 1.0000000 2.136631e-10 1.068315e-10 [72,] 1.0000000 8.795079e-10 4.397539e-10 [73,] 1.0000000 7.089977e-09 3.544989e-09 [74,] 1.0000000 4.317546e-08 2.158773e-08 [75,] 0.9999997 5.436366e-07 2.718183e-07 [76,] 0.9999974 5.290244e-06 2.645122e-06 [77,] 0.9999849 3.011961e-05 1.505981e-05 [78,] 0.9998661 2.678675e-04 1.339337e-04 [79,] 0.9996477 7.046941e-04 3.523471e-04 > postscript(file="/var/www/html/rcomp/tmp/1fnlq1291409893.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2fnlq1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3pwkb1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4pwkb1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5pwkb1291409893.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 -103387.0397 2936875.4516 508893.7371 -633713.8167 -880217.8319 -193617.1624 7 8 9 10 11 12 1095053.2091 476787.1991 -725675.9287 578745.3061 457965.3572 758846.4051 13 14 15 16 17 18 604167.5452 -505663.9308 -260893.9792 541027.0438 -259329.8960 -301663.7065 19 20 21 22 23 24 -636403.7071 20936.1128 90860.9998 -419889.2020 100389.4601 -159240.7445 25 26 27 28 29 30 -99058.3766 289754.9236 -657103.2585 -219487.4587 577431.7775 243972.7477 31 32 33 34 35 36 243507.6887 -167584.3847 140743.3944 93240.6806 -308777.0058 21745.2962 37 38 39 40 41 42 275963.3616 152914.4601 165465.9636 -172572.9085 -192147.7346 -152.8003 43 44 45 46 47 48 59654.3540 -84003.2243 21992.7796 -138401.2187 113380.3590 -149053.5866 49 50 51 52 53 54 -58172.4144 -187495.8185 108224.6759 -9717.6635 -188569.0372 120585.0268 55 56 57 58 59 60 -237903.6047 72139.7742 206940.0957 43676.8093 -116060.7308 -252199.5252 61 62 63 64 65 66 -40245.9057 -120460.0388 -28987.5520 -242179.3221 20654.0473 -16861.5212 67 68 69 70 71 72 -190153.5077 -2483.9129 -134759.5433 -64086.7390 -107260.0004 122588.8847 73 74 75 76 77 78 -178499.0979 -93880.1004 -153510.7855 -73623.8082 -164099.4883 -134406.8603 79 80 81 82 83 84 -20946.8047 51139.6183 -10649.0475 -58415.1070 -195302.3812 5953.9759 85 86 87 88 89 90 -81782.8523 -140502.8645 23683.1814 -113951.1162 -140612.6340 -92503.9273 91 92 93 94 95 96 -71639.2295 -49835.5118 68877.9462 -238256.8598 81943.8504 -21490.8823 97 98 99 100 -66233.4537 30937.6637 -135062.1427 -26820.4682 > postscript(file="/var/www/html/rcomp/tmp/6in2e1291409893.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 -103387.0397 NA 1 2936875.4516 -103387.0397 2 508893.7371 2936875.4516 3 -633713.8167 508893.7371 4 -880217.8319 -633713.8167 5 -193617.1624 -880217.8319 6 1095053.2091 -193617.1624 7 476787.1991 1095053.2091 8 -725675.9287 476787.1991 9 578745.3061 -725675.9287 10 457965.3572 578745.3061 11 758846.4051 457965.3572 12 604167.5452 758846.4051 13 -505663.9308 604167.5452 14 -260893.9792 -505663.9308 15 541027.0438 -260893.9792 16 -259329.8960 541027.0438 17 -301663.7065 -259329.8960 18 -636403.7071 -301663.7065 19 20936.1128 -636403.7071 20 90860.9998 20936.1128 21 -419889.2020 90860.9998 22 100389.4601 -419889.2020 23 -159240.7445 100389.4601 24 -99058.3766 -159240.7445 25 289754.9236 -99058.3766 26 -657103.2585 289754.9236 27 -219487.4587 -657103.2585 28 577431.7775 -219487.4587 29 243972.7477 577431.7775 30 243507.6887 243972.7477 31 -167584.3847 243507.6887 32 140743.3944 -167584.3847 33 93240.6806 140743.3944 34 -308777.0058 93240.6806 35 21745.2962 -308777.0058 36 275963.3616 21745.2962 37 152914.4601 275963.3616 38 165465.9636 152914.4601 39 -172572.9085 165465.9636 40 -192147.7346 -172572.9085 41 -152.8003 -192147.7346 42 59654.3540 -152.8003 43 -84003.2243 59654.3540 44 21992.7796 -84003.2243 45 -138401.2187 21992.7796 46 113380.3590 -138401.2187 47 -149053.5866 113380.3590 48 -58172.4144 -149053.5866 49 -187495.8185 -58172.4144 50 108224.6759 -187495.8185 51 -9717.6635 108224.6759 52 -188569.0372 -9717.6635 53 120585.0268 -188569.0372 54 -237903.6047 120585.0268 55 72139.7742 -237903.6047 56 206940.0957 72139.7742 57 43676.8093 206940.0957 58 -116060.7308 43676.8093 59 -252199.5252 -116060.7308 60 -40245.9057 -252199.5252 61 -120460.0388 -40245.9057 62 -28987.5520 -120460.0388 63 -242179.3221 -28987.5520 64 20654.0473 -242179.3221 65 -16861.5212 20654.0473 66 -190153.5077 -16861.5212 67 -2483.9129 -190153.5077 68 -134759.5433 -2483.9129 69 -64086.7390 -134759.5433 70 -107260.0004 -64086.7390 71 122588.8847 -107260.0004 72 -178499.0979 122588.8847 73 -93880.1004 -178499.0979 74 -153510.7855 -93880.1004 75 -73623.8082 -153510.7855 76 -164099.4883 -73623.8082 77 -134406.8603 -164099.4883 78 -20946.8047 -134406.8603 79 51139.6183 -20946.8047 80 -10649.0475 51139.6183 81 -58415.1070 -10649.0475 82 -195302.3812 -58415.1070 83 5953.9759 -195302.3812 84 -81782.8523 5953.9759 85 -140502.8645 -81782.8523 86 23683.1814 -140502.8645 87 -113951.1162 23683.1814 88 -140612.6340 -113951.1162 89 -92503.9273 -140612.6340 90 -71639.2295 -92503.9273 91 -49835.5118 -71639.2295 92 68877.9462 -49835.5118 93 -238256.8598 68877.9462 94 81943.8504 -238256.8598 95 -21490.8823 81943.8504 96 -66233.4537 -21490.8823 97 30937.6637 -66233.4537 98 -135062.1427 30937.6637 99 -26820.4682 -135062.1427 100 NA -26820.4682 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 2936875.4516 -103387.0397 [2,] 508893.7371 2936875.4516 [3,] -633713.8167 508893.7371 [4,] -880217.8319 -633713.8167 [5,] -193617.1624 -880217.8319 [6,] 1095053.2091 -193617.1624 [7,] 476787.1991 1095053.2091 [8,] -725675.9287 476787.1991 [9,] 578745.3061 -725675.9287 [10,] 457965.3572 578745.3061 [11,] 758846.4051 457965.3572 [12,] 604167.5452 758846.4051 [13,] -505663.9308 604167.5452 [14,] -260893.9792 -505663.9308 [15,] 541027.0438 -260893.9792 [16,] -259329.8960 541027.0438 [17,] -301663.7065 -259329.8960 [18,] -636403.7071 -301663.7065 [19,] 20936.1128 -636403.7071 [20,] 90860.9998 20936.1128 [21,] -419889.2020 90860.9998 [22,] 100389.4601 -419889.2020 [23,] -159240.7445 100389.4601 [24,] -99058.3766 -159240.7445 [25,] 289754.9236 -99058.3766 [26,] -657103.2585 289754.9236 [27,] -219487.4587 -657103.2585 [28,] 577431.7775 -219487.4587 [29,] 243972.7477 577431.7775 [30,] 243507.6887 243972.7477 [31,] -167584.3847 243507.6887 [32,] 140743.3944 -167584.3847 [33,] 93240.6806 140743.3944 [34,] -308777.0058 93240.6806 [35,] 21745.2962 -308777.0058 [36,] 275963.3616 21745.2962 [37,] 152914.4601 275963.3616 [38,] 165465.9636 152914.4601 [39,] -172572.9085 165465.9636 [40,] -192147.7346 -172572.9085 [41,] -152.8003 -192147.7346 [42,] 59654.3540 -152.8003 [43,] -84003.2243 59654.3540 [44,] 21992.7796 -84003.2243 [45,] -138401.2187 21992.7796 [46,] 113380.3590 -138401.2187 [47,] -149053.5866 113380.3590 [48,] -58172.4144 -149053.5866 [49,] -187495.8185 -58172.4144 [50,] 108224.6759 -187495.8185 [51,] -9717.6635 108224.6759 [52,] -188569.0372 -9717.6635 [53,] 120585.0268 -188569.0372 [54,] -237903.6047 120585.0268 [55,] 72139.7742 -237903.6047 [56,] 206940.0957 72139.7742 [57,] 43676.8093 206940.0957 [58,] -116060.7308 43676.8093 [59,] -252199.5252 -116060.7308 [60,] -40245.9057 -252199.5252 [61,] -120460.0388 -40245.9057 [62,] -28987.5520 -120460.0388 [63,] -242179.3221 -28987.5520 [64,] 20654.0473 -242179.3221 [65,] -16861.5212 20654.0473 [66,] -190153.5077 -16861.5212 [67,] -2483.9129 -190153.5077 [68,] -134759.5433 -2483.9129 [69,] -64086.7390 -134759.5433 [70,] -107260.0004 -64086.7390 [71,] 122588.8847 -107260.0004 [72,] -178499.0979 122588.8847 [73,] -93880.1004 -178499.0979 [74,] -153510.7855 -93880.1004 [75,] -73623.8082 -153510.7855 [76,] -164099.4883 -73623.8082 [77,] -134406.8603 -164099.4883 [78,] -20946.8047 -134406.8603 [79,] 51139.6183 -20946.8047 [80,] -10649.0475 51139.6183 [81,] -58415.1070 -10649.0475 [82,] -195302.3812 -58415.1070 [83,] 5953.9759 -195302.3812 [84,] -81782.8523 5953.9759 [85,] -140502.8645 -81782.8523 [86,] 23683.1814 -140502.8645 [87,] -113951.1162 23683.1814 [88,] -140612.6340 -113951.1162 [89,] -92503.9273 -140612.6340 [90,] -71639.2295 -92503.9273 [91,] -49835.5118 -71639.2295 [92,] 68877.9462 -49835.5118 [93,] -238256.8598 68877.9462 [94,] 81943.8504 -238256.8598 [95,] -21490.8823 81943.8504 [96,] -66233.4537 -21490.8823 [97,] 30937.6637 -66233.4537 [98,] -135062.1427 30937.6637 [99,] -26820.4682 -135062.1427 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 2936875.4516 -103387.0397 2 508893.7371 2936875.4516 3 -633713.8167 508893.7371 4 -880217.8319 -633713.8167 5 -193617.1624 -880217.8319 6 1095053.2091 -193617.1624 7 476787.1991 1095053.2091 8 -725675.9287 476787.1991 9 578745.3061 -725675.9287 10 457965.3572 578745.3061 11 758846.4051 457965.3572 12 604167.5452 758846.4051 13 -505663.9308 604167.5452 14 -260893.9792 -505663.9308 15 541027.0438 -260893.9792 16 -259329.8960 541027.0438 17 -301663.7065 -259329.8960 18 -636403.7071 -301663.7065 19 20936.1128 -636403.7071 20 90860.9998 20936.1128 21 -419889.2020 90860.9998 22 100389.4601 -419889.2020 23 -159240.7445 100389.4601 24 -99058.3766 -159240.7445 25 289754.9236 -99058.3766 26 -657103.2585 289754.9236 27 -219487.4587 -657103.2585 28 577431.7775 -219487.4587 29 243972.7477 577431.7775 30 243507.6887 243972.7477 31 -167584.3847 243507.6887 32 140743.3944 -167584.3847 33 93240.6806 140743.3944 34 -308777.0058 93240.6806 35 21745.2962 -308777.0058 36 275963.3616 21745.2962 37 152914.4601 275963.3616 38 165465.9636 152914.4601 39 -172572.9085 165465.9636 40 -192147.7346 -172572.9085 41 -152.8003 -192147.7346 42 59654.3540 -152.8003 43 -84003.2243 59654.3540 44 21992.7796 -84003.2243 45 -138401.2187 21992.7796 46 113380.3590 -138401.2187 47 -149053.5866 113380.3590 48 -58172.4144 -149053.5866 49 -187495.8185 -58172.4144 50 108224.6759 -187495.8185 51 -9717.6635 108224.6759 52 -188569.0372 -9717.6635 53 120585.0268 -188569.0372 54 -237903.6047 120585.0268 55 72139.7742 -237903.6047 56 206940.0957 72139.7742 57 43676.8093 206940.0957 58 -116060.7308 43676.8093 59 -252199.5252 -116060.7308 60 -40245.9057 -252199.5252 61 -120460.0388 -40245.9057 62 -28987.5520 -120460.0388 63 -242179.3221 -28987.5520 64 20654.0473 -242179.3221 65 -16861.5212 20654.0473 66 -190153.5077 -16861.5212 67 -2483.9129 -190153.5077 68 -134759.5433 -2483.9129 69 -64086.7390 -134759.5433 70 -107260.0004 -64086.7390 71 122588.8847 -107260.0004 72 -178499.0979 122588.8847 73 -93880.1004 -178499.0979 74 -153510.7855 -93880.1004 75 -73623.8082 -153510.7855 76 -164099.4883 -73623.8082 77 -134406.8603 -164099.4883 78 -20946.8047 -134406.8603 79 51139.6183 -20946.8047 80 -10649.0475 51139.6183 81 -58415.1070 -10649.0475 82 -195302.3812 -58415.1070 83 5953.9759 -195302.3812 84 -81782.8523 5953.9759 85 -140502.8645 -81782.8523 86 23683.1814 -140502.8645 87 -113951.1162 23683.1814 88 -140612.6340 -113951.1162 89 -92503.9273 -140612.6340 90 -71639.2295 -92503.9273 91 -49835.5118 -71639.2295 92 68877.9462 -49835.5118 93 -238256.8598 68877.9462 94 81943.8504 -238256.8598 95 -21490.8823 81943.8504 96 -66233.4537 -21490.8823 97 30937.6637 -66233.4537 98 -135062.1427 30937.6637 99 -26820.4682 -135062.1427 > 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/rcomp/tmp/7tfjz1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8tfjz1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9tfjz1291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10m6i21291409893.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/11p6g81291409893.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/rcomp/tmp/12spxe1291409893.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/rcomp/tmp/13hqu81291409893.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/rcomp/tmp/14lrbw1291409893.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/rcomp/tmp/1569r11291409893.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/rcomp/tmp/169sq71291409893.tab") + } > > try(system("convert tmp/1fnlq1291409893.ps tmp/1fnlq1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/2fnlq1291409893.ps tmp/2fnlq1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/3pwkb1291409893.ps tmp/3pwkb1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/4pwkb1291409893.ps tmp/4pwkb1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/5pwkb1291409893.ps tmp/5pwkb1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/6in2e1291409893.ps tmp/6in2e1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/7tfjz1291409893.ps tmp/7tfjz1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/8tfjz1291409893.ps tmp/8tfjz1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/9tfjz1291409893.ps tmp/9tfjz1291409893.png",intern=TRUE)) character(0) > try(system("convert tmp/10m6i21291409893.ps tmp/10m6i21291409893.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.114 1.660 7.118