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Type 'q()' to quit R. > x <- array(list(1 + ,162556 + ,162556 + ,1081 + ,1081 + ,213118 + ,213118 + ,230380558 + ,6282929 + ,1 + ,29790 + ,29790 + ,309 + ,309 + ,81767 + ,81767 + ,25266003 + ,4324047 + ,1 + ,87550 + ,87550 + ,458 + ,458 + ,153198 + ,153198 + ,70164684 + ,4108272 + ,0 + ,84738 + ,0 + ,588 + ,0 + ,-26007 + ,0 + ,-15292116 + ,-1212617 + ,1 + ,54660 + ,54660 + ,299 + ,299 + ,126942 + ,126942 + ,37955658 + ,1485329 + ,1 + ,42634 + ,42634 + ,156 + ,156 + ,157214 + ,157214 + ,24525384 + ,1779876 + ,0 + ,40949 + ,0 + ,481 + ,0 + ,129352 + ,0 + ,62218312 + ,1367203 + ,1 + ,42312 + ,42312 + ,323 + ,323 + ,234817 + ,234817 + ,75845891 + ,2519076 + ,1 + ,37704 + ,37704 + ,452 + ,452 + ,60448 + ,60448 + ,27322496 + ,912684 + ,1 + ,16275 + ,16275 + ,109 + ,109 + ,47818 + ,47818 + ,5212162 + ,1443586 + ,0 + ,25830 + ,0 + ,115 + ,0 + ,245546 + ,0 + ,28237790 + ,1220017 + ,0 + ,12679 + ,0 + ,110 + ,0 + ,48020 + ,0 + ,5282200 + ,984885 + ,1 + ,18014 + ,18014 + ,239 + ,239 + ,-1710 + 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,73221 + ,73221 + ,805431 + ,329118) + ,dim=c(9 + ,100) + ,dimnames=list(c('Group' + ,'Costs' + ,'GrCosts' + ,'Trades' + ,'GrTrades' + ,'Dividends' + ,'GrDiv' + ,'TrDiv' + ,'Wealth ') + ,1:100)) > y <- array(NA,dim=c(9,100),dimnames=list(c('Group','Costs','GrCosts','Trades','GrTrades','Dividends','GrDiv','TrDiv','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 = '2' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Costs Group GrCosts Trades GrTrades Dividends GrDiv TrDiv Wealth\r 1 162556 1 162556 1081 1081 213118 213118 230380558 6282929 2 29790 1 29790 309 309 81767 81767 25266003 4324047 3 87550 1 87550 458 458 153198 153198 70164684 4108272 4 84738 0 0 588 0 -26007 0 -15292116 -1212617 5 54660 1 54660 299 299 126942 126942 37955658 1485329 6 42634 1 42634 156 156 157214 157214 24525384 1779876 7 40949 0 0 481 0 129352 0 62218312 1367203 8 42312 1 42312 323 323 234817 234817 75845891 2519076 9 37704 1 37704 452 452 60448 60448 27322496 912684 10 16275 1 16275 109 109 47818 47818 5212162 1443586 11 25830 0 0 115 0 245546 0 28237790 1220017 12 12679 0 0 110 0 48020 0 5282200 984885 13 18014 1 18014 239 239 -1710 -1710 -408690 1457425 14 43556 0 0 247 0 32648 0 8064056 -572920 15 24524 1 24524 497 497 95350 95350 47388950 929144 16 6532 0 0 103 0 151352 0 15589256 1151176 17 7123 0 0 109 0 288170 0 31410530 790090 18 20813 1 20813 502 502 114337 114337 57397174 774497 19 37597 1 37597 248 248 37884 37884 9395232 990576 20 17821 0 0 373 0 122844 0 45820812 454195 21 12988 1 12988 119 119 82340 82340 9798460 876607 22 22330 1 22330 84 84 79801 79801 6703284 711969 23 13326 0 0 102 0 165548 0 16885896 702380 24 16189 0 0 295 0 116384 0 34333280 264449 25 7146 0 0 105 0 134028 0 14072940 450033 26 15824 0 0 64 0 63838 0 4085632 541063 27 26088 1 26088 267 267 74996 74996 20023932 588864 28 11326 0 0 129 0 31080 0 4009320 -37216 29 8568 0 0 37 0 32168 0 1190216 783310 30 14416 0 0 361 0 49857 0 17998377 467359 31 3369 1 3369 28 28 87161 87161 2440508 688779 32 11819 1 11819 85 85 106113 106113 9019605 608419 33 6620 1 6620 44 44 80570 80570 3545080 696348 34 4519 1 4519 49 49 102129 102129 5004321 597793 35 2220 0 0 22 0 301670 0 6636740 821730 36 18562 0 0 155 0 102313 0 15858515 377934 37 10327 0 0 91 0 88577 0 8060507 651939 38 5336 1 5336 81 81 112477 112477 9110637 697458 39 2365 1 2365 79 79 191778 191778 15150462 700368 40 4069 0 0 145 0 79804 0 11571580 225986 41 7710 0 0 816 0 128294 0 104687904 348695 42 13718 0 0 61 0 96448 0 5883328 373683 43 4525 0 0 226 0 93811 0 21201286 501709 44 6869 0 0 105 0 117520 0 12339600 413743 45 4628 0 0 62 0 69159 0 4287858 379825 46 3653 1 3653 24 24 101792 101792 2443008 336260 47 1265 1 1265 26 26 210568 210568 5474768 636765 48 7489 1 7489 322 322 136996 136996 44112712 481231 49 4901 0 0 84 0 121920 0 10241280 469107 50 2284 0 0 33 0 76403 0 2521299 211928 51 3160 1 3160 108 108 108094 108094 11674152 563925 52 4150 1 4150 150 150 134759 134759 20213850 511939 53 7285 1 7285 115 115 188873 188873 21720395 521016 54 1134 1 1134 162 162 146216 146216 23686992 543856 55 4658 1 4658 158 158 156608 156608 24744064 329304 56 2384 0 0 97 0 61348 0 5950756 423262 57 3748 0 0 9 0 50350 0 453150 509665 58 5371 0 0 66 0 87720 0 5789520 455881 59 1285 0 0 107 0 99489 0 10645323 367772 60 9327 1 9327 101 101 87419 87419 8829319 406339 61 5565 1 5565 47 47 94355 94355 4434685 493408 62 1528 0 0 38 0 60326 0 2292388 232942 63 3122 1 3122 34 34 94670 94670 3218780 416002 64 7317 1 7317 84 84 82425 82425 6923700 337430 65 2675 0 0 79 0 59017 0 4662343 361517 66 13253 0 0 947 0 90829 0 86015063 360962 67 880 0 0 74 0 80791 0 5978534 235561 68 2053 1 2053 53 53 100423 100423 5322419 408247 69 1424 0 0 94 0 131116 0 12324904 450296 70 4036 1 4036 63 63 100269 100269 6316947 418799 71 3045 1 3045 58 58 27330 27330 1585140 247405 72 5119 0 0 49 0 39039 0 1912911 378519 73 1431 0 0 34 0 106885 0 3634090 326638 74 554 0 0 11 0 79285 0 872135 328233 75 1975 0 0 35 0 118881 0 4160835 386225 76 1286 1 1286 17 17 77623 77623 1319591 283662 77 1012 0 0 47 0 114768 0 5394096 370225 78 810 0 0 43 0 74015 0 3182645 269236 79 1280 0 0 117 0 69465 0 8127405 365732 80 666 1 666 171 171 117869 117869 20155599 420383 81 1380 0 0 26 0 60982 0 1585532 345811 82 4608 1 4608 73 73 90131 90131 6579563 431809 83 876 0 0 59 0 138971 0 8199289 418876 84 814 0 0 18 0 39625 0 713250 297476 85 514 0 0 15 0 102725 0 1540875 416776 86 5692 1 5692 72 72 64239 64239 4625208 357257 87 3642 0 0 86 0 90262 0 7762532 458343 88 540 0 0 14 0 103960 0 1455440 388386 89 2099 0 0 64 0 106611 0 6823104 358934 90 567 0 0 11 0 103345 0 1136795 407560 91 2001 0 0 52 0 95551 0 4968652 392558 92 2949 1 2949 41 41 82903 82903 3399023 373177 93 2253 0 0 99 0 63593 0 6295707 428370 94 6533 1 6533 75 75 126910 126910 9518250 369419 95 1889 0 0 45 0 37527 0 1688715 358649 96 3055 1 3055 43 43 60247 60247 2590621 376641 97 272 0 0 8 0 112995 0 903960 467427 98 1414 1 1414 198 198 70184 70184 13896432 364885 99 2564 0 0 22 0 130140 0 2863080 436230 100 1383 1 1383 11 11 73221 73221 805431 329118 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Group GrCosts Trades GrTrades Dividends 2.064e+03 -1.191e+04 1.219e+00 7.526e+01 -3.277e+01 2.021e-02 GrDiv TrDiv `Wealth\r` 6.061e-02 -4.116e-04 -1.129e-03 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -26106.7 -3736.2 -529.6 1887.8 31281.0 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.064e+03 2.550e+03 0.809 0.42042 Group -1.191e+04 3.855e+03 -3.090 0.00265 ** GrCosts 1.219e+00 1.106e-01 11.021 < 2e-16 *** Trades 7.526e+01 9.707e+00 7.754 1.24e-11 *** GrTrades -3.277e+01 1.345e+01 -2.437 0.01677 * Dividends 2.021e-02 2.208e-02 0.915 0.36239 GrDiv 6.061e-02 3.248e-02 1.866 0.06524 . TrDiv -4.116e-04 8.560e-05 -4.809 5.97e-06 *** `Wealth\r` -1.129e-03 1.909e-03 -0.591 0.55575 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 7801 on 91 degrees of freedom Multiple R-squared: 0.8827, Adjusted R-squared: 0.8723 F-statistic: 85.56 on 8 and 91 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,] 0.9824120 3.517590e-02 1.758795e-02 [2,] 0.9650577 6.988458e-02 3.494229e-02 [3,] 0.9997172 5.655983e-04 2.827991e-04 [4,] 0.9994049 1.190124e-03 5.950621e-04 [5,] 0.9999224 1.551078e-04 7.755392e-05 [6,] 0.9999142 1.716411e-04 8.582054e-05 [7,] 0.9997995 4.010429e-04 2.005214e-04 [8,] 0.9995851 8.298922e-04 4.149461e-04 [9,] 0.9999997 5.615008e-07 2.807504e-07 [10,] 0.9999995 9.029213e-07 4.514606e-07 [11,] 0.9999990 1.997388e-06 9.986940e-07 [12,] 0.9999994 1.204480e-06 6.022398e-07 [13,] 1.0000000 1.276981e-08 6.384906e-09 [14,] 1.0000000 1.250621e-08 6.253105e-09 [15,] 1.0000000 6.667993e-10 3.333996e-10 [16,] 1.0000000 1.807156e-09 9.035780e-10 [17,] 1.0000000 2.927443e-10 1.463721e-10 [18,] 1.0000000 6.312813e-10 3.156406e-10 [19,] 1.0000000 2.352007e-13 1.176004e-13 [20,] 1.0000000 4.737396e-13 2.368698e-13 [21,] 1.0000000 1.469198e-12 7.345990e-13 [22,] 1.0000000 3.438214e-12 1.719107e-12 [23,] 1.0000000 9.562464e-12 4.781232e-12 [24,] 1.0000000 2.112782e-11 1.056391e-11 [25,] 1.0000000 5.807655e-17 2.903827e-17 [26,] 1.0000000 6.600830e-18 3.300415e-18 [27,] 1.0000000 2.438058e-17 1.219029e-17 [28,] 1.0000000 9.427599e-17 4.713800e-17 [29,] 1.0000000 6.589168e-17 3.294584e-17 [30,] 1.0000000 7.638395e-21 3.819198e-21 [31,] 1.0000000 3.570160e-31 1.785080e-31 [32,] 1.0000000 6.750693e-31 3.375346e-31 [33,] 1.0000000 3.837637e-33 1.918819e-33 [34,] 1.0000000 2.085987e-33 1.042993e-33 [35,] 1.0000000 1.780774e-32 8.903868e-33 [36,] 1.0000000 1.416503e-31 7.082516e-32 [37,] 1.0000000 9.923014e-31 4.961507e-31 [38,] 1.0000000 2.604958e-31 1.302479e-31 [39,] 1.0000000 6.648118e-31 3.324059e-31 [40,] 1.0000000 4.191627e-30 2.095814e-30 [41,] 1.0000000 3.558324e-29 1.779162e-29 [42,] 1.0000000 3.480722e-28 1.740361e-28 [43,] 1.0000000 1.722359e-27 8.611796e-28 [44,] 1.0000000 1.466102e-26 7.330508e-27 [45,] 1.0000000 6.231919e-26 3.115960e-26 [46,] 1.0000000 4.592221e-25 2.296111e-25 [47,] 1.0000000 1.308366e-26 6.541831e-27 [48,] 1.0000000 5.421719e-26 2.710859e-26 [49,] 1.0000000 5.736040e-25 2.868020e-25 [50,] 1.0000000 4.685356e-24 2.342678e-24 [51,] 1.0000000 3.842190e-23 1.921095e-23 [52,] 1.0000000 3.607127e-22 1.803563e-22 [53,] 1.0000000 3.419119e-21 1.709559e-21 [54,] 1.0000000 2.724283e-20 1.362142e-20 [55,] 1.0000000 2.036846e-20 1.018423e-20 [56,] 1.0000000 1.669042e-19 8.345209e-20 [57,] 1.0000000 1.646164e-18 8.230820e-19 [58,] 1.0000000 1.145166e-17 5.725829e-18 [59,] 1.0000000 1.096722e-16 5.483609e-17 [60,] 1.0000000 8.860304e-16 4.430152e-16 [61,] 1.0000000 7.145459e-18 3.572729e-18 [62,] 1.0000000 7.369305e-17 3.684652e-17 [63,] 1.0000000 8.680714e-16 4.340357e-16 [64,] 1.0000000 5.693829e-15 2.846915e-15 [65,] 1.0000000 6.017806e-14 3.008903e-14 [66,] 1.0000000 6.613191e-13 3.306595e-13 [67,] 1.0000000 7.451589e-12 3.725794e-12 [68,] 1.0000000 1.064350e-11 5.321751e-12 [69,] 1.0000000 1.379150e-10 6.895751e-11 [70,] 1.0000000 1.572623e-09 7.863117e-10 [71,] 1.0000000 1.836378e-08 9.181889e-09 [72,] 1.0000000 3.029581e-08 1.514791e-08 [73,] 0.9999998 4.031531e-07 2.015765e-07 [74,] 0.9999980 4.061463e-06 2.030731e-06 [75,] 0.9999774 4.521410e-05 2.260705e-05 [76,] 0.9998091 3.817863e-04 1.908931e-04 [77,] 0.9988151 2.369816e-03 1.184908e-03 > postscript(file="/var/www/rcomp/tmp/12rra1293220729.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/22rra1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3v08v1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4v08v1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5v08v1293220729.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 13051.52696 -1124.21050 -7627.46946 31281.04033 -7772.98108 -6707.49428 7 8 9 10 11 12 27224.07641 1954.41958 -10214.67691 1568.22664 23149.24307 4652.19458 13 14 15 16 17 18 -2631.91642 24914.97468 -3785.53264 1373.96976 4852.88201 -775.49395 19 20 21 22 23 24 -6990.17926 4575.42871 320.06890 -1491.21784 7983.31250 4001.64656 25 26 27 28 29 30 771.77925 9945.94392 -4357.42987 533.57528 4443.85320 -7889.03681 31 32 33 34 35 36 2661.08257 -524.07378 2265.81325 1260.00347 -3937.11627 9719.22910 37 38 39 40 41 42 3678.17907 687.92898 -2496.66209 -5502.39391 -14874.84913 7957.61861 43 44 45 46 47 48 -7150.62075 73.96513 -1305.88705 1189.46245 -5577.03763 2157.90663 49 50 51 52 53 54 -1203.66476 -2530.40680 1275.32003 575.42536 -2366.18971 1265.08244 55 56 57 58 59 60 17.08619 -5292.68663 751.36439 -535.09226 -6045.44397 545.54886 61 62 63 64 65 66 1392.09888 -3408.27182 1865.65092 1249.10402 -4199.89664 -26106.72872 67 68 69 70 71 72 -5659.10609 1684.33946 -4782.71933 1259.28948 5442.17621 -206.74883 73 74 75 76 77 78 -3487.20313 -3210.39347 -2976.82891 3436.28512 -4270.27049 -4371.83741 79 80 81 82 83 84 -7234.99469 1682.94444 -2829.89449 1651.33511 -4588.98604 -2775.74455 85 86 87 88 89 90 -3649.97775 2660.59444 -3005.80419 -3640.89931 -3722.39842 -3485.19414 91 92 93 94 95 96 -3419.07939 2582.87873 -5471.82927 -688.04505 -3219.85467 3976.89022 97 98 99 100 -3777.70127 1586.64096 -2114.71519 3865.48014 > postscript(file="/var/www/rcomp/tmp/6osqy1293220729.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 13051.52696 NA 1 -1124.21050 13051.52696 2 -7627.46946 -1124.21050 3 31281.04033 -7627.46946 4 -7772.98108 31281.04033 5 -6707.49428 -7772.98108 6 27224.07641 -6707.49428 7 1954.41958 27224.07641 8 -10214.67691 1954.41958 9 1568.22664 -10214.67691 10 23149.24307 1568.22664 11 4652.19458 23149.24307 12 -2631.91642 4652.19458 13 24914.97468 -2631.91642 14 -3785.53264 24914.97468 15 1373.96976 -3785.53264 16 4852.88201 1373.96976 17 -775.49395 4852.88201 18 -6990.17926 -775.49395 19 4575.42871 -6990.17926 20 320.06890 4575.42871 21 -1491.21784 320.06890 22 7983.31250 -1491.21784 23 4001.64656 7983.31250 24 771.77925 4001.64656 25 9945.94392 771.77925 26 -4357.42987 9945.94392 27 533.57528 -4357.42987 28 4443.85320 533.57528 29 -7889.03681 4443.85320 30 2661.08257 -7889.03681 31 -524.07378 2661.08257 32 2265.81325 -524.07378 33 1260.00347 2265.81325 34 -3937.11627 1260.00347 35 9719.22910 -3937.11627 36 3678.17907 9719.22910 37 687.92898 3678.17907 38 -2496.66209 687.92898 39 -5502.39391 -2496.66209 40 -14874.84913 -5502.39391 41 7957.61861 -14874.84913 42 -7150.62075 7957.61861 43 73.96513 -7150.62075 44 -1305.88705 73.96513 45 1189.46245 -1305.88705 46 -5577.03763 1189.46245 47 2157.90663 -5577.03763 48 -1203.66476 2157.90663 49 -2530.40680 -1203.66476 50 1275.32003 -2530.40680 51 575.42536 1275.32003 52 -2366.18971 575.42536 53 1265.08244 -2366.18971 54 17.08619 1265.08244 55 -5292.68663 17.08619 56 751.36439 -5292.68663 57 -535.09226 751.36439 58 -6045.44397 -535.09226 59 545.54886 -6045.44397 60 1392.09888 545.54886 61 -3408.27182 1392.09888 62 1865.65092 -3408.27182 63 1249.10402 1865.65092 64 -4199.89664 1249.10402 65 -26106.72872 -4199.89664 66 -5659.10609 -26106.72872 67 1684.33946 -5659.10609 68 -4782.71933 1684.33946 69 1259.28948 -4782.71933 70 5442.17621 1259.28948 71 -206.74883 5442.17621 72 -3487.20313 -206.74883 73 -3210.39347 -3487.20313 74 -2976.82891 -3210.39347 75 3436.28512 -2976.82891 76 -4270.27049 3436.28512 77 -4371.83741 -4270.27049 78 -7234.99469 -4371.83741 79 1682.94444 -7234.99469 80 -2829.89449 1682.94444 81 1651.33511 -2829.89449 82 -4588.98604 1651.33511 83 -2775.74455 -4588.98604 84 -3649.97775 -2775.74455 85 2660.59444 -3649.97775 86 -3005.80419 2660.59444 87 -3640.89931 -3005.80419 88 -3722.39842 -3640.89931 89 -3485.19414 -3722.39842 90 -3419.07939 -3485.19414 91 2582.87873 -3419.07939 92 -5471.82927 2582.87873 93 -688.04505 -5471.82927 94 -3219.85467 -688.04505 95 3976.89022 -3219.85467 96 -3777.70127 3976.89022 97 1586.64096 -3777.70127 98 -2114.71519 1586.64096 99 3865.48014 -2114.71519 100 NA 3865.48014 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1124.21050 13051.52696 [2,] -7627.46946 -1124.21050 [3,] 31281.04033 -7627.46946 [4,] -7772.98108 31281.04033 [5,] -6707.49428 -7772.98108 [6,] 27224.07641 -6707.49428 [7,] 1954.41958 27224.07641 [8,] -10214.67691 1954.41958 [9,] 1568.22664 -10214.67691 [10,] 23149.24307 1568.22664 [11,] 4652.19458 23149.24307 [12,] -2631.91642 4652.19458 [13,] 24914.97468 -2631.91642 [14,] -3785.53264 24914.97468 [15,] 1373.96976 -3785.53264 [16,] 4852.88201 1373.96976 [17,] -775.49395 4852.88201 [18,] -6990.17926 -775.49395 [19,] 4575.42871 -6990.17926 [20,] 320.06890 4575.42871 [21,] -1491.21784 320.06890 [22,] 7983.31250 -1491.21784 [23,] 4001.64656 7983.31250 [24,] 771.77925 4001.64656 [25,] 9945.94392 771.77925 [26,] -4357.42987 9945.94392 [27,] 533.57528 -4357.42987 [28,] 4443.85320 533.57528 [29,] -7889.03681 4443.85320 [30,] 2661.08257 -7889.03681 [31,] -524.07378 2661.08257 [32,] 2265.81325 -524.07378 [33,] 1260.00347 2265.81325 [34,] -3937.11627 1260.00347 [35,] 9719.22910 -3937.11627 [36,] 3678.17907 9719.22910 [37,] 687.92898 3678.17907 [38,] -2496.66209 687.92898 [39,] -5502.39391 -2496.66209 [40,] -14874.84913 -5502.39391 [41,] 7957.61861 -14874.84913 [42,] -7150.62075 7957.61861 [43,] 73.96513 -7150.62075 [44,] -1305.88705 73.96513 [45,] 1189.46245 -1305.88705 [46,] -5577.03763 1189.46245 [47,] 2157.90663 -5577.03763 [48,] -1203.66476 2157.90663 [49,] -2530.40680 -1203.66476 [50,] 1275.32003 -2530.40680 [51,] 575.42536 1275.32003 [52,] -2366.18971 575.42536 [53,] 1265.08244 -2366.18971 [54,] 17.08619 1265.08244 [55,] -5292.68663 17.08619 [56,] 751.36439 -5292.68663 [57,] -535.09226 751.36439 [58,] -6045.44397 -535.09226 [59,] 545.54886 -6045.44397 [60,] 1392.09888 545.54886 [61,] -3408.27182 1392.09888 [62,] 1865.65092 -3408.27182 [63,] 1249.10402 1865.65092 [64,] -4199.89664 1249.10402 [65,] -26106.72872 -4199.89664 [66,] -5659.10609 -26106.72872 [67,] 1684.33946 -5659.10609 [68,] -4782.71933 1684.33946 [69,] 1259.28948 -4782.71933 [70,] 5442.17621 1259.28948 [71,] -206.74883 5442.17621 [72,] -3487.20313 -206.74883 [73,] -3210.39347 -3487.20313 [74,] -2976.82891 -3210.39347 [75,] 3436.28512 -2976.82891 [76,] -4270.27049 3436.28512 [77,] -4371.83741 -4270.27049 [78,] -7234.99469 -4371.83741 [79,] 1682.94444 -7234.99469 [80,] -2829.89449 1682.94444 [81,] 1651.33511 -2829.89449 [82,] -4588.98604 1651.33511 [83,] -2775.74455 -4588.98604 [84,] -3649.97775 -2775.74455 [85,] 2660.59444 -3649.97775 [86,] -3005.80419 2660.59444 [87,] -3640.89931 -3005.80419 [88,] -3722.39842 -3640.89931 [89,] -3485.19414 -3722.39842 [90,] -3419.07939 -3485.19414 [91,] 2582.87873 -3419.07939 [92,] -5471.82927 2582.87873 [93,] -688.04505 -5471.82927 [94,] -3219.85467 -688.04505 [95,] 3976.89022 -3219.85467 [96,] -3777.70127 3976.89022 [97,] 1586.64096 -3777.70127 [98,] -2114.71519 1586.64096 [99,] 3865.48014 -2114.71519 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1124.21050 13051.52696 2 -7627.46946 -1124.21050 3 31281.04033 -7627.46946 4 -7772.98108 31281.04033 5 -6707.49428 -7772.98108 6 27224.07641 -6707.49428 7 1954.41958 27224.07641 8 -10214.67691 1954.41958 9 1568.22664 -10214.67691 10 23149.24307 1568.22664 11 4652.19458 23149.24307 12 -2631.91642 4652.19458 13 24914.97468 -2631.91642 14 -3785.53264 24914.97468 15 1373.96976 -3785.53264 16 4852.88201 1373.96976 17 -775.49395 4852.88201 18 -6990.17926 -775.49395 19 4575.42871 -6990.17926 20 320.06890 4575.42871 21 -1491.21784 320.06890 22 7983.31250 -1491.21784 23 4001.64656 7983.31250 24 771.77925 4001.64656 25 9945.94392 771.77925 26 -4357.42987 9945.94392 27 533.57528 -4357.42987 28 4443.85320 533.57528 29 -7889.03681 4443.85320 30 2661.08257 -7889.03681 31 -524.07378 2661.08257 32 2265.81325 -524.07378 33 1260.00347 2265.81325 34 -3937.11627 1260.00347 35 9719.22910 -3937.11627 36 3678.17907 9719.22910 37 687.92898 3678.17907 38 -2496.66209 687.92898 39 -5502.39391 -2496.66209 40 -14874.84913 -5502.39391 41 7957.61861 -14874.84913 42 -7150.62075 7957.61861 43 73.96513 -7150.62075 44 -1305.88705 73.96513 45 1189.46245 -1305.88705 46 -5577.03763 1189.46245 47 2157.90663 -5577.03763 48 -1203.66476 2157.90663 49 -2530.40680 -1203.66476 50 1275.32003 -2530.40680 51 575.42536 1275.32003 52 -2366.18971 575.42536 53 1265.08244 -2366.18971 54 17.08619 1265.08244 55 -5292.68663 17.08619 56 751.36439 -5292.68663 57 -535.09226 751.36439 58 -6045.44397 -535.09226 59 545.54886 -6045.44397 60 1392.09888 545.54886 61 -3408.27182 1392.09888 62 1865.65092 -3408.27182 63 1249.10402 1865.65092 64 -4199.89664 1249.10402 65 -26106.72872 -4199.89664 66 -5659.10609 -26106.72872 67 1684.33946 -5659.10609 68 -4782.71933 1684.33946 69 1259.28948 -4782.71933 70 5442.17621 1259.28948 71 -206.74883 5442.17621 72 -3487.20313 -206.74883 73 -3210.39347 -3487.20313 74 -2976.82891 -3210.39347 75 3436.28512 -2976.82891 76 -4270.27049 3436.28512 77 -4371.83741 -4270.27049 78 -7234.99469 -4371.83741 79 1682.94444 -7234.99469 80 -2829.89449 1682.94444 81 1651.33511 -2829.89449 82 -4588.98604 1651.33511 83 -2775.74455 -4588.98604 84 -3649.97775 -2775.74455 85 2660.59444 -3649.97775 86 -3005.80419 2660.59444 87 -3640.89931 -3005.80419 88 -3722.39842 -3640.89931 89 -3485.19414 -3722.39842 90 -3419.07939 -3485.19414 91 2582.87873 -3419.07939 92 -5471.82927 2582.87873 93 -688.04505 -5471.82927 94 -3219.85467 -688.04505 95 3976.89022 -3219.85467 96 -3777.70127 3976.89022 97 1586.64096 -3777.70127 98 -2114.71519 1586.64096 99 3865.48014 -2114.71519 > 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/rcomp/tmp/7osqy1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/9yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/10yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/11k15o1293220729.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/rcomp/tmp/12524c1293220729.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/rcomp/tmp/13u31o1293220729.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/rcomp/tmp/145ui91293220729.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/rcomp/tmp/158vyx1293220729.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/rcomp/tmp/164n0g1293220730.tab") + } > > try(system("convert tmp/12rra1293220729.ps tmp/12rra1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/22rra1293220729.ps tmp/22rra1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/3v08v1293220729.ps tmp/3v08v1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/4v08v1293220729.ps tmp/4v08v1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/5v08v1293220729.ps tmp/5v08v1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/6osqy1293220729.ps tmp/6osqy1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/7osqy1293220729.ps tmp/7osqy1293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/8yjo01293220729.ps tmp/8yjo01293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/9yjo01293220729.ps tmp/9yjo01293220729.png",intern=TRUE)) character(0) > try(system("convert tmp/10yjo01293220729.ps tmp/10yjo01293220729.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.840 0.830 4.645