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Type 'q()' to quit R. > x <- array(list(1 + ,1 + ,1 + ,1167 + ,333 + ,333 + ,70 + ,70 + ,1 + ,2 + ,2 + ,669 + ,223 + ,223 + ,44 + ,44 + ,1 + ,3 + ,3 + ,1053 + ,371 + ,371 + ,35 + ,35 + ,1 + ,4 + ,4 + ,1939 + ,873 + ,873 + ,119 + ,119 + ,1 + ,5 + ,5 + ,678 + ,186 + ,186 + ,30 + ,30 + ,1 + ,6 + ,6 + ,321 + ,111 + ,111 + ,23 + ,23 + ,1 + ,7 + ,7 + ,2667 + ,1277 + ,1277 + ,46 + ,46 + ,1 + ,8 + ,8 + ,345 + ,102 + ,102 + ,39 + ,39 + ,1 + ,9 + ,9 + ,1367 + ,580 + ,580 + ,58 + ,58 + ,1 + ,10 + ,10 + ,1158 + ,420 + ,420 + ,51 + ,51 + ,1 + ,11 + ,11 + ,1385 + ,521 + ,521 + ,65 + ,65 + ,1 + ,12 + ,12 + ,1155 + ,358 + ,358 + ,40 + ,40 + ,1 + ,13 + ,13 + ,1120 + ,435 + ,435 + ,41 + ,41 + ,1 + ,14 + ,14 + ,1703 + ,690 + ,690 + ,76 + ,76 + ,1 + ,15 + ,15 + ,1189 + ,393 + ,393 + ,31 + ,31 + ,1 + ,16 + ,16 + ,3083 + ,1149 + ,1149 + ,82 + ,82 + ,1 + ,17 + ,17 + ,1357 + ,486 + ,486 + ,36 + ,36 + ,1 + ,18 + ,18 + ,1892 + ,767 + ,767 + ,62 + ,62 + ,1 + ,19 + ,19 + ,883 + ,338 + ,338 + ,28 + ,28 + ,1 + ,20 + ,20 + ,1627 + ,485 + ,485 + ,38 + ,38 + ,1 + ,21 + ,21 + ,1412 + ,465 + ,465 + ,70 + ,70 + ,1 + ,22 + ,22 + ,1900 + ,816 + ,816 + ,76 + ,76 + ,1 + ,23 + ,23 + ,777 + ,265 + ,265 + ,33 + ,33 + ,1 + ,24 + ,24 + ,904 + ,307 + ,307 + ,40 + ,40 + ,1 + ,25 + ,25 + ,2115 + ,850 + ,850 + ,126 + ,126 + ,1 + ,26 + ,26 + ,1858 + ,704 + ,704 + ,56 + ,56 + ,1 + ,27 + ,27 + ,1781 + ,693 + ,693 + ,63 + ,63 + ,1 + ,28 + ,28 + ,1286 + ,387 + ,387 + ,46 + ,46 + ,1 + ,29 + ,29 + ,1035 + ,406 + ,406 + ,35 + ,35 + ,1 + ,30 + ,30 + ,1557 + ,573 + ,573 + ,108 + ,108 + ,0 + ,31 + ,0 + ,1527 + ,595 + ,0 + ,34 + ,0 + ,0 + ,32 + ,0 + ,1220 + ,394 + ,0 + ,54 + ,0 + ,0 + ,33 + ,0 + ,1368 + ,521 + ,0 + ,35 + ,0 + ,0 + ,34 + ,0 + ,564 + ,172 + ,0 + ,23 + ,0 + ,0 + ,35 + ,0 + ,1990 + ,835 + ,0 + ,46 + ,0 + ,0 + ,36 + ,0 + ,1557 + ,669 + ,0 + ,49 + ,0 + ,0 + ,37 + ,0 + ,2057 + ,749 + ,0 + ,56 + ,0 + ,0 + ,38 + ,0 + ,1111 + ,368 + ,0 + ,38 + ,0 + ,0 + ,39 + ,0 + ,686 + ,216 + ,0 + ,19 + ,0 + ,0 + ,40 + ,0 + ,2011 + ,772 + ,0 + ,29 + ,0 + ,0 + ,41 + ,0 + ,2232 + ,1084 + ,0 + ,26 + ,0 + ,0 + ,42 + ,0 + ,1032 + ,445 + ,0 + ,52 + ,0 + ,0 + ,43 + ,0 + ,1166 + ,451 + ,0 + ,54 + ,0 + ,0 + ,44 + ,0 + ,1020 + ,300 + ,0 + ,45 + ,0 + ,0 + ,45 + ,0 + ,1735 + ,836 + ,0 + ,56 + ,0 + ,0 + ,46 + ,0 + ,3623 + ,1417 + ,0 + ,596 + ,0 + ,0 + ,47 + ,0 + ,918 + ,330 + ,0 + ,57 + ,0 + ,0 + ,48 + ,0 + ,1579 + ,477 + ,0 + ,55 + ,0 + ,0 + ,49 + ,0 + ,2790 + ,1028 + ,0 + ,99 + ,0 + ,0 + ,50 + ,0 + ,1496 + ,646 + ,0 + ,51 + ,0 + ,0 + ,51 + ,0 + ,1108 + ,342 + ,0 + ,21 + ,0 + ,0 + ,52 + ,0 + ,496 + ,218 + ,0 + ,20 + ,0 + ,0 + ,53 + ,0 + ,1750 + ,591 + ,0 + ,58 + ,0 + ,0 + ,54 + ,0 + ,744 + ,255 + ,0 + ,21 + ,0 + ,0 + ,55 + ,0 + ,1101 + ,434 + ,0 + ,66 + ,0 + ,0 + ,56 + ,0 + ,1612 + ,654 + ,0 + ,47 + ,0 + ,0 + ,57 + ,0 + ,1805 + ,478 + ,0 + ,55 + ,0 + ,0 + ,58 + ,0 + ,2460 + ,753 + ,0 + ,158 + ,0 + ,0 + ,59 + ,0 + ,1653 + ,689 + ,0 + ,46 + ,0 + ,0 + ,60 + ,0 + ,1234 + ,470 + ,0 + ,45 + ,0) + ,dim=c(8 + ,60) + ,dimnames=list(c('Pop' + ,'t' + ,'pop_t' + ,'y' + ,'x1' + ,'x1_p' + ,'x2' + ,'x2_p') + ,1:60)) > y <- array(NA,dim=c(8,60),dimnames=list(c('Pop','t','pop_t','y','x1','x1_p','x2','x2_p'),1:60)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '4' > 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 y Pop t pop_t x1 x1_p x2 x2_p 1 1167 1 1 1 333 333 70 70 2 669 1 2 2 223 223 44 44 3 1053 1 3 3 371 371 35 35 4 1939 1 4 4 873 873 119 119 5 678 1 5 5 186 186 30 30 6 321 1 6 6 111 111 23 23 7 2667 1 7 7 1277 1277 46 46 8 345 1 8 8 102 102 39 39 9 1367 1 9 9 580 580 58 58 10 1158 1 10 10 420 420 51 51 11 1385 1 11 11 521 521 65 65 12 1155 1 12 12 358 358 40 40 13 1120 1 13 13 435 435 41 41 14 1703 1 14 14 690 690 76 76 15 1189 1 15 15 393 393 31 31 16 3083 1 16 16 1149 1149 82 82 17 1357 1 17 17 486 486 36 36 18 1892 1 18 18 767 767 62 62 19 883 1 19 19 338 338 28 28 20 1627 1 20 20 485 485 38 38 21 1412 1 21 21 465 465 70 70 22 1900 1 22 22 816 816 76 76 23 777 1 23 23 265 265 33 33 24 904 1 24 24 307 307 40 40 25 2115 1 25 25 850 850 126 126 26 1858 1 26 26 704 704 56 56 27 1781 1 27 27 693 693 63 63 28 1286 1 28 28 387 387 46 46 29 1035 1 29 29 406 406 35 35 30 1557 1 30 30 573 573 108 108 31 1527 0 31 0 595 0 34 0 32 1220 0 32 0 394 0 54 0 33 1368 0 33 0 521 0 35 0 34 564 0 34 0 172 0 23 0 35 1990 0 35 0 835 0 46 0 36 1557 0 36 0 669 0 49 0 37 2057 0 37 0 749 0 56 0 38 1111 0 38 0 368 0 38 0 39 686 0 39 0 216 0 19 0 40 2011 0 40 0 772 0 29 0 41 2232 0 41 0 1084 0 26 0 42 1032 0 42 0 445 0 52 0 43 1166 0 43 0 451 0 54 0 44 1020 0 44 0 300 0 45 0 45 1735 0 45 0 836 0 56 0 46 3623 0 46 0 1417 0 596 0 47 918 0 47 0 330 0 57 0 48 1579 0 48 0 477 0 55 0 49 2790 0 49 0 1028 0 99 0 50 1496 0 50 0 646 0 51 0 51 1108 0 51 0 342 0 21 0 52 496 0 52 0 218 0 20 0 53 1750 0 53 0 591 0 58 0 54 744 0 54 0 255 0 21 0 55 1101 0 55 0 434 0 66 0 56 1612 0 56 0 654 0 47 0 57 1805 0 57 0 478 0 55 0 58 2460 0 58 0 753 0 158 0 59 1653 0 59 0 689 0 46 0 60 1234 0 60 0 470 0 45 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Pop t pop_t x1 x1_p 61.407593 127.734587 4.823237 0.136681 2.054663 0.008315 x2 x2_p 0.945522 -0.169169 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -314.10 -122.37 -24.78 88.23 434.54 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 61.407593 195.515413 0.314 0.7547 Pop 127.734587 216.831301 0.589 0.5583 t 4.823237 3.843805 1.255 0.2152 pop_t 0.136681 5.465292 0.025 0.9801 x1 2.054663 0.153570 13.379 <2e-16 *** x1_p 0.008315 0.214291 0.039 0.9692 x2 0.945522 0.421586 2.243 0.0292 * x2_p -0.169169 1.642450 -0.103 0.9184 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 180.9 on 52 degrees of freedom Multiple R-squared: 0.9311, Adjusted R-squared: 0.9218 F-statistic: 100.3 on 7 and 52 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,] 0.6394027188 0.7211945624 0.3605973 [2,] 0.6197420085 0.7605159829 0.3802580 [3,] 0.4764288223 0.9528576447 0.5235712 [4,] 0.3510858843 0.7021717685 0.6489141 [5,] 0.2780706357 0.5561412713 0.7219294 [6,] 0.6255827534 0.7488344932 0.3744172 [7,] 0.5173891140 0.9652217720 0.4826109 [8,] 0.4302310986 0.8604621972 0.5697689 [9,] 0.4052727213 0.8105454425 0.5947273 [10,] 0.4773160503 0.9546321007 0.5226839 [11,] 0.3997208505 0.7994417010 0.6002791 [12,] 0.4067409910 0.8134819819 0.5932590 [13,] 0.3596359344 0.7192718687 0.6403641 [14,] 0.2998189426 0.5996378853 0.7001811 [15,] 0.2572760052 0.5145520104 0.7427240 [16,] 0.1914529045 0.3829058090 0.8085471 [17,] 0.1377968588 0.2755937176 0.8622031 [18,] 0.1016171967 0.2032343935 0.8983828 [19,] 0.0870510445 0.1741020890 0.9129490 [20,] 0.0586086583 0.1172173165 0.9413913 [21,] 0.0377871581 0.0755743162 0.9622128 [22,] 0.0261715473 0.0523430947 0.9738285 [23,] 0.0159557331 0.0319114662 0.9840443 [24,] 0.0090414653 0.0180829307 0.9909585 [25,] 0.0049574011 0.0099148021 0.9950426 [26,] 0.0027806906 0.0055613811 0.9972193 [27,] 0.0038874073 0.0077748146 0.9961126 [28,] 0.0024525125 0.0049050251 0.9975475 [29,] 0.0012707258 0.0025414516 0.9987293 [30,] 0.0013302429 0.0026604857 0.9986698 [31,] 0.0013573193 0.0027146387 0.9986427 [32,] 0.0012031017 0.0024062034 0.9987969 [33,] 0.0005313627 0.0010627253 0.9994686 [34,] 0.0004195976 0.0008391952 0.9995804 [35,] 0.0009031596 0.0018063192 0.9990968 [36,] 0.0063310372 0.0126620744 0.9936690 [37,] 0.0045280544 0.0090561089 0.9954719 [38,] 0.0064662553 0.0129325105 0.9935337 [39,] 0.0058770639 0.0117541277 0.9941229 > postscript(file="/var/wessaorg/rcomp/tmp/11w161321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2hqlq1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3trba1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/49uzz1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5yxa01321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 60 Frequency = 1 1 2 3 4 5 6 231.5814384 -24.2656931 56.4408075 -163.3478281 57.0536946 -144.7483884 7 8 9 10 11 12 -226.9969391 -124.5230765 -108.3372581 13.2138002 16.0241420 136.7384981 13 14 15 16 17 18 -62.8470891 -38.0388036 90.6416926 380.4762775 52.9831237 -16.8588405 19 20 21 22 23 24 -119.4051196 308.6136423 105.0699748 -140.6533883 -98.5291535 -68.5686273 25 26 27 28 29 30 -49.4920733 44.0875629 -20.6140698 123.8953310 -162.7212823 -46.8723548 31 32 33 34 35 36 61.3995959 143.6532602 43.8526911 -36.5467575 0.6411699 -98.9445100 37 38 39 40 41 42 225.2405275 74.2634396 -25.2860431 143.0426537 -278.9989954 -195.4758976 43 44 45 46 47 48 -80.5181589 87.4224747 -314.1010827 -135.2656482 -102.0334021 253.9988864 49 50 51 52 53 54 286.4531511 -182.1036125 78.0564828 -283.0429714 163.8145092 -121.6575127 55 56 57 58 59 60 -179.8139883 -107.6982528 434.5350911 422.2906520 -152.1356601 -125.0420921 > postscript(file="/var/wessaorg/rcomp/tmp/64lgl1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 60 Frequency = 1 lag(myerror, k = 1) myerror 0 231.5814384 NA 1 -24.2656931 231.5814384 2 56.4408075 -24.2656931 3 -163.3478281 56.4408075 4 57.0536946 -163.3478281 5 -144.7483884 57.0536946 6 -226.9969391 -144.7483884 7 -124.5230765 -226.9969391 8 -108.3372581 -124.5230765 9 13.2138002 -108.3372581 10 16.0241420 13.2138002 11 136.7384981 16.0241420 12 -62.8470891 136.7384981 13 -38.0388036 -62.8470891 14 90.6416926 -38.0388036 15 380.4762775 90.6416926 16 52.9831237 380.4762775 17 -16.8588405 52.9831237 18 -119.4051196 -16.8588405 19 308.6136423 -119.4051196 20 105.0699748 308.6136423 21 -140.6533883 105.0699748 22 -98.5291535 -140.6533883 23 -68.5686273 -98.5291535 24 -49.4920733 -68.5686273 25 44.0875629 -49.4920733 26 -20.6140698 44.0875629 27 123.8953310 -20.6140698 28 -162.7212823 123.8953310 29 -46.8723548 -162.7212823 30 61.3995959 -46.8723548 31 143.6532602 61.3995959 32 43.8526911 143.6532602 33 -36.5467575 43.8526911 34 0.6411699 -36.5467575 35 -98.9445100 0.6411699 36 225.2405275 -98.9445100 37 74.2634396 225.2405275 38 -25.2860431 74.2634396 39 143.0426537 -25.2860431 40 -278.9989954 143.0426537 41 -195.4758976 -278.9989954 42 -80.5181589 -195.4758976 43 87.4224747 -80.5181589 44 -314.1010827 87.4224747 45 -135.2656482 -314.1010827 46 -102.0334021 -135.2656482 47 253.9988864 -102.0334021 48 286.4531511 253.9988864 49 -182.1036125 286.4531511 50 78.0564828 -182.1036125 51 -283.0429714 78.0564828 52 163.8145092 -283.0429714 53 -121.6575127 163.8145092 54 -179.8139883 -121.6575127 55 -107.6982528 -179.8139883 56 434.5350911 -107.6982528 57 422.2906520 434.5350911 58 -152.1356601 422.2906520 59 -125.0420921 -152.1356601 60 NA -125.0420921 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -24.2656931 231.5814384 [2,] 56.4408075 -24.2656931 [3,] -163.3478281 56.4408075 [4,] 57.0536946 -163.3478281 [5,] -144.7483884 57.0536946 [6,] -226.9969391 -144.7483884 [7,] -124.5230765 -226.9969391 [8,] -108.3372581 -124.5230765 [9,] 13.2138002 -108.3372581 [10,] 16.0241420 13.2138002 [11,] 136.7384981 16.0241420 [12,] -62.8470891 136.7384981 [13,] -38.0388036 -62.8470891 [14,] 90.6416926 -38.0388036 [15,] 380.4762775 90.6416926 [16,] 52.9831237 380.4762775 [17,] -16.8588405 52.9831237 [18,] -119.4051196 -16.8588405 [19,] 308.6136423 -119.4051196 [20,] 105.0699748 308.6136423 [21,] -140.6533883 105.0699748 [22,] -98.5291535 -140.6533883 [23,] -68.5686273 -98.5291535 [24,] -49.4920733 -68.5686273 [25,] 44.0875629 -49.4920733 [26,] -20.6140698 44.0875629 [27,] 123.8953310 -20.6140698 [28,] -162.7212823 123.8953310 [29,] -46.8723548 -162.7212823 [30,] 61.3995959 -46.8723548 [31,] 143.6532602 61.3995959 [32,] 43.8526911 143.6532602 [33,] -36.5467575 43.8526911 [34,] 0.6411699 -36.5467575 [35,] -98.9445100 0.6411699 [36,] 225.2405275 -98.9445100 [37,] 74.2634396 225.2405275 [38,] -25.2860431 74.2634396 [39,] 143.0426537 -25.2860431 [40,] -278.9989954 143.0426537 [41,] -195.4758976 -278.9989954 [42,] -80.5181589 -195.4758976 [43,] 87.4224747 -80.5181589 [44,] -314.1010827 87.4224747 [45,] -135.2656482 -314.1010827 [46,] -102.0334021 -135.2656482 [47,] 253.9988864 -102.0334021 [48,] 286.4531511 253.9988864 [49,] -182.1036125 286.4531511 [50,] 78.0564828 -182.1036125 [51,] -283.0429714 78.0564828 [52,] 163.8145092 -283.0429714 [53,] -121.6575127 163.8145092 [54,] -179.8139883 -121.6575127 [55,] -107.6982528 -179.8139883 [56,] 434.5350911 -107.6982528 [57,] 422.2906520 434.5350911 [58,] -152.1356601 422.2906520 [59,] -125.0420921 -152.1356601 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -24.2656931 231.5814384 2 56.4408075 -24.2656931 3 -163.3478281 56.4408075 4 57.0536946 -163.3478281 5 -144.7483884 57.0536946 6 -226.9969391 -144.7483884 7 -124.5230765 -226.9969391 8 -108.3372581 -124.5230765 9 13.2138002 -108.3372581 10 16.0241420 13.2138002 11 136.7384981 16.0241420 12 -62.8470891 136.7384981 13 -38.0388036 -62.8470891 14 90.6416926 -38.0388036 15 380.4762775 90.6416926 16 52.9831237 380.4762775 17 -16.8588405 52.9831237 18 -119.4051196 -16.8588405 19 308.6136423 -119.4051196 20 105.0699748 308.6136423 21 -140.6533883 105.0699748 22 -98.5291535 -140.6533883 23 -68.5686273 -98.5291535 24 -49.4920733 -68.5686273 25 44.0875629 -49.4920733 26 -20.6140698 44.0875629 27 123.8953310 -20.6140698 28 -162.7212823 123.8953310 29 -46.8723548 -162.7212823 30 61.3995959 -46.8723548 31 143.6532602 61.3995959 32 43.8526911 143.6532602 33 -36.5467575 43.8526911 34 0.6411699 -36.5467575 35 -98.9445100 0.6411699 36 225.2405275 -98.9445100 37 74.2634396 225.2405275 38 -25.2860431 74.2634396 39 143.0426537 -25.2860431 40 -278.9989954 143.0426537 41 -195.4758976 -278.9989954 42 -80.5181589 -195.4758976 43 87.4224747 -80.5181589 44 -314.1010827 87.4224747 45 -135.2656482 -314.1010827 46 -102.0334021 -135.2656482 47 253.9988864 -102.0334021 48 286.4531511 253.9988864 49 -182.1036125 286.4531511 50 78.0564828 -182.1036125 51 -283.0429714 78.0564828 52 163.8145092 -283.0429714 53 -121.6575127 163.8145092 54 -179.8139883 -121.6575127 55 -107.6982528 -179.8139883 56 434.5350911 -107.6982528 57 422.2906520 434.5350911 58 -152.1356601 422.2906520 59 -125.0420921 -152.1356601 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7k5n21321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/86bw81321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/97xfo1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10o1ei1321960222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11sqs21321960222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12kr1i1321960222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13ocit1321960222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14xzeh1321960222.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/1551jb1321960222.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/16cgkk1321960222.tab") + } > > try(system("convert tmp/11w161321960222.ps tmp/11w161321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/2hqlq1321960222.ps tmp/2hqlq1321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/3trba1321960222.ps tmp/3trba1321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/49uzz1321960222.ps tmp/49uzz1321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/5yxa01321960222.ps tmp/5yxa01321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/64lgl1321960222.ps tmp/64lgl1321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/7k5n21321960222.ps tmp/7k5n21321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/86bw81321960222.ps tmp/86bw81321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/97xfo1321960222.ps tmp/97xfo1321960222.png",intern=TRUE)) character(0) > try(system("convert tmp/10o1ei1321960222.ps tmp/10o1ei1321960222.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.249 0.486 3.764