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Type 'q()' to quit R. > x <- array(list(589 + ,0 + ,591 + ,595 + ,594 + ,611 + ,584 + ,0 + ,589 + ,591 + ,595 + ,594 + ,573 + ,0 + ,584 + ,589 + ,591 + ,595 + ,567 + ,0 + ,573 + ,584 + ,589 + ,591 + ,569 + ,0 + ,567 + ,573 + ,584 + ,589 + ,621 + ,0 + ,569 + ,567 + ,573 + ,584 + ,629 + ,0 + ,621 + ,569 + ,567 + ,573 + ,628 + ,0 + ,629 + ,621 + ,569 + ,567 + ,612 + ,0 + ,628 + ,629 + ,621 + ,569 + ,595 + ,0 + ,612 + ,628 + ,629 + ,621 + ,597 + ,0 + ,595 + ,612 + ,628 + ,629 + ,593 + ,0 + ,597 + ,595 + ,612 + ,628 + ,590 + ,0 + ,593 + ,597 + ,595 + ,612 + ,580 + ,0 + ,590 + ,593 + ,597 + ,595 + ,574 + ,0 + ,580 + ,590 + ,593 + ,597 + ,573 + ,0 + ,574 + ,580 + ,590 + ,593 + ,573 + ,0 + ,573 + ,574 + ,580 + ,590 + ,620 + ,0 + ,573 + ,573 + ,574 + ,580 + ,626 + ,0 + ,620 + ,573 + ,573 + ,574 + ,620 + ,0 + ,626 + ,620 + ,573 + ,573 + ,588 + ,0 + ,620 + ,626 + ,620 + ,573 + ,566 + ,0 + ,588 + ,620 + ,626 + ,620 + ,557 + ,0 + ,566 + ,588 + ,620 + ,626 + ,561 + ,0 + ,557 + ,566 + ,588 + ,620 + ,549 + ,0 + ,561 + ,557 + ,566 + ,588 + ,532 + ,0 + ,549 + ,561 + ,557 + ,566 + ,526 + ,0 + ,532 + ,549 + ,561 + ,557 + ,511 + ,0 + ,526 + ,532 + ,549 + ,561 + ,499 + ,0 + ,511 + ,526 + ,532 + ,549 + ,555 + ,0 + ,499 + ,511 + ,526 + ,532 + ,565 + ,0 + ,555 + ,499 + ,511 + ,526 + ,542 + ,0 + ,565 + ,555 + ,499 + ,511 + ,527 + ,0 + ,542 + ,565 + ,555 + ,499 + ,510 + ,0 + ,527 + ,542 + ,565 + ,555 + ,514 + ,0 + ,510 + ,527 + ,542 + ,565 + ,517 + ,0 + ,514 + ,510 + ,527 + ,542 + ,508 + ,0 + ,517 + ,514 + ,510 + ,527 + ,493 + ,0 + ,508 + ,517 + ,514 + ,510 + ,490 + ,0 + ,493 + ,508 + ,517 + ,514 + ,469 + ,0 + ,490 + ,493 + ,508 + ,517 + ,478 + ,0 + ,469 + ,490 + ,493 + ,508 + ,528 + ,0 + ,478 + ,469 + ,490 + ,493 + ,534 + ,0 + ,528 + ,478 + ,469 + ,490 + ,518 + ,1 + ,534 + ,528 + ,478 + ,469 + ,506 + ,1 + ,518 + ,534 + ,528 + ,478 + ,502 + ,1 + ,506 + ,518 + ,534 + ,528 + ,516 + ,1 + ,502 + ,506 + ,518 + ,534 + ,528 + ,1 + ,516 + ,502 + ,506 + ,518 + ,533 + ,1 + ,528 + ,516 + ,502 + ,506 + ,536 + ,1 + ,533 + ,528 + ,516 + ,502 + ,537 + ,1 + ,536 + ,533 + ,528 + ,516 + ,524 + ,1 + ,537 + ,536 + ,533 + ,528 + ,536 + ,1 + ,524 + ,537 + ,536 + ,533 + ,587 + ,1 + ,536 + ,524 + ,537 + ,536 + ,597 + ,1 + ,587 + ,536 + ,524 + ,537 + ,581 + ,1 + ,597 + ,587 + ,536 + ,524) + ,dim=c(6 + ,56) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2' + ,'Y3' + ,'Y4') + ,1:56)) > y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:56)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > #'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 Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 589 0 591 595 594 611 1 0 0 0 0 0 0 0 0 0 0 1 2 584 0 589 591 595 594 0 1 0 0 0 0 0 0 0 0 0 2 3 573 0 584 589 591 595 0 0 1 0 0 0 0 0 0 0 0 3 4 567 0 573 584 589 591 0 0 0 1 0 0 0 0 0 0 0 4 5 569 0 567 573 584 589 0 0 0 0 1 0 0 0 0 0 0 5 6 621 0 569 567 573 584 0 0 0 0 0 1 0 0 0 0 0 6 7 629 0 621 569 567 573 0 0 0 0 0 0 1 0 0 0 0 7 8 628 0 629 621 569 567 0 0 0 0 0 0 0 1 0 0 0 8 9 612 0 628 629 621 569 0 0 0 0 0 0 0 0 1 0 0 9 10 595 0 612 628 629 621 0 0 0 0 0 0 0 0 0 1 0 10 11 597 0 595 612 628 629 0 0 0 0 0 0 0 0 0 0 1 11 12 593 0 597 595 612 628 0 0 0 0 0 0 0 0 0 0 0 12 13 590 0 593 597 595 612 1 0 0 0 0 0 0 0 0 0 0 13 14 580 0 590 593 597 595 0 1 0 0 0 0 0 0 0 0 0 14 15 574 0 580 590 593 597 0 0 1 0 0 0 0 0 0 0 0 15 16 573 0 574 580 590 593 0 0 0 1 0 0 0 0 0 0 0 16 17 573 0 573 574 580 590 0 0 0 0 1 0 0 0 0 0 0 17 18 620 0 573 573 574 580 0 0 0 0 0 1 0 0 0 0 0 18 19 626 0 620 573 573 574 0 0 0 0 0 0 1 0 0 0 0 19 20 620 0 626 620 573 573 0 0 0 0 0 0 0 1 0 0 0 20 21 588 0 620 626 620 573 0 0 0 0 0 0 0 0 1 0 0 21 22 566 0 588 620 626 620 0 0 0 0 0 0 0 0 0 1 0 22 23 557 0 566 588 620 626 0 0 0 0 0 0 0 0 0 0 1 23 24 561 0 557 566 588 620 0 0 0 0 0 0 0 0 0 0 0 24 25 549 0 561 557 566 588 1 0 0 0 0 0 0 0 0 0 0 25 26 532 0 549 561 557 566 0 1 0 0 0 0 0 0 0 0 0 26 27 526 0 532 549 561 557 0 0 1 0 0 0 0 0 0 0 0 27 28 511 0 526 532 549 561 0 0 0 1 0 0 0 0 0 0 0 28 29 499 0 511 526 532 549 0 0 0 0 1 0 0 0 0 0 0 29 30 555 0 499 511 526 532 0 0 0 0 0 1 0 0 0 0 0 30 31 565 0 555 499 511 526 0 0 0 0 0 0 1 0 0 0 0 31 32 542 0 565 555 499 511 0 0 0 0 0 0 0 1 0 0 0 32 33 527 0 542 565 555 499 0 0 0 0 0 0 0 0 1 0 0 33 34 510 0 527 542 565 555 0 0 0 0 0 0 0 0 0 1 0 34 35 514 0 510 527 542 565 0 0 0 0 0 0 0 0 0 0 1 35 36 517 0 514 510 527 542 0 0 0 0 0 0 0 0 0 0 0 36 37 508 0 517 514 510 527 1 0 0 0 0 0 0 0 0 0 0 37 38 493 0 508 517 514 510 0 1 0 0 0 0 0 0 0 0 0 38 39 490 0 493 508 517 514 0 0 1 0 0 0 0 0 0 0 0 39 40 469 0 490 493 508 517 0 0 0 1 0 0 0 0 0 0 0 40 41 478 0 469 490 493 508 0 0 0 0 1 0 0 0 0 0 0 41 42 528 0 478 469 490 493 0 0 0 0 0 1 0 0 0 0 0 42 43 534 0 528 478 469 490 0 0 0 0 0 0 1 0 0 0 0 43 44 518 1 534 528 478 469 0 0 0 0 0 0 0 1 0 0 0 44 45 506 1 518 534 528 478 0 0 0 0 0 0 0 0 1 0 0 45 46 502 1 506 518 534 528 0 0 0 0 0 0 0 0 0 1 0 46 47 516 1 502 506 518 534 0 0 0 0 0 0 0 0 0 0 1 47 48 528 1 516 502 506 518 0 0 0 0 0 0 0 0 0 0 0 48 49 533 1 528 516 502 506 1 0 0 0 0 0 0 0 0 0 0 49 50 536 1 533 528 516 502 0 1 0 0 0 0 0 0 0 0 0 50 51 537 1 536 533 528 516 0 0 1 0 0 0 0 0 0 0 0 51 52 524 1 537 536 533 528 0 0 0 1 0 0 0 0 0 0 0 52 53 536 1 524 537 536 533 0 0 0 0 1 0 0 0 0 0 0 53 54 587 1 536 524 537 536 0 0 0 0 0 1 0 0 0 0 0 54 55 597 1 587 536 524 537 0 0 0 0 0 0 1 0 0 0 0 55 56 581 1 597 587 536 524 0 0 0 0 0 0 0 1 0 0 0 56 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 Y3 Y4 74.86259 11.45798 0.88383 0.14893 0.06805 -0.20561 M1 M2 M3 M4 M5 M6 -11.00933 -19.39432 -15.28710 -19.65897 -6.71985 43.09483 M7 M8 M9 M10 M11 t 5.60930 -25.87023 -37.98172 -24.30985 -2.82507 -0.36025 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -13.2972 -3.0595 0.3324 3.6071 11.6386 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 74.86259 28.84990 2.595 0.013372 * X 11.45798 4.01351 2.855 0.006938 ** Y1 0.88383 0.15028 5.881 8.29e-07 *** Y2 0.14893 0.20592 0.723 0.473966 Y3 0.06805 0.20612 0.330 0.743089 Y4 -0.20561 0.15849 -1.297 0.202354 M1 -11.00933 5.01568 -2.195 0.034346 * M2 -19.39432 6.20817 -3.124 0.003408 ** M3 -15.28710 6.00491 -2.546 0.015082 * M4 -19.65897 5.14591 -3.820 0.000479 *** M5 -6.71985 5.33704 -1.259 0.215675 M6 43.09483 4.97129 8.669 1.55e-10 *** M7 5.60930 8.93740 0.628 0.534006 M8 -25.87023 11.08918 -2.333 0.025046 * M9 -37.98172 12.58719 -3.017 0.004531 ** M10 -24.30985 6.85896 -3.544 0.001063 ** M11 -2.82507 5.32112 -0.531 0.598567 t -0.36025 0.13288 -2.711 0.010012 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 6.264 on 38 degrees of freedom Multiple R-squared: 0.9844, Adjusted R-squared: 0.9774 F-statistic: 141.2 on 17 and 38 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,] 0.6065063 0.7869874 0.39349369 [2,] 0.4746464 0.9492929 0.52535355 [3,] 0.5287233 0.9425534 0.47127668 [4,] 0.6485695 0.7028609 0.35143046 [5,] 0.5835253 0.8329495 0.41647474 [6,] 0.4978727 0.9957455 0.50212726 [7,] 0.4843820 0.9687640 0.51561798 [8,] 0.4936607 0.9873214 0.50633931 [9,] 0.8266624 0.3466752 0.17333759 [10,] 0.8858361 0.2283279 0.11416393 [11,] 0.9176620 0.1646761 0.08233803 [12,] 0.9107750 0.1784499 0.08922496 [13,] 0.8924583 0.2150833 0.10754165 [14,] 0.7883900 0.4232199 0.21160996 [15,] 0.7772159 0.4455683 0.22278413 > postscript(file="/var/www/html/rcomp/tmp/12mja1258658203.ps",horizontal=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2o8nn1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3fd281258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/448m31258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5aqcm1258658203.ps",horizontal=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 = 56 Frequency = 1 1 2 3 4 5 -2.451057e-01 2.300095e+00 -7.252037e+00 1.260556e+00 -2.448087e+00 6 7 8 9 10 -1.056101e+00 -3.320913e+00 1.133432e+01 4.370991e+00 -1.503086e+00 11 12 13 14 15 -1.506709e+00 -6.324228e+00 3.149985e+00 1.510967e+00 1.732539e+00 16 17 18 19 20 1.163864e+01 9.008561e-01 -3.052426e+00 -1.912433e+00 1.141925e+01 21 22 23 24 25 -6.898020e+00 -3.778072e+00 -8.050678e+00 5.659393e+00 -2.248375e+00 26 27 28 29 30 -4.403761e+00 5.388510e-01 -2.552217e-01 -1.199345e+01 4.304960e+00 31 32 33 34 35 4.230286e+00 -6.375598e+00 3.656822e+00 8.615994e-01 4.617424e+00 36 37 38 39 40 4.407768e-01 -2.364088e+00 -4.878685e+00 3.590460e+00 -6.562732e+00 41 42 43 44 45 8.035989e+00 8.745031e-01 5.445569e-04 -1.329719e+01 -1.129793e+00 46 47 48 49 50 4.419559e+00 4.939963e+00 2.240583e-01 1.707583e+00 5.471384e+00 51 52 53 54 55 1.390188e+00 -6.081243e+00 5.504694e+00 -1.070935e+00 1.002515e+00 56 -3.080783e+00 > postscript(file="/var/www/html/rcomp/tmp/6k30x1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 56 Frequency = 1 lag(myerror, k = 1) myerror 0 -2.451057e-01 NA 1 2.300095e+00 -2.451057e-01 2 -7.252037e+00 2.300095e+00 3 1.260556e+00 -7.252037e+00 4 -2.448087e+00 1.260556e+00 5 -1.056101e+00 -2.448087e+00 6 -3.320913e+00 -1.056101e+00 7 1.133432e+01 -3.320913e+00 8 4.370991e+00 1.133432e+01 9 -1.503086e+00 4.370991e+00 10 -1.506709e+00 -1.503086e+00 11 -6.324228e+00 -1.506709e+00 12 3.149985e+00 -6.324228e+00 13 1.510967e+00 3.149985e+00 14 1.732539e+00 1.510967e+00 15 1.163864e+01 1.732539e+00 16 9.008561e-01 1.163864e+01 17 -3.052426e+00 9.008561e-01 18 -1.912433e+00 -3.052426e+00 19 1.141925e+01 -1.912433e+00 20 -6.898020e+00 1.141925e+01 21 -3.778072e+00 -6.898020e+00 22 -8.050678e+00 -3.778072e+00 23 5.659393e+00 -8.050678e+00 24 -2.248375e+00 5.659393e+00 25 -4.403761e+00 -2.248375e+00 26 5.388510e-01 -4.403761e+00 27 -2.552217e-01 5.388510e-01 28 -1.199345e+01 -2.552217e-01 29 4.304960e+00 -1.199345e+01 30 4.230286e+00 4.304960e+00 31 -6.375598e+00 4.230286e+00 32 3.656822e+00 -6.375598e+00 33 8.615994e-01 3.656822e+00 34 4.617424e+00 8.615994e-01 35 4.407768e-01 4.617424e+00 36 -2.364088e+00 4.407768e-01 37 -4.878685e+00 -2.364088e+00 38 3.590460e+00 -4.878685e+00 39 -6.562732e+00 3.590460e+00 40 8.035989e+00 -6.562732e+00 41 8.745031e-01 8.035989e+00 42 5.445569e-04 8.745031e-01 43 -1.329719e+01 5.445569e-04 44 -1.129793e+00 -1.329719e+01 45 4.419559e+00 -1.129793e+00 46 4.939963e+00 4.419559e+00 47 2.240583e-01 4.939963e+00 48 1.707583e+00 2.240583e-01 49 5.471384e+00 1.707583e+00 50 1.390188e+00 5.471384e+00 51 -6.081243e+00 1.390188e+00 52 5.504694e+00 -6.081243e+00 53 -1.070935e+00 5.504694e+00 54 1.002515e+00 -1.070935e+00 55 -3.080783e+00 1.002515e+00 56 NA -3.080783e+00 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 2.300095e+00 -2.451057e-01 [2,] -7.252037e+00 2.300095e+00 [3,] 1.260556e+00 -7.252037e+00 [4,] -2.448087e+00 1.260556e+00 [5,] -1.056101e+00 -2.448087e+00 [6,] -3.320913e+00 -1.056101e+00 [7,] 1.133432e+01 -3.320913e+00 [8,] 4.370991e+00 1.133432e+01 [9,] -1.503086e+00 4.370991e+00 [10,] -1.506709e+00 -1.503086e+00 [11,] -6.324228e+00 -1.506709e+00 [12,] 3.149985e+00 -6.324228e+00 [13,] 1.510967e+00 3.149985e+00 [14,] 1.732539e+00 1.510967e+00 [15,] 1.163864e+01 1.732539e+00 [16,] 9.008561e-01 1.163864e+01 [17,] -3.052426e+00 9.008561e-01 [18,] -1.912433e+00 -3.052426e+00 [19,] 1.141925e+01 -1.912433e+00 [20,] -6.898020e+00 1.141925e+01 [21,] -3.778072e+00 -6.898020e+00 [22,] -8.050678e+00 -3.778072e+00 [23,] 5.659393e+00 -8.050678e+00 [24,] -2.248375e+00 5.659393e+00 [25,] -4.403761e+00 -2.248375e+00 [26,] 5.388510e-01 -4.403761e+00 [27,] -2.552217e-01 5.388510e-01 [28,] -1.199345e+01 -2.552217e-01 [29,] 4.304960e+00 -1.199345e+01 [30,] 4.230286e+00 4.304960e+00 [31,] -6.375598e+00 4.230286e+00 [32,] 3.656822e+00 -6.375598e+00 [33,] 8.615994e-01 3.656822e+00 [34,] 4.617424e+00 8.615994e-01 [35,] 4.407768e-01 4.617424e+00 [36,] -2.364088e+00 4.407768e-01 [37,] -4.878685e+00 -2.364088e+00 [38,] 3.590460e+00 -4.878685e+00 [39,] -6.562732e+00 3.590460e+00 [40,] 8.035989e+00 -6.562732e+00 [41,] 8.745031e-01 8.035989e+00 [42,] 5.445569e-04 8.745031e-01 [43,] -1.329719e+01 5.445569e-04 [44,] -1.129793e+00 -1.329719e+01 [45,] 4.419559e+00 -1.129793e+00 [46,] 4.939963e+00 4.419559e+00 [47,] 2.240583e-01 4.939963e+00 [48,] 1.707583e+00 2.240583e-01 [49,] 5.471384e+00 1.707583e+00 [50,] 1.390188e+00 5.471384e+00 [51,] -6.081243e+00 1.390188e+00 [52,] 5.504694e+00 -6.081243e+00 [53,] -1.070935e+00 5.504694e+00 [54,] 1.002515e+00 -1.070935e+00 [55,] -3.080783e+00 1.002515e+00 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 2.300095e+00 -2.451057e-01 2 -7.252037e+00 2.300095e+00 3 1.260556e+00 -7.252037e+00 4 -2.448087e+00 1.260556e+00 5 -1.056101e+00 -2.448087e+00 6 -3.320913e+00 -1.056101e+00 7 1.133432e+01 -3.320913e+00 8 4.370991e+00 1.133432e+01 9 -1.503086e+00 4.370991e+00 10 -1.506709e+00 -1.503086e+00 11 -6.324228e+00 -1.506709e+00 12 3.149985e+00 -6.324228e+00 13 1.510967e+00 3.149985e+00 14 1.732539e+00 1.510967e+00 15 1.163864e+01 1.732539e+00 16 9.008561e-01 1.163864e+01 17 -3.052426e+00 9.008561e-01 18 -1.912433e+00 -3.052426e+00 19 1.141925e+01 -1.912433e+00 20 -6.898020e+00 1.141925e+01 21 -3.778072e+00 -6.898020e+00 22 -8.050678e+00 -3.778072e+00 23 5.659393e+00 -8.050678e+00 24 -2.248375e+00 5.659393e+00 25 -4.403761e+00 -2.248375e+00 26 5.388510e-01 -4.403761e+00 27 -2.552217e-01 5.388510e-01 28 -1.199345e+01 -2.552217e-01 29 4.304960e+00 -1.199345e+01 30 4.230286e+00 4.304960e+00 31 -6.375598e+00 4.230286e+00 32 3.656822e+00 -6.375598e+00 33 8.615994e-01 3.656822e+00 34 4.617424e+00 8.615994e-01 35 4.407768e-01 4.617424e+00 36 -2.364088e+00 4.407768e-01 37 -4.878685e+00 -2.364088e+00 38 3.590460e+00 -4.878685e+00 39 -6.562732e+00 3.590460e+00 40 8.035989e+00 -6.562732e+00 41 8.745031e-01 8.035989e+00 42 5.445569e-04 8.745031e-01 43 -1.329719e+01 5.445569e-04 44 -1.129793e+00 -1.329719e+01 45 4.419559e+00 -1.129793e+00 46 4.939963e+00 4.419559e+00 47 2.240583e-01 4.939963e+00 48 1.707583e+00 2.240583e-01 49 5.471384e+00 1.707583e+00 50 1.390188e+00 5.471384e+00 51 -6.081243e+00 1.390188e+00 52 5.504694e+00 -6.081243e+00 53 -1.070935e+00 5.504694e+00 54 1.002515e+00 -1.070935e+00 55 -3.080783e+00 1.002515e+00 > 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/7bh7l1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/81vic1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/97fjd1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10z3eq1258658203.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11mzbz1258658203.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/12uj3t1258658203.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/13bl2g1258658203.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/14mtrg1258658203.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/15h1vx1258658204.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/16gila1258658204.tab") + } > system("convert tmp/12mja1258658203.ps tmp/12mja1258658203.png") > system("convert tmp/2o8nn1258658203.ps tmp/2o8nn1258658203.png") > system("convert tmp/3fd281258658203.ps tmp/3fd281258658203.png") > system("convert tmp/448m31258658203.ps tmp/448m31258658203.png") > system("convert tmp/5aqcm1258658203.ps tmp/5aqcm1258658203.png") > system("convert tmp/6k30x1258658203.ps tmp/6k30x1258658203.png") > system("convert tmp/7bh7l1258658203.ps tmp/7bh7l1258658203.png") > system("convert tmp/81vic1258658203.ps tmp/81vic1258658203.png") > system("convert tmp/97fjd1258658203.ps tmp/97fjd1258658203.png") > system("convert tmp/10z3eq1258658203.ps tmp/10z3eq1258658203.png") > > > proc.time() user system elapsed 2.326 1.544 2.724