R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) 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 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0) + ,dim=c(6 + ,86) + ,dimnames=list(c('UseLimit' + ,'T40' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome ') + ,1:86)) > y <- array(NA,dim=c(6,86),dimnames=list(c('UseLimit','T40','Used','CorrectAnalysis','Useful','Outcome '),1:86)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = '' > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '4' > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, 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 CorrectAnalysis UseLimit T40 Used Useful Outcome\r 1 0 1 1 0 0 1 2 0 0 0 0 0 0 3 0 0 0 0 0 0 4 0 0 0 0 0 0 5 0 0 0 0 0 0 6 0 1 0 0 1 1 7 0 0 0 0 0 0 8 0 0 1 0 0 0 9 0 0 0 0 0 1 10 0 1 0 0 0 0 11 0 1 1 0 0 0 12 0 0 0 0 0 0 13 0 0 0 1 1 0 14 0 1 1 0 0 0 15 0 0 0 1 1 1 16 0 0 1 1 1 1 17 1 1 1 1 1 0 18 0 1 1 0 0 0 19 0 0 0 0 0 1 20 1 0 1 1 1 1 21 0 1 0 0 1 0 22 0 1 0 1 1 1 23 0 0 0 0 1 1 24 0 1 0 0 1 1 25 0 0 1 1 0 1 26 0 0 0 1 1 0 27 0 1 0 0 0 1 28 0 0 0 1 0 0 29 0 0 0 0 0 1 30 0 0 0 0 1 0 31 0 0 0 0 0 0 32 0 1 0 0 0 0 33 0 1 0 0 1 0 34 0 0 1 0 0 1 35 0 0 0 0 0 0 36 0 0 0 0 0 0 37 0 1 1 1 1 0 38 0 0 0 1 0 1 39 0 0 0 0 1 1 40 0 0 1 0 1 0 41 1 0 0 1 1 1 42 0 0 0 1 0 1 43 0 1 0 0 1 1 44 0 1 1 0 0 0 45 0 0 0 0 1 0 46 0 0 0 0 1 1 47 0 0 0 0 0 0 48 0 0 0 0 0 1 49 0 0 0 0 1 1 50 0 0 0 0 0 0 51 0 0 1 1 0 0 52 1 1 1 1 1 0 53 0 0 0 0 0 1 54 1 0 0 1 0 0 55 0 0 0 0 0 0 56 0 0 1 1 0 1 57 0 0 0 1 1 1 58 0 0 0 0 0 1 59 0 0 0 0 0 1 60 1 1 1 1 1 1 61 0 1 1 0 0 1 62 0 0 0 1 1 0 63 0 0 0 0 0 0 64 0 1 1 0 0 1 65 0 0 0 0 0 0 66 0 0 0 0 0 0 67 1 0 1 1 1 0 68 0 1 0 0 0 0 69 0 0 0 0 0 1 70 0 0 0 1 0 0 71 0 0 0 0 0 0 72 0 0 0 0 0 1 73 0 0 0 1 0 1 74 0 1 0 1 0 0 75 0 0 0 0 0 1 76 0 0 1 0 1 1 77 0 0 0 0 0 1 78 0 0 0 1 1 1 79 1 0 1 1 0 1 80 0 0 1 0 1 0 81 0 0 0 0 0 0 82 0 1 0 1 0 1 83 0 0 0 0 0 0 84 1 0 0 1 0 0 85 0 0 0 0 1 1 86 0 1 0 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) UseLimit T40 Used Useful -0.025501 -0.007484 0.150191 0.280285 0.063988 `Outcome\\r` -0.046232 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.46148 -0.13801 0.02037 0.03299 0.74522 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.025501 0.049180 -0.519 0.6055 UseLimit -0.007484 0.067009 -0.112 0.9113 T40 0.150191 0.068758 2.184 0.0319 * Used 0.280285 0.065026 4.310 4.6e-05 *** Useful 0.063988 0.063324 1.010 0.3153 `Outcome\\r` -0.046232 0.058251 -0.794 0.4297 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2653 on 80 degrees of freedom Multiple R-squared: 0.3014, Adjusted R-squared: 0.2578 F-statistic: 6.904 on 5 and 80 DF, p-value: 2.104e-05 > 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,] 0.00000000 0.00000000 1.0000000 [2,] 0.00000000 0.00000000 1.0000000 [3,] 0.00000000 0.00000000 1.0000000 [4,] 0.00000000 0.00000000 1.0000000 [5,] 0.00000000 0.00000000 1.0000000 [6,] 0.00000000 0.00000000 1.0000000 [7,] 0.00000000 0.00000000 1.0000000 [8,] 0.00000000 0.00000000 1.0000000 [9,] 0.16651077 0.33302153 0.8334892 [10,] 0.13262392 0.26524783 0.8673761 [11,] 0.10973609 0.21947219 0.8902639 [12,] 0.51022835 0.97954331 0.4897717 [13,] 0.42708628 0.85417256 0.5729137 [14,] 0.40479099 0.80958198 0.5952090 [15,] 0.32809553 0.65619106 0.6719045 [16,] 0.25996285 0.51992570 0.7400372 [17,] 0.25944367 0.51888735 0.7405563 [18,] 0.26173034 0.52346068 0.7382697 [19,] 0.22043269 0.44086537 0.7795673 [20,] 0.18498959 0.36997919 0.8150104 [21,] 0.14656524 0.29313049 0.8534348 [22,] 0.11178880 0.22357759 0.8882112 [23,] 0.08223682 0.16447364 0.9177632 [24,] 0.05934000 0.11868001 0.9406600 [25,] 0.04186241 0.08372483 0.9581376 [26,] 0.02981090 0.05962180 0.9701891 [27,] 0.02005172 0.04010344 0.9799483 [28,] 0.01314609 0.02629218 0.9868539 [29,] 0.02602167 0.05204335 0.9739783 [30,] 0.01974426 0.03948852 0.9802557 [31,] 0.01294759 0.02589517 0.9870524 [32,] 0.01150242 0.02300485 0.9884976 [33,] 0.16774887 0.33549774 0.8322511 [34,] 0.14556430 0.29112860 0.8544357 [35,] 0.11203573 0.22407145 0.8879643 [36,] 0.09104755 0.18209511 0.9089524 [37,] 0.06757171 0.13514342 0.9324283 [38,] 0.04917167 0.09834333 0.9508283 [39,] 0.03478304 0.06956608 0.9652170 [40,] 0.02449390 0.04898779 0.9755061 [41,] 0.01673536 0.03347072 0.9832646 [42,] 0.01102497 0.02204994 0.9889750 [43,] 0.02868874 0.05737748 0.9713113 [44,] 0.08836239 0.17672479 0.9116376 [45,] 0.06672859 0.13345718 0.9332714 [46,] 0.31273849 0.62547699 0.6872615 [47,] 0.25438687 0.50877375 0.7456131 [48,] 0.46735662 0.93471324 0.5326434 [49,] 0.43849668 0.87699336 0.5615033 [50,] 0.37497772 0.74995545 0.6250223 [51,] 0.31486692 0.62973383 0.6851331 [52,] 0.64220226 0.71559549 0.3577977 [53,] 0.58486880 0.83026239 0.4151312 [54,] 0.56855298 0.86289404 0.4314470 [55,] 0.49390554 0.98781108 0.5060945 [56,] 0.43862266 0.87724532 0.5613773 [57,] 0.36336336 0.72672673 0.6366366 [58,] 0.29270936 0.58541873 0.7072906 [59,] 0.43773313 0.87546626 0.5622669 [60,] 0.37581049 0.75162099 0.6241895 [61,] 0.29440446 0.58880892 0.7055955 [62,] 0.40628887 0.81257773 0.5937111 [63,] 0.33158864 0.66317729 0.6684114 [64,] 0.24470714 0.48941428 0.7552929 [65,] 0.40854741 0.81709482 0.5914526 [66,] 0.39865097 0.79730194 0.6013490 [67,] 0.28350223 0.56700447 0.7164978 [68,] 0.18226298 0.36452596 0.8177370 [69,] 0.10190187 0.20380374 0.8980981 > postscript(file="/var/fisher/rcomp/tmp/1c44l1356107007.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/fisher/rcomp/tmp/2ilb41356107007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3i2jf1356107007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4mkcy1356107007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5xl501356107007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 86 Frequency = 1 1 2 3 4 5 6 -0.070973338 0.025501350 0.025501350 0.025501350 0.025501350 0.015229741 7 8 9 10 11 12 0.025501350 -0.124689670 0.071733275 0.032985758 -0.117205263 0.025501350 13 14 15 16 17 18 -0.318771848 -0.117205263 -0.272539923 -0.422730944 0.538521539 -0.117205263 19 20 21 22 23 24 0.071733275 0.577269056 -0.031002184 -0.265055515 0.007745333 0.015229741 25 26 27 28 29 30 -0.358743002 -0.318771848 0.079217683 -0.254783906 0.071733275 -0.038486591 31 32 33 34 35 36 0.025501350 0.032985758 -0.031002184 -0.078457745 0.025501350 0.025501350 37 38 39 40 41 42 -0.461478461 -0.208551981 0.007745333 -0.188677612 0.727460077 -0.208551981 43 44 45 46 47 48 0.015229741 -0.117205263 -0.038486591 0.007745333 0.025501350 0.071733275 49 50 51 52 53 54 0.007745333 0.025501350 -0.404974927 0.538521539 0.071733275 0.745216094 55 56 57 58 59 60 0.025501350 -0.358743002 -0.272539923 0.071733275 0.071733275 0.584753464 61 62 63 64 65 66 -0.070973338 -0.318771848 0.025501350 -0.070973338 0.025501350 0.025501350 67 68 69 70 71 72 0.531037131 0.032985758 0.071733275 -0.254783906 0.025501350 0.071733275 73 74 75 76 77 78 -0.208551981 -0.247299498 0.071733275 -0.142445687 0.071733275 -0.272539923 79 80 81 82 83 84 0.641256998 -0.188677612 0.025501350 -0.201067574 0.025501350 0.745216094 85 86 0.007745333 0.032985758 > postscript(file="/var/fisher/rcomp/tmp/6iamf1356107008.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 = 86 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.070973338 NA 1 0.025501350 -0.070973338 2 0.025501350 0.025501350 3 0.025501350 0.025501350 4 0.025501350 0.025501350 5 0.015229741 0.025501350 6 0.025501350 0.015229741 7 -0.124689670 0.025501350 8 0.071733275 -0.124689670 9 0.032985758 0.071733275 10 -0.117205263 0.032985758 11 0.025501350 -0.117205263 12 -0.318771848 0.025501350 13 -0.117205263 -0.318771848 14 -0.272539923 -0.117205263 15 -0.422730944 -0.272539923 16 0.538521539 -0.422730944 17 -0.117205263 0.538521539 18 0.071733275 -0.117205263 19 0.577269056 0.071733275 20 -0.031002184 0.577269056 21 -0.265055515 -0.031002184 22 0.007745333 -0.265055515 23 0.015229741 0.007745333 24 -0.358743002 0.015229741 25 -0.318771848 -0.358743002 26 0.079217683 -0.318771848 27 -0.254783906 0.079217683 28 0.071733275 -0.254783906 29 -0.038486591 0.071733275 30 0.025501350 -0.038486591 31 0.032985758 0.025501350 32 -0.031002184 0.032985758 33 -0.078457745 -0.031002184 34 0.025501350 -0.078457745 35 0.025501350 0.025501350 36 -0.461478461 0.025501350 37 -0.208551981 -0.461478461 38 0.007745333 -0.208551981 39 -0.188677612 0.007745333 40 0.727460077 -0.188677612 41 -0.208551981 0.727460077 42 0.015229741 -0.208551981 43 -0.117205263 0.015229741 44 -0.038486591 -0.117205263 45 0.007745333 -0.038486591 46 0.025501350 0.007745333 47 0.071733275 0.025501350 48 0.007745333 0.071733275 49 0.025501350 0.007745333 50 -0.404974927 0.025501350 51 0.538521539 -0.404974927 52 0.071733275 0.538521539 53 0.745216094 0.071733275 54 0.025501350 0.745216094 55 -0.358743002 0.025501350 56 -0.272539923 -0.358743002 57 0.071733275 -0.272539923 58 0.071733275 0.071733275 59 0.584753464 0.071733275 60 -0.070973338 0.584753464 61 -0.318771848 -0.070973338 62 0.025501350 -0.318771848 63 -0.070973338 0.025501350 64 0.025501350 -0.070973338 65 0.025501350 0.025501350 66 0.531037131 0.025501350 67 0.032985758 0.531037131 68 0.071733275 0.032985758 69 -0.254783906 0.071733275 70 0.025501350 -0.254783906 71 0.071733275 0.025501350 72 -0.208551981 0.071733275 73 -0.247299498 -0.208551981 74 0.071733275 -0.247299498 75 -0.142445687 0.071733275 76 0.071733275 -0.142445687 77 -0.272539923 0.071733275 78 0.641256998 -0.272539923 79 -0.188677612 0.641256998 80 0.025501350 -0.188677612 81 -0.201067574 0.025501350 82 0.025501350 -0.201067574 83 0.745216094 0.025501350 84 0.007745333 0.745216094 85 0.032985758 0.007745333 86 NA 0.032985758 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.025501350 -0.070973338 [2,] 0.025501350 0.025501350 [3,] 0.025501350 0.025501350 [4,] 0.025501350 0.025501350 [5,] 0.015229741 0.025501350 [6,] 0.025501350 0.015229741 [7,] -0.124689670 0.025501350 [8,] 0.071733275 -0.124689670 [9,] 0.032985758 0.071733275 [10,] -0.117205263 0.032985758 [11,] 0.025501350 -0.117205263 [12,] -0.318771848 0.025501350 [13,] -0.117205263 -0.318771848 [14,] -0.272539923 -0.117205263 [15,] -0.422730944 -0.272539923 [16,] 0.538521539 -0.422730944 [17,] -0.117205263 0.538521539 [18,] 0.071733275 -0.117205263 [19,] 0.577269056 0.071733275 [20,] -0.031002184 0.577269056 [21,] -0.265055515 -0.031002184 [22,] 0.007745333 -0.265055515 [23,] 0.015229741 0.007745333 [24,] -0.358743002 0.015229741 [25,] -0.318771848 -0.358743002 [26,] 0.079217683 -0.318771848 [27,] -0.254783906 0.079217683 [28,] 0.071733275 -0.254783906 [29,] -0.038486591 0.071733275 [30,] 0.025501350 -0.038486591 [31,] 0.032985758 0.025501350 [32,] -0.031002184 0.032985758 [33,] -0.078457745 -0.031002184 [34,] 0.025501350 -0.078457745 [35,] 0.025501350 0.025501350 [36,] -0.461478461 0.025501350 [37,] -0.208551981 -0.461478461 [38,] 0.007745333 -0.208551981 [39,] -0.188677612 0.007745333 [40,] 0.727460077 -0.188677612 [41,] -0.208551981 0.727460077 [42,] 0.015229741 -0.208551981 [43,] -0.117205263 0.015229741 [44,] -0.038486591 -0.117205263 [45,] 0.007745333 -0.038486591 [46,] 0.025501350 0.007745333 [47,] 0.071733275 0.025501350 [48,] 0.007745333 0.071733275 [49,] 0.025501350 0.007745333 [50,] -0.404974927 0.025501350 [51,] 0.538521539 -0.404974927 [52,] 0.071733275 0.538521539 [53,] 0.745216094 0.071733275 [54,] 0.025501350 0.745216094 [55,] -0.358743002 0.025501350 [56,] -0.272539923 -0.358743002 [57,] 0.071733275 -0.272539923 [58,] 0.071733275 0.071733275 [59,] 0.584753464 0.071733275 [60,] -0.070973338 0.584753464 [61,] -0.318771848 -0.070973338 [62,] 0.025501350 -0.318771848 [63,] -0.070973338 0.025501350 [64,] 0.025501350 -0.070973338 [65,] 0.025501350 0.025501350 [66,] 0.531037131 0.025501350 [67,] 0.032985758 0.531037131 [68,] 0.071733275 0.032985758 [69,] -0.254783906 0.071733275 [70,] 0.025501350 -0.254783906 [71,] 0.071733275 0.025501350 [72,] -0.208551981 0.071733275 [73,] -0.247299498 -0.208551981 [74,] 0.071733275 -0.247299498 [75,] -0.142445687 0.071733275 [76,] 0.071733275 -0.142445687 [77,] -0.272539923 0.071733275 [78,] 0.641256998 -0.272539923 [79,] -0.188677612 0.641256998 [80,] 0.025501350 -0.188677612 [81,] -0.201067574 0.025501350 [82,] 0.025501350 -0.201067574 [83,] 0.745216094 0.025501350 [84,] 0.007745333 0.745216094 [85,] 0.032985758 0.007745333 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.025501350 -0.070973338 2 0.025501350 0.025501350 3 0.025501350 0.025501350 4 0.025501350 0.025501350 5 0.015229741 0.025501350 6 0.025501350 0.015229741 7 -0.124689670 0.025501350 8 0.071733275 -0.124689670 9 0.032985758 0.071733275 10 -0.117205263 0.032985758 11 0.025501350 -0.117205263 12 -0.318771848 0.025501350 13 -0.117205263 -0.318771848 14 -0.272539923 -0.117205263 15 -0.422730944 -0.272539923 16 0.538521539 -0.422730944 17 -0.117205263 0.538521539 18 0.071733275 -0.117205263 19 0.577269056 0.071733275 20 -0.031002184 0.577269056 21 -0.265055515 -0.031002184 22 0.007745333 -0.265055515 23 0.015229741 0.007745333 24 -0.358743002 0.015229741 25 -0.318771848 -0.358743002 26 0.079217683 -0.318771848 27 -0.254783906 0.079217683 28 0.071733275 -0.254783906 29 -0.038486591 0.071733275 30 0.025501350 -0.038486591 31 0.032985758 0.025501350 32 -0.031002184 0.032985758 33 -0.078457745 -0.031002184 34 0.025501350 -0.078457745 35 0.025501350 0.025501350 36 -0.461478461 0.025501350 37 -0.208551981 -0.461478461 38 0.007745333 -0.208551981 39 -0.188677612 0.007745333 40 0.727460077 -0.188677612 41 -0.208551981 0.727460077 42 0.015229741 -0.208551981 43 -0.117205263 0.015229741 44 -0.038486591 -0.117205263 45 0.007745333 -0.038486591 46 0.025501350 0.007745333 47 0.071733275 0.025501350 48 0.007745333 0.071733275 49 0.025501350 0.007745333 50 -0.404974927 0.025501350 51 0.538521539 -0.404974927 52 0.071733275 0.538521539 53 0.745216094 0.071733275 54 0.025501350 0.745216094 55 -0.358743002 0.025501350 56 -0.272539923 -0.358743002 57 0.071733275 -0.272539923 58 0.071733275 0.071733275 59 0.584753464 0.071733275 60 -0.070973338 0.584753464 61 -0.318771848 -0.070973338 62 0.025501350 -0.318771848 63 -0.070973338 0.025501350 64 0.025501350 -0.070973338 65 0.025501350 0.025501350 66 0.531037131 0.025501350 67 0.032985758 0.531037131 68 0.071733275 0.032985758 69 -0.254783906 0.071733275 70 0.025501350 -0.254783906 71 0.071733275 0.025501350 72 -0.208551981 0.071733275 73 -0.247299498 -0.208551981 74 0.071733275 -0.247299498 75 -0.142445687 0.071733275 76 0.071733275 -0.142445687 77 -0.272539923 0.071733275 78 0.641256998 -0.272539923 79 -0.188677612 0.641256998 80 0.025501350 -0.188677612 81 -0.201067574 0.025501350 82 0.025501350 -0.201067574 83 0.745216094 0.025501350 84 0.007745333 0.745216094 85 0.032985758 0.007745333 > 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/fisher/rcomp/tmp/7wfev1356107008.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/fisher/rcomp/tmp/87hzv1356107008.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/fisher/rcomp/tmp/94pg91356107008.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/fisher/rcomp/tmp/107brq1356107008.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/11ck3g1356107008.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/12ggaq1356107008.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/13r3al1356107008.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/14fmgh1356107008.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/fisher/rcomp/tmp/155pa01356107008.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/fisher/rcomp/tmp/168uuz1356107008.tab") + } > > try(system("convert tmp/1c44l1356107007.ps tmp/1c44l1356107007.png",intern=TRUE)) character(0) > try(system("convert tmp/2ilb41356107007.ps tmp/2ilb41356107007.png",intern=TRUE)) character(0) > try(system("convert tmp/3i2jf1356107007.ps tmp/3i2jf1356107007.png",intern=TRUE)) character(0) > try(system("convert tmp/4mkcy1356107007.ps tmp/4mkcy1356107007.png",intern=TRUE)) character(0) > try(system("convert tmp/5xl501356107007.ps tmp/5xl501356107007.png",intern=TRUE)) character(0) > try(system("convert tmp/6iamf1356107008.ps tmp/6iamf1356107008.png",intern=TRUE)) character(0) > try(system("convert tmp/7wfev1356107008.ps tmp/7wfev1356107008.png",intern=TRUE)) character(0) > try(system("convert tmp/87hzv1356107008.ps tmp/87hzv1356107008.png",intern=TRUE)) character(0) > try(system("convert tmp/94pg91356107008.ps tmp/94pg91356107008.png",intern=TRUE)) character(0) > try(system("convert tmp/107brq1356107008.ps tmp/107brq1356107008.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.778 1.795 8.652