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 + ,0 + ,1 + ,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 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0) + ,dim=c(7 + ,68) + ,dimnames=list(c('UseLimit' + ,'T40' + ,'T20' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome ') + ,1:68)) > y <- array(NA,dim=c(7,68),dimnames=list(c('UseLimit','T40','T20','Used','CorrectAnalysis','Useful','Outcome '),1:68)) > 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 = 'Do not include Seasonal Dummies' > par1 = '5' > par3 <- 'Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '5' > #'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, 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 T20 Used Useful Outcome\r\r t 1 0 1 1 0 0 0 1 1 2 0 0 0 1 0 0 0 2 3 0 0 0 0 0 0 0 3 4 0 0 0 0 0 0 0 4 5 0 0 0 0 0 0 0 5 6 0 1 0 1 0 1 1 6 7 0 0 0 0 0 0 0 7 8 0 0 1 0 0 0 0 8 9 0 0 0 1 0 0 1 9 10 0 1 0 0 0 0 0 10 11 0 1 1 1 0 0 0 11 12 0 0 0 0 0 0 0 12 13 0 0 0 0 1 1 0 13 14 0 1 1 0 0 0 0 14 15 0 0 0 0 1 1 1 15 16 0 0 1 0 1 1 1 16 17 1 1 1 0 1 1 0 17 18 0 1 1 0 0 0 0 18 19 0 0 0 1 0 0 1 19 20 1 0 1 0 1 1 1 20 21 0 1 0 0 0 1 0 21 22 0 1 0 1 1 1 1 22 23 0 0 0 0 0 1 1 23 24 0 1 0 0 0 1 1 24 25 0 0 1 1 1 0 1 25 26 0 0 0 1 1 1 0 26 27 0 1 0 0 0 0 1 27 28 0 0 0 1 1 0 0 28 29 0 0 0 0 0 0 1 29 30 0 0 0 0 0 1 0 30 31 0 0 0 0 0 0 0 31 32 0 1 0 0 0 0 0 32 33 0 1 0 0 0 1 0 33 34 0 0 1 0 0 0 1 34 35 0 0 0 0 0 0 0 35 36 0 0 0 0 0 0 0 36 37 0 1 1 1 1 1 0 37 38 0 0 0 0 1 0 1 38 39 0 0 0 0 0 1 1 39 40 0 0 1 1 0 1 0 40 41 1 0 0 0 1 1 1 41 42 0 0 0 0 1 0 1 42 43 0 1 0 0 0 1 1 43 44 0 1 1 0 0 0 0 44 45 0 0 0 0 0 1 0 45 46 0 0 0 0 0 1 1 46 47 0 0 0 0 0 0 0 47 48 0 0 0 0 0 0 1 48 49 0 0 0 0 0 1 1 49 50 0 0 0 0 0 0 0 50 51 0 0 1 0 1 0 0 51 52 1 1 1 1 1 1 0 52 53 0 0 0 1 0 0 1 53 54 1 0 0 0 1 0 0 54 55 0 0 0 0 0 0 0 55 56 0 0 1 1 1 0 1 56 57 0 0 0 0 1 1 1 57 58 0 0 0 0 0 0 1 58 59 0 0 0 0 0 0 1 59 60 1 1 1 1 1 1 1 60 61 0 1 1 1 0 0 1 61 62 0 0 0 1 1 1 0 62 63 0 0 0 0 0 0 0 63 64 0 1 1 0 0 0 1 64 65 0 0 0 0 0 0 0 65 66 0 0 0 0 0 0 0 66 67 1 0 1 0 1 1 0 67 68 0 1 0 0 0 0 0 68 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) UseLimit T40 T20 -0.098769 0.045694 0.136487 -0.105813 Used Useful `Outcome\\r\\r` t 0.279608 0.110973 -0.047806 0.001919 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.43920 -0.12005 -0.02695 0.07785 0.71551 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.098769 0.076434 -1.292 0.20123 UseLimit 0.045694 0.076609 0.596 0.55312 T40 0.136487 0.078846 1.731 0.08858 . T20 -0.105813 0.077196 -1.371 0.17558 Used 0.279608 0.082984 3.369 0.00132 ** Useful 0.110973 0.073063 1.519 0.13405 `Outcome\\r\\r` -0.047806 0.064379 -0.743 0.46064 t 0.001919 0.001621 1.184 0.24110 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2584 on 60 degrees of freedom Multiple R-squared: 0.3619, Adjusted R-squared: 0.2875 F-statistic: 4.861 on 7 and 60 DF, p-value: 0.0002177 > 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,] 0.000000000 0.000000000 1.0000000 [2,] 0.000000000 0.000000000 1.0000000 [3,] 0.000000000 0.000000000 1.0000000 [4,] 0.000000000 0.000000000 1.0000000 [5,] 0.000000000 0.000000000 1.0000000 [6,] 0.000000000 0.000000000 1.0000000 [7,] 0.344900459 0.689800917 0.6550995 [8,] 0.261793640 0.523587280 0.7382064 [9,] 0.258120296 0.516240592 0.7418797 [10,] 0.731450589 0.537098821 0.2685494 [11,] 0.653913264 0.692173472 0.3460867 [12,] 0.630865698 0.738268605 0.3691343 [13,] 0.545844652 0.908310696 0.4541553 [14,] 0.460007507 0.920015013 0.5399925 [15,] 0.419439776 0.838879552 0.5805602 [16,] 0.377790228 0.755580456 0.6222098 [17,] 0.318835107 0.637670215 0.6811649 [18,] 0.251033017 0.502066034 0.7489670 [19,] 0.203315032 0.406630064 0.7966850 [20,] 0.152110126 0.304220252 0.8478899 [21,] 0.114063630 0.228127259 0.8859364 [22,] 0.081096915 0.162193831 0.9189031 [23,] 0.056781063 0.113562126 0.9432189 [24,] 0.040130075 0.080260150 0.9598699 [25,] 0.027591380 0.055182760 0.9724086 [26,] 0.018911158 0.037822315 0.9810888 [27,] 0.031163687 0.062327375 0.9688363 [28,] 0.023920816 0.047841633 0.9760792 [29,] 0.014665849 0.029331698 0.9853342 [30,] 0.008771044 0.017542089 0.9912290 [31,] 0.126078344 0.252156689 0.8739217 [32,] 0.104708252 0.209416504 0.8952917 [33,] 0.079461983 0.158923967 0.9205380 [34,] 0.065585820 0.131171640 0.9344142 [35,] 0.047109108 0.094218215 0.9528909 [36,] 0.030346981 0.060693962 0.9696530 [37,] 0.018775763 0.037551525 0.9812242 [38,] 0.011315639 0.022631277 0.9886844 [39,] 0.006485154 0.012970309 0.9935148 [40,] 0.003522519 0.007045039 0.9964775 [41,] 0.029483206 0.058966412 0.9705168 [42,] 0.058017860 0.116035721 0.9419821 [43,] 0.064982958 0.129965916 0.9350170 [44,] 0.318713487 0.637426974 0.6812865 [45,] 0.214765711 0.429531423 0.7852343 [46,] 0.134458115 0.268916229 0.8655419 [47,] 0.252536903 0.505073806 0.7474631 > postscript(file="/var/fisher/rcomp/tmp/1h2pe1356024407.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2caoe1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/36z5w1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/42o5m1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5yt2x1356024407.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 = 68 Frequency = 1 1 2 3 4 5 6 -0.037524330 0.200743486 0.093011145 0.091091726 0.089172307 0.084205500 7 8 9 10 11 12 0.085333469 -0.053072927 0.235113727 0.033881706 0.001288233 0.075736375 13 14 15 16 17 18 -0.316763973 -0.110282946 -0.272796638 -0.411203034 0.493377868 -0.117960622 19 20 21 22 23 24 0.215919539 0.581119290 -0.098204877 -0.226113154 -0.008544036 -0.056156961 25 26 27 28 29 30 -0.211691904 -0.235903495 0.049057758 -0.128769356 0.090912428 -0.069786140 31 32 33 34 35 36 0.039267418 -0.008345508 -0.121237903 -0.055171644 0.031589742 0.029670324 37 38 39 40 41 42 -0.439197585 -0.205970295 -0.039254737 -0.119654382 0.677298472 -0.213647970 43 44 45 46 47 48 -0.092625919 -0.167865511 -0.098577422 -0.052690669 0.008556717 0.054443470 49 50 51 52 53 54 -0.058448925 0.002798460 -0.415215889 0.532011132 0.150659299 0.715512832 55 56 57 58 59 60 -0.006798634 -0.271193888 -0.353412229 0.035249282 0.033329863 0.564461954 61 62 63 64 65 66 -0.046876535 -0.305002572 -0.022153984 -0.158447715 -0.025992822 -0.027912241 67 68 0.443100434 -0.077444585 > postscript(file="/var/fisher/rcomp/tmp/6t9dm1356024407.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 = 68 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.037524330 NA 1 0.200743486 -0.037524330 2 0.093011145 0.200743486 3 0.091091726 0.093011145 4 0.089172307 0.091091726 5 0.084205500 0.089172307 6 0.085333469 0.084205500 7 -0.053072927 0.085333469 8 0.235113727 -0.053072927 9 0.033881706 0.235113727 10 0.001288233 0.033881706 11 0.075736375 0.001288233 12 -0.316763973 0.075736375 13 -0.110282946 -0.316763973 14 -0.272796638 -0.110282946 15 -0.411203034 -0.272796638 16 0.493377868 -0.411203034 17 -0.117960622 0.493377868 18 0.215919539 -0.117960622 19 0.581119290 0.215919539 20 -0.098204877 0.581119290 21 -0.226113154 -0.098204877 22 -0.008544036 -0.226113154 23 -0.056156961 -0.008544036 24 -0.211691904 -0.056156961 25 -0.235903495 -0.211691904 26 0.049057758 -0.235903495 27 -0.128769356 0.049057758 28 0.090912428 -0.128769356 29 -0.069786140 0.090912428 30 0.039267418 -0.069786140 31 -0.008345508 0.039267418 32 -0.121237903 -0.008345508 33 -0.055171644 -0.121237903 34 0.031589742 -0.055171644 35 0.029670324 0.031589742 36 -0.439197585 0.029670324 37 -0.205970295 -0.439197585 38 -0.039254737 -0.205970295 39 -0.119654382 -0.039254737 40 0.677298472 -0.119654382 41 -0.213647970 0.677298472 42 -0.092625919 -0.213647970 43 -0.167865511 -0.092625919 44 -0.098577422 -0.167865511 45 -0.052690669 -0.098577422 46 0.008556717 -0.052690669 47 0.054443470 0.008556717 48 -0.058448925 0.054443470 49 0.002798460 -0.058448925 50 -0.415215889 0.002798460 51 0.532011132 -0.415215889 52 0.150659299 0.532011132 53 0.715512832 0.150659299 54 -0.006798634 0.715512832 55 -0.271193888 -0.006798634 56 -0.353412229 -0.271193888 57 0.035249282 -0.353412229 58 0.033329863 0.035249282 59 0.564461954 0.033329863 60 -0.046876535 0.564461954 61 -0.305002572 -0.046876535 62 -0.022153984 -0.305002572 63 -0.158447715 -0.022153984 64 -0.025992822 -0.158447715 65 -0.027912241 -0.025992822 66 0.443100434 -0.027912241 67 -0.077444585 0.443100434 68 NA -0.077444585 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.200743486 -0.037524330 [2,] 0.093011145 0.200743486 [3,] 0.091091726 0.093011145 [4,] 0.089172307 0.091091726 [5,] 0.084205500 0.089172307 [6,] 0.085333469 0.084205500 [7,] -0.053072927 0.085333469 [8,] 0.235113727 -0.053072927 [9,] 0.033881706 0.235113727 [10,] 0.001288233 0.033881706 [11,] 0.075736375 0.001288233 [12,] -0.316763973 0.075736375 [13,] -0.110282946 -0.316763973 [14,] -0.272796638 -0.110282946 [15,] -0.411203034 -0.272796638 [16,] 0.493377868 -0.411203034 [17,] -0.117960622 0.493377868 [18,] 0.215919539 -0.117960622 [19,] 0.581119290 0.215919539 [20,] -0.098204877 0.581119290 [21,] -0.226113154 -0.098204877 [22,] -0.008544036 -0.226113154 [23,] -0.056156961 -0.008544036 [24,] -0.211691904 -0.056156961 [25,] -0.235903495 -0.211691904 [26,] 0.049057758 -0.235903495 [27,] -0.128769356 0.049057758 [28,] 0.090912428 -0.128769356 [29,] -0.069786140 0.090912428 [30,] 0.039267418 -0.069786140 [31,] -0.008345508 0.039267418 [32,] -0.121237903 -0.008345508 [33,] -0.055171644 -0.121237903 [34,] 0.031589742 -0.055171644 [35,] 0.029670324 0.031589742 [36,] -0.439197585 0.029670324 [37,] -0.205970295 -0.439197585 [38,] -0.039254737 -0.205970295 [39,] -0.119654382 -0.039254737 [40,] 0.677298472 -0.119654382 [41,] -0.213647970 0.677298472 [42,] -0.092625919 -0.213647970 [43,] -0.167865511 -0.092625919 [44,] -0.098577422 -0.167865511 [45,] -0.052690669 -0.098577422 [46,] 0.008556717 -0.052690669 [47,] 0.054443470 0.008556717 [48,] -0.058448925 0.054443470 [49,] 0.002798460 -0.058448925 [50,] -0.415215889 0.002798460 [51,] 0.532011132 -0.415215889 [52,] 0.150659299 0.532011132 [53,] 0.715512832 0.150659299 [54,] -0.006798634 0.715512832 [55,] -0.271193888 -0.006798634 [56,] -0.353412229 -0.271193888 [57,] 0.035249282 -0.353412229 [58,] 0.033329863 0.035249282 [59,] 0.564461954 0.033329863 [60,] -0.046876535 0.564461954 [61,] -0.305002572 -0.046876535 [62,] -0.022153984 -0.305002572 [63,] -0.158447715 -0.022153984 [64,] -0.025992822 -0.158447715 [65,] -0.027912241 -0.025992822 [66,] 0.443100434 -0.027912241 [67,] -0.077444585 0.443100434 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.200743486 -0.037524330 2 0.093011145 0.200743486 3 0.091091726 0.093011145 4 0.089172307 0.091091726 5 0.084205500 0.089172307 6 0.085333469 0.084205500 7 -0.053072927 0.085333469 8 0.235113727 -0.053072927 9 0.033881706 0.235113727 10 0.001288233 0.033881706 11 0.075736375 0.001288233 12 -0.316763973 0.075736375 13 -0.110282946 -0.316763973 14 -0.272796638 -0.110282946 15 -0.411203034 -0.272796638 16 0.493377868 -0.411203034 17 -0.117960622 0.493377868 18 0.215919539 -0.117960622 19 0.581119290 0.215919539 20 -0.098204877 0.581119290 21 -0.226113154 -0.098204877 22 -0.008544036 -0.226113154 23 -0.056156961 -0.008544036 24 -0.211691904 -0.056156961 25 -0.235903495 -0.211691904 26 0.049057758 -0.235903495 27 -0.128769356 0.049057758 28 0.090912428 -0.128769356 29 -0.069786140 0.090912428 30 0.039267418 -0.069786140 31 -0.008345508 0.039267418 32 -0.121237903 -0.008345508 33 -0.055171644 -0.121237903 34 0.031589742 -0.055171644 35 0.029670324 0.031589742 36 -0.439197585 0.029670324 37 -0.205970295 -0.439197585 38 -0.039254737 -0.205970295 39 -0.119654382 -0.039254737 40 0.677298472 -0.119654382 41 -0.213647970 0.677298472 42 -0.092625919 -0.213647970 43 -0.167865511 -0.092625919 44 -0.098577422 -0.167865511 45 -0.052690669 -0.098577422 46 0.008556717 -0.052690669 47 0.054443470 0.008556717 48 -0.058448925 0.054443470 49 0.002798460 -0.058448925 50 -0.415215889 0.002798460 51 0.532011132 -0.415215889 52 0.150659299 0.532011132 53 0.715512832 0.150659299 54 -0.006798634 0.715512832 55 -0.271193888 -0.006798634 56 -0.353412229 -0.271193888 57 0.035249282 -0.353412229 58 0.033329863 0.035249282 59 0.564461954 0.033329863 60 -0.046876535 0.564461954 61 -0.305002572 -0.046876535 62 -0.022153984 -0.305002572 63 -0.158447715 -0.022153984 64 -0.025992822 -0.158447715 65 -0.027912241 -0.025992822 66 0.443100434 -0.027912241 67 -0.077444585 0.443100434 > 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/7blws1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8w6mt1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9q8ai1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/10uezc1356024407.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11iwtz1356024407.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/129qvg1356024407.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/13ts1u1356024407.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/1455a61356024407.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/15jnmj1356024408.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/166fsd1356024408.tab") + } > > try(system("convert tmp/1h2pe1356024407.ps tmp/1h2pe1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/2caoe1356024407.ps tmp/2caoe1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/36z5w1356024407.ps tmp/36z5w1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/42o5m1356024407.ps tmp/42o5m1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/5yt2x1356024407.ps tmp/5yt2x1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/6t9dm1356024407.ps tmp/6t9dm1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/7blws1356024407.ps tmp/7blws1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/8w6mt1356024407.ps tmp/8w6mt1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/9q8ai1356024407.ps tmp/9q8ai1356024407.png",intern=TRUE)) character(0) > try(system("convert tmp/10uezc1356024407.ps tmp/10uezc1356024407.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.697 1.857 8.601