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 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1) + ,dim=c(6 + ,85) + ,dimnames=list(c('UseLimit' + ,'T40' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome') + ,1:85)) > y <- array(NA,dim=c(6,85),dimnames=list(c('UseLimit','T40','Used','CorrectAnalysis','Useful','Outcome'),1:85)) > 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 = '2' > par3 <- 'Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '2' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo 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 T40 UseLimit Used CorrectAnalysis Useful Outcome t 1 1 1 1 1 1 1 1 2 0 0 1 1 1 0 2 3 0 0 1 1 1 0 3 4 0 0 1 1 1 0 4 5 0 0 1 1 1 0 5 6 0 1 1 1 0 1 6 7 0 0 1 1 1 0 7 8 1 0 1 1 1 0 8 9 0 0 1 1 1 1 9 10 0 1 1 1 1 0 10 11 1 1 1 1 1 0 11 12 0 0 1 1 1 0 12 13 0 0 0 1 0 0 13 14 1 1 1 1 1 0 14 15 0 0 0 1 0 1 15 16 1 0 0 1 0 1 16 17 1 1 0 0 0 0 17 18 1 1 1 1 1 0 18 19 0 0 1 1 1 1 19 20 1 0 0 0 0 1 20 21 0 1 1 1 0 0 21 22 0 1 0 1 0 1 22 23 0 0 1 1 0 1 23 24 0 1 1 1 0 1 24 25 1 0 0 1 1 1 25 26 0 0 0 1 0 0 26 27 0 1 1 1 1 1 27 28 0 0 0 1 1 0 28 29 0 0 1 1 1 1 29 30 0 0 1 1 0 0 30 31 0 0 1 1 1 0 31 32 0 1 1 1 1 0 32 33 0 1 1 1 0 0 33 34 1 0 1 1 1 1 34 35 0 0 1 1 1 0 35 36 0 0 1 1 1 0 36 37 1 1 0 1 0 0 37 38 0 0 0 1 1 1 38 39 0 0 1 1 0 1 39 40 1 0 1 1 0 0 40 41 0 0 0 0 0 1 41 42 0 0 0 1 1 1 42 43 0 1 1 1 0 1 43 44 1 1 1 1 1 0 44 45 0 0 1 1 0 0 45 46 0 0 1 1 0 1 46 47 0 0 1 1 1 0 47 48 0 0 1 1 1 1 48 49 0 0 1 1 0 1 49 50 0 0 1 1 1 0 50 51 1 0 0 1 1 0 51 52 1 1 0 0 0 0 52 53 0 0 1 1 1 1 53 54 0 0 0 0 1 0 54 55 0 0 1 1 1 0 55 56 1 0 0 1 1 1 56 57 0 0 0 1 0 1 57 58 0 0 1 1 1 1 58 59 0 0 1 1 1 1 59 60 1 1 0 0 0 1 60 61 1 1 1 1 1 1 61 62 0 0 0 1 0 0 62 63 0 0 1 1 1 0 63 64 1 1 1 1 1 1 64 65 0 0 1 1 1 0 65 66 0 0 1 1 1 0 66 67 1 0 0 0 0 0 67 68 0 1 1 1 1 0 68 69 0 0 1 1 1 1 69 70 0 0 0 1 1 0 70 71 0 0 1 1 1 0 71 72 0 0 1 1 1 1 72 73 0 0 0 1 1 1 73 74 0 1 0 1 1 0 74 75 0 0 1 1 1 1 75 76 1 0 1 1 0 1 76 77 0 0 1 1 1 1 77 78 0 0 0 1 0 1 78 79 1 0 0 0 1 1 79 80 1 0 1 1 0 0 80 81 0 0 1 1 1 0 81 82 0 1 0 1 1 1 82 83 0 0 1 1 1 0 83 84 0 0 0 0 1 0 84 85 0 0 1 1 0 1 85 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) UseLimit Used CorrectAnalysis 0.626002 0.265017 -0.076233 -0.385442 Useful Outcome t 0.012820 0.025478 -0.001201 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.6022 -0.1976 -0.1339 0.1556 0.9318 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.626002 0.185259 3.379 0.00114 ** UseLimit 0.265017 0.105418 2.514 0.01400 * Used -0.076233 0.114676 -0.665 0.50816 CorrectAnalysis -0.385442 0.173557 -2.221 0.02926 * Useful 0.012820 0.102105 0.126 0.90040 Outcome 0.025478 0.093864 0.271 0.78678 t -0.001201 0.001945 -0.618 0.53860 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.421 on 78 degrees of freedom Multiple R-squared: 0.1759, Adjusted R-squared: 0.1125 F-statistic: 2.775 on 6 and 78 DF, p-value: 0.01692 > 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,] 0.9120316 0.1759369 0.08796843 [2,] 0.9100833 0.1798333 0.08991666 [3,] 0.8473757 0.3052487 0.15262434 [4,] 0.7655482 0.4689036 0.23445181 [5,] 0.7269428 0.5461144 0.27305720 [6,] 0.6362489 0.7275022 0.36375108 [7,] 0.7783615 0.4432770 0.22163850 [8,] 0.7010945 0.5978110 0.29890549 [9,] 0.6598244 0.6803513 0.34017565 [10,] 0.6280756 0.7438488 0.37192438 [11,] 0.6038882 0.7922235 0.39611175 [12,] 0.5267128 0.9465743 0.47328716 [13,] 0.6807277 0.6385445 0.31927226 [14,] 0.6285301 0.7429398 0.37146991 [15,] 0.5802807 0.8394387 0.41971933 [16,] 0.5876176 0.8247647 0.41238236 [17,] 0.5221359 0.9557282 0.47786411 [18,] 0.5982594 0.8034813 0.40174065 [19,] 0.6040938 0.7918125 0.39590623 [20,] 0.5353735 0.9292531 0.46462654 [21,] 0.5054315 0.9891371 0.49456853 [22,] 0.4356840 0.8713681 0.56431596 [23,] 0.4141288 0.8282576 0.58587122 [24,] 0.3980754 0.7961507 0.60192464 [25,] 0.6192486 0.7615029 0.38075143 [26,] 0.5562081 0.8875838 0.44379188 [27,] 0.4915601 0.9831203 0.50843986 [28,] 0.5417017 0.9165966 0.45829828 [29,] 0.5319400 0.9361199 0.46805995 [30,] 0.4782527 0.9565054 0.52174731 [31,] 0.7238276 0.5523448 0.27617238 [32,] 0.7855477 0.4289046 0.21445228 [33,] 0.7488182 0.5023637 0.25118185 [34,] 0.7673029 0.4653941 0.23269705 [35,] 0.8057786 0.3884427 0.19422137 [36,] 0.7651171 0.4697657 0.23488287 [37,] 0.7383568 0.5232864 0.26164320 [38,] 0.6859276 0.6281448 0.31407241 [39,] 0.6345557 0.7308886 0.36544432 [40,] 0.6319702 0.7360595 0.36802976 [41,] 0.5759925 0.8480150 0.42400749 [42,] 0.7943438 0.4113124 0.20565621 [43,] 0.7413233 0.5173534 0.25867671 [44,] 0.6993456 0.6013087 0.30065436 [45,] 0.7496724 0.5006552 0.25032758 [46,] 0.6965190 0.6069619 0.30348095 [47,] 0.9221949 0.1556101 0.07780507 [48,] 0.9028800 0.1942400 0.09711999 [49,] 0.8759458 0.2481085 0.12405423 [50,] 0.8509456 0.2981088 0.14905441 [51,] 0.8832177 0.2335647 0.11678235 [52,] 0.8795606 0.2408787 0.12043937 [53,] 0.8641792 0.2716416 0.13582080 [54,] 0.8191520 0.3616960 0.18084802 [55,] 0.8813015 0.2373970 0.11869851 [56,] 0.8334337 0.3331326 0.16656628 [57,] 0.7743652 0.4512695 0.22563475 [58,] 0.7337465 0.5325069 0.26625346 [59,] 0.7430598 0.5138804 0.25694020 [60,] 0.6968861 0.6062277 0.30311386 [61,] 0.6106135 0.7787729 0.38938645 [62,] 0.5584418 0.8831165 0.44155823 [63,] 0.5352261 0.9295479 0.46477393 [64,] 0.4666019 0.9332038 0.53339810 [65,] 0.5874049 0.8251902 0.41259511 [66,] 0.5465170 0.9069660 0.45348300 > postscript(file="/var/fisher/rcomp/tmp/1yel21356185325.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2bj9z1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/39ftg1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4p4se1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5meou1356185325.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 = 85 Frequency = 1 1 2 3 4 5 6 0.53355923 -0.17474517 -0.17354382 -0.17234247 -0.17114112 -0.44761360 7 8 9 10 11 12 -0.16873842 0.83246294 -0.19181341 -0.43015091 0.57105044 -0.16273166 13 14 15 16 17 18 -0.22494264 0.57465450 -0.24801764 0.75318371 0.12940432 0.57945990 19 20 21 22 23 24 -0.17979989 0.37254723 -0.40411563 -0.50462473 -0.16217408 -0.42598928 25 26 27 28 29 30 0.75117547 -0.20932507 -0.43520563 -0.21974278 -0.16778638 -0.12828692 31 32 33 34 35 36 -0.13990598 -0.40372118 -0.38969942 0.83822038 -0.13510057 -0.13389922 37 38 39 40 41 42 0.53887324 -0.23320697 -0.14295245 0.88372659 -0.60222439 -0.22840156 43 44 45 46 47 48 -0.40316360 0.61069504 -0.11026665 -0.13454299 -0.12068436 -0.14496070 49 50 51 52 53 54 -0.13093894 -0.11708030 0.80788830 0.17145162 -0.13895395 -0.57394953 55 56 57 58 59 60 -0.11107355 0.78841736 -0.19756088 -0.13294719 -0.13174584 0.15558474 61 62 63 64 65 66 0.60564032 -0.16607642 -0.10146273 0.60924437 -0.09906003 -0.09785868 67 68 69 70 71 72 0.45448845 -0.36047253 -0.11973232 -0.16928602 -0.09185192 -0.11612827 73 74 75 76 77 78 -0.19115966 -0.42949717 -0.11252421 0.90149755 -0.11012151 -0.17233250 79 80 81 82 83 84 0.43060655 0.93178065 -0.07983841 -0.44536405 -0.07743571 -0.53790899 85 -0.08769029 > postscript(file="/var/fisher/rcomp/tmp/6svdq1356185325.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 = 85 Frequency = 1 lag(myerror, k = 1) myerror 0 0.53355923 NA 1 -0.17474517 0.53355923 2 -0.17354382 -0.17474517 3 -0.17234247 -0.17354382 4 -0.17114112 -0.17234247 5 -0.44761360 -0.17114112 6 -0.16873842 -0.44761360 7 0.83246294 -0.16873842 8 -0.19181341 0.83246294 9 -0.43015091 -0.19181341 10 0.57105044 -0.43015091 11 -0.16273166 0.57105044 12 -0.22494264 -0.16273166 13 0.57465450 -0.22494264 14 -0.24801764 0.57465450 15 0.75318371 -0.24801764 16 0.12940432 0.75318371 17 0.57945990 0.12940432 18 -0.17979989 0.57945990 19 0.37254723 -0.17979989 20 -0.40411563 0.37254723 21 -0.50462473 -0.40411563 22 -0.16217408 -0.50462473 23 -0.42598928 -0.16217408 24 0.75117547 -0.42598928 25 -0.20932507 0.75117547 26 -0.43520563 -0.20932507 27 -0.21974278 -0.43520563 28 -0.16778638 -0.21974278 29 -0.12828692 -0.16778638 30 -0.13990598 -0.12828692 31 -0.40372118 -0.13990598 32 -0.38969942 -0.40372118 33 0.83822038 -0.38969942 34 -0.13510057 0.83822038 35 -0.13389922 -0.13510057 36 0.53887324 -0.13389922 37 -0.23320697 0.53887324 38 -0.14295245 -0.23320697 39 0.88372659 -0.14295245 40 -0.60222439 0.88372659 41 -0.22840156 -0.60222439 42 -0.40316360 -0.22840156 43 0.61069504 -0.40316360 44 -0.11026665 0.61069504 45 -0.13454299 -0.11026665 46 -0.12068436 -0.13454299 47 -0.14496070 -0.12068436 48 -0.13093894 -0.14496070 49 -0.11708030 -0.13093894 50 0.80788830 -0.11708030 51 0.17145162 0.80788830 52 -0.13895395 0.17145162 53 -0.57394953 -0.13895395 54 -0.11107355 -0.57394953 55 0.78841736 -0.11107355 56 -0.19756088 0.78841736 57 -0.13294719 -0.19756088 58 -0.13174584 -0.13294719 59 0.15558474 -0.13174584 60 0.60564032 0.15558474 61 -0.16607642 0.60564032 62 -0.10146273 -0.16607642 63 0.60924437 -0.10146273 64 -0.09906003 0.60924437 65 -0.09785868 -0.09906003 66 0.45448845 -0.09785868 67 -0.36047253 0.45448845 68 -0.11973232 -0.36047253 69 -0.16928602 -0.11973232 70 -0.09185192 -0.16928602 71 -0.11612827 -0.09185192 72 -0.19115966 -0.11612827 73 -0.42949717 -0.19115966 74 -0.11252421 -0.42949717 75 0.90149755 -0.11252421 76 -0.11012151 0.90149755 77 -0.17233250 -0.11012151 78 0.43060655 -0.17233250 79 0.93178065 0.43060655 80 -0.07983841 0.93178065 81 -0.44536405 -0.07983841 82 -0.07743571 -0.44536405 83 -0.53790899 -0.07743571 84 -0.08769029 -0.53790899 85 NA -0.08769029 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.17474517 0.53355923 [2,] -0.17354382 -0.17474517 [3,] -0.17234247 -0.17354382 [4,] -0.17114112 -0.17234247 [5,] -0.44761360 -0.17114112 [6,] -0.16873842 -0.44761360 [7,] 0.83246294 -0.16873842 [8,] -0.19181341 0.83246294 [9,] -0.43015091 -0.19181341 [10,] 0.57105044 -0.43015091 [11,] -0.16273166 0.57105044 [12,] -0.22494264 -0.16273166 [13,] 0.57465450 -0.22494264 [14,] -0.24801764 0.57465450 [15,] 0.75318371 -0.24801764 [16,] 0.12940432 0.75318371 [17,] 0.57945990 0.12940432 [18,] -0.17979989 0.57945990 [19,] 0.37254723 -0.17979989 [20,] -0.40411563 0.37254723 [21,] -0.50462473 -0.40411563 [22,] -0.16217408 -0.50462473 [23,] -0.42598928 -0.16217408 [24,] 0.75117547 -0.42598928 [25,] -0.20932507 0.75117547 [26,] -0.43520563 -0.20932507 [27,] -0.21974278 -0.43520563 [28,] -0.16778638 -0.21974278 [29,] -0.12828692 -0.16778638 [30,] -0.13990598 -0.12828692 [31,] -0.40372118 -0.13990598 [32,] -0.38969942 -0.40372118 [33,] 0.83822038 -0.38969942 [34,] -0.13510057 0.83822038 [35,] -0.13389922 -0.13510057 [36,] 0.53887324 -0.13389922 [37,] -0.23320697 0.53887324 [38,] -0.14295245 -0.23320697 [39,] 0.88372659 -0.14295245 [40,] -0.60222439 0.88372659 [41,] -0.22840156 -0.60222439 [42,] -0.40316360 -0.22840156 [43,] 0.61069504 -0.40316360 [44,] -0.11026665 0.61069504 [45,] -0.13454299 -0.11026665 [46,] -0.12068436 -0.13454299 [47,] -0.14496070 -0.12068436 [48,] -0.13093894 -0.14496070 [49,] -0.11708030 -0.13093894 [50,] 0.80788830 -0.11708030 [51,] 0.17145162 0.80788830 [52,] -0.13895395 0.17145162 [53,] -0.57394953 -0.13895395 [54,] -0.11107355 -0.57394953 [55,] 0.78841736 -0.11107355 [56,] -0.19756088 0.78841736 [57,] -0.13294719 -0.19756088 [58,] -0.13174584 -0.13294719 [59,] 0.15558474 -0.13174584 [60,] 0.60564032 0.15558474 [61,] -0.16607642 0.60564032 [62,] -0.10146273 -0.16607642 [63,] 0.60924437 -0.10146273 [64,] -0.09906003 0.60924437 [65,] -0.09785868 -0.09906003 [66,] 0.45448845 -0.09785868 [67,] -0.36047253 0.45448845 [68,] -0.11973232 -0.36047253 [69,] -0.16928602 -0.11973232 [70,] -0.09185192 -0.16928602 [71,] -0.11612827 -0.09185192 [72,] -0.19115966 -0.11612827 [73,] -0.42949717 -0.19115966 [74,] -0.11252421 -0.42949717 [75,] 0.90149755 -0.11252421 [76,] -0.11012151 0.90149755 [77,] -0.17233250 -0.11012151 [78,] 0.43060655 -0.17233250 [79,] 0.93178065 0.43060655 [80,] -0.07983841 0.93178065 [81,] -0.44536405 -0.07983841 [82,] -0.07743571 -0.44536405 [83,] -0.53790899 -0.07743571 [84,] -0.08769029 -0.53790899 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.17474517 0.53355923 2 -0.17354382 -0.17474517 3 -0.17234247 -0.17354382 4 -0.17114112 -0.17234247 5 -0.44761360 -0.17114112 6 -0.16873842 -0.44761360 7 0.83246294 -0.16873842 8 -0.19181341 0.83246294 9 -0.43015091 -0.19181341 10 0.57105044 -0.43015091 11 -0.16273166 0.57105044 12 -0.22494264 -0.16273166 13 0.57465450 -0.22494264 14 -0.24801764 0.57465450 15 0.75318371 -0.24801764 16 0.12940432 0.75318371 17 0.57945990 0.12940432 18 -0.17979989 0.57945990 19 0.37254723 -0.17979989 20 -0.40411563 0.37254723 21 -0.50462473 -0.40411563 22 -0.16217408 -0.50462473 23 -0.42598928 -0.16217408 24 0.75117547 -0.42598928 25 -0.20932507 0.75117547 26 -0.43520563 -0.20932507 27 -0.21974278 -0.43520563 28 -0.16778638 -0.21974278 29 -0.12828692 -0.16778638 30 -0.13990598 -0.12828692 31 -0.40372118 -0.13990598 32 -0.38969942 -0.40372118 33 0.83822038 -0.38969942 34 -0.13510057 0.83822038 35 -0.13389922 -0.13510057 36 0.53887324 -0.13389922 37 -0.23320697 0.53887324 38 -0.14295245 -0.23320697 39 0.88372659 -0.14295245 40 -0.60222439 0.88372659 41 -0.22840156 -0.60222439 42 -0.40316360 -0.22840156 43 0.61069504 -0.40316360 44 -0.11026665 0.61069504 45 -0.13454299 -0.11026665 46 -0.12068436 -0.13454299 47 -0.14496070 -0.12068436 48 -0.13093894 -0.14496070 49 -0.11708030 -0.13093894 50 0.80788830 -0.11708030 51 0.17145162 0.80788830 52 -0.13895395 0.17145162 53 -0.57394953 -0.13895395 54 -0.11107355 -0.57394953 55 0.78841736 -0.11107355 56 -0.19756088 0.78841736 57 -0.13294719 -0.19756088 58 -0.13174584 -0.13294719 59 0.15558474 -0.13174584 60 0.60564032 0.15558474 61 -0.16607642 0.60564032 62 -0.10146273 -0.16607642 63 0.60924437 -0.10146273 64 -0.09906003 0.60924437 65 -0.09785868 -0.09906003 66 0.45448845 -0.09785868 67 -0.36047253 0.45448845 68 -0.11973232 -0.36047253 69 -0.16928602 -0.11973232 70 -0.09185192 -0.16928602 71 -0.11612827 -0.09185192 72 -0.19115966 -0.11612827 73 -0.42949717 -0.19115966 74 -0.11252421 -0.42949717 75 0.90149755 -0.11252421 76 -0.11012151 0.90149755 77 -0.17233250 -0.11012151 78 0.43060655 -0.17233250 79 0.93178065 0.43060655 80 -0.07983841 0.93178065 81 -0.44536405 -0.07983841 82 -0.07743571 -0.44536405 83 -0.53790899 -0.07743571 84 -0.08769029 -0.53790899 > 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/769ol1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8bqps1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9gdzb1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/106khq1356185325.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11j8jh1356185325.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/12uklx1356185325.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/1394nq1356185325.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/140w9e1356185325.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/153gr91356185325.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/16exgm1356185325.tab") + } > > try(system("convert tmp/1yel21356185325.ps tmp/1yel21356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/2bj9z1356185325.ps tmp/2bj9z1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/39ftg1356185325.ps tmp/39ftg1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/4p4se1356185325.ps tmp/4p4se1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/5meou1356185325.ps tmp/5meou1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/6svdq1356185325.ps tmp/6svdq1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/769ol1356185325.ps tmp/769ol1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/8bqps1356185325.ps tmp/8bqps1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/9gdzb1356185325.ps tmp/9gdzb1356185325.png",intern=TRUE)) character(0) > try(system("convert tmp/106khq1356185325.ps tmp/106khq1356185325.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.420 1.776 8.242