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]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '5' > par3 <- 'No 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 Useful UseLimit T40 Used CorrectAnalysis Outcome 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 1 1 0 0 0 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 1 0 0 1 0 0 14 0 1 1 0 0 0 15 1 0 0 1 0 1 16 1 0 1 1 0 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 1 1 0 0 0 0 22 1 1 0 1 0 1 23 1 0 0 0 0 1 24 1 1 0 0 0 1 25 0 0 1 1 0 1 26 1 0 0 1 0 0 27 0 1 0 0 0 1 28 0 0 0 1 0 0 29 0 0 0 0 0 1 30 1 0 0 0 0 0 31 0 0 0 0 0 0 32 0 1 0 0 0 0 33 1 1 0 0 0 0 34 0 0 1 0 0 1 35 0 0 0 0 0 0 36 0 0 0 0 0 0 37 1 1 1 1 0 0 38 0 0 0 1 0 1 39 1 0 0 0 0 1 40 1 0 1 0 0 0 41 1 0 0 1 1 1 42 0 0 0 1 0 1 43 1 1 0 0 0 1 44 0 1 1 0 0 0 45 1 0 0 0 0 0 46 1 0 0 0 0 1 47 0 0 0 0 0 0 48 0 0 0 0 0 1 49 1 0 0 0 0 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 0 0 0 1 1 0 55 0 0 0 0 0 0 56 0 0 1 1 0 1 57 1 0 0 1 0 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 1 0 0 1 0 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 1 0 1 0 0 1 77 0 0 0 0 0 1 78 1 0 0 1 0 1 79 0 0 1 1 1 1 80 1 0 1 0 0 0 81 0 0 0 0 0 0 82 0 1 0 1 0 1 83 0 0 0 0 0 0 84 0 0 0 1 1 0 85 1 0 0 0 0 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 0.170633 0.106578 0.001388 0.204411 CorrectAnalysis Outcome 0.196952 0.130991 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.7044 -0.3016 -0.1706 0.4936 0.8294 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.170633 0.084294 2.024 0.0463 * UseLimit 0.106578 0.116964 0.911 0.3649 T40 0.001388 0.124175 0.011 0.9911 Used 0.204411 0.124560 1.641 0.1047 CorrectAnalysis 0.196952 0.194909 1.010 0.3153 Outcome 0.130991 0.101547 1.290 0.2008 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4654 on 80 degrees of freedom Multiple R-squared: 0.113, Adjusted R-squared: 0.05761 F-statistic: 2.039 on 5 and 80 DF, p-value: 0.08191 > 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,] 0.2813299409 0.562659882 0.7186701 [2,] 0.2888104973 0.577620995 0.7111895 [3,] 0.1695719988 0.339143998 0.8304280 [4,] 0.0920932808 0.184186562 0.9079067 [5,] 0.0496130691 0.099226138 0.9503869 [6,] 0.0244697267 0.048939453 0.9755303 [7,] 0.0143045244 0.028609049 0.9856955 [8,] 0.0075118043 0.015023609 0.9924882 [9,] 0.0033260622 0.006652124 0.9966739 [10,] 0.0014630251 0.002926050 0.9985370 [11,] 0.0008496271 0.001699254 0.9991504 [12,] 0.0003657240 0.000731448 0.9996343 [13,] 0.0047616333 0.009523267 0.9952384 [14,] 0.0065819770 0.013163954 0.9934180 [15,] 0.0330358527 0.066071705 0.9669641 [16,] 0.0358052926 0.071610585 0.9641947 [17,] 0.0612092279 0.122418456 0.9387908 [18,] 0.0573635294 0.114727059 0.9426365 [19,] 0.0838347214 0.167669443 0.9161653 [20,] 0.1337236058 0.267447212 0.8662764 [21,] 0.1127872530 0.225574506 0.8872127 [22,] 0.2450556722 0.490111344 0.7549443 [23,] 0.1988295417 0.397659083 0.8011705 [24,] 0.1804550583 0.360910117 0.8195449 [25,] 0.2429971692 0.485994338 0.7570028 [26,] 0.2140437595 0.428087519 0.7859562 [27,] 0.1727050559 0.345410112 0.8272949 [28,] 0.1368849245 0.273769849 0.8631151 [29,] 0.1432111447 0.286422289 0.8567889 [30,] 0.2004563005 0.400912601 0.7995437 [31,] 0.2796532463 0.559306493 0.7203468 [32,] 0.4664742080 0.932948416 0.5335258 [33,] 0.4297762883 0.859552577 0.5702237 [34,] 0.4539639403 0.907927881 0.5460361 [35,] 0.5269953419 0.946009316 0.4730047 [36,] 0.4808203247 0.961640649 0.5191797 [37,] 0.6263642814 0.747271437 0.3736357 [38,] 0.7215508845 0.556898231 0.2784491 [39,] 0.6718362015 0.656327597 0.3281638 [40,] 0.6315876679 0.736824664 0.3684123 [41,] 0.7427882110 0.514423578 0.2572118 [42,] 0.6926913260 0.614617348 0.3073087 [43,] 0.7335624675 0.532875065 0.2664375 [44,] 0.7319980782 0.536003844 0.2680019 [45,] 0.6898540284 0.620291943 0.3101460 [46,] 0.7092730093 0.581453981 0.2907270 [47,] 0.6530639145 0.693872171 0.3469361 [48,] 0.7967661916 0.406467617 0.2032338 [49,] 0.8124128440 0.375174312 0.1875872 [50,] 0.7697110654 0.460577869 0.2302889 [51,] 0.7205256739 0.558948652 0.2794743 [52,] 0.8084950231 0.383009954 0.1915050 [53,] 0.7838161357 0.432367729 0.2161839 [54,] 0.8252511001 0.349497800 0.1747489 [55,] 0.7765495674 0.446900865 0.2234504 [56,] 0.8080989028 0.383802194 0.1919011 [57,] 0.7519155002 0.496169000 0.2480845 [58,] 0.6882506591 0.623498682 0.3117493 [59,] 0.7348834240 0.530233152 0.2651166 [60,] 0.6683476476 0.663304705 0.3316524 [61,] 0.6070139535 0.785972093 0.3929860 [62,] 0.5719293601 0.856141280 0.4280706 [63,] 0.4945314880 0.989062976 0.5054685 [64,] 0.4256153691 0.851230738 0.5743846 [65,] 0.4977589634 0.995517927 0.5022410 [66,] 0.4163521014 0.832704203 0.5836479 [67,] 0.3587936951 0.717587390 0.6412063 [68,] 0.2697594763 0.539518953 0.7302405 [69,] 0.2707385922 0.541477184 0.7292614 > postscript(file="/var/wessaorg/rcomp/tmp/1z4kk1356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2mj9r1356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3hvd41356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/40spx1356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5ynik1356127532.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 7 -0.4095911 -0.1706333 -0.1706333 -0.1706333 -0.1706333 0.5917974 -0.1706333 8 9 10 11 12 13 14 -0.1720218 -0.3016241 -0.2772118 -0.2786003 -0.1706333 0.6249555 -0.2786003 15 16 17 18 19 20 21 0.4939647 0.4925763 0.3200363 -0.2786003 -0.3016241 0.2956240 0.7227882 22 23 24 25 26 27 28 0.3873862 0.6983759 0.5917974 -0.5074237 0.6249555 -0.4082026 -0.3750445 29 30 31 32 33 34 35 -0.3016241 0.8293667 -0.1706333 -0.2772118 0.7227882 -0.3030126 -0.1706333 36 37 38 39 40 41 42 -0.1706333 0.5169886 -0.5060353 0.6983759 0.8279782 0.2970125 -0.5060353 43 44 45 46 47 48 49 0.5917974 -0.2786003 0.8293667 0.6983759 -0.1706333 -0.3016241 0.6983759 50 51 52 53 54 55 56 -0.1706333 -0.3764329 0.3200363 -0.3016241 -0.5719967 -0.1706333 -0.5074237 57 58 59 60 61 62 63 0.4939647 -0.3016241 -0.3016241 0.1890455 -0.4095911 0.6249555 -0.1706333 64 65 66 67 68 69 70 -0.4095911 -0.1706333 -0.1706333 0.4266148 -0.2772118 -0.3016241 -0.3750445 71 72 73 74 75 76 77 -0.1706333 -0.3016241 -0.5060353 -0.4816230 -0.3016241 0.6969874 -0.3016241 78 79 80 81 82 83 84 0.4939647 -0.7043760 0.8279782 -0.1706333 -0.6126138 -0.1706333 -0.5719967 85 86 0.6983759 -0.2772118 > postscript(file="/var/wessaorg/rcomp/tmp/65gfm1356127532.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 -0.4095911 NA 1 -0.1706333 -0.4095911 2 -0.1706333 -0.1706333 3 -0.1706333 -0.1706333 4 -0.1706333 -0.1706333 5 0.5917974 -0.1706333 6 -0.1706333 0.5917974 7 -0.1720218 -0.1706333 8 -0.3016241 -0.1720218 9 -0.2772118 -0.3016241 10 -0.2786003 -0.2772118 11 -0.1706333 -0.2786003 12 0.6249555 -0.1706333 13 -0.2786003 0.6249555 14 0.4939647 -0.2786003 15 0.4925763 0.4939647 16 0.3200363 0.4925763 17 -0.2786003 0.3200363 18 -0.3016241 -0.2786003 19 0.2956240 -0.3016241 20 0.7227882 0.2956240 21 0.3873862 0.7227882 22 0.6983759 0.3873862 23 0.5917974 0.6983759 24 -0.5074237 0.5917974 25 0.6249555 -0.5074237 26 -0.4082026 0.6249555 27 -0.3750445 -0.4082026 28 -0.3016241 -0.3750445 29 0.8293667 -0.3016241 30 -0.1706333 0.8293667 31 -0.2772118 -0.1706333 32 0.7227882 -0.2772118 33 -0.3030126 0.7227882 34 -0.1706333 -0.3030126 35 -0.1706333 -0.1706333 36 0.5169886 -0.1706333 37 -0.5060353 0.5169886 38 0.6983759 -0.5060353 39 0.8279782 0.6983759 40 0.2970125 0.8279782 41 -0.5060353 0.2970125 42 0.5917974 -0.5060353 43 -0.2786003 0.5917974 44 0.8293667 -0.2786003 45 0.6983759 0.8293667 46 -0.1706333 0.6983759 47 -0.3016241 -0.1706333 48 0.6983759 -0.3016241 49 -0.1706333 0.6983759 50 -0.3764329 -0.1706333 51 0.3200363 -0.3764329 52 -0.3016241 0.3200363 53 -0.5719967 -0.3016241 54 -0.1706333 -0.5719967 55 -0.5074237 -0.1706333 56 0.4939647 -0.5074237 57 -0.3016241 0.4939647 58 -0.3016241 -0.3016241 59 0.1890455 -0.3016241 60 -0.4095911 0.1890455 61 0.6249555 -0.4095911 62 -0.1706333 0.6249555 63 -0.4095911 -0.1706333 64 -0.1706333 -0.4095911 65 -0.1706333 -0.1706333 66 0.4266148 -0.1706333 67 -0.2772118 0.4266148 68 -0.3016241 -0.2772118 69 -0.3750445 -0.3016241 70 -0.1706333 -0.3750445 71 -0.3016241 -0.1706333 72 -0.5060353 -0.3016241 73 -0.4816230 -0.5060353 74 -0.3016241 -0.4816230 75 0.6969874 -0.3016241 76 -0.3016241 0.6969874 77 0.4939647 -0.3016241 78 -0.7043760 0.4939647 79 0.8279782 -0.7043760 80 -0.1706333 0.8279782 81 -0.6126138 -0.1706333 82 -0.1706333 -0.6126138 83 -0.5719967 -0.1706333 84 0.6983759 -0.5719967 85 -0.2772118 0.6983759 86 NA -0.2772118 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.1706333 -0.4095911 [2,] -0.1706333 -0.1706333 [3,] -0.1706333 -0.1706333 [4,] -0.1706333 -0.1706333 [5,] 0.5917974 -0.1706333 [6,] -0.1706333 0.5917974 [7,] -0.1720218 -0.1706333 [8,] -0.3016241 -0.1720218 [9,] -0.2772118 -0.3016241 [10,] -0.2786003 -0.2772118 [11,] -0.1706333 -0.2786003 [12,] 0.6249555 -0.1706333 [13,] -0.2786003 0.6249555 [14,] 0.4939647 -0.2786003 [15,] 0.4925763 0.4939647 [16,] 0.3200363 0.4925763 [17,] -0.2786003 0.3200363 [18,] -0.3016241 -0.2786003 [19,] 0.2956240 -0.3016241 [20,] 0.7227882 0.2956240 [21,] 0.3873862 0.7227882 [22,] 0.6983759 0.3873862 [23,] 0.5917974 0.6983759 [24,] -0.5074237 0.5917974 [25,] 0.6249555 -0.5074237 [26,] -0.4082026 0.6249555 [27,] -0.3750445 -0.4082026 [28,] -0.3016241 -0.3750445 [29,] 0.8293667 -0.3016241 [30,] -0.1706333 0.8293667 [31,] -0.2772118 -0.1706333 [32,] 0.7227882 -0.2772118 [33,] -0.3030126 0.7227882 [34,] -0.1706333 -0.3030126 [35,] -0.1706333 -0.1706333 [36,] 0.5169886 -0.1706333 [37,] -0.5060353 0.5169886 [38,] 0.6983759 -0.5060353 [39,] 0.8279782 0.6983759 [40,] 0.2970125 0.8279782 [41,] -0.5060353 0.2970125 [42,] 0.5917974 -0.5060353 [43,] -0.2786003 0.5917974 [44,] 0.8293667 -0.2786003 [45,] 0.6983759 0.8293667 [46,] -0.1706333 0.6983759 [47,] -0.3016241 -0.1706333 [48,] 0.6983759 -0.3016241 [49,] -0.1706333 0.6983759 [50,] -0.3764329 -0.1706333 [51,] 0.3200363 -0.3764329 [52,] -0.3016241 0.3200363 [53,] -0.5719967 -0.3016241 [54,] -0.1706333 -0.5719967 [55,] -0.5074237 -0.1706333 [56,] 0.4939647 -0.5074237 [57,] -0.3016241 0.4939647 [58,] -0.3016241 -0.3016241 [59,] 0.1890455 -0.3016241 [60,] -0.4095911 0.1890455 [61,] 0.6249555 -0.4095911 [62,] -0.1706333 0.6249555 [63,] -0.4095911 -0.1706333 [64,] -0.1706333 -0.4095911 [65,] -0.1706333 -0.1706333 [66,] 0.4266148 -0.1706333 [67,] -0.2772118 0.4266148 [68,] -0.3016241 -0.2772118 [69,] -0.3750445 -0.3016241 [70,] -0.1706333 -0.3750445 [71,] -0.3016241 -0.1706333 [72,] -0.5060353 -0.3016241 [73,] -0.4816230 -0.5060353 [74,] -0.3016241 -0.4816230 [75,] 0.6969874 -0.3016241 [76,] -0.3016241 0.6969874 [77,] 0.4939647 -0.3016241 [78,] -0.7043760 0.4939647 [79,] 0.8279782 -0.7043760 [80,] -0.1706333 0.8279782 [81,] -0.6126138 -0.1706333 [82,] -0.1706333 -0.6126138 [83,] -0.5719967 -0.1706333 [84,] 0.6983759 -0.5719967 [85,] -0.2772118 0.6983759 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.1706333 -0.4095911 2 -0.1706333 -0.1706333 3 -0.1706333 -0.1706333 4 -0.1706333 -0.1706333 5 0.5917974 -0.1706333 6 -0.1706333 0.5917974 7 -0.1720218 -0.1706333 8 -0.3016241 -0.1720218 9 -0.2772118 -0.3016241 10 -0.2786003 -0.2772118 11 -0.1706333 -0.2786003 12 0.6249555 -0.1706333 13 -0.2786003 0.6249555 14 0.4939647 -0.2786003 15 0.4925763 0.4939647 16 0.3200363 0.4925763 17 -0.2786003 0.3200363 18 -0.3016241 -0.2786003 19 0.2956240 -0.3016241 20 0.7227882 0.2956240 21 0.3873862 0.7227882 22 0.6983759 0.3873862 23 0.5917974 0.6983759 24 -0.5074237 0.5917974 25 0.6249555 -0.5074237 26 -0.4082026 0.6249555 27 -0.3750445 -0.4082026 28 -0.3016241 -0.3750445 29 0.8293667 -0.3016241 30 -0.1706333 0.8293667 31 -0.2772118 -0.1706333 32 0.7227882 -0.2772118 33 -0.3030126 0.7227882 34 -0.1706333 -0.3030126 35 -0.1706333 -0.1706333 36 0.5169886 -0.1706333 37 -0.5060353 0.5169886 38 0.6983759 -0.5060353 39 0.8279782 0.6983759 40 0.2970125 0.8279782 41 -0.5060353 0.2970125 42 0.5917974 -0.5060353 43 -0.2786003 0.5917974 44 0.8293667 -0.2786003 45 0.6983759 0.8293667 46 -0.1706333 0.6983759 47 -0.3016241 -0.1706333 48 0.6983759 -0.3016241 49 -0.1706333 0.6983759 50 -0.3764329 -0.1706333 51 0.3200363 -0.3764329 52 -0.3016241 0.3200363 53 -0.5719967 -0.3016241 54 -0.1706333 -0.5719967 55 -0.5074237 -0.1706333 56 0.4939647 -0.5074237 57 -0.3016241 0.4939647 58 -0.3016241 -0.3016241 59 0.1890455 -0.3016241 60 -0.4095911 0.1890455 61 0.6249555 -0.4095911 62 -0.1706333 0.6249555 63 -0.4095911 -0.1706333 64 -0.1706333 -0.4095911 65 -0.1706333 -0.1706333 66 0.4266148 -0.1706333 67 -0.2772118 0.4266148 68 -0.3016241 -0.2772118 69 -0.3750445 -0.3016241 70 -0.1706333 -0.3750445 71 -0.3016241 -0.1706333 72 -0.5060353 -0.3016241 73 -0.4816230 -0.5060353 74 -0.3016241 -0.4816230 75 0.6969874 -0.3016241 76 -0.3016241 0.6969874 77 0.4939647 -0.3016241 78 -0.7043760 0.4939647 79 0.8279782 -0.7043760 80 -0.1706333 0.8279782 81 -0.6126138 -0.1706333 82 -0.1706333 -0.6126138 83 -0.5719967 -0.1706333 84 0.6983759 -0.5719967 85 -0.2772118 0.6983759 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7h5d41356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8qt4q1356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9fouq1356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/105sk11356127532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11kmu61356127532.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12g0451356127532.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13gkve1356127532.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14rer21356127532.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/15pk9i1356127532.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/160pji1356127532.tab") + } > > try(system("convert tmp/1z4kk1356127532.ps tmp/1z4kk1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/2mj9r1356127532.ps tmp/2mj9r1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/3hvd41356127532.ps tmp/3hvd41356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/40spx1356127532.ps tmp/40spx1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/5ynik1356127532.ps tmp/5ynik1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/65gfm1356127532.ps tmp/65gfm1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/7h5d41356127532.ps tmp/7h5d41356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/8qt4q1356127532.ps tmp/8qt4q1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/9fouq1356127532.ps tmp/9fouq1356127532.png",intern=TRUE)) character(0) > try(system("convert tmp/105sk11356127532.ps tmp/105sk11356127532.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.661 1.216 8.920