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(4 + ,0 + ,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 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + 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,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 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0) + ,dim=c(6 + ,154) + ,dimnames=list(c('Weeks*t' + ,'UseLimit' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome') + ,1:154)) > y <- array(NA,dim=c(6,154),dimnames=list(c('Weeks*t','UseLimit','Used','CorrectAnalysis','Useful','Outcome'),1:154)) > 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 = '6' > par3 <- 'Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '6' > #'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 Outcome Weeks*t UseLimit Used CorrectAnalysis Useful t 1 1 4 0 0 0 0 1 2 0 0 0 0 0 0 2 3 0 0 0 0 0 0 3 4 0 0 0 0 0 0 4 5 0 0 0 0 0 0 5 6 1 0 0 0 0 1 6 7 0 0 0 0 0 0 7 8 0 4 0 0 0 0 8 9 1 0 0 0 0 0 9 10 0 0 0 0 0 0 10 11 0 4 0 0 0 0 11 12 0 0 0 0 0 0 12 13 0 0 0 0 0 1 13 14 0 4 0 0 0 0 14 15 1 0 0 0 0 1 15 16 1 4 0 0 0 1 16 17 0 4 0 0 1 1 17 18 0 4 0 0 0 0 18 19 1 0 0 0 0 0 19 20 1 4 0 0 1 1 20 21 0 0 0 0 0 1 21 22 1 0 0 0 0 1 22 23 1 0 0 0 0 1 23 24 1 0 0 0 0 1 24 25 1 4 0 0 0 0 25 26 0 0 0 0 0 1 26 27 1 0 0 0 0 0 27 28 0 0 0 0 0 0 28 29 1 0 0 0 0 0 29 30 0 0 0 0 0 1 30 31 0 0 0 0 0 0 31 32 0 0 0 0 0 0 32 33 0 0 0 0 0 1 33 34 1 4 0 0 0 0 34 35 0 0 0 0 0 0 35 36 0 0 0 0 0 0 36 37 0 4 0 0 0 1 37 38 1 0 0 0 0 0 38 39 1 0 0 0 0 1 39 40 0 4 0 0 0 1 40 41 1 0 0 0 1 1 41 42 1 0 0 0 0 0 42 43 1 0 0 0 0 1 43 44 0 4 0 0 0 0 44 45 0 0 0 0 0 1 45 46 1 0 0 0 0 1 46 47 0 0 0 0 0 0 47 48 1 0 0 0 0 0 48 49 1 0 0 0 0 1 49 50 0 0 0 0 0 0 50 51 0 4 0 0 0 0 51 52 0 4 0 0 1 1 52 53 1 0 0 0 0 0 53 54 0 0 0 0 1 0 54 55 0 0 0 0 0 0 55 56 1 4 0 0 0 0 56 57 1 0 0 0 0 1 57 58 1 0 0 0 0 0 58 59 1 0 0 0 0 0 59 60 1 4 0 0 1 1 60 61 1 4 0 0 0 0 61 62 0 0 0 0 0 1 62 63 0 0 0 0 0 0 63 64 1 4 0 0 0 0 64 65 0 0 0 0 0 0 65 66 0 0 0 0 0 0 66 67 0 4 0 0 1 1 67 68 0 0 0 0 0 0 68 69 1 0 0 0 0 0 69 70 0 0 0 0 0 0 70 71 0 0 0 0 0 0 71 72 1 0 0 0 0 0 72 73 1 0 0 0 0 0 73 74 0 0 0 0 0 0 74 75 1 0 0 0 0 0 75 76 1 4 0 0 0 1 76 77 1 0 0 0 0 0 77 78 1 0 0 0 0 1 78 79 1 4 0 0 1 0 79 80 0 4 0 0 0 1 80 81 0 0 0 0 0 0 81 82 1 0 0 0 0 0 82 83 0 0 0 0 0 0 83 84 0 0 0 0 1 0 84 85 1 0 0 0 0 1 85 86 0 0 0 0 0 0 86 87 1 0 0 0 0 0 87 88 1 2 0 0 0 0 88 89 0 0 0 0 0 0 89 90 1 0 0 0 0 0 90 91 0 0 0 0 0 1 91 92 0 2 0 0 0 0 92 93 0 0 0 0 0 1 93 94 0 0 0 0 0 0 94 95 0 2 0 0 0 0 95 96 1 0 0 0 0 0 96 97 0 2 0 0 0 0 97 98 0 0 0 0 0 0 98 99 0 0 0 0 0 0 99 100 1 0 0 0 0 0 100 101 1 0 0 0 0 0 101 102 0 0 0 0 0 0 102 103 0 0 0 0 0 0 103 104 0 0 0 0 0 0 104 105 0 2 0 0 0 0 105 106 0 0 0 0 0 0 106 107 0 0 0 0 0 0 107 108 0 2 0 0 0 0 108 109 0 0 0 0 0 0 109 110 0 0 0 0 0 0 110 111 0 2 0 0 0 1 111 112 0 2 0 0 0 0 112 113 0 0 0 0 0 0 113 114 0 2 0 0 0 0 114 115 0 0 0 0 0 0 115 116 0 0 0 0 0 0 116 117 1 0 0 0 0 0 117 118 0 0 0 0 0 0 118 119 0 0 0 0 0 0 119 120 1 0 0 0 0 0 120 121 0 0 0 0 0 0 121 122 0 0 0 0 0 0 122 123 0 2 0 0 0 0 123 124 1 0 0 0 0 1 124 125 1 0 0 0 0 0 125 126 0 2 0 0 0 0 126 127 0 0 0 0 0 1 127 128 1 0 0 0 0 0 128 129 0 0 0 0 0 0 129 130 1 0 0 0 0 0 130 131 0 0 0 0 0 0 131 132 1 0 0 0 0 0 132 133 0 0 0 0 0 0 133 134 0 0 0 0 0 0 134 135 0 0 0 0 0 0 135 136 0 0 0 0 0 0 136 137 1 0 0 0 0 1 137 138 1 2 0 0 0 1 138 139 0 2 0 0 0 0 139 140 0 0 0 0 0 0 140 141 1 0 0 0 1 0 141 142 1 2 0 0 0 0 142 143 0 0 0 0 0 0 143 144 1 0 0 0 0 1 144 145 0 0 0 0 0 1 145 146 1 2 0 0 0 0 146 147 0 2 0 0 0 0 147 148 0 2 0 0 0 0 148 149 0 0 0 0 0 0 149 150 1 0 0 0 0 1 150 151 1 0 0 0 0 0 151 152 0 0 0 0 1 0 152 153 0 0 0 0 1 1 153 154 0 0 0 0 0 0 154 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `Weeks*t` UseLimit Used 0.4004304 -0.0016249 NA NA CorrectAnalysis Useful t -0.0400296 0.1856307 -0.0006361 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.5778 -0.3645 -0.3186 0.5813 0.7293 Coefficients: (2 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 0.4004304 0.0935215 4.282 3.31e-05 *** `Weeks*t` -0.0016249 0.0281321 -0.058 0.954 UseLimit NA NA NA NA Used NA NA NA NA CorrectAnalysis -0.0400296 0.1543843 -0.259 0.796 Useful 0.1856307 0.0926859 2.003 0.047 * t -0.0006361 0.0009184 -0.693 0.490 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4888 on 149 degrees of freedom Multiple R-squared: 0.03368, Adjusted R-squared: 0.007739 F-statistic: 1.298 on 4 and 149 DF, p-value: 0.2733 > 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,] 0.85886600 0.2822680 0.1411340 [2,] 0.79485150 0.4102970 0.2051485 [3,] 0.68769234 0.6246153 0.3123077 [4,] 0.69658652 0.6068270 0.3034135 [5,] 0.59335402 0.8132920 0.4066460 [6,] 0.61169275 0.7766145 0.3883073 [7,] 0.53186717 0.9362657 0.4681328 [8,] 0.44176369 0.8835274 0.5582363 [9,] 0.35605837 0.7121167 0.6439416 [10,] 0.59437786 0.8112443 0.4056221 [11,] 0.65238425 0.6952315 0.3476158 [12,] 0.69738440 0.6052312 0.3026156 [13,] 0.66683464 0.6663307 0.3331654 [14,] 0.62176020 0.7564796 0.3782398 [15,] 0.56874068 0.8625186 0.4312593 [16,] 0.57585306 0.8482939 0.4241469 [17,] 0.66220820 0.6755836 0.3377918 [18,] 0.66425965 0.6714807 0.3357403 [19,] 0.66074185 0.6785163 0.3392581 [20,] 0.65762844 0.6847431 0.3423716 [21,] 0.72023410 0.5595318 0.2797659 [22,] 0.70892174 0.5821565 0.2910783 [23,] 0.68745186 0.6250963 0.3125481 [24,] 0.71014191 0.5797162 0.2898581 [25,] 0.70996273 0.5800745 0.2900373 [26,] 0.68637422 0.6272516 0.3136258 [27,] 0.65858310 0.6828338 0.3414169 [28,] 0.69664530 0.6067094 0.3033547 [29,] 0.72745859 0.5450828 0.2725414 [30,] 0.71092881 0.5781424 0.2890712 [31,] 0.73214182 0.5357164 0.2678582 [32,] 0.71059547 0.5788091 0.2894045 [33,] 0.71647875 0.5670425 0.2835213 [34,] 0.69384697 0.6123061 0.3061530 [35,] 0.68399801 0.6320040 0.3160020 [36,] 0.70551224 0.5889755 0.2944878 [37,] 0.68599269 0.6280146 0.3140073 [38,] 0.67603624 0.6479275 0.3239638 [39,] 0.68278852 0.6344230 0.3172115 [40,] 0.65968595 0.6806281 0.3403141 [41,] 0.65353228 0.6929354 0.3464677 [42,] 0.63871070 0.7225786 0.3612893 [43,] 0.65741617 0.6851677 0.3425838 [44,] 0.66770865 0.6645827 0.3322913 [45,] 0.64967338 0.7006532 0.3503266 [46,] 0.63660372 0.7267926 0.3633963 [47,] 0.65328742 0.6934252 0.3467126 [48,] 0.62962514 0.7407497 0.3703749 [49,] 0.63561246 0.7287751 0.3643875 [50,] 0.63954679 0.7209064 0.3604532 [51,] 0.62523450 0.7495310 0.3747655 [52,] 0.62638399 0.7472320 0.3736160 [53,] 0.66438427 0.6712315 0.3356157 [54,] 0.66181285 0.6763743 0.3381871 [55,] 0.67163028 0.6567394 0.3283697 [56,] 0.66776156 0.6644769 0.3322384 [57,] 0.66076881 0.6784624 0.3392312 [58,] 0.67124395 0.6575121 0.3287561 [59,] 0.66141053 0.6771789 0.3385895 [60,] 0.67123188 0.6575362 0.3287681 [61,] 0.66130169 0.6773966 0.3386983 [62,] 0.65008586 0.6998283 0.3499141 [63,] 0.66154691 0.6769062 0.3384531 [64,] 0.67329876 0.6534025 0.3267012 [65,] 0.66252426 0.6749515 0.3374757 [66,] 0.67610619 0.6477876 0.3238938 [67,] 0.66172349 0.6765530 0.3382765 [68,] 0.67855216 0.6428957 0.3214478 [69,] 0.66553400 0.6689320 0.3344660 [70,] 0.72193817 0.5561237 0.2780618 [71,] 0.72982135 0.5403573 0.2701787 [72,] 0.71845862 0.5630828 0.2815414 [73,] 0.74373553 0.5125289 0.2562645 [74,] 0.73088431 0.5382314 0.2691157 [75,] 0.70555497 0.5888901 0.2944450 [76,] 0.70221254 0.5955749 0.2977875 [77,] 0.68538098 0.6292380 0.3146190 [78,] 0.72059247 0.5588151 0.2794075 [79,] 0.77786753 0.4442649 0.2221325 [80,] 0.76144219 0.4771156 0.2385578 [81,] 0.80693116 0.3861377 0.1930688 [82,] 0.80840520 0.3831896 0.1915948 [83,] 0.78926988 0.4214602 0.2107301 [84,] 0.79018036 0.4196393 0.2098196 [85,] 0.76921841 0.4615632 0.2307816 [86,] 0.74333201 0.5133360 0.2566680 [87,] 0.79192354 0.4161529 0.2080765 [88,] 0.76621139 0.4675772 0.2337886 [89,] 0.73992488 0.5201502 0.2600751 [90,] 0.71170075 0.5765985 0.2882993 [91,] 0.77058803 0.4588239 0.2294120 [92,] 0.83590221 0.3281956 0.1640978 [93,] 0.81117311 0.3776538 0.1888269 [94,] 0.78348784 0.4330243 0.2165122 [95,] 0.75290942 0.4941812 0.2470906 [96,] 0.71836387 0.5632723 0.2816361 [97,] 0.68230162 0.6353968 0.3176984 [98,] 0.64418215 0.7116357 0.3558179 [99,] 0.60158176 0.7968365 0.3984182 [100,] 0.56050237 0.8789953 0.4394976 [101,] 0.51929101 0.9614180 0.4807090 [102,] 0.50843892 0.9831222 0.4915611 [103,] 0.46695800 0.9339160 0.5330420 [104,] 0.42935808 0.8587162 0.5706419 [105,] 0.39447260 0.7889452 0.6055274 [106,] 0.36268297 0.7253659 0.6373170 [107,] 0.33511373 0.6702275 0.6648863 [108,] 0.37106903 0.7421381 0.6289310 [109,] 0.33898914 0.6779783 0.6610109 [110,] 0.31189255 0.6237851 0.6881074 [111,] 0.34618338 0.6923668 0.6538166 [112,] 0.31381001 0.6276200 0.6861900 [113,] 0.28751081 0.5750216 0.7124892 [114,] 0.27292049 0.5458410 0.7270795 [115,] 0.24628770 0.4925754 0.7537123 [116,] 0.27343606 0.5468721 0.7265639 [117,] 0.26202904 0.5240581 0.7379710 [118,] 0.31308847 0.6261769 0.6869115 [119,] 0.33668829 0.6733766 0.6633117 [120,] 0.30699351 0.6139870 0.6930065 [121,] 0.34551009 0.6910202 0.6544899 [122,] 0.30357729 0.6071546 0.6964227 [123,] 0.37119723 0.7423945 0.6288028 [124,] 0.31241308 0.6248262 0.6875869 [125,] 0.26138804 0.5227761 0.7386120 [126,] 0.22176733 0.4435347 0.7782327 [127,] 0.20114241 0.4022848 0.7988576 [128,] 0.15647814 0.3129563 0.8435219 [129,] 0.11693538 0.2338708 0.8830646 [130,] 0.11626821 0.2325364 0.8837318 [131,] 0.11918661 0.2383732 0.8808134 [132,] 0.12650244 0.2530049 0.8734976 [133,] 0.13017447 0.2603489 0.8698255 [134,] 0.08662205 0.1732441 0.9133780 [135,] 0.06303229 0.1260646 0.9369677 > postscript(file="/var/wessaorg/rcomp/tmp/1ik5v1355914791.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/21z8a1355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3vk7e1355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4p23a1355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5w83k1355914791.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 = 154 Frequency = 1 1 2 3 4 5 6 7 0.6067055 -0.3991581 -0.3985220 -0.3978859 -0.3972498 0.4177556 -0.3959776 8 9 10 11 12 13 14 -0.3888417 0.6052947 -0.3940692 -0.3869333 -0.3927970 -0.5777916 -0.3850250 15 16 17 18 19 20 21 0.4234806 0.4306165 -0.5287178 -0.3824805 0.6116558 0.4731905 -0.5727027 22 23 24 25 26 27 28 0.4279334 0.4285696 0.4292057 0.6219723 -0.5695221 0.6167448 -0.3826191 29 30 31 32 33 34 35 0.6180170 -0.5669776 -0.3807108 -0.3800747 -0.5650693 0.6276973 -0.3781663 36 37 38 39 40 41 42 -0.3775302 -0.5560251 0.6237420 0.4387474 -0.5541167 0.4800492 0.6262865 43 44 45 46 47 48 49 0.4412919 -0.3659415 -0.5574359 0.4432002 -0.3705329 0.6301032 0.4451086 50 51 52 53 54 55 56 -0.3686246 -0.3614887 -0.5064538 0.6332838 -0.3260506 -0.3654440 0.6416919 57 58 59 60 61 62 63 0.4501975 0.6364643 0.6371005 0.4986351 0.6448724 -0.5466219 -0.3603551 64 65 66 67 68 69 70 0.6467808 -0.3590829 -0.3584467 -0.4969120 -0.3571745 0.6434616 -0.3559023 71 72 73 74 75 76 77 -0.3552662 0.6453700 0.6460061 -0.3533578 0.6472783 0.4687834 0.6485505 78 79 80 81 82 83 84 0.4635559 0.6963521 -0.5286721 -0.3489050 0.6517311 -0.3476328 -0.3069671 85 86 87 88 89 90 91 0.4680087 -0.3457244 0.6549117 0.6587977 -0.3438161 0.6568200 -0.5281746 92 93 94 95 96 97 98 -0.3386579 -0.5269023 -0.3406355 -0.3367495 0.6606367 -0.3354773 -0.3380910 99 100 101 102 103 104 105 -0.3374549 0.6631812 0.6638173 -0.3355466 -0.3349105 -0.3342743 -0.3303884 106 107 108 109 110 111 112 -0.3330021 -0.3323660 -0.3284800 -0.3310938 -0.3304577 -0.5122024 -0.3259355 113 114 115 116 117 118 119 -0.3285493 -0.3246633 -0.3272771 -0.3266410 0.6739952 -0.3253687 -0.3247326 120 121 122 123 124 125 126 0.6759035 -0.3234604 -0.3228243 -0.3189383 0.4928172 0.6790841 -0.3170299 127 128 129 130 131 132 133 -0.5052744 0.6809924 -0.3183715 0.6822647 -0.3170992 0.6835369 -0.3158270 134 135 136 137 138 139 140 -0.3151909 -0.3145548 -0.3139186 0.5010867 0.5049727 -0.3087604 -0.3113742 141 142 143 144 145 146 147 0.7292915 0.6931479 -0.3094658 0.5055396 -0.4938243 0.6956924 -0.3036715 148 149 150 151 152 153 154 -0.3030354 -0.3056491 0.5093562 0.6956231 -0.2637112 -0.4487059 -0.3024686 > postscript(file="/var/wessaorg/rcomp/tmp/6p5bf1355914791.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 = 154 Frequency = 1 lag(myerror, k = 1) myerror 0 0.6067055 NA 1 -0.3991581 0.6067055 2 -0.3985220 -0.3991581 3 -0.3978859 -0.3985220 4 -0.3972498 -0.3978859 5 0.4177556 -0.3972498 6 -0.3959776 0.4177556 7 -0.3888417 -0.3959776 8 0.6052947 -0.3888417 9 -0.3940692 0.6052947 10 -0.3869333 -0.3940692 11 -0.3927970 -0.3869333 12 -0.5777916 -0.3927970 13 -0.3850250 -0.5777916 14 0.4234806 -0.3850250 15 0.4306165 0.4234806 16 -0.5287178 0.4306165 17 -0.3824805 -0.5287178 18 0.6116558 -0.3824805 19 0.4731905 0.6116558 20 -0.5727027 0.4731905 21 0.4279334 -0.5727027 22 0.4285696 0.4279334 23 0.4292057 0.4285696 24 0.6219723 0.4292057 25 -0.5695221 0.6219723 26 0.6167448 -0.5695221 27 -0.3826191 0.6167448 28 0.6180170 -0.3826191 29 -0.5669776 0.6180170 30 -0.3807108 -0.5669776 31 -0.3800747 -0.3807108 32 -0.5650693 -0.3800747 33 0.6276973 -0.5650693 34 -0.3781663 0.6276973 35 -0.3775302 -0.3781663 36 -0.5560251 -0.3775302 37 0.6237420 -0.5560251 38 0.4387474 0.6237420 39 -0.5541167 0.4387474 40 0.4800492 -0.5541167 41 0.6262865 0.4800492 42 0.4412919 0.6262865 43 -0.3659415 0.4412919 44 -0.5574359 -0.3659415 45 0.4432002 -0.5574359 46 -0.3705329 0.4432002 47 0.6301032 -0.3705329 48 0.4451086 0.6301032 49 -0.3686246 0.4451086 50 -0.3614887 -0.3686246 51 -0.5064538 -0.3614887 52 0.6332838 -0.5064538 53 -0.3260506 0.6332838 54 -0.3654440 -0.3260506 55 0.6416919 -0.3654440 56 0.4501975 0.6416919 57 0.6364643 0.4501975 58 0.6371005 0.6364643 59 0.4986351 0.6371005 60 0.6448724 0.4986351 61 -0.5466219 0.6448724 62 -0.3603551 -0.5466219 63 0.6467808 -0.3603551 64 -0.3590829 0.6467808 65 -0.3584467 -0.3590829 66 -0.4969120 -0.3584467 67 -0.3571745 -0.4969120 68 0.6434616 -0.3571745 69 -0.3559023 0.6434616 70 -0.3552662 -0.3559023 71 0.6453700 -0.3552662 72 0.6460061 0.6453700 73 -0.3533578 0.6460061 74 0.6472783 -0.3533578 75 0.4687834 0.6472783 76 0.6485505 0.4687834 77 0.4635559 0.6485505 78 0.6963521 0.4635559 79 -0.5286721 0.6963521 80 -0.3489050 -0.5286721 81 0.6517311 -0.3489050 82 -0.3476328 0.6517311 83 -0.3069671 -0.3476328 84 0.4680087 -0.3069671 85 -0.3457244 0.4680087 86 0.6549117 -0.3457244 87 0.6587977 0.6549117 88 -0.3438161 0.6587977 89 0.6568200 -0.3438161 90 -0.5281746 0.6568200 91 -0.3386579 -0.5281746 92 -0.5269023 -0.3386579 93 -0.3406355 -0.5269023 94 -0.3367495 -0.3406355 95 0.6606367 -0.3367495 96 -0.3354773 0.6606367 97 -0.3380910 -0.3354773 98 -0.3374549 -0.3380910 99 0.6631812 -0.3374549 100 0.6638173 0.6631812 101 -0.3355466 0.6638173 102 -0.3349105 -0.3355466 103 -0.3342743 -0.3349105 104 -0.3303884 -0.3342743 105 -0.3330021 -0.3303884 106 -0.3323660 -0.3330021 107 -0.3284800 -0.3323660 108 -0.3310938 -0.3284800 109 -0.3304577 -0.3310938 110 -0.5122024 -0.3304577 111 -0.3259355 -0.5122024 112 -0.3285493 -0.3259355 113 -0.3246633 -0.3285493 114 -0.3272771 -0.3246633 115 -0.3266410 -0.3272771 116 0.6739952 -0.3266410 117 -0.3253687 0.6739952 118 -0.3247326 -0.3253687 119 0.6759035 -0.3247326 120 -0.3234604 0.6759035 121 -0.3228243 -0.3234604 122 -0.3189383 -0.3228243 123 0.4928172 -0.3189383 124 0.6790841 0.4928172 125 -0.3170299 0.6790841 126 -0.5052744 -0.3170299 127 0.6809924 -0.5052744 128 -0.3183715 0.6809924 129 0.6822647 -0.3183715 130 -0.3170992 0.6822647 131 0.6835369 -0.3170992 132 -0.3158270 0.6835369 133 -0.3151909 -0.3158270 134 -0.3145548 -0.3151909 135 -0.3139186 -0.3145548 136 0.5010867 -0.3139186 137 0.5049727 0.5010867 138 -0.3087604 0.5049727 139 -0.3113742 -0.3087604 140 0.7292915 -0.3113742 141 0.6931479 0.7292915 142 -0.3094658 0.6931479 143 0.5055396 -0.3094658 144 -0.4938243 0.5055396 145 0.6956924 -0.4938243 146 -0.3036715 0.6956924 147 -0.3030354 -0.3036715 148 -0.3056491 -0.3030354 149 0.5093562 -0.3056491 150 0.6956231 0.5093562 151 -0.2637112 0.6956231 152 -0.4487059 -0.2637112 153 -0.3024686 -0.4487059 154 NA -0.3024686 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.3991581 0.6067055 [2,] -0.3985220 -0.3991581 [3,] -0.3978859 -0.3985220 [4,] -0.3972498 -0.3978859 [5,] 0.4177556 -0.3972498 [6,] -0.3959776 0.4177556 [7,] -0.3888417 -0.3959776 [8,] 0.6052947 -0.3888417 [9,] -0.3940692 0.6052947 [10,] -0.3869333 -0.3940692 [11,] -0.3927970 -0.3869333 [12,] -0.5777916 -0.3927970 [13,] -0.3850250 -0.5777916 [14,] 0.4234806 -0.3850250 [15,] 0.4306165 0.4234806 [16,] -0.5287178 0.4306165 [17,] -0.3824805 -0.5287178 [18,] 0.6116558 -0.3824805 [19,] 0.4731905 0.6116558 [20,] -0.5727027 0.4731905 [21,] 0.4279334 -0.5727027 [22,] 0.4285696 0.4279334 [23,] 0.4292057 0.4285696 [24,] 0.6219723 0.4292057 [25,] -0.5695221 0.6219723 [26,] 0.6167448 -0.5695221 [27,] -0.3826191 0.6167448 [28,] 0.6180170 -0.3826191 [29,] -0.5669776 0.6180170 [30,] -0.3807108 -0.5669776 [31,] -0.3800747 -0.3807108 [32,] -0.5650693 -0.3800747 [33,] 0.6276973 -0.5650693 [34,] -0.3781663 0.6276973 [35,] -0.3775302 -0.3781663 [36,] -0.5560251 -0.3775302 [37,] 0.6237420 -0.5560251 [38,] 0.4387474 0.6237420 [39,] -0.5541167 0.4387474 [40,] 0.4800492 -0.5541167 [41,] 0.6262865 0.4800492 [42,] 0.4412919 0.6262865 [43,] -0.3659415 0.4412919 [44,] -0.5574359 -0.3659415 [45,] 0.4432002 -0.5574359 [46,] -0.3705329 0.4432002 [47,] 0.6301032 -0.3705329 [48,] 0.4451086 0.6301032 [49,] -0.3686246 0.4451086 [50,] -0.3614887 -0.3686246 [51,] -0.5064538 -0.3614887 [52,] 0.6332838 -0.5064538 [53,] -0.3260506 0.6332838 [54,] -0.3654440 -0.3260506 [55,] 0.6416919 -0.3654440 [56,] 0.4501975 0.6416919 [57,] 0.6364643 0.4501975 [58,] 0.6371005 0.6364643 [59,] 0.4986351 0.6371005 [60,] 0.6448724 0.4986351 [61,] -0.5466219 0.6448724 [62,] -0.3603551 -0.5466219 [63,] 0.6467808 -0.3603551 [64,] -0.3590829 0.6467808 [65,] -0.3584467 -0.3590829 [66,] -0.4969120 -0.3584467 [67,] -0.3571745 -0.4969120 [68,] 0.6434616 -0.3571745 [69,] -0.3559023 0.6434616 [70,] -0.3552662 -0.3559023 [71,] 0.6453700 -0.3552662 [72,] 0.6460061 0.6453700 [73,] -0.3533578 0.6460061 [74,] 0.6472783 -0.3533578 [75,] 0.4687834 0.6472783 [76,] 0.6485505 0.4687834 [77,] 0.4635559 0.6485505 [78,] 0.6963521 0.4635559 [79,] -0.5286721 0.6963521 [80,] -0.3489050 -0.5286721 [81,] 0.6517311 -0.3489050 [82,] -0.3476328 0.6517311 [83,] -0.3069671 -0.3476328 [84,] 0.4680087 -0.3069671 [85,] -0.3457244 0.4680087 [86,] 0.6549117 -0.3457244 [87,] 0.6587977 0.6549117 [88,] -0.3438161 0.6587977 [89,] 0.6568200 -0.3438161 [90,] -0.5281746 0.6568200 [91,] -0.3386579 -0.5281746 [92,] -0.5269023 -0.3386579 [93,] -0.3406355 -0.5269023 [94,] -0.3367495 -0.3406355 [95,] 0.6606367 -0.3367495 [96,] -0.3354773 0.6606367 [97,] -0.3380910 -0.3354773 [98,] -0.3374549 -0.3380910 [99,] 0.6631812 -0.3374549 [100,] 0.6638173 0.6631812 [101,] -0.3355466 0.6638173 [102,] -0.3349105 -0.3355466 [103,] -0.3342743 -0.3349105 [104,] -0.3303884 -0.3342743 [105,] -0.3330021 -0.3303884 [106,] -0.3323660 -0.3330021 [107,] -0.3284800 -0.3323660 [108,] -0.3310938 -0.3284800 [109,] -0.3304577 -0.3310938 [110,] -0.5122024 -0.3304577 [111,] -0.3259355 -0.5122024 [112,] -0.3285493 -0.3259355 [113,] -0.3246633 -0.3285493 [114,] -0.3272771 -0.3246633 [115,] -0.3266410 -0.3272771 [116,] 0.6739952 -0.3266410 [117,] -0.3253687 0.6739952 [118,] -0.3247326 -0.3253687 [119,] 0.6759035 -0.3247326 [120,] -0.3234604 0.6759035 [121,] -0.3228243 -0.3234604 [122,] -0.3189383 -0.3228243 [123,] 0.4928172 -0.3189383 [124,] 0.6790841 0.4928172 [125,] -0.3170299 0.6790841 [126,] -0.5052744 -0.3170299 [127,] 0.6809924 -0.5052744 [128,] -0.3183715 0.6809924 [129,] 0.6822647 -0.3183715 [130,] -0.3170992 0.6822647 [131,] 0.6835369 -0.3170992 [132,] -0.3158270 0.6835369 [133,] -0.3151909 -0.3158270 [134,] -0.3145548 -0.3151909 [135,] -0.3139186 -0.3145548 [136,] 0.5010867 -0.3139186 [137,] 0.5049727 0.5010867 [138,] -0.3087604 0.5049727 [139,] -0.3113742 -0.3087604 [140,] 0.7292915 -0.3113742 [141,] 0.6931479 0.7292915 [142,] -0.3094658 0.6931479 [143,] 0.5055396 -0.3094658 [144,] -0.4938243 0.5055396 [145,] 0.6956924 -0.4938243 [146,] -0.3036715 0.6956924 [147,] -0.3030354 -0.3036715 [148,] -0.3056491 -0.3030354 [149,] 0.5093562 -0.3056491 [150,] 0.6956231 0.5093562 [151,] -0.2637112 0.6956231 [152,] -0.4487059 -0.2637112 [153,] -0.3024686 -0.4487059 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.3991581 0.6067055 2 -0.3985220 -0.3991581 3 -0.3978859 -0.3985220 4 -0.3972498 -0.3978859 5 0.4177556 -0.3972498 6 -0.3959776 0.4177556 7 -0.3888417 -0.3959776 8 0.6052947 -0.3888417 9 -0.3940692 0.6052947 10 -0.3869333 -0.3940692 11 -0.3927970 -0.3869333 12 -0.5777916 -0.3927970 13 -0.3850250 -0.5777916 14 0.4234806 -0.3850250 15 0.4306165 0.4234806 16 -0.5287178 0.4306165 17 -0.3824805 -0.5287178 18 0.6116558 -0.3824805 19 0.4731905 0.6116558 20 -0.5727027 0.4731905 21 0.4279334 -0.5727027 22 0.4285696 0.4279334 23 0.4292057 0.4285696 24 0.6219723 0.4292057 25 -0.5695221 0.6219723 26 0.6167448 -0.5695221 27 -0.3826191 0.6167448 28 0.6180170 -0.3826191 29 -0.5669776 0.6180170 30 -0.3807108 -0.5669776 31 -0.3800747 -0.3807108 32 -0.5650693 -0.3800747 33 0.6276973 -0.5650693 34 -0.3781663 0.6276973 35 -0.3775302 -0.3781663 36 -0.5560251 -0.3775302 37 0.6237420 -0.5560251 38 0.4387474 0.6237420 39 -0.5541167 0.4387474 40 0.4800492 -0.5541167 41 0.6262865 0.4800492 42 0.4412919 0.6262865 43 -0.3659415 0.4412919 44 -0.5574359 -0.3659415 45 0.4432002 -0.5574359 46 -0.3705329 0.4432002 47 0.6301032 -0.3705329 48 0.4451086 0.6301032 49 -0.3686246 0.4451086 50 -0.3614887 -0.3686246 51 -0.5064538 -0.3614887 52 0.6332838 -0.5064538 53 -0.3260506 0.6332838 54 -0.3654440 -0.3260506 55 0.6416919 -0.3654440 56 0.4501975 0.6416919 57 0.6364643 0.4501975 58 0.6371005 0.6364643 59 0.4986351 0.6371005 60 0.6448724 0.4986351 61 -0.5466219 0.6448724 62 -0.3603551 -0.5466219 63 0.6467808 -0.3603551 64 -0.3590829 0.6467808 65 -0.3584467 -0.3590829 66 -0.4969120 -0.3584467 67 -0.3571745 -0.4969120 68 0.6434616 -0.3571745 69 -0.3559023 0.6434616 70 -0.3552662 -0.3559023 71 0.6453700 -0.3552662 72 0.6460061 0.6453700 73 -0.3533578 0.6460061 74 0.6472783 -0.3533578 75 0.4687834 0.6472783 76 0.6485505 0.4687834 77 0.4635559 0.6485505 78 0.6963521 0.4635559 79 -0.5286721 0.6963521 80 -0.3489050 -0.5286721 81 0.6517311 -0.3489050 82 -0.3476328 0.6517311 83 -0.3069671 -0.3476328 84 0.4680087 -0.3069671 85 -0.3457244 0.4680087 86 0.6549117 -0.3457244 87 0.6587977 0.6549117 88 -0.3438161 0.6587977 89 0.6568200 -0.3438161 90 -0.5281746 0.6568200 91 -0.3386579 -0.5281746 92 -0.5269023 -0.3386579 93 -0.3406355 -0.5269023 94 -0.3367495 -0.3406355 95 0.6606367 -0.3367495 96 -0.3354773 0.6606367 97 -0.3380910 -0.3354773 98 -0.3374549 -0.3380910 99 0.6631812 -0.3374549 100 0.6638173 0.6631812 101 -0.3355466 0.6638173 102 -0.3349105 -0.3355466 103 -0.3342743 -0.3349105 104 -0.3303884 -0.3342743 105 -0.3330021 -0.3303884 106 -0.3323660 -0.3330021 107 -0.3284800 -0.3323660 108 -0.3310938 -0.3284800 109 -0.3304577 -0.3310938 110 -0.5122024 -0.3304577 111 -0.3259355 -0.5122024 112 -0.3285493 -0.3259355 113 -0.3246633 -0.3285493 114 -0.3272771 -0.3246633 115 -0.3266410 -0.3272771 116 0.6739952 -0.3266410 117 -0.3253687 0.6739952 118 -0.3247326 -0.3253687 119 0.6759035 -0.3247326 120 -0.3234604 0.6759035 121 -0.3228243 -0.3234604 122 -0.3189383 -0.3228243 123 0.4928172 -0.3189383 124 0.6790841 0.4928172 125 -0.3170299 0.6790841 126 -0.5052744 -0.3170299 127 0.6809924 -0.5052744 128 -0.3183715 0.6809924 129 0.6822647 -0.3183715 130 -0.3170992 0.6822647 131 0.6835369 -0.3170992 132 -0.3158270 0.6835369 133 -0.3151909 -0.3158270 134 -0.3145548 -0.3151909 135 -0.3139186 -0.3145548 136 0.5010867 -0.3139186 137 0.5049727 0.5010867 138 -0.3087604 0.5049727 139 -0.3113742 -0.3087604 140 0.7292915 -0.3113742 141 0.6931479 0.7292915 142 -0.3094658 0.6931479 143 0.5055396 -0.3094658 144 -0.4938243 0.5055396 145 0.6956924 -0.4938243 146 -0.3036715 0.6956924 147 -0.3030354 -0.3036715 148 -0.3056491 -0.3030354 149 0.5093562 -0.3056491 150 0.6956231 0.5093562 151 -0.2637112 0.6956231 152 -0.4487059 -0.2637112 153 -0.3024686 -0.4487059 > 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/79h7e1355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8p3s71355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9ldqc1355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10fbi81355914791.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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='') + } + } Error: subscript out of bounds Execution halted