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 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,1 + ,0) + ,dim=c(5 + ,154) + ,dimnames=list(c('Treatment' + ,'No_treatment' + ,'4weken' + ,'2weken' + ,'Juiste_toepassing') + ,1:154)) > y <- array(NA,dim=c(5,154),dimnames=list(c('Treatment','No_treatment','4weken','2weken','Juiste_toepassing'),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 = '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 Juiste_toepassing Treatment No_treatment 4weken 2weken 1 0 1 0 1 0 2 0 0 1 1 0 3 0 0 1 1 0 4 0 0 1 1 0 5 1 0 1 1 0 6 0 0 1 1 0 7 0 0 1 1 0 8 0 1 0 1 0 9 0 0 1 1 0 10 0 0 1 1 0 11 0 1 0 1 0 12 0 0 1 1 0 13 0 0 1 1 0 14 0 1 0 1 0 15 0 0 1 1 0 16 0 1 0 1 0 17 1 1 0 1 0 18 0 1 0 1 0 19 0 0 1 1 0 20 1 1 0 1 0 21 0 0 1 1 0 22 0 0 1 1 0 23 0 0 1 1 0 24 0 0 1 1 0 25 0 1 0 1 0 26 0 0 1 1 0 27 0 0 1 1 0 28 0 0 1 1 0 29 0 0 1 1 0 30 0 0 1 1 0 31 0 0 1 1 0 32 0 0 1 1 0 33 0 0 1 1 0 34 0 1 0 1 0 35 0 0 1 1 0 36 0 0 1 1 0 37 0 1 0 1 0 38 0 0 1 1 0 39 0 0 1 1 0 40 0 1 0 1 0 41 1 0 1 1 0 42 0 0 1 1 0 43 0 0 1 1 0 44 0 1 0 1 0 45 0 0 1 1 0 46 0 0 1 1 0 47 0 0 1 1 0 48 0 0 1 1 0 49 0 0 1 1 0 50 0 0 1 1 0 51 0 1 0 1 0 52 1 1 0 1 0 53 0 0 1 1 0 54 1 0 1 1 0 55 0 0 1 1 0 56 0 1 0 1 0 57 0 0 1 1 0 58 0 0 1 1 0 59 0 0 1 1 0 60 1 1 0 1 0 61 0 1 0 1 0 62 0 0 1 1 0 63 0 0 1 1 0 64 0 1 0 1 0 65 0 0 1 1 0 66 0 0 1 1 0 67 1 1 0 1 0 68 0 0 1 1 0 69 0 0 1 1 0 70 0 0 1 1 0 71 0 0 1 1 0 72 0 0 1 1 0 73 0 0 1 1 0 74 0 0 1 1 0 75 0 0 1 1 0 76 0 1 0 1 0 77 0 0 1 1 0 78 0 0 1 1 0 79 1 1 0 1 0 80 0 1 0 1 0 81 0 0 1 1 0 82 0 0 1 1 0 83 0 0 1 1 0 84 1 0 1 1 0 85 0 0 1 1 0 86 0 0 1 1 0 87 0 0 1 0 1 88 0 1 0 0 1 89 0 0 1 0 1 90 0 0 1 0 1 91 0 0 1 0 1 92 0 1 0 0 1 93 0 0 1 0 1 94 0 0 1 0 1 95 0 1 0 0 1 96 0 0 1 0 1 97 0 1 0 0 1 98 0 0 1 0 1 99 0 0 1 0 1 100 0 0 1 0 1 101 0 0 1 0 1 102 0 0 1 0 1 103 0 0 1 0 1 104 0 0 1 0 1 105 0 1 0 0 1 106 0 0 1 0 1 107 0 0 1 0 1 108 0 1 0 0 1 109 0 0 1 0 1 110 0 0 1 0 1 111 0 1 0 0 1 112 0 1 0 0 1 113 0 0 1 0 1 114 0 1 0 0 1 115 0 0 1 0 1 116 0 0 1 0 1 117 0 0 1 0 1 118 0 0 1 0 1 119 0 0 1 0 1 120 0 0 1 0 1 121 0 0 1 0 1 122 0 0 1 0 1 123 0 1 0 0 1 124 0 0 1 0 1 125 0 0 1 0 1 126 0 1 0 0 1 127 0 0 1 0 1 128 0 0 1 0 1 129 0 0 1 0 1 130 0 0 1 0 1 131 0 0 1 0 1 132 0 0 1 0 1 133 0 0 1 0 1 134 0 0 1 0 1 135 0 0 1 0 1 136 0 0 1 0 1 137 0 0 1 0 1 138 0 1 0 0 1 139 0 1 0 0 1 140 0 0 1 0 1 141 1 0 1 0 1 142 0 1 0 0 1 143 0 0 1 0 1 144 0 0 1 0 1 145 0 0 1 0 1 146 0 1 0 0 1 147 0 1 0 0 1 148 0 1 0 0 1 149 0 0 1 0 1 150 0 0 1 0 1 151 0 0 1 0 1 152 1 0 1 0 1 153 1 0 1 0 1 154 0 0 1 0 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Treatment No_treatment `4weken` `2weken` 0.02236 0.08702 NA 0.07064 NA > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.18002 -0.09301 -0.09301 -0.02236 0.97764 Coefficients: (2 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 0.02236 0.03576 0.625 0.5326 Treatment 0.08702 0.05068 1.717 0.0881 . No_treatment NA NA NA NA `4weken` 0.07064 0.04475 1.578 0.1166 `2weken` NA NA NA NA --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2757 on 151 degrees of freedom Multiple R-squared: 0.03544, Adjusted R-squared: 0.02267 F-statistic: 2.774 on 2 and 151 DF, p-value: 0.06558 > 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,] 0.9869165999 0.0261668002 0.0130834001 [2,] 0.9737322699 0.0525354602 0.0262677301 [3,] 0.9527252053 0.0945495894 0.0472747947 [4,] 0.9179873766 0.1640252468 0.0820126234 [5,] 0.8760009627 0.2479980746 0.1239990373 [6,] 0.8227922824 0.3544154352 0.1772077176 [7,] 0.7542421155 0.4915157689 0.2457578845 [8,] 0.6825650542 0.6348698917 0.3174349458 [9,] 0.6006262575 0.7987474850 0.3993737425 [10,] 0.9680590043 0.0638819914 0.0319409957 [11,] 0.9559610021 0.0880779957 0.0440389979 [12,] 0.9369321332 0.1261357336 0.0630678668 [13,] 0.9938449354 0.0123101293 0.0061550646 [14,] 0.9903589633 0.0192820734 0.0096410367 [15,] 0.9853331377 0.0293337246 0.0146668623 [16,] 0.9783049369 0.0433901261 0.0216950631 [17,] 0.9687607067 0.0624785866 0.0312392933 [18,] 0.9627599418 0.0744801164 0.0372400582 [19,] 0.9485875075 0.1028249849 0.0514124925 [20,] 0.9306565114 0.1386869773 0.0693434886 [21,] 0.9085331756 0.1829336489 0.0914668244 [22,] 0.8818924564 0.2362150873 0.1181075436 [23,] 0.8505571894 0.2988856212 0.1494428106 [24,] 0.8145294390 0.3709411220 0.1854705610 [25,] 0.7740099577 0.4519800846 0.2259900423 [26,] 0.7294028347 0.5411943306 0.2705971653 [27,] 0.7044939205 0.5910121590 0.2955060795 [28,] 0.6552422432 0.6895155137 0.3447577568 [29,] 0.6037328062 0.7925343875 0.3962671938 [30,] 0.5730765282 0.8538469437 0.4269234718 [31,] 0.5202122328 0.9595755344 0.4797877672 [32,] 0.4675036585 0.9350073170 0.5324963415 [33,] 0.4353209741 0.8706419483 0.5646790259 [34,] 0.8715455255 0.2569089490 0.1284544745 [35,] 0.8440747529 0.3118504943 0.1559252471 [36,] 0.8132145827 0.3735708346 0.1867854173 [37,] 0.7899702962 0.4200594077 0.2100297038 [38,] 0.7539173382 0.4921653237 0.2460826618 [39,] 0.7150870039 0.5698259923 0.2849129961 [40,] 0.6738860862 0.6522278276 0.3261139138 [41,] 0.6308074433 0.7383851134 0.3691925567 [42,] 0.5864106758 0.8271786485 0.4135893242 [43,] 0.5412987924 0.9174024151 0.4587012076 [44,] 0.5108536838 0.9782926323 0.4891463162 [45,] 0.8245822136 0.3508355728 0.1754177864 [46,] 0.7943199840 0.4113600320 0.2056800160 [47,] 0.9735306636 0.0529386728 0.0264693364 [48,] 0.9660509829 0.0678980343 0.0339490171 [49,] 0.9604573842 0.0790852315 0.0395426158 [50,] 0.9503312262 0.0993375475 0.0496687738 [51,] 0.9383406187 0.1233187626 0.0616593813 [52,] 0.9243377836 0.1513244328 0.0756622164 [53,] 0.9887421674 0.0225156652 0.0112578326 [54,] 0.9866280802 0.0267438396 0.0133719198 [55,] 0.9825244448 0.0349511104 0.0174755552 [56,] 0.9774441348 0.0451117304 0.0225558652 [57,] 0.9737231479 0.0525537041 0.0262768521 [58,] 0.9668062507 0.0663874985 0.0331937493 [59,] 0.9585853254 0.0828293492 0.0414146746 [60,] 0.9957568444 0.0084863112 0.0042431556 [61,] 0.9942392267 0.0115215467 0.0057607733 [62,] 0.9922853730 0.0154292539 0.0077146270 [63,] 0.9898123738 0.0203752524 0.0101876262 [64,] 0.9867385263 0.0265229475 0.0132614737 [65,] 0.9829923552 0.0340152896 0.0170076448 [66,] 0.9785261538 0.0429476924 0.0214738462 [67,] 0.9733357878 0.0533284244 0.0266642122 [68,] 0.9674894269 0.0650211462 0.0325105731 [69,] 0.9635921208 0.0728157584 0.0364078792 [70,] 0.9572664269 0.0854671461 0.0427335731 [71,] 0.9512563521 0.0974872958 0.0487436479 [72,] 0.9952153354 0.0095693293 0.0047846646 [73,] 0.9941629919 0.0116740162 0.0058370081 [74,] 0.9926719571 0.0146560858 0.0073280429 [75,] 0.9913137290 0.0173725420 0.0086862710 [76,] 0.9907579877 0.0184840247 0.0092420123 [77,] 0.9998010545 0.0003978911 0.0001989455 [78,] 0.9996878661 0.0006242678 0.0003121339 [79,] 0.9995163899 0.0009672203 0.0004836101 [80,] 0.9992676710 0.0014646580 0.0007323290 [81,] 0.9989193838 0.0021612324 0.0010806162 [82,] 0.9984178402 0.0031643196 0.0015821598 [83,] 0.9977008790 0.0045982420 0.0022991210 [84,] 0.9966944595 0.0066110811 0.0033055405 [85,] 0.9953347121 0.0093305758 0.0046652879 [86,] 0.9934633379 0.0130733242 0.0065366621 [87,] 0.9909438909 0.0181122183 0.0090561091 [88,] 0.9876108771 0.0247782458 0.0123891229 [89,] 0.9832551761 0.0334896479 0.0167448239 [90,] 0.9775498874 0.0449002251 0.0224501126 [91,] 0.9703850395 0.0592299210 0.0296149605 [92,] 0.9613803040 0.0772393920 0.0386196960 [93,] 0.9502212827 0.0995574345 0.0497787173 [94,] 0.9365870389 0.1268259223 0.0634129611 [95,] 0.9201644540 0.1596710921 0.0798355460 [96,] 0.9006654675 0.1986690650 0.0993345325 [97,] 0.8778464553 0.2443070894 0.1221535447 [98,] 0.8508821708 0.2982356584 0.1491178292 [99,] 0.8208141513 0.3583716974 0.1791858487 [100,] 0.7871250057 0.4257499887 0.2128749943 [101,] 0.7484659630 0.5030680741 0.2515340370 [102,] 0.7077671113 0.5844657774 0.2922328887 [103,] 0.6641628500 0.6716743000 0.3358371500 [104,] 0.6156750543 0.7686498914 0.3843249457 [105,] 0.5647067034 0.8705865931 0.4352932966 [106,] 0.5152289481 0.9695421037 0.4847710519 [107,] 0.4620377582 0.9240755164 0.5379622418 [108,] 0.4124805009 0.8249610017 0.5875194991 [109,] 0.3641774658 0.7283549316 0.6358225342 [110,] 0.3178574844 0.6357149688 0.6821425156 [111,] 0.2741623944 0.5483247887 0.7258376056 [112,] 0.2336194240 0.4672388481 0.7663805760 [113,] 0.1966219707 0.3932439414 0.8033780293 [114,] 0.1634199697 0.3268399394 0.8365800303 [115,] 0.1341200792 0.2682401583 0.8658799208 [116,] 0.1054120028 0.2108240055 0.8945879972 [117,] 0.0839168153 0.1678336306 0.9160831847 [118,] 0.0659323856 0.1318647713 0.9340676144 [119,] 0.0488389458 0.0976778915 0.9511610542 [120,] 0.0371171750 0.0742343500 0.9628828250 [121,] 0.0278402167 0.0556804334 0.9721597833 [122,] 0.0206243600 0.0412487200 0.9793756400 [123,] 0.0151067096 0.0302134192 0.9848932904 [124,] 0.0109575408 0.0219150816 0.9890424592 [125,] 0.0078877832 0.0157755665 0.9921122168 [126,] 0.0056521776 0.0113043553 0.9943478224 [127,] 0.0040489468 0.0080978936 0.9959510532 [128,] 0.0029169704 0.0058339408 0.9970830296 [129,] 0.0021314845 0.0042629690 0.9978685155 [130,] 0.0015993208 0.0031986416 0.9984006792 [131,] 0.0008591998 0.0017183996 0.9991408002 [132,] 0.0004381835 0.0008763671 0.9995618165 [133,] 0.0003191912 0.0006383823 0.9996808088 [134,] 0.0067673952 0.0135347905 0.9932326048 [135,] 0.0034823573 0.0069647146 0.9965176427 [136,] 0.0021885984 0.0043771967 0.9978114016 [137,] 0.0014041274 0.0028082548 0.9985958726 [138,] 0.0009568859 0.0019137718 0.9990431141 [139,] 0.0003287317 0.0006574635 0.9996712683 > postscript(file="/var/wessaorg/rcomp/tmp/1cz161355946338.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2q16f1355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/33m641355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4e36z1355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5d67n1355946338.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 -0.18002357 -0.09300727 -0.09300727 -0.09300727 0.90699273 -0.09300727 7 8 9 10 11 12 -0.09300727 -0.18002357 -0.09300727 -0.09300727 -0.18002357 -0.09300727 13 14 15 16 17 18 -0.09300727 -0.18002357 -0.09300727 -0.18002357 0.81997643 -0.18002357 19 20 21 22 23 24 -0.09300727 0.81997643 -0.09300727 -0.09300727 -0.09300727 -0.09300727 25 26 27 28 29 30 -0.18002357 -0.09300727 -0.09300727 -0.09300727 -0.09300727 -0.09300727 31 32 33 34 35 36 -0.09300727 -0.09300727 -0.09300727 -0.18002357 -0.09300727 -0.09300727 37 38 39 40 41 42 -0.18002357 -0.09300727 -0.09300727 -0.18002357 0.90699273 -0.09300727 43 44 45 46 47 48 -0.09300727 -0.18002357 -0.09300727 -0.09300727 -0.09300727 -0.09300727 49 50 51 52 53 54 -0.09300727 -0.09300727 -0.18002357 0.81997643 -0.09300727 0.90699273 55 56 57 58 59 60 -0.09300727 -0.18002357 -0.09300727 -0.09300727 -0.09300727 0.81997643 61 62 63 64 65 66 -0.18002357 -0.09300727 -0.09300727 -0.18002357 -0.09300727 -0.09300727 67 68 69 70 71 72 0.81997643 -0.09300727 -0.09300727 -0.09300727 -0.09300727 -0.09300727 73 74 75 76 77 78 -0.09300727 -0.09300727 -0.09300727 -0.18002357 -0.09300727 -0.09300727 79 80 81 82 83 84 0.81997643 -0.18002357 -0.09300727 -0.09300727 -0.09300727 0.90699273 85 86 87 88 89 90 -0.09300727 -0.09300727 -0.02236357 -0.10937987 -0.02236357 -0.02236357 91 92 93 94 95 96 -0.02236357 -0.10937987 -0.02236357 -0.02236357 -0.10937987 -0.02236357 97 98 99 100 101 102 -0.10937987 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 103 104 105 106 107 108 -0.02236357 -0.02236357 -0.10937987 -0.02236357 -0.02236357 -0.10937987 109 110 111 112 113 114 -0.02236357 -0.02236357 -0.10937987 -0.10937987 -0.02236357 -0.10937987 115 116 117 118 119 120 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 121 122 123 124 125 126 -0.02236357 -0.02236357 -0.10937987 -0.02236357 -0.02236357 -0.10937987 127 128 129 130 131 132 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 133 134 135 136 137 138 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.02236357 -0.10937987 139 140 141 142 143 144 -0.10937987 -0.02236357 0.97763643 -0.10937987 -0.02236357 -0.02236357 145 146 147 148 149 150 -0.02236357 -0.10937987 -0.10937987 -0.10937987 -0.02236357 -0.02236357 151 152 153 154 -0.02236357 0.97763643 0.97763643 -0.02236357 > postscript(file="/var/wessaorg/rcomp/tmp/66v9a1355946338.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 -0.18002357 NA 1 -0.09300727 -0.18002357 2 -0.09300727 -0.09300727 3 -0.09300727 -0.09300727 4 0.90699273 -0.09300727 5 -0.09300727 0.90699273 6 -0.09300727 -0.09300727 7 -0.18002357 -0.09300727 8 -0.09300727 -0.18002357 9 -0.09300727 -0.09300727 10 -0.18002357 -0.09300727 11 -0.09300727 -0.18002357 12 -0.09300727 -0.09300727 13 -0.18002357 -0.09300727 14 -0.09300727 -0.18002357 15 -0.18002357 -0.09300727 16 0.81997643 -0.18002357 17 -0.18002357 0.81997643 18 -0.09300727 -0.18002357 19 0.81997643 -0.09300727 20 -0.09300727 0.81997643 21 -0.09300727 -0.09300727 22 -0.09300727 -0.09300727 23 -0.09300727 -0.09300727 24 -0.18002357 -0.09300727 25 -0.09300727 -0.18002357 26 -0.09300727 -0.09300727 27 -0.09300727 -0.09300727 28 -0.09300727 -0.09300727 29 -0.09300727 -0.09300727 30 -0.09300727 -0.09300727 31 -0.09300727 -0.09300727 32 -0.09300727 -0.09300727 33 -0.18002357 -0.09300727 34 -0.09300727 -0.18002357 35 -0.09300727 -0.09300727 36 -0.18002357 -0.09300727 37 -0.09300727 -0.18002357 38 -0.09300727 -0.09300727 39 -0.18002357 -0.09300727 40 0.90699273 -0.18002357 41 -0.09300727 0.90699273 42 -0.09300727 -0.09300727 43 -0.18002357 -0.09300727 44 -0.09300727 -0.18002357 45 -0.09300727 -0.09300727 46 -0.09300727 -0.09300727 47 -0.09300727 -0.09300727 48 -0.09300727 -0.09300727 49 -0.09300727 -0.09300727 50 -0.18002357 -0.09300727 51 0.81997643 -0.18002357 52 -0.09300727 0.81997643 53 0.90699273 -0.09300727 54 -0.09300727 0.90699273 55 -0.18002357 -0.09300727 56 -0.09300727 -0.18002357 57 -0.09300727 -0.09300727 58 -0.09300727 -0.09300727 59 0.81997643 -0.09300727 60 -0.18002357 0.81997643 61 -0.09300727 -0.18002357 62 -0.09300727 -0.09300727 63 -0.18002357 -0.09300727 64 -0.09300727 -0.18002357 65 -0.09300727 -0.09300727 66 0.81997643 -0.09300727 67 -0.09300727 0.81997643 68 -0.09300727 -0.09300727 69 -0.09300727 -0.09300727 70 -0.09300727 -0.09300727 71 -0.09300727 -0.09300727 72 -0.09300727 -0.09300727 73 -0.09300727 -0.09300727 74 -0.09300727 -0.09300727 75 -0.18002357 -0.09300727 76 -0.09300727 -0.18002357 77 -0.09300727 -0.09300727 78 0.81997643 -0.09300727 79 -0.18002357 0.81997643 80 -0.09300727 -0.18002357 81 -0.09300727 -0.09300727 82 -0.09300727 -0.09300727 83 0.90699273 -0.09300727 84 -0.09300727 0.90699273 85 -0.09300727 -0.09300727 86 -0.02236357 -0.09300727 87 -0.10937987 -0.02236357 88 -0.02236357 -0.10937987 89 -0.02236357 -0.02236357 90 -0.02236357 -0.02236357 91 -0.10937987 -0.02236357 92 -0.02236357 -0.10937987 93 -0.02236357 -0.02236357 94 -0.10937987 -0.02236357 95 -0.02236357 -0.10937987 96 -0.10937987 -0.02236357 97 -0.02236357 -0.10937987 98 -0.02236357 -0.02236357 99 -0.02236357 -0.02236357 100 -0.02236357 -0.02236357 101 -0.02236357 -0.02236357 102 -0.02236357 -0.02236357 103 -0.02236357 -0.02236357 104 -0.10937987 -0.02236357 105 -0.02236357 -0.10937987 106 -0.02236357 -0.02236357 107 -0.10937987 -0.02236357 108 -0.02236357 -0.10937987 109 -0.02236357 -0.02236357 110 -0.10937987 -0.02236357 111 -0.10937987 -0.10937987 112 -0.02236357 -0.10937987 113 -0.10937987 -0.02236357 114 -0.02236357 -0.10937987 115 -0.02236357 -0.02236357 116 -0.02236357 -0.02236357 117 -0.02236357 -0.02236357 118 -0.02236357 -0.02236357 119 -0.02236357 -0.02236357 120 -0.02236357 -0.02236357 121 -0.02236357 -0.02236357 122 -0.10937987 -0.02236357 123 -0.02236357 -0.10937987 124 -0.02236357 -0.02236357 125 -0.10937987 -0.02236357 126 -0.02236357 -0.10937987 127 -0.02236357 -0.02236357 128 -0.02236357 -0.02236357 129 -0.02236357 -0.02236357 130 -0.02236357 -0.02236357 131 -0.02236357 -0.02236357 132 -0.02236357 -0.02236357 133 -0.02236357 -0.02236357 134 -0.02236357 -0.02236357 135 -0.02236357 -0.02236357 136 -0.02236357 -0.02236357 137 -0.10937987 -0.02236357 138 -0.10937987 -0.10937987 139 -0.02236357 -0.10937987 140 0.97763643 -0.02236357 141 -0.10937987 0.97763643 142 -0.02236357 -0.10937987 143 -0.02236357 -0.02236357 144 -0.02236357 -0.02236357 145 -0.10937987 -0.02236357 146 -0.10937987 -0.10937987 147 -0.10937987 -0.10937987 148 -0.02236357 -0.10937987 149 -0.02236357 -0.02236357 150 -0.02236357 -0.02236357 151 0.97763643 -0.02236357 152 0.97763643 0.97763643 153 -0.02236357 0.97763643 154 NA -0.02236357 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.09300727 -0.18002357 [2,] -0.09300727 -0.09300727 [3,] -0.09300727 -0.09300727 [4,] 0.90699273 -0.09300727 [5,] -0.09300727 0.90699273 [6,] -0.09300727 -0.09300727 [7,] -0.18002357 -0.09300727 [8,] -0.09300727 -0.18002357 [9,] -0.09300727 -0.09300727 [10,] -0.18002357 -0.09300727 [11,] -0.09300727 -0.18002357 [12,] -0.09300727 -0.09300727 [13,] -0.18002357 -0.09300727 [14,] -0.09300727 -0.18002357 [15,] -0.18002357 -0.09300727 [16,] 0.81997643 -0.18002357 [17,] -0.18002357 0.81997643 [18,] -0.09300727 -0.18002357 [19,] 0.81997643 -0.09300727 [20,] -0.09300727 0.81997643 [21,] -0.09300727 -0.09300727 [22,] -0.09300727 -0.09300727 [23,] -0.09300727 -0.09300727 [24,] -0.18002357 -0.09300727 [25,] -0.09300727 -0.18002357 [26,] -0.09300727 -0.09300727 [27,] -0.09300727 -0.09300727 [28,] -0.09300727 -0.09300727 [29,] -0.09300727 -0.09300727 [30,] -0.09300727 -0.09300727 [31,] -0.09300727 -0.09300727 [32,] -0.09300727 -0.09300727 [33,] -0.18002357 -0.09300727 [34,] -0.09300727 -0.18002357 [35,] -0.09300727 -0.09300727 [36,] -0.18002357 -0.09300727 [37,] -0.09300727 -0.18002357 [38,] -0.09300727 -0.09300727 [39,] -0.18002357 -0.09300727 [40,] 0.90699273 -0.18002357 [41,] -0.09300727 0.90699273 [42,] -0.09300727 -0.09300727 [43,] -0.18002357 -0.09300727 [44,] -0.09300727 -0.18002357 [45,] -0.09300727 -0.09300727 [46,] -0.09300727 -0.09300727 [47,] -0.09300727 -0.09300727 [48,] -0.09300727 -0.09300727 [49,] -0.09300727 -0.09300727 [50,] -0.18002357 -0.09300727 [51,] 0.81997643 -0.18002357 [52,] -0.09300727 0.81997643 [53,] 0.90699273 -0.09300727 [54,] -0.09300727 0.90699273 [55,] -0.18002357 -0.09300727 [56,] -0.09300727 -0.18002357 [57,] -0.09300727 -0.09300727 [58,] -0.09300727 -0.09300727 [59,] 0.81997643 -0.09300727 [60,] -0.18002357 0.81997643 [61,] -0.09300727 -0.18002357 [62,] -0.09300727 -0.09300727 [63,] -0.18002357 -0.09300727 [64,] -0.09300727 -0.18002357 [65,] -0.09300727 -0.09300727 [66,] 0.81997643 -0.09300727 [67,] -0.09300727 0.81997643 [68,] -0.09300727 -0.09300727 [69,] -0.09300727 -0.09300727 [70,] -0.09300727 -0.09300727 [71,] -0.09300727 -0.09300727 [72,] -0.09300727 -0.09300727 [73,] -0.09300727 -0.09300727 [74,] -0.09300727 -0.09300727 [75,] -0.18002357 -0.09300727 [76,] -0.09300727 -0.18002357 [77,] -0.09300727 -0.09300727 [78,] 0.81997643 -0.09300727 [79,] -0.18002357 0.81997643 [80,] -0.09300727 -0.18002357 [81,] -0.09300727 -0.09300727 [82,] -0.09300727 -0.09300727 [83,] 0.90699273 -0.09300727 [84,] -0.09300727 0.90699273 [85,] -0.09300727 -0.09300727 [86,] -0.02236357 -0.09300727 [87,] -0.10937987 -0.02236357 [88,] -0.02236357 -0.10937987 [89,] -0.02236357 -0.02236357 [90,] -0.02236357 -0.02236357 [91,] -0.10937987 -0.02236357 [92,] -0.02236357 -0.10937987 [93,] -0.02236357 -0.02236357 [94,] -0.10937987 -0.02236357 [95,] -0.02236357 -0.10937987 [96,] -0.10937987 -0.02236357 [97,] -0.02236357 -0.10937987 [98,] -0.02236357 -0.02236357 [99,] -0.02236357 -0.02236357 [100,] -0.02236357 -0.02236357 [101,] -0.02236357 -0.02236357 [102,] -0.02236357 -0.02236357 [103,] -0.02236357 -0.02236357 [104,] -0.10937987 -0.02236357 [105,] -0.02236357 -0.10937987 [106,] -0.02236357 -0.02236357 [107,] -0.10937987 -0.02236357 [108,] -0.02236357 -0.10937987 [109,] -0.02236357 -0.02236357 [110,] -0.10937987 -0.02236357 [111,] -0.10937987 -0.10937987 [112,] -0.02236357 -0.10937987 [113,] -0.10937987 -0.02236357 [114,] -0.02236357 -0.10937987 [115,] -0.02236357 -0.02236357 [116,] -0.02236357 -0.02236357 [117,] -0.02236357 -0.02236357 [118,] -0.02236357 -0.02236357 [119,] -0.02236357 -0.02236357 [120,] -0.02236357 -0.02236357 [121,] -0.02236357 -0.02236357 [122,] -0.10937987 -0.02236357 [123,] -0.02236357 -0.10937987 [124,] -0.02236357 -0.02236357 [125,] -0.10937987 -0.02236357 [126,] -0.02236357 -0.10937987 [127,] -0.02236357 -0.02236357 [128,] -0.02236357 -0.02236357 [129,] -0.02236357 -0.02236357 [130,] -0.02236357 -0.02236357 [131,] -0.02236357 -0.02236357 [132,] -0.02236357 -0.02236357 [133,] -0.02236357 -0.02236357 [134,] -0.02236357 -0.02236357 [135,] -0.02236357 -0.02236357 [136,] -0.02236357 -0.02236357 [137,] -0.10937987 -0.02236357 [138,] -0.10937987 -0.10937987 [139,] -0.02236357 -0.10937987 [140,] 0.97763643 -0.02236357 [141,] -0.10937987 0.97763643 [142,] -0.02236357 -0.10937987 [143,] -0.02236357 -0.02236357 [144,] -0.02236357 -0.02236357 [145,] -0.10937987 -0.02236357 [146,] -0.10937987 -0.10937987 [147,] -0.10937987 -0.10937987 [148,] -0.02236357 -0.10937987 [149,] -0.02236357 -0.02236357 [150,] -0.02236357 -0.02236357 [151,] 0.97763643 -0.02236357 [152,] 0.97763643 0.97763643 [153,] -0.02236357 0.97763643 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.09300727 -0.18002357 2 -0.09300727 -0.09300727 3 -0.09300727 -0.09300727 4 0.90699273 -0.09300727 5 -0.09300727 0.90699273 6 -0.09300727 -0.09300727 7 -0.18002357 -0.09300727 8 -0.09300727 -0.18002357 9 -0.09300727 -0.09300727 10 -0.18002357 -0.09300727 11 -0.09300727 -0.18002357 12 -0.09300727 -0.09300727 13 -0.18002357 -0.09300727 14 -0.09300727 -0.18002357 15 -0.18002357 -0.09300727 16 0.81997643 -0.18002357 17 -0.18002357 0.81997643 18 -0.09300727 -0.18002357 19 0.81997643 -0.09300727 20 -0.09300727 0.81997643 21 -0.09300727 -0.09300727 22 -0.09300727 -0.09300727 23 -0.09300727 -0.09300727 24 -0.18002357 -0.09300727 25 -0.09300727 -0.18002357 26 -0.09300727 -0.09300727 27 -0.09300727 -0.09300727 28 -0.09300727 -0.09300727 29 -0.09300727 -0.09300727 30 -0.09300727 -0.09300727 31 -0.09300727 -0.09300727 32 -0.09300727 -0.09300727 33 -0.18002357 -0.09300727 34 -0.09300727 -0.18002357 35 -0.09300727 -0.09300727 36 -0.18002357 -0.09300727 37 -0.09300727 -0.18002357 38 -0.09300727 -0.09300727 39 -0.18002357 -0.09300727 40 0.90699273 -0.18002357 41 -0.09300727 0.90699273 42 -0.09300727 -0.09300727 43 -0.18002357 -0.09300727 44 -0.09300727 -0.18002357 45 -0.09300727 -0.09300727 46 -0.09300727 -0.09300727 47 -0.09300727 -0.09300727 48 -0.09300727 -0.09300727 49 -0.09300727 -0.09300727 50 -0.18002357 -0.09300727 51 0.81997643 -0.18002357 52 -0.09300727 0.81997643 53 0.90699273 -0.09300727 54 -0.09300727 0.90699273 55 -0.18002357 -0.09300727 56 -0.09300727 -0.18002357 57 -0.09300727 -0.09300727 58 -0.09300727 -0.09300727 59 0.81997643 -0.09300727 60 -0.18002357 0.81997643 61 -0.09300727 -0.18002357 62 -0.09300727 -0.09300727 63 -0.18002357 -0.09300727 64 -0.09300727 -0.18002357 65 -0.09300727 -0.09300727 66 0.81997643 -0.09300727 67 -0.09300727 0.81997643 68 -0.09300727 -0.09300727 69 -0.09300727 -0.09300727 70 -0.09300727 -0.09300727 71 -0.09300727 -0.09300727 72 -0.09300727 -0.09300727 73 -0.09300727 -0.09300727 74 -0.09300727 -0.09300727 75 -0.18002357 -0.09300727 76 -0.09300727 -0.18002357 77 -0.09300727 -0.09300727 78 0.81997643 -0.09300727 79 -0.18002357 0.81997643 80 -0.09300727 -0.18002357 81 -0.09300727 -0.09300727 82 -0.09300727 -0.09300727 83 0.90699273 -0.09300727 84 -0.09300727 0.90699273 85 -0.09300727 -0.09300727 86 -0.02236357 -0.09300727 87 -0.10937987 -0.02236357 88 -0.02236357 -0.10937987 89 -0.02236357 -0.02236357 90 -0.02236357 -0.02236357 91 -0.10937987 -0.02236357 92 -0.02236357 -0.10937987 93 -0.02236357 -0.02236357 94 -0.10937987 -0.02236357 95 -0.02236357 -0.10937987 96 -0.10937987 -0.02236357 97 -0.02236357 -0.10937987 98 -0.02236357 -0.02236357 99 -0.02236357 -0.02236357 100 -0.02236357 -0.02236357 101 -0.02236357 -0.02236357 102 -0.02236357 -0.02236357 103 -0.02236357 -0.02236357 104 -0.10937987 -0.02236357 105 -0.02236357 -0.10937987 106 -0.02236357 -0.02236357 107 -0.10937987 -0.02236357 108 -0.02236357 -0.10937987 109 -0.02236357 -0.02236357 110 -0.10937987 -0.02236357 111 -0.10937987 -0.10937987 112 -0.02236357 -0.10937987 113 -0.10937987 -0.02236357 114 -0.02236357 -0.10937987 115 -0.02236357 -0.02236357 116 -0.02236357 -0.02236357 117 -0.02236357 -0.02236357 118 -0.02236357 -0.02236357 119 -0.02236357 -0.02236357 120 -0.02236357 -0.02236357 121 -0.02236357 -0.02236357 122 -0.10937987 -0.02236357 123 -0.02236357 -0.10937987 124 -0.02236357 -0.02236357 125 -0.10937987 -0.02236357 126 -0.02236357 -0.10937987 127 -0.02236357 -0.02236357 128 -0.02236357 -0.02236357 129 -0.02236357 -0.02236357 130 -0.02236357 -0.02236357 131 -0.02236357 -0.02236357 132 -0.02236357 -0.02236357 133 -0.02236357 -0.02236357 134 -0.02236357 -0.02236357 135 -0.02236357 -0.02236357 136 -0.02236357 -0.02236357 137 -0.10937987 -0.02236357 138 -0.10937987 -0.10937987 139 -0.02236357 -0.10937987 140 0.97763643 -0.02236357 141 -0.10937987 0.97763643 142 -0.02236357 -0.10937987 143 -0.02236357 -0.02236357 144 -0.02236357 -0.02236357 145 -0.10937987 -0.02236357 146 -0.10937987 -0.10937987 147 -0.10937987 -0.10937987 148 -0.02236357 -0.10937987 149 -0.02236357 -0.02236357 150 -0.02236357 -0.02236357 151 0.97763643 -0.02236357 152 0.97763643 0.97763643 153 -0.02236357 0.97763643 > 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/7aifz1355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8m0yj1355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/92rb21355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10ta0q1355946338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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