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 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,1 + ,0 + ,4 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,4 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,4 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,1 + ,1 + ,0 + ,4 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + 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,1 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,2 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,2 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0) + ,dim=c(7 + ,154) + ,dimnames=list(c('Weeks' + ,'UseLimit' + ,'T40enT20' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome') + ,1:154)) > y <- array(NA,dim=c(7,154),dimnames=list(c('Weeks','UseLimit','T40enT20','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 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '6' > par3 <- 'No 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 Useful Weeks UseLimit T40enT20 Used CorrectAnalysis Outcome 1 1 4 1 1 0 0 0 2 0 4 0 0 0 0 0 3 0 4 0 0 0 0 0 4 0 4 0 0 0 0 0 5 0 4 0 0 0 0 0 6 1 4 1 0 0 1 0 7 0 4 0 0 0 0 0 8 0 4 0 1 0 0 0 9 1 4 0 0 0 0 0 10 0 4 1 0 0 0 0 11 0 4 1 1 0 0 0 12 0 4 0 0 0 0 0 13 0 4 0 0 1 1 0 14 0 4 1 1 0 0 0 15 1 4 0 0 1 1 0 16 1 4 0 1 1 1 0 17 0 4 1 1 1 1 1 18 0 4 1 1 0 0 0 19 1 4 0 0 0 0 0 20 1 4 0 1 1 1 1 21 0 4 1 0 0 1 0 22 1 4 1 0 1 1 0 23 1 4 0 0 0 1 0 24 1 4 1 0 0 1 0 25 1 4 0 1 1 0 0 26 0 4 0 0 1 1 0 27 1 4 1 0 0 0 0 28 0 4 0 0 1 0 0 29 1 4 0 0 0 0 0 30 0 4 0 0 0 1 0 31 0 4 0 0 0 0 0 32 0 4 1 0 0 0 0 33 0 4 1 0 0 1 0 34 1 4 0 1 0 0 0 35 0 4 0 0 0 0 0 36 0 4 0 0 0 0 0 37 0 4 1 1 1 1 0 38 1 4 0 0 1 0 0 39 1 4 0 0 0 1 0 40 0 4 0 1 0 1 0 41 1 4 0 0 1 1 1 42 1 4 0 0 1 0 0 43 1 4 1 0 0 1 0 44 0 4 1 1 0 0 0 45 0 4 0 0 0 1 0 46 1 4 0 0 0 1 0 47 0 4 0 0 0 0 0 48 1 4 0 0 0 0 0 49 1 4 0 0 0 1 0 50 0 4 0 0 0 0 0 51 0 4 0 1 1 0 0 52 0 4 1 1 1 1 1 53 1 4 0 0 0 0 0 54 0 4 0 0 1 0 1 55 0 4 0 0 0 0 0 56 1 4 0 1 1 0 0 57 1 4 0 0 1 1 0 58 1 4 0 0 0 0 0 59 1 4 0 0 0 0 0 60 1 4 1 1 1 1 1 61 1 4 1 1 0 0 0 62 0 4 0 0 1 1 0 63 0 4 0 0 0 0 0 64 1 4 1 1 0 0 0 65 0 4 0 0 0 0 0 66 0 4 0 0 0 0 0 67 0 4 0 1 1 1 1 68 0 4 1 0 0 0 0 69 1 4 0 0 0 0 0 70 0 4 0 0 1 0 0 71 0 4 0 0 0 0 0 72 1 4 0 0 0 0 0 73 1 4 0 0 1 0 0 74 0 4 1 0 1 0 0 75 1 4 0 0 0 0 0 76 1 4 0 1 0 1 0 77 1 4 0 0 0 0 0 78 1 4 0 0 1 1 0 79 1 4 0 1 1 0 1 80 0 4 0 1 0 1 0 81 0 4 0 0 0 0 0 82 1 4 1 0 1 0 0 83 0 4 0 0 0 0 0 84 0 4 0 0 1 0 1 85 1 4 0 0 0 1 0 86 0 4 1 0 0 0 0 87 1 2 1 0 0 0 0 88 1 2 1 1 1 0 0 89 0 2 0 0 0 0 0 90 1 2 0 0 0 0 0 91 0 2 0 0 0 1 0 92 0 2 1 1 0 0 0 93 0 2 1 0 0 1 0 94 0 2 0 0 0 0 0 95 0 2 0 1 0 0 0 96 1 2 0 0 0 0 0 97 0 2 1 1 0 0 0 98 0 2 0 0 0 0 0 99 0 2 1 0 0 0 0 100 1 2 0 0 0 0 0 101 1 2 1 0 0 0 0 102 0 2 0 0 0 0 0 103 0 2 0 0 0 0 0 104 0 2 0 0 0 0 0 105 0 2 0 1 1 0 0 106 0 2 0 0 0 0 0 107 0 2 0 0 0 0 0 108 0 2 1 1 1 0 0 109 0 2 0 0 0 0 0 110 0 2 1 0 0 0 0 111 0 2 1 1 1 1 0 112 0 2 0 1 0 0 0 113 0 2 0 0 1 0 0 114 0 2 1 1 1 0 0 115 0 2 1 0 0 0 0 116 0 2 0 0 0 0 0 117 1 2 1 0 0 0 0 118 0 2 1 0 0 0 0 119 0 2 0 0 0 0 0 120 1 2 0 0 0 0 0 121 0 2 1 0 0 0 0 122 0 2 0 0 0 0 0 123 0 2 1 1 1 0 0 124 1 2 0 0 1 1 0 125 1 2 0 0 0 0 0 126 0 2 0 1 0 0 0 127 0 2 0 0 0 1 0 128 1 2 0 0 0 0 0 129 0 2 0 0 0 0 0 130 1 2 0 0 0 0 0 131 0 2 1 0 0 0 0 132 1 2 1 0 0 0 0 133 0 2 1 0 1 0 0 134 0 2 0 0 0 0 0 135 0 2 0 0 0 0 0 136 0 2 0 0 0 0 0 137 1 2 1 0 1 1 0 138 1 2 1 1 1 1 0 139 0 2 0 1 0 0 0 140 0 2 0 0 0 0 0 141 1 2 0 0 1 0 1 142 1 2 0 1 1 0 0 143 0 2 1 0 0 0 0 144 1 2 0 0 0 1 0 145 0 2 0 0 0 1 0 146 1 2 0 1 0 0 0 147 0 2 0 1 1 0 0 148 0 2 0 1 0 0 0 149 0 2 1 0 0 0 0 150 1 2 0 0 0 1 0 151 1 2 0 0 0 0 0 152 0 2 1 0 1 0 1 153 0 2 1 0 1 1 1 154 0 2 1 0 1 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Weeks UseLimit T40enT20 0.18371 0.05955 -0.07624 -0.03930 Used CorrectAnalysis Outcome 0.09806 0.15766 -0.11409 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.6776 -0.4179 -0.2744 0.5193 0.7734 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.18371 0.13676 1.343 0.181 Weeks 0.05955 0.04076 1.461 0.146 UseLimit -0.07624 0.08606 -0.886 0.377 T40enT20 -0.03930 0.09426 -0.417 0.677 Used 0.09806 0.10102 0.971 0.333 CorrectAnalysis 0.15766 0.09411 1.675 0.096 . Outcome -0.11409 0.16522 -0.690 0.491 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4858 on 147 degrees of freedom Multiple R-squared: 0.05824, Adjusted R-squared: 0.0198 F-statistic: 1.515 on 6 and 147 DF, p-value: 0.177 > 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,] 0.8463342 0.3073315 0.1536658 [2,] 0.8166965 0.3666070 0.1833035 [3,] 0.7213202 0.5573596 0.2786798 [4,] 0.6165084 0.7669831 0.3834916 [5,] 0.5478265 0.9043470 0.4521735 [6,] 0.6406809 0.7186381 0.3593191 [7,] 0.5759023 0.8481954 0.4240977 [8,] 0.4835595 0.9671191 0.5164405 [9,] 0.4197121 0.8394242 0.5802879 [10,] 0.5807713 0.8384575 0.4192287 [11,] 0.5976415 0.8047169 0.4023585 [12,] 0.6633101 0.6733799 0.3366899 [13,] 0.6589660 0.6820679 0.3410340 [14,] 0.6130291 0.7739419 0.3869709 [15,] 0.5780586 0.8438827 0.4219414 [16,] 0.6044528 0.7910944 0.3955472 [17,] 0.6858721 0.6282557 0.3141279 [18,] 0.7619782 0.4760436 0.2380218 [19,] 0.7339594 0.5320811 0.2660406 [20,] 0.7723618 0.4552764 0.2276382 [21,] 0.7920177 0.4159647 0.2079823 [22,] 0.7639916 0.4720167 0.2360084 [23,] 0.7312842 0.5374317 0.2687158 [24,] 0.7316728 0.5366544 0.2683272 [25,] 0.7434107 0.5131786 0.2565893 [26,] 0.7149358 0.5701284 0.2850642 [27,] 0.6847397 0.6305206 0.3152603 [28,] 0.7173483 0.5653035 0.2826517 [29,] 0.7337730 0.5324540 0.2662270 [30,] 0.7249313 0.5501375 0.2750687 [31,] 0.7380471 0.5239058 0.2619529 [32,] 0.7199658 0.5600685 0.2800342 [33,] 0.7125591 0.5748817 0.2874409 [34,] 0.7202194 0.5595612 0.2797806 [35,] 0.6888550 0.6222901 0.3111450 [36,] 0.6941583 0.6116834 0.3058417 [37,] 0.6895481 0.6209037 0.3104519 [38,] 0.6717776 0.6564448 0.3282224 [39,] 0.6928170 0.6143660 0.3071830 [40,] 0.6817786 0.6364429 0.3182214 [41,] 0.6663348 0.6673303 0.3336652 [42,] 0.6593521 0.6812958 0.3406479 [43,] 0.6581883 0.6836233 0.3418117 [44,] 0.6740090 0.6519821 0.3259910 [45,] 0.6581063 0.6837874 0.3418937 [46,] 0.6449068 0.7101865 0.3550932 [47,] 0.6505072 0.6989857 0.3494928 [48,] 0.6188981 0.7622039 0.3811019 [49,] 0.6359285 0.7281429 0.3640715 [50,] 0.6508025 0.6983951 0.3491975 [51,] 0.6627191 0.6745618 0.3372809 [52,] 0.7048071 0.5903858 0.2951929 [53,] 0.7386641 0.5226718 0.2613359 [54,] 0.7270808 0.5458383 0.2729192 [55,] 0.7630947 0.4738106 0.2369053 [56,] 0.7512643 0.4974714 0.2487357 [57,] 0.7401402 0.5197196 0.2598598 [58,] 0.7439892 0.5120217 0.2560108 [59,] 0.7255847 0.5488306 0.2744153 [60,] 0.7374056 0.5251887 0.2625944 [61,] 0.7466715 0.5066569 0.2533285 [62,] 0.7415387 0.5169226 0.2584613 [63,] 0.7495957 0.5008085 0.2504043 [64,] 0.7420670 0.5158660 0.2579330 [65,] 0.7412580 0.5174840 0.2587420 [66,] 0.7481216 0.5037568 0.2518784 [67,] 0.7395958 0.5208084 0.2604042 [68,] 0.7539038 0.4921923 0.2460962 [69,] 0.7315704 0.5368592 0.2684296 [70,] 0.7758366 0.4483269 0.2241634 [71,] 0.7717196 0.4565607 0.2282804 [72,] 0.7567426 0.4865148 0.2432574 [73,] 0.7736347 0.4527306 0.2263653 [74,] 0.7542891 0.4914218 0.2457109 [75,] 0.7366070 0.5267860 0.2633930 [76,] 0.7361282 0.5277437 0.2638718 [77,] 0.7028354 0.5943291 0.2971646 [78,] 0.7251065 0.5497871 0.2748935 [79,] 0.7547172 0.4905656 0.2452828 [80,] 0.7667902 0.4664195 0.2332098 [81,] 0.7803842 0.4392316 0.2196158 [82,] 0.8038346 0.3923307 0.1961654 [83,] 0.7816507 0.4366987 0.2183493 [84,] 0.7776508 0.4446984 0.2223492 [85,] 0.7581825 0.4836351 0.2418175 [86,] 0.7289280 0.5421440 0.2710720 [87,] 0.7645929 0.4708142 0.2354071 [88,] 0.7305788 0.5388424 0.2694212 [89,] 0.7061705 0.5876589 0.2938295 [90,] 0.6701805 0.6596391 0.3298195 [91,] 0.7127006 0.5745988 0.2872994 [92,] 0.7801010 0.4397981 0.2198990 [93,] 0.7577913 0.4844173 0.2422087 [94,] 0.7339632 0.5320737 0.2660368 [95,] 0.7090084 0.5819832 0.2909916 [96,] 0.6863456 0.6273089 0.3136544 [97,] 0.6593511 0.6812978 0.3406489 [98,] 0.6324410 0.7351180 0.3675590 [99,] 0.5907660 0.8184680 0.4092340 [100,] 0.5628714 0.8742571 0.4371286 [101,] 0.5156256 0.9687488 0.4843744 [102,] 0.5026594 0.9946812 0.4973406 [103,] 0.4639399 0.9278797 0.5360601 [104,] 0.4573753 0.9147505 0.5426247 [105,] 0.4156022 0.8312043 0.5843978 [106,] 0.3672312 0.7344624 0.6327688 [107,] 0.3413733 0.6827466 0.6586267 [108,] 0.4500025 0.9000050 0.5499975 [109,] 0.3958068 0.7916136 0.6041932 [110,] 0.3711202 0.7422403 0.6288798 [111,] 0.4082202 0.8164404 0.5917798 [112,] 0.3535625 0.7071250 0.6464375 [113,] 0.3275567 0.6551135 0.6724433 [114,] 0.2872473 0.5744947 0.7127527 [115,] 0.2500932 0.5001864 0.7499068 [116,] 0.2824432 0.5648865 0.7175568 [117,] 0.2519318 0.5038635 0.7480682 [118,] 0.2780279 0.5560559 0.7219721 [119,] 0.3190290 0.6380580 0.6809710 [120,] 0.2831460 0.5662919 0.7168540 [121,] 0.3343460 0.6686921 0.6656540 [122,] 0.2741008 0.5482017 0.7258992 [123,] 0.4671962 0.9343924 0.5328038 [124,] 0.4041403 0.8082806 0.5958597 [125,] 0.3482949 0.6965898 0.6517051 [126,] 0.2995366 0.5990732 0.7004634 [127,] 0.2613292 0.5226584 0.7386708 [128,] 0.2352990 0.4705980 0.7647010 [129,] 0.3365706 0.6731413 0.6634294 [130,] 0.2993721 0.5987442 0.7006279 [131,] 0.4088932 0.8177864 0.5911068 [132,] 0.3104978 0.6209957 0.6895022 [133,] 0.3747591 0.7495181 0.6252409 [134,] 0.2569762 0.5139524 0.7430238 [135,] 0.1909270 0.3818541 0.8090730 > postscript(file="/var/wessaorg/rcomp/tmp/140jg1356101751.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2x7781356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ajk11356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4hi1f1356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5xa101356101751.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 0.6936215 -0.4219182 -0.4219182 -0.4219182 -0.4219182 0.4966602 -0.4219182 8 9 10 11 12 13 14 -0.3826196 0.5780818 -0.3456771 -0.3063785 -0.4219182 -0.6776372 -0.3063785 15 16 17 18 19 20 21 0.3223628 0.3616614 -0.4480122 -0.3063785 0.5780818 0.4757466 -0.5033398 22 23 24 25 26 27 28 0.3986040 0.4204191 0.4966602 0.5193241 -0.6776372 0.6543229 -0.5199745 29 30 31 32 33 34 35 0.5780818 -0.5795809 -0.4219182 -0.3456771 -0.5033398 0.6173804 -0.4219182 36 37 38 39 40 41 42 -0.4219182 -0.5620975 0.4800255 0.4204191 -0.5402823 0.4364481 0.4800255 43 44 45 46 47 48 49 0.4966602 -0.3063785 -0.5795809 0.4204191 -0.4219182 0.5780818 0.4204191 50 51 52 53 54 55 56 -0.4219182 -0.4806759 -0.4480122 0.5780818 -0.4058892 -0.4219182 0.5193241 57 58 59 60 61 62 63 0.3223628 0.5780818 0.5780818 0.5519878 0.6936215 -0.6776372 -0.4219182 64 65 66 67 68 69 70 0.6936215 -0.4219182 -0.4219182 -0.5242534 -0.3456771 0.5780818 -0.5199745 71 72 73 74 75 76 77 -0.4219182 0.5780818 0.4800255 -0.4437333 0.5780818 0.4597177 0.5780818 78 79 80 81 82 83 84 0.3223628 0.6334093 -0.5402823 -0.4219182 0.5562667 -0.4219182 -0.4058892 85 86 87 88 89 90 91 0.4204191 -0.3456771 0.7734271 0.7146694 -0.3028140 0.6971860 -0.4604767 92 93 94 95 96 97 98 -0.1872744 -0.3842356 -0.3028140 -0.2635155 0.6971860 -0.1872744 -0.3028140 99 100 101 102 103 104 105 -0.2265729 0.6971860 0.7734271 -0.3028140 -0.3028140 -0.3028140 -0.3615718 106 107 108 109 110 111 112 -0.3028140 -0.3028140 -0.2853306 -0.3028140 -0.2265729 -0.4429933 -0.2635155 113 114 115 116 117 118 119 -0.4008703 -0.2853306 -0.2265729 -0.3028140 0.7734271 -0.2265729 -0.3028140 120 121 122 123 124 125 126 0.6971860 -0.2265729 -0.3028140 -0.2853306 0.4414670 0.6971860 -0.2635155 127 128 129 130 131 132 133 -0.4604767 0.6971860 -0.3028140 0.6971860 -0.2265729 0.7734271 -0.3246292 134 135 136 137 138 139 140 -0.3028140 -0.3028140 -0.3028140 0.5177081 0.5570067 -0.2635155 -0.3028140 141 142 143 144 145 146 147 0.7132150 0.6384282 -0.2265729 0.5395233 -0.4604767 0.7364845 -0.3615718 148 149 150 151 152 153 154 -0.2635155 -0.2265729 0.5395233 0.6971860 -0.2105439 -0.3682066 -0.3246292 > postscript(file="/var/wessaorg/rcomp/tmp/699tl1356101751.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 0.6936215 NA 1 -0.4219182 0.6936215 2 -0.4219182 -0.4219182 3 -0.4219182 -0.4219182 4 -0.4219182 -0.4219182 5 0.4966602 -0.4219182 6 -0.4219182 0.4966602 7 -0.3826196 -0.4219182 8 0.5780818 -0.3826196 9 -0.3456771 0.5780818 10 -0.3063785 -0.3456771 11 -0.4219182 -0.3063785 12 -0.6776372 -0.4219182 13 -0.3063785 -0.6776372 14 0.3223628 -0.3063785 15 0.3616614 0.3223628 16 -0.4480122 0.3616614 17 -0.3063785 -0.4480122 18 0.5780818 -0.3063785 19 0.4757466 0.5780818 20 -0.5033398 0.4757466 21 0.3986040 -0.5033398 22 0.4204191 0.3986040 23 0.4966602 0.4204191 24 0.5193241 0.4966602 25 -0.6776372 0.5193241 26 0.6543229 -0.6776372 27 -0.5199745 0.6543229 28 0.5780818 -0.5199745 29 -0.5795809 0.5780818 30 -0.4219182 -0.5795809 31 -0.3456771 -0.4219182 32 -0.5033398 -0.3456771 33 0.6173804 -0.5033398 34 -0.4219182 0.6173804 35 -0.4219182 -0.4219182 36 -0.5620975 -0.4219182 37 0.4800255 -0.5620975 38 0.4204191 0.4800255 39 -0.5402823 0.4204191 40 0.4364481 -0.5402823 41 0.4800255 0.4364481 42 0.4966602 0.4800255 43 -0.3063785 0.4966602 44 -0.5795809 -0.3063785 45 0.4204191 -0.5795809 46 -0.4219182 0.4204191 47 0.5780818 -0.4219182 48 0.4204191 0.5780818 49 -0.4219182 0.4204191 50 -0.4806759 -0.4219182 51 -0.4480122 -0.4806759 52 0.5780818 -0.4480122 53 -0.4058892 0.5780818 54 -0.4219182 -0.4058892 55 0.5193241 -0.4219182 56 0.3223628 0.5193241 57 0.5780818 0.3223628 58 0.5780818 0.5780818 59 0.5519878 0.5780818 60 0.6936215 0.5519878 61 -0.6776372 0.6936215 62 -0.4219182 -0.6776372 63 0.6936215 -0.4219182 64 -0.4219182 0.6936215 65 -0.4219182 -0.4219182 66 -0.5242534 -0.4219182 67 -0.3456771 -0.5242534 68 0.5780818 -0.3456771 69 -0.5199745 0.5780818 70 -0.4219182 -0.5199745 71 0.5780818 -0.4219182 72 0.4800255 0.5780818 73 -0.4437333 0.4800255 74 0.5780818 -0.4437333 75 0.4597177 0.5780818 76 0.5780818 0.4597177 77 0.3223628 0.5780818 78 0.6334093 0.3223628 79 -0.5402823 0.6334093 80 -0.4219182 -0.5402823 81 0.5562667 -0.4219182 82 -0.4219182 0.5562667 83 -0.4058892 -0.4219182 84 0.4204191 -0.4058892 85 -0.3456771 0.4204191 86 0.7734271 -0.3456771 87 0.7146694 0.7734271 88 -0.3028140 0.7146694 89 0.6971860 -0.3028140 90 -0.4604767 0.6971860 91 -0.1872744 -0.4604767 92 -0.3842356 -0.1872744 93 -0.3028140 -0.3842356 94 -0.2635155 -0.3028140 95 0.6971860 -0.2635155 96 -0.1872744 0.6971860 97 -0.3028140 -0.1872744 98 -0.2265729 -0.3028140 99 0.6971860 -0.2265729 100 0.7734271 0.6971860 101 -0.3028140 0.7734271 102 -0.3028140 -0.3028140 103 -0.3028140 -0.3028140 104 -0.3615718 -0.3028140 105 -0.3028140 -0.3615718 106 -0.3028140 -0.3028140 107 -0.2853306 -0.3028140 108 -0.3028140 -0.2853306 109 -0.2265729 -0.3028140 110 -0.4429933 -0.2265729 111 -0.2635155 -0.4429933 112 -0.4008703 -0.2635155 113 -0.2853306 -0.4008703 114 -0.2265729 -0.2853306 115 -0.3028140 -0.2265729 116 0.7734271 -0.3028140 117 -0.2265729 0.7734271 118 -0.3028140 -0.2265729 119 0.6971860 -0.3028140 120 -0.2265729 0.6971860 121 -0.3028140 -0.2265729 122 -0.2853306 -0.3028140 123 0.4414670 -0.2853306 124 0.6971860 0.4414670 125 -0.2635155 0.6971860 126 -0.4604767 -0.2635155 127 0.6971860 -0.4604767 128 -0.3028140 0.6971860 129 0.6971860 -0.3028140 130 -0.2265729 0.6971860 131 0.7734271 -0.2265729 132 -0.3246292 0.7734271 133 -0.3028140 -0.3246292 134 -0.3028140 -0.3028140 135 -0.3028140 -0.3028140 136 0.5177081 -0.3028140 137 0.5570067 0.5177081 138 -0.2635155 0.5570067 139 -0.3028140 -0.2635155 140 0.7132150 -0.3028140 141 0.6384282 0.7132150 142 -0.2265729 0.6384282 143 0.5395233 -0.2265729 144 -0.4604767 0.5395233 145 0.7364845 -0.4604767 146 -0.3615718 0.7364845 147 -0.2635155 -0.3615718 148 -0.2265729 -0.2635155 149 0.5395233 -0.2265729 150 0.6971860 0.5395233 151 -0.2105439 0.6971860 152 -0.3682066 -0.2105439 153 -0.3246292 -0.3682066 154 NA -0.3246292 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.4219182 0.6936215 [2,] -0.4219182 -0.4219182 [3,] -0.4219182 -0.4219182 [4,] -0.4219182 -0.4219182 [5,] 0.4966602 -0.4219182 [6,] -0.4219182 0.4966602 [7,] -0.3826196 -0.4219182 [8,] 0.5780818 -0.3826196 [9,] -0.3456771 0.5780818 [10,] -0.3063785 -0.3456771 [11,] -0.4219182 -0.3063785 [12,] -0.6776372 -0.4219182 [13,] -0.3063785 -0.6776372 [14,] 0.3223628 -0.3063785 [15,] 0.3616614 0.3223628 [16,] -0.4480122 0.3616614 [17,] -0.3063785 -0.4480122 [18,] 0.5780818 -0.3063785 [19,] 0.4757466 0.5780818 [20,] -0.5033398 0.4757466 [21,] 0.3986040 -0.5033398 [22,] 0.4204191 0.3986040 [23,] 0.4966602 0.4204191 [24,] 0.5193241 0.4966602 [25,] -0.6776372 0.5193241 [26,] 0.6543229 -0.6776372 [27,] -0.5199745 0.6543229 [28,] 0.5780818 -0.5199745 [29,] -0.5795809 0.5780818 [30,] -0.4219182 -0.5795809 [31,] -0.3456771 -0.4219182 [32,] -0.5033398 -0.3456771 [33,] 0.6173804 -0.5033398 [34,] -0.4219182 0.6173804 [35,] -0.4219182 -0.4219182 [36,] -0.5620975 -0.4219182 [37,] 0.4800255 -0.5620975 [38,] 0.4204191 0.4800255 [39,] -0.5402823 0.4204191 [40,] 0.4364481 -0.5402823 [41,] 0.4800255 0.4364481 [42,] 0.4966602 0.4800255 [43,] -0.3063785 0.4966602 [44,] -0.5795809 -0.3063785 [45,] 0.4204191 -0.5795809 [46,] -0.4219182 0.4204191 [47,] 0.5780818 -0.4219182 [48,] 0.4204191 0.5780818 [49,] -0.4219182 0.4204191 [50,] -0.4806759 -0.4219182 [51,] -0.4480122 -0.4806759 [52,] 0.5780818 -0.4480122 [53,] -0.4058892 0.5780818 [54,] -0.4219182 -0.4058892 [55,] 0.5193241 -0.4219182 [56,] 0.3223628 0.5193241 [57,] 0.5780818 0.3223628 [58,] 0.5780818 0.5780818 [59,] 0.5519878 0.5780818 [60,] 0.6936215 0.5519878 [61,] -0.6776372 0.6936215 [62,] -0.4219182 -0.6776372 [63,] 0.6936215 -0.4219182 [64,] -0.4219182 0.6936215 [65,] -0.4219182 -0.4219182 [66,] -0.5242534 -0.4219182 [67,] -0.3456771 -0.5242534 [68,] 0.5780818 -0.3456771 [69,] -0.5199745 0.5780818 [70,] -0.4219182 -0.5199745 [71,] 0.5780818 -0.4219182 [72,] 0.4800255 0.5780818 [73,] -0.4437333 0.4800255 [74,] 0.5780818 -0.4437333 [75,] 0.4597177 0.5780818 [76,] 0.5780818 0.4597177 [77,] 0.3223628 0.5780818 [78,] 0.6334093 0.3223628 [79,] -0.5402823 0.6334093 [80,] -0.4219182 -0.5402823 [81,] 0.5562667 -0.4219182 [82,] -0.4219182 0.5562667 [83,] -0.4058892 -0.4219182 [84,] 0.4204191 -0.4058892 [85,] -0.3456771 0.4204191 [86,] 0.7734271 -0.3456771 [87,] 0.7146694 0.7734271 [88,] -0.3028140 0.7146694 [89,] 0.6971860 -0.3028140 [90,] -0.4604767 0.6971860 [91,] -0.1872744 -0.4604767 [92,] -0.3842356 -0.1872744 [93,] -0.3028140 -0.3842356 [94,] -0.2635155 -0.3028140 [95,] 0.6971860 -0.2635155 [96,] -0.1872744 0.6971860 [97,] -0.3028140 -0.1872744 [98,] -0.2265729 -0.3028140 [99,] 0.6971860 -0.2265729 [100,] 0.7734271 0.6971860 [101,] -0.3028140 0.7734271 [102,] -0.3028140 -0.3028140 [103,] -0.3028140 -0.3028140 [104,] -0.3615718 -0.3028140 [105,] -0.3028140 -0.3615718 [106,] -0.3028140 -0.3028140 [107,] -0.2853306 -0.3028140 [108,] -0.3028140 -0.2853306 [109,] -0.2265729 -0.3028140 [110,] -0.4429933 -0.2265729 [111,] -0.2635155 -0.4429933 [112,] -0.4008703 -0.2635155 [113,] -0.2853306 -0.4008703 [114,] -0.2265729 -0.2853306 [115,] -0.3028140 -0.2265729 [116,] 0.7734271 -0.3028140 [117,] -0.2265729 0.7734271 [118,] -0.3028140 -0.2265729 [119,] 0.6971860 -0.3028140 [120,] -0.2265729 0.6971860 [121,] -0.3028140 -0.2265729 [122,] -0.2853306 -0.3028140 [123,] 0.4414670 -0.2853306 [124,] 0.6971860 0.4414670 [125,] -0.2635155 0.6971860 [126,] -0.4604767 -0.2635155 [127,] 0.6971860 -0.4604767 [128,] -0.3028140 0.6971860 [129,] 0.6971860 -0.3028140 [130,] -0.2265729 0.6971860 [131,] 0.7734271 -0.2265729 [132,] -0.3246292 0.7734271 [133,] -0.3028140 -0.3246292 [134,] -0.3028140 -0.3028140 [135,] -0.3028140 -0.3028140 [136,] 0.5177081 -0.3028140 [137,] 0.5570067 0.5177081 [138,] -0.2635155 0.5570067 [139,] -0.3028140 -0.2635155 [140,] 0.7132150 -0.3028140 [141,] 0.6384282 0.7132150 [142,] -0.2265729 0.6384282 [143,] 0.5395233 -0.2265729 [144,] -0.4604767 0.5395233 [145,] 0.7364845 -0.4604767 [146,] -0.3615718 0.7364845 [147,] -0.2635155 -0.3615718 [148,] -0.2265729 -0.2635155 [149,] 0.5395233 -0.2265729 [150,] 0.6971860 0.5395233 [151,] -0.2105439 0.6971860 [152,] -0.3682066 -0.2105439 [153,] -0.3246292 -0.3682066 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.4219182 0.6936215 2 -0.4219182 -0.4219182 3 -0.4219182 -0.4219182 4 -0.4219182 -0.4219182 5 0.4966602 -0.4219182 6 -0.4219182 0.4966602 7 -0.3826196 -0.4219182 8 0.5780818 -0.3826196 9 -0.3456771 0.5780818 10 -0.3063785 -0.3456771 11 -0.4219182 -0.3063785 12 -0.6776372 -0.4219182 13 -0.3063785 -0.6776372 14 0.3223628 -0.3063785 15 0.3616614 0.3223628 16 -0.4480122 0.3616614 17 -0.3063785 -0.4480122 18 0.5780818 -0.3063785 19 0.4757466 0.5780818 20 -0.5033398 0.4757466 21 0.3986040 -0.5033398 22 0.4204191 0.3986040 23 0.4966602 0.4204191 24 0.5193241 0.4966602 25 -0.6776372 0.5193241 26 0.6543229 -0.6776372 27 -0.5199745 0.6543229 28 0.5780818 -0.5199745 29 -0.5795809 0.5780818 30 -0.4219182 -0.5795809 31 -0.3456771 -0.4219182 32 -0.5033398 -0.3456771 33 0.6173804 -0.5033398 34 -0.4219182 0.6173804 35 -0.4219182 -0.4219182 36 -0.5620975 -0.4219182 37 0.4800255 -0.5620975 38 0.4204191 0.4800255 39 -0.5402823 0.4204191 40 0.4364481 -0.5402823 41 0.4800255 0.4364481 42 0.4966602 0.4800255 43 -0.3063785 0.4966602 44 -0.5795809 -0.3063785 45 0.4204191 -0.5795809 46 -0.4219182 0.4204191 47 0.5780818 -0.4219182 48 0.4204191 0.5780818 49 -0.4219182 0.4204191 50 -0.4806759 -0.4219182 51 -0.4480122 -0.4806759 52 0.5780818 -0.4480122 53 -0.4058892 0.5780818 54 -0.4219182 -0.4058892 55 0.5193241 -0.4219182 56 0.3223628 0.5193241 57 0.5780818 0.3223628 58 0.5780818 0.5780818 59 0.5519878 0.5780818 60 0.6936215 0.5519878 61 -0.6776372 0.6936215 62 -0.4219182 -0.6776372 63 0.6936215 -0.4219182 64 -0.4219182 0.6936215 65 -0.4219182 -0.4219182 66 -0.5242534 -0.4219182 67 -0.3456771 -0.5242534 68 0.5780818 -0.3456771 69 -0.5199745 0.5780818 70 -0.4219182 -0.5199745 71 0.5780818 -0.4219182 72 0.4800255 0.5780818 73 -0.4437333 0.4800255 74 0.5780818 -0.4437333 75 0.4597177 0.5780818 76 0.5780818 0.4597177 77 0.3223628 0.5780818 78 0.6334093 0.3223628 79 -0.5402823 0.6334093 80 -0.4219182 -0.5402823 81 0.5562667 -0.4219182 82 -0.4219182 0.5562667 83 -0.4058892 -0.4219182 84 0.4204191 -0.4058892 85 -0.3456771 0.4204191 86 0.7734271 -0.3456771 87 0.7146694 0.7734271 88 -0.3028140 0.7146694 89 0.6971860 -0.3028140 90 -0.4604767 0.6971860 91 -0.1872744 -0.4604767 92 -0.3842356 -0.1872744 93 -0.3028140 -0.3842356 94 -0.2635155 -0.3028140 95 0.6971860 -0.2635155 96 -0.1872744 0.6971860 97 -0.3028140 -0.1872744 98 -0.2265729 -0.3028140 99 0.6971860 -0.2265729 100 0.7734271 0.6971860 101 -0.3028140 0.7734271 102 -0.3028140 -0.3028140 103 -0.3028140 -0.3028140 104 -0.3615718 -0.3028140 105 -0.3028140 -0.3615718 106 -0.3028140 -0.3028140 107 -0.2853306 -0.3028140 108 -0.3028140 -0.2853306 109 -0.2265729 -0.3028140 110 -0.4429933 -0.2265729 111 -0.2635155 -0.4429933 112 -0.4008703 -0.2635155 113 -0.2853306 -0.4008703 114 -0.2265729 -0.2853306 115 -0.3028140 -0.2265729 116 0.7734271 -0.3028140 117 -0.2265729 0.7734271 118 -0.3028140 -0.2265729 119 0.6971860 -0.3028140 120 -0.2265729 0.6971860 121 -0.3028140 -0.2265729 122 -0.2853306 -0.3028140 123 0.4414670 -0.2853306 124 0.6971860 0.4414670 125 -0.2635155 0.6971860 126 -0.4604767 -0.2635155 127 0.6971860 -0.4604767 128 -0.3028140 0.6971860 129 0.6971860 -0.3028140 130 -0.2265729 0.6971860 131 0.7734271 -0.2265729 132 -0.3246292 0.7734271 133 -0.3028140 -0.3246292 134 -0.3028140 -0.3028140 135 -0.3028140 -0.3028140 136 0.5177081 -0.3028140 137 0.5570067 0.5177081 138 -0.2635155 0.5570067 139 -0.3028140 -0.2635155 140 0.7132150 -0.3028140 141 0.6384282 0.7132150 142 -0.2265729 0.6384282 143 0.5395233 -0.2265729 144 -0.4604767 0.5395233 145 0.7364845 -0.4604767 146 -0.3615718 0.7364845 147 -0.2635155 -0.3615718 148 -0.2265729 -0.2635155 149 0.5395233 -0.2265729 150 0.6971860 0.5395233 151 -0.2105439 0.6971860 152 -0.3682066 -0.2105439 153 -0.3246292 -0.3682066 > 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/7xmuq1356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/88rcc1356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9ezae1356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10fj0g1356101751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11th6n1356101751.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/12lbw21356101751.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/1349mv1356101751.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/14qgr41356101751.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/157xz81356101751.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/162j1y1356101751.tab") + } > > try(system("convert tmp/140jg1356101751.ps tmp/140jg1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/2x7781356101751.ps tmp/2x7781356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/3ajk11356101751.ps tmp/3ajk11356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/4hi1f1356101751.ps tmp/4hi1f1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/5xa101356101751.ps tmp/5xa101356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/699tl1356101751.ps tmp/699tl1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/7xmuq1356101751.ps tmp/7xmuq1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/88rcc1356101751.ps tmp/88rcc1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/9ezae1356101751.ps tmp/9ezae1356101751.png",intern=TRUE)) character(0) > try(system("convert tmp/10fj0g1356101751.ps tmp/10fj0g1356101751.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.900 1.327 10.291