R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 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. Natural language support but running in an English locale 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(3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,2 + ,2 + ,2 + ,3 + ,3 + ,3 + ,2 + ,3 + ,4 + ,4 + ,4 + ,5 + ,4 + ,4 + ,4 + ,5 + ,3 + ,2 + ,4 + ,3 + ,4 + ,2 + ,3 + ,4 + ,4 + ,4 + ,2 + ,4 + ,2 + ,3 + ,2 + ,4 + ,3 + ,2 + ,4 + ,2 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,3 + ,5 + ,4 + ,2 + ,4 + ,3 + ,5 + ,2 + ,3 + ,3 + ,4 + ,4 + ,3 + ,2 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,3 + ,3 + ,4 + ,2 + ,1 + ,2 + ,3 + ,2 + ,3 + ,3 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,3 + ,3 + ,4 + ,2 + ,3 + ,4 + ,3 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,3 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,2 + ,2 + ,2 + ,3 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,2 + ,5 + ,3 + ,5 + ,3 + ,2 + ,3 + ,3 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,3 + ,5 + ,4 + ,4 + ,4 + ,2 + ,2 + ,5 + ,2 + ,5 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,3 + ,4 + ,2 + ,2 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,5 + ,3 + ,3 + ,3 + ,4 + ,4 + ,2 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,5 + ,3 + ,4 + ,1 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,1 + ,1 + ,4 + ,1 + ,5 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,5 + ,3 + ,2 + ,4 + ,2 + ,3 + ,3 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,5 + ,4 + ,3 + ,3 + ,3 + ,2 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,1 + ,4 + ,3 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,2 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,2 + ,4 + ,3 + ,3 + ,4 + ,3 + ,5 + ,2 + ,2 + ,4 + ,3 + ,2 + ,4 + ,3 + ,2 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,2 + ,4 + ,3 + ,4 + ,5 + ,1 + ,3 + ,2 + ,2 + ,3 + ,2 + ,4 + ,2 + ,4 + ,4 + ,2 + ,2 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,3 + ,4 + ,5 + ,5 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,1 + ,3 + ,1 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,1 + ,3 + ,5 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,3 + ,2 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,1 + ,1 + ,3 + ,1 + ,1 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,4 + ,4 + ,4 + ,4 + ,5 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,4 + ,3 + ,2 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,3 + ,3) + ,dim=c(5 + ,151) + ,dimnames=list(c('SocialVisible' + ,'ManyFriends' + ,'MakeNewFriends' + ,'QuiteAccepted' + ,'IntendMakeNewFriends') + ,1:151)) > y <- array(NA,dim=c(5,151),dimnames=list(c('SocialVisible','ManyFriends','MakeNewFriends','QuiteAccepted','IntendMakeNewFriends'),1:151)) > 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 = '1' > #'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.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 SocialVisible ManyFriends MakeNewFriends QuiteAccepted IntendMakeNewFriends 1 3 3 4 4 4 2 4 3 4 3 4 3 4 4 3 4 3 4 3 3 4 3 2 5 2 2 3 3 3 6 2 3 4 4 4 7 5 4 4 4 5 8 3 2 4 3 4 9 2 3 4 4 4 10 2 4 2 3 2 11 4 3 2 4 2 12 3 3 4 3 4 13 3 4 4 4 4 14 4 2 4 3 5 15 4 2 4 3 5 16 2 3 3 4 4 17 3 2 4 3 3 18 4 4 4 4 4 19 2 2 3 3 4 20 2 1 2 3 2 21 3 3 2 4 4 22 4 4 4 4 4 23 2 2 3 3 4 24 2 3 4 3 4 25 3 3 4 4 4 26 4 4 3 4 4 27 4 3 3 4 4 28 3 3 2 4 3 29 3 4 3 4 3 30 4 4 4 4 4 31 2 4 3 2 3 32 3 3 3 4 4 33 4 4 4 4 4 34 2 2 4 3 4 35 4 4 3 4 4 36 4 3 4 4 4 37 2 2 2 3 3 38 3 4 3 4 4 39 4 4 4 4 4 40 4 4 4 3 4 41 3 4 3 4 3 42 4 2 5 3 5 43 3 2 3 3 4 44 3 3 3 3 4 45 3 4 4 3 4 46 3 5 4 4 4 47 2 2 5 2 5 48 4 3 3 3 4 49 4 3 4 4 4 50 4 2 4 3 4 51 2 2 2 3 3 52 3 3 4 4 4 53 3 2 4 3 4 54 3 4 4 4 5 55 3 3 3 4 4 56 2 3 3 4 3 57 4 4 3 5 3 58 4 1 2 4 4 59 4 4 4 4 4 60 3 2 4 3 4 61 4 4 4 3 4 62 3 4 3 3 3 63 4 4 4 4 3 64 3 2 3 3 3 65 3 4 4 4 4 66 3 2 4 3 4 67 3 4 4 3 4 68 4 4 4 3 4 69 1 1 4 1 5 70 4 4 4 4 3 71 4 4 4 4 4 72 3 3 4 4 3 73 5 3 2 4 2 74 3 3 3 4 4 75 3 3 4 4 4 76 3 3 4 3 5 77 4 3 3 3 2 78 4 4 4 3 4 79 3 1 4 3 4 80 3 3 4 4 4 81 4 3 3 4 4 82 2 3 3 4 3 83 4 4 3 2 4 84 3 3 4 3 5 85 2 2 4 3 2 86 4 3 2 4 2 87 4 4 4 4 4 88 3 3 3 4 4 89 4 4 4 4 3 90 4 3 3 4 4 91 4 4 4 4 4 92 3 4 3 4 4 93 3 3 3 3 4 94 4 2 4 3 4 95 5 1 3 2 2 96 3 2 4 2 4 97 4 2 2 4 4 98 4 3 4 3 4 99 4 4 4 4 4 100 4 4 4 4 4 101 5 3 4 5 5 102 4 3 4 3 4 103 3 1 3 1 4 104 4 3 4 4 4 105 4 3 3 3 3 106 4 4 4 4 4 107 4 2 3 4 4 108 4 3 3 4 4 109 3 3 2 4 3 110 4 3 4 3 4 111 4 4 4 4 4 112 4 4 4 4 4 113 4 4 1 3 5 114 4 4 4 3 4 115 4 2 4 4 4 116 4 3 4 4 4 117 3 4 3 3 4 118 4 3 4 3 4 119 3 4 4 3 4 120 3 2 3 4 4 121 4 4 4 4 4 122 4 4 4 3 4 123 4 3 4 3 4 124 4 4 4 4 4 125 3 3 4 4 4 126 3 3 3 4 3 127 1 1 3 1 1 128 4 4 4 4 4 129 3 4 4 4 4 130 4 2 4 4 4 131 4 3 4 4 4 132 3 4 4 4 4 133 4 3 4 4 4 134 4 4 4 4 4 135 2 2 4 4 4 136 4 5 4 4 4 137 3 3 3 4 3 138 3 4 3 4 4 139 4 3 4 4 4 140 4 4 4 4 4 141 3 3 4 4 4 142 3 3 4 4 4 143 3 2 4 4 4 144 4 4 4 4 4 145 4 4 4 4 4 146 3 3 4 4 4 147 4 4 4 5 4 148 3 2 4 3 3 149 4 4 4 4 3 150 4 4 4 3 4 151 4 3 4 3 3 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) ManyFriends MakeNewFriends 1.12352 0.20501 0.08583 QuiteAccepted IntendMakeNewFriends 0.25852 0.10774 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.5469 -0.5469 0.1831 0.5066 2.6815 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.12352 0.46038 2.440 0.01587 * ManyFriends 0.20501 0.07435 2.757 0.00658 ** MakeNewFriends 0.08583 0.09535 0.900 0.36950 QuiteAccepted 0.25852 0.09539 2.710 0.00753 ** IntendMakeNewFriends 0.10774 0.09353 1.152 0.25124 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.7132 on 146 degrees of freedom Multiple R-squared: 0.1924, Adjusted R-squared: 0.1703 F-statistic: 8.696 on 4 and 146 DF, p-value: 2.528e-06 > 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,] 0.3480496 0.696099200 0.651950400 [2,] 0.3060334 0.612066728 0.693966636 [3,] 0.8321745 0.335650907 0.167825454 [4,] 0.9899611 0.020077851 0.010038925 [5,] 0.9813365 0.037327013 0.018663507 [6,] 0.9765606 0.046878867 0.023439434 [7,] 0.9744364 0.051127178 0.025563589 [8,] 0.9659725 0.068055069 0.034027534 [9,] 0.9850168 0.029966412 0.014983206 [10,] 0.9777360 0.044527933 0.022263967 [11,] 0.9702803 0.059439439 0.029719720 [12,] 0.9745103 0.050979469 0.025489734 [13,] 0.9650809 0.069838160 0.034919080 [14,] 0.9498845 0.100230918 0.050115459 [15,] 0.9343554 0.131289192 0.065644596 [16,] 0.9387001 0.122599857 0.061299928 [17,] 0.9659009 0.068198150 0.034099075 [18,] 0.9544861 0.091027827 0.045513913 [19,] 0.9440711 0.111857787 0.055928893 [20,] 0.9443985 0.111203054 0.055601527 [21,] 0.9263480 0.147304084 0.073652042 [22,] 0.9102584 0.179483266 0.089741633 [23,] 0.8885852 0.222829594 0.111414797 [24,] 0.8989986 0.202002858 0.101001429 [25,] 0.8772705 0.245459076 0.122729538 [26,] 0.8510853 0.297829421 0.148914710 [27,] 0.8634188 0.273162479 0.136581239 [28,] 0.8394697 0.321060569 0.160530285 [29,] 0.8240389 0.351922243 0.175961121 [30,] 0.8113753 0.377249415 0.188624708 [31,] 0.8024941 0.395011817 0.197505909 [32,] 0.7676607 0.464678585 0.232339292 [33,] 0.7566690 0.486662016 0.243331008 [34,] 0.7335033 0.532993338 0.266496669 [35,] 0.7442942 0.511411572 0.255705786 [36,] 0.7091056 0.581788823 0.290894412 [37,] 0.6660780 0.667843909 0.333921954 [38,] 0.6365980 0.726803929 0.363401964 [39,] 0.6783443 0.643311392 0.321655696 [40,] 0.7028727 0.594254555 0.297127278 [41,] 0.7428847 0.514230550 0.257115275 [42,] 0.7225722 0.554855581 0.277427791 [43,] 0.7715800 0.456839967 0.228419984 [44,] 0.7769778 0.446044320 0.223022160 [45,] 0.7594721 0.481055779 0.240527890 [46,] 0.7200719 0.559856278 0.279928139 [47,] 0.7436103 0.512779392 0.256389696 [48,] 0.7199435 0.560112912 0.280056456 [49,] 0.8135396 0.372920804 0.186460402 [50,] 0.7871570 0.425686096 0.212843048 [51,] 0.8212413 0.357517457 0.178758729 [52,] 0.7949190 0.410162044 0.205081022 [53,] 0.7594650 0.481070093 0.240535047 [54,] 0.7562191 0.487561893 0.243780947 [55,] 0.7348865 0.530226961 0.265113481 [56,] 0.7134585 0.573082916 0.286541458 [57,] 0.6835481 0.632903732 0.316451866 [58,] 0.6887494 0.622501221 0.311250611 [59,] 0.6458180 0.708364025 0.354182013 [60,] 0.6213173 0.757365339 0.378682669 [61,] 0.6108570 0.778286092 0.389143046 [62,] 0.7484099 0.503180139 0.251590070 [63,] 0.7223540 0.555291912 0.277645956 [64,] 0.6863187 0.627362617 0.313681308 [65,] 0.6613459 0.677308173 0.338654087 [66,] 0.8767309 0.246538231 0.123269115 [67,] 0.8659036 0.268192785 0.134096393 [68,] 0.8588129 0.282374186 0.141187093 [69,] 0.8504911 0.299017812 0.149508906 [70,] 0.8861459 0.227708228 0.113854114 [71,] 0.8766247 0.246750602 0.123375301 [72,] 0.8551354 0.289729236 0.144864618 [73,] 0.8494207 0.301158626 0.150579313 [74,] 0.8358197 0.328360627 0.164180314 [75,] 0.9094512 0.181097652 0.090548826 [76,] 0.9170463 0.165907457 0.082953728 [77,] 0.9159142 0.168171637 0.084085818 [78,] 0.9310704 0.137859262 0.068929631 [79,] 0.9433080 0.113384048 0.056692024 [80,] 0.9298073 0.140385438 0.070192719 [81,] 0.9243835 0.151232955 0.075616477 [82,] 0.9138310 0.172338037 0.086169019 [83,] 0.9032053 0.193589394 0.096794697 [84,] 0.8829098 0.234180414 0.117090207 [85,] 0.8843439 0.231312187 0.115656093 [86,] 0.8725370 0.254926001 0.127463001 [87,] 0.8768394 0.246321222 0.123160611 [88,] 0.9989173 0.002165448 0.001082724 [89,] 0.9985468 0.002906308 0.001453154 [90,] 0.9987837 0.002432691 0.001216346 [91,] 0.9985296 0.002940748 0.001470374 [92,] 0.9978257 0.004348691 0.002174346 [93,] 0.9968198 0.006360453 0.003180227 [94,] 0.9978507 0.004298575 0.002149288 [95,] 0.9974208 0.005158416 0.002579208 [96,] 0.9965291 0.006941742 0.003470871 [97,] 0.9954770 0.009045978 0.004522989 [98,] 0.9974215 0.005157051 0.002578526 [99,] 0.9961834 0.007633209 0.003816605 [100,] 0.9969321 0.006135833 0.003067917 [101,] 0.9968198 0.006360411 0.003180206 [102,] 0.9956528 0.008694362 0.004347181 [103,] 0.9947915 0.010417081 0.005208540 [104,] 0.9923589 0.015282285 0.007641143 [105,] 0.9889551 0.022089817 0.011044909 [106,] 0.9934985 0.013003046 0.006501523 [107,] 0.9910586 0.017882764 0.008941382 [108,] 0.9919578 0.016084342 0.008042171 [109,] 0.9902340 0.019531926 0.009765963 [110,] 0.9857718 0.028456482 0.014228241 [111,] 0.9856365 0.028727010 0.014363505 [112,] 0.9876843 0.024631481 0.012315740 [113,] 0.9858195 0.028361084 0.014180542 [114,] 0.9788716 0.042256732 0.021128366 [115,] 0.9704468 0.059106402 0.029553201 [116,] 0.9736754 0.052649228 0.026324614 [117,] 0.9619255 0.076148903 0.038074452 [118,] 0.9543229 0.091354194 0.045677097 [119,] 0.9387402 0.122519667 0.061259834 [120,] 0.9539656 0.092068743 0.046034371 [121,] 0.9350753 0.129849358 0.064924679 [122,] 0.9492967 0.101406591 0.050703296 [123,] 0.9791763 0.041647414 0.020823707 [124,] 0.9830825 0.033834977 0.016917488 [125,] 0.9923796 0.015240823 0.007620411 [126,] 0.9956637 0.008672572 0.004336286 [127,] 0.9916483 0.016703472 0.008351736 [128,] 0.9972084 0.005583107 0.002791553 [129,] 0.9963169 0.007366123 0.003683061 [130,] 0.9925685 0.014863012 0.007431506 [131,] 0.9832995 0.033400988 0.016700494 [132,] 0.9936348 0.012730354 0.006365177 [133,] 0.9836183 0.032763395 0.016381697 [134,] 0.9710883 0.057823470 0.028911735 [135,] 0.9567076 0.086584811 0.043292405 [136,] 0.9167595 0.166481045 0.083240522 > postscript(file="/var/www/html/freestat/rcomp/tmp/138521291302421.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2e0n51291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3e0n51291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4e0n51291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/56rmq1291302421.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 = 151 Frequency = 1 1 2 3 4 5 6 -0.546912916 0.711611392 0.441651049 -0.072914811 -0.889812344 -1.546912916 7 8 9 10 11 12 1.140344037 -0.083382458 -1.546912916 -1.106254528 0.840227313 -0.288388608 13 14 15 16 17 18 -0.751919065 0.808880644 0.808880644 -1.461079700 0.024354440 0.248080935 19 20 21 22 23 24 -0.997549242 -0.491236080 -0.375246483 0.248080935 -0.997549242 -1.288388608 25 26 27 28 29 30 -0.546912916 0.333914151 0.538920300 -0.267509585 -0.558348951 0.248080935 31 32 33 34 35 36 -1.041300334 -0.461079700 0.248080935 -1.083382458 0.333914151 0.453087084 37 38 39 40 41 42 -0.803979127 -0.666085849 0.248080935 0.506605243 -0.558348951 0.723047427 43 44 45 46 47 48 0.002450758 -0.202555391 -0.493394757 -0.956925215 -1.018428264 0.797444609 49 50 51 52 53 54 0.453087084 0.916617542 -0.803979127 -0.546912916 -0.083382458 -0.859655963 55 56 57 58 59 60 -0.461079700 -1.353342801 0.183126741 1.034765816 0.248080935 -0.083382458 61 62 63 64 65 66 0.506605243 -0.299824643 0.355817833 0.110187656 -0.751919065 -0.083382458 67 68 69 70 71 72 -0.493394757 0.506605243 -1.469064590 0.355817833 0.248080935 -0.439176018 73 74 75 76 77 78 1.840227313 -0.461079700 -0.546912916 -0.396125506 1.012918405 0.506605243 79 80 81 82 83 84 0.121623691 -0.546912916 0.538920300 -1.353342801 0.850962767 -0.396125506 85 86 87 88 89 90 -0.867908662 0.840227313 0.248080935 -0.461079700 0.355817833 0.538920300 91 92 93 94 95 96 0.248080935 -0.666085849 -0.202555391 0.916617542 2.681455012 0.175141850 97 98 99 100 101 102 0.829759666 0.711611392 0.248080935 0.248080935 1.086825878 0.711611392 103 104 105 106 107 108 0.724505524 0.453087084 0.905181507 0.248080935 0.743926450 0.538920300 109 110 111 112 113 114 -0.267509585 0.711611392 0.248080935 0.248080935 0.656367994 0.506605243 115 116 117 118 119 120 0.658093234 0.453087084 -0.407561541 0.711611392 -0.493394757 -0.256073550 121 122 123 124 125 126 0.248080935 0.506605243 0.711611392 0.248080935 -0.546912916 -0.353342801 127 128 129 130 131 132 -0.952283781 0.248080935 -0.751919065 0.658093234 0.453087084 -0.751919065 133 134 135 136 137 138 0.453087084 0.248080935 -1.341906766 0.043074785 -0.353342801 -0.666085849 139 140 141 142 143 144 0.453087084 0.248080935 -0.546912916 -0.546912916 -0.341906766 0.248080935 145 146 147 148 149 150 0.248080935 -0.546912916 -0.010443373 0.024354440 0.355817833 0.506605243 151 0.819348291 > postscript(file="/var/www/html/freestat/rcomp/tmp/66rmq1291302421.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 = 151 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.546912916 NA 1 0.711611392 -0.546912916 2 0.441651049 0.711611392 3 -0.072914811 0.441651049 4 -0.889812344 -0.072914811 5 -1.546912916 -0.889812344 6 1.140344037 -1.546912916 7 -0.083382458 1.140344037 8 -1.546912916 -0.083382458 9 -1.106254528 -1.546912916 10 0.840227313 -1.106254528 11 -0.288388608 0.840227313 12 -0.751919065 -0.288388608 13 0.808880644 -0.751919065 14 0.808880644 0.808880644 15 -1.461079700 0.808880644 16 0.024354440 -1.461079700 17 0.248080935 0.024354440 18 -0.997549242 0.248080935 19 -0.491236080 -0.997549242 20 -0.375246483 -0.491236080 21 0.248080935 -0.375246483 22 -0.997549242 0.248080935 23 -1.288388608 -0.997549242 24 -0.546912916 -1.288388608 25 0.333914151 -0.546912916 26 0.538920300 0.333914151 27 -0.267509585 0.538920300 28 -0.558348951 -0.267509585 29 0.248080935 -0.558348951 30 -1.041300334 0.248080935 31 -0.461079700 -1.041300334 32 0.248080935 -0.461079700 33 -1.083382458 0.248080935 34 0.333914151 -1.083382458 35 0.453087084 0.333914151 36 -0.803979127 0.453087084 37 -0.666085849 -0.803979127 38 0.248080935 -0.666085849 39 0.506605243 0.248080935 40 -0.558348951 0.506605243 41 0.723047427 -0.558348951 42 0.002450758 0.723047427 43 -0.202555391 0.002450758 44 -0.493394757 -0.202555391 45 -0.956925215 -0.493394757 46 -1.018428264 -0.956925215 47 0.797444609 -1.018428264 48 0.453087084 0.797444609 49 0.916617542 0.453087084 50 -0.803979127 0.916617542 51 -0.546912916 -0.803979127 52 -0.083382458 -0.546912916 53 -0.859655963 -0.083382458 54 -0.461079700 -0.859655963 55 -1.353342801 -0.461079700 56 0.183126741 -1.353342801 57 1.034765816 0.183126741 58 0.248080935 1.034765816 59 -0.083382458 0.248080935 60 0.506605243 -0.083382458 61 -0.299824643 0.506605243 62 0.355817833 -0.299824643 63 0.110187656 0.355817833 64 -0.751919065 0.110187656 65 -0.083382458 -0.751919065 66 -0.493394757 -0.083382458 67 0.506605243 -0.493394757 68 -1.469064590 0.506605243 69 0.355817833 -1.469064590 70 0.248080935 0.355817833 71 -0.439176018 0.248080935 72 1.840227313 -0.439176018 73 -0.461079700 1.840227313 74 -0.546912916 -0.461079700 75 -0.396125506 -0.546912916 76 1.012918405 -0.396125506 77 0.506605243 1.012918405 78 0.121623691 0.506605243 79 -0.546912916 0.121623691 80 0.538920300 -0.546912916 81 -1.353342801 0.538920300 82 0.850962767 -1.353342801 83 -0.396125506 0.850962767 84 -0.867908662 -0.396125506 85 0.840227313 -0.867908662 86 0.248080935 0.840227313 87 -0.461079700 0.248080935 88 0.355817833 -0.461079700 89 0.538920300 0.355817833 90 0.248080935 0.538920300 91 -0.666085849 0.248080935 92 -0.202555391 -0.666085849 93 0.916617542 -0.202555391 94 2.681455012 0.916617542 95 0.175141850 2.681455012 96 0.829759666 0.175141850 97 0.711611392 0.829759666 98 0.248080935 0.711611392 99 0.248080935 0.248080935 100 1.086825878 0.248080935 101 0.711611392 1.086825878 102 0.724505524 0.711611392 103 0.453087084 0.724505524 104 0.905181507 0.453087084 105 0.248080935 0.905181507 106 0.743926450 0.248080935 107 0.538920300 0.743926450 108 -0.267509585 0.538920300 109 0.711611392 -0.267509585 110 0.248080935 0.711611392 111 0.248080935 0.248080935 112 0.656367994 0.248080935 113 0.506605243 0.656367994 114 0.658093234 0.506605243 115 0.453087084 0.658093234 116 -0.407561541 0.453087084 117 0.711611392 -0.407561541 118 -0.493394757 0.711611392 119 -0.256073550 -0.493394757 120 0.248080935 -0.256073550 121 0.506605243 0.248080935 122 0.711611392 0.506605243 123 0.248080935 0.711611392 124 -0.546912916 0.248080935 125 -0.353342801 -0.546912916 126 -0.952283781 -0.353342801 127 0.248080935 -0.952283781 128 -0.751919065 0.248080935 129 0.658093234 -0.751919065 130 0.453087084 0.658093234 131 -0.751919065 0.453087084 132 0.453087084 -0.751919065 133 0.248080935 0.453087084 134 -1.341906766 0.248080935 135 0.043074785 -1.341906766 136 -0.353342801 0.043074785 137 -0.666085849 -0.353342801 138 0.453087084 -0.666085849 139 0.248080935 0.453087084 140 -0.546912916 0.248080935 141 -0.546912916 -0.546912916 142 -0.341906766 -0.546912916 143 0.248080935 -0.341906766 144 0.248080935 0.248080935 145 -0.546912916 0.248080935 146 -0.010443373 -0.546912916 147 0.024354440 -0.010443373 148 0.355817833 0.024354440 149 0.506605243 0.355817833 150 0.819348291 0.506605243 151 NA 0.819348291 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.711611392 -0.546912916 [2,] 0.441651049 0.711611392 [3,] -0.072914811 0.441651049 [4,] -0.889812344 -0.072914811 [5,] -1.546912916 -0.889812344 [6,] 1.140344037 -1.546912916 [7,] -0.083382458 1.140344037 [8,] -1.546912916 -0.083382458 [9,] -1.106254528 -1.546912916 [10,] 0.840227313 -1.106254528 [11,] -0.288388608 0.840227313 [12,] -0.751919065 -0.288388608 [13,] 0.808880644 -0.751919065 [14,] 0.808880644 0.808880644 [15,] -1.461079700 0.808880644 [16,] 0.024354440 -1.461079700 [17,] 0.248080935 0.024354440 [18,] -0.997549242 0.248080935 [19,] -0.491236080 -0.997549242 [20,] -0.375246483 -0.491236080 [21,] 0.248080935 -0.375246483 [22,] -0.997549242 0.248080935 [23,] -1.288388608 -0.997549242 [24,] -0.546912916 -1.288388608 [25,] 0.333914151 -0.546912916 [26,] 0.538920300 0.333914151 [27,] -0.267509585 0.538920300 [28,] -0.558348951 -0.267509585 [29,] 0.248080935 -0.558348951 [30,] -1.041300334 0.248080935 [31,] -0.461079700 -1.041300334 [32,] 0.248080935 -0.461079700 [33,] -1.083382458 0.248080935 [34,] 0.333914151 -1.083382458 [35,] 0.453087084 0.333914151 [36,] -0.803979127 0.453087084 [37,] -0.666085849 -0.803979127 [38,] 0.248080935 -0.666085849 [39,] 0.506605243 0.248080935 [40,] -0.558348951 0.506605243 [41,] 0.723047427 -0.558348951 [42,] 0.002450758 0.723047427 [43,] -0.202555391 0.002450758 [44,] -0.493394757 -0.202555391 [45,] -0.956925215 -0.493394757 [46,] -1.018428264 -0.956925215 [47,] 0.797444609 -1.018428264 [48,] 0.453087084 0.797444609 [49,] 0.916617542 0.453087084 [50,] -0.803979127 0.916617542 [51,] -0.546912916 -0.803979127 [52,] -0.083382458 -0.546912916 [53,] -0.859655963 -0.083382458 [54,] -0.461079700 -0.859655963 [55,] -1.353342801 -0.461079700 [56,] 0.183126741 -1.353342801 [57,] 1.034765816 0.183126741 [58,] 0.248080935 1.034765816 [59,] -0.083382458 0.248080935 [60,] 0.506605243 -0.083382458 [61,] -0.299824643 0.506605243 [62,] 0.355817833 -0.299824643 [63,] 0.110187656 0.355817833 [64,] -0.751919065 0.110187656 [65,] -0.083382458 -0.751919065 [66,] -0.493394757 -0.083382458 [67,] 0.506605243 -0.493394757 [68,] -1.469064590 0.506605243 [69,] 0.355817833 -1.469064590 [70,] 0.248080935 0.355817833 [71,] -0.439176018 0.248080935 [72,] 1.840227313 -0.439176018 [73,] -0.461079700 1.840227313 [74,] -0.546912916 -0.461079700 [75,] -0.396125506 -0.546912916 [76,] 1.012918405 -0.396125506 [77,] 0.506605243 1.012918405 [78,] 0.121623691 0.506605243 [79,] -0.546912916 0.121623691 [80,] 0.538920300 -0.546912916 [81,] -1.353342801 0.538920300 [82,] 0.850962767 -1.353342801 [83,] -0.396125506 0.850962767 [84,] -0.867908662 -0.396125506 [85,] 0.840227313 -0.867908662 [86,] 0.248080935 0.840227313 [87,] -0.461079700 0.248080935 [88,] 0.355817833 -0.461079700 [89,] 0.538920300 0.355817833 [90,] 0.248080935 0.538920300 [91,] -0.666085849 0.248080935 [92,] -0.202555391 -0.666085849 [93,] 0.916617542 -0.202555391 [94,] 2.681455012 0.916617542 [95,] 0.175141850 2.681455012 [96,] 0.829759666 0.175141850 [97,] 0.711611392 0.829759666 [98,] 0.248080935 0.711611392 [99,] 0.248080935 0.248080935 [100,] 1.086825878 0.248080935 [101,] 0.711611392 1.086825878 [102,] 0.724505524 0.711611392 [103,] 0.453087084 0.724505524 [104,] 0.905181507 0.453087084 [105,] 0.248080935 0.905181507 [106,] 0.743926450 0.248080935 [107,] 0.538920300 0.743926450 [108,] -0.267509585 0.538920300 [109,] 0.711611392 -0.267509585 [110,] 0.248080935 0.711611392 [111,] 0.248080935 0.248080935 [112,] 0.656367994 0.248080935 [113,] 0.506605243 0.656367994 [114,] 0.658093234 0.506605243 [115,] 0.453087084 0.658093234 [116,] -0.407561541 0.453087084 [117,] 0.711611392 -0.407561541 [118,] -0.493394757 0.711611392 [119,] -0.256073550 -0.493394757 [120,] 0.248080935 -0.256073550 [121,] 0.506605243 0.248080935 [122,] 0.711611392 0.506605243 [123,] 0.248080935 0.711611392 [124,] -0.546912916 0.248080935 [125,] -0.353342801 -0.546912916 [126,] -0.952283781 -0.353342801 [127,] 0.248080935 -0.952283781 [128,] -0.751919065 0.248080935 [129,] 0.658093234 -0.751919065 [130,] 0.453087084 0.658093234 [131,] -0.751919065 0.453087084 [132,] 0.453087084 -0.751919065 [133,] 0.248080935 0.453087084 [134,] -1.341906766 0.248080935 [135,] 0.043074785 -1.341906766 [136,] -0.353342801 0.043074785 [137,] -0.666085849 -0.353342801 [138,] 0.453087084 -0.666085849 [139,] 0.248080935 0.453087084 [140,] -0.546912916 0.248080935 [141,] -0.546912916 -0.546912916 [142,] -0.341906766 -0.546912916 [143,] 0.248080935 -0.341906766 [144,] 0.248080935 0.248080935 [145,] -0.546912916 0.248080935 [146,] -0.010443373 -0.546912916 [147,] 0.024354440 -0.010443373 [148,] 0.355817833 0.024354440 [149,] 0.506605243 0.355817833 [150,] 0.819348291 0.506605243 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.711611392 -0.546912916 2 0.441651049 0.711611392 3 -0.072914811 0.441651049 4 -0.889812344 -0.072914811 5 -1.546912916 -0.889812344 6 1.140344037 -1.546912916 7 -0.083382458 1.140344037 8 -1.546912916 -0.083382458 9 -1.106254528 -1.546912916 10 0.840227313 -1.106254528 11 -0.288388608 0.840227313 12 -0.751919065 -0.288388608 13 0.808880644 -0.751919065 14 0.808880644 0.808880644 15 -1.461079700 0.808880644 16 0.024354440 -1.461079700 17 0.248080935 0.024354440 18 -0.997549242 0.248080935 19 -0.491236080 -0.997549242 20 -0.375246483 -0.491236080 21 0.248080935 -0.375246483 22 -0.997549242 0.248080935 23 -1.288388608 -0.997549242 24 -0.546912916 -1.288388608 25 0.333914151 -0.546912916 26 0.538920300 0.333914151 27 -0.267509585 0.538920300 28 -0.558348951 -0.267509585 29 0.248080935 -0.558348951 30 -1.041300334 0.248080935 31 -0.461079700 -1.041300334 32 0.248080935 -0.461079700 33 -1.083382458 0.248080935 34 0.333914151 -1.083382458 35 0.453087084 0.333914151 36 -0.803979127 0.453087084 37 -0.666085849 -0.803979127 38 0.248080935 -0.666085849 39 0.506605243 0.248080935 40 -0.558348951 0.506605243 41 0.723047427 -0.558348951 42 0.002450758 0.723047427 43 -0.202555391 0.002450758 44 -0.493394757 -0.202555391 45 -0.956925215 -0.493394757 46 -1.018428264 -0.956925215 47 0.797444609 -1.018428264 48 0.453087084 0.797444609 49 0.916617542 0.453087084 50 -0.803979127 0.916617542 51 -0.546912916 -0.803979127 52 -0.083382458 -0.546912916 53 -0.859655963 -0.083382458 54 -0.461079700 -0.859655963 55 -1.353342801 -0.461079700 56 0.183126741 -1.353342801 57 1.034765816 0.183126741 58 0.248080935 1.034765816 59 -0.083382458 0.248080935 60 0.506605243 -0.083382458 61 -0.299824643 0.506605243 62 0.355817833 -0.299824643 63 0.110187656 0.355817833 64 -0.751919065 0.110187656 65 -0.083382458 -0.751919065 66 -0.493394757 -0.083382458 67 0.506605243 -0.493394757 68 -1.469064590 0.506605243 69 0.355817833 -1.469064590 70 0.248080935 0.355817833 71 -0.439176018 0.248080935 72 1.840227313 -0.439176018 73 -0.461079700 1.840227313 74 -0.546912916 -0.461079700 75 -0.396125506 -0.546912916 76 1.012918405 -0.396125506 77 0.506605243 1.012918405 78 0.121623691 0.506605243 79 -0.546912916 0.121623691 80 0.538920300 -0.546912916 81 -1.353342801 0.538920300 82 0.850962767 -1.353342801 83 -0.396125506 0.850962767 84 -0.867908662 -0.396125506 85 0.840227313 -0.867908662 86 0.248080935 0.840227313 87 -0.461079700 0.248080935 88 0.355817833 -0.461079700 89 0.538920300 0.355817833 90 0.248080935 0.538920300 91 -0.666085849 0.248080935 92 -0.202555391 -0.666085849 93 0.916617542 -0.202555391 94 2.681455012 0.916617542 95 0.175141850 2.681455012 96 0.829759666 0.175141850 97 0.711611392 0.829759666 98 0.248080935 0.711611392 99 0.248080935 0.248080935 100 1.086825878 0.248080935 101 0.711611392 1.086825878 102 0.724505524 0.711611392 103 0.453087084 0.724505524 104 0.905181507 0.453087084 105 0.248080935 0.905181507 106 0.743926450 0.248080935 107 0.538920300 0.743926450 108 -0.267509585 0.538920300 109 0.711611392 -0.267509585 110 0.248080935 0.711611392 111 0.248080935 0.248080935 112 0.656367994 0.248080935 113 0.506605243 0.656367994 114 0.658093234 0.506605243 115 0.453087084 0.658093234 116 -0.407561541 0.453087084 117 0.711611392 -0.407561541 118 -0.493394757 0.711611392 119 -0.256073550 -0.493394757 120 0.248080935 -0.256073550 121 0.506605243 0.248080935 122 0.711611392 0.506605243 123 0.248080935 0.711611392 124 -0.546912916 0.248080935 125 -0.353342801 -0.546912916 126 -0.952283781 -0.353342801 127 0.248080935 -0.952283781 128 -0.751919065 0.248080935 129 0.658093234 -0.751919065 130 0.453087084 0.658093234 131 -0.751919065 0.453087084 132 0.453087084 -0.751919065 133 0.248080935 0.453087084 134 -1.341906766 0.248080935 135 0.043074785 -1.341906766 136 -0.353342801 0.043074785 137 -0.666085849 -0.353342801 138 0.453087084 -0.666085849 139 0.248080935 0.453087084 140 -0.546912916 0.248080935 141 -0.546912916 -0.546912916 142 -0.341906766 -0.546912916 143 0.248080935 -0.341906766 144 0.248080935 0.248080935 145 -0.546912916 0.248080935 146 -0.010443373 -0.546912916 147 0.024354440 -0.010443373 148 0.355817833 0.024354440 149 0.506605243 0.355817833 150 0.819348291 0.506605243 > 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/www/html/freestat/rcomp/tmp/7zi3t1291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8zi3t1291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9zi3t1291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10a92e1291302421.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/www/html/freestat/rcomp/tmp/11ds1k1291302421.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/www/html/freestat/rcomp/tmp/12zsz81291302421.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/www/html/freestat/rcomp/tmp/135bw11291302421.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/www/html/freestat/rcomp/tmp/14ylwm1291302421.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/www/html/freestat/rcomp/tmp/1513ca1291302421.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/www/html/freestat/rcomp/tmp/16gvs11291302421.tab") + } > > try(system("convert tmp/138521291302421.ps tmp/138521291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/2e0n51291302421.ps tmp/2e0n51291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/3e0n51291302421.ps tmp/3e0n51291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/4e0n51291302421.ps tmp/4e0n51291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/56rmq1291302421.ps tmp/56rmq1291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/66rmq1291302421.ps tmp/66rmq1291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/7zi3t1291302421.ps tmp/7zi3t1291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/8zi3t1291302421.ps tmp/8zi3t1291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/9zi3t1291302421.ps tmp/9zi3t1291302421.png",intern=TRUE)) character(0) > try(system("convert tmp/10a92e1291302421.ps tmp/10a92e1291302421.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.324 2.582 5.871