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(7 + ,5 + ,1 + ,6 + ,5 + ,7 + ,5 + ,2 + ,1 + ,6 + ,2 + ,3 + ,5 + ,6 + ,3 + ,6 + ,6 + ,3 + ,5 + ,6 + ,2 + ,4 + ,4 + ,6 + ,8 + ,6 + ,3 + ,2 + ,6 + ,2 + ,6 + ,5 + ,2 + ,7 + ,3 + ,3 + ,6 + ,5 + ,2 + ,6 + ,5 + ,1 + ,4 + ,6 + ,2 + ,5 + ,3 + ,2 + ,5 + ,6 + ,4 + ,6 + ,5 + ,5 + ,5 + ,5 + ,4 + ,7 + ,4 + ,1 + ,5 + ,5 + ,1 + ,7 + ,1 + ,6 + ,6 + ,5 + ,2 + ,4 + ,6 + ,1 + ,7 + ,6 + ,1 + ,1 + ,6 + ,1 + ,7 + ,5 + ,3 + ,6 + ,6 + ,2 + ,6 + ,5 + ,2 + ,4 + ,4 + ,1 + ,7 + ,6 + ,5 + ,5 + ,6 + ,3 + ,7 + ,6 + ,2 + ,5 + ,5 + ,2 + ,5 + ,4 + ,5 + ,6 + ,3 + ,2 + ,8 + ,5 + ,4 + ,4 + ,5 + ,2 + ,7 + ,5 + ,2 + ,6 + ,4 + ,2 + ,5 + ,5 + ,2 + ,3 + ,5 + ,2 + ,7 + ,6 + ,5 + ,3 + ,6 + ,2 + ,5 + ,5 + ,1 + ,5 + ,3 + ,1 + ,10 + ,7 + ,4 + ,5 + ,4 + ,3 + ,5 + ,6 + ,1 + ,5 + ,5 + ,2 + ,4 + ,6 + ,3 + ,5 + ,4 + ,3 + ,4 + ,6 + ,2 + ,5 + ,5 + ,4 + ,5 + ,6 + ,2 + ,2 + ,6 + ,5 + ,5 + ,4 + ,1 + ,6 + ,7 + ,2 + ,6 + ,5 + ,3 + ,7 + ,2 + ,5 + ,5 + ,6 + ,4 + ,2 + ,4 + ,5 + ,5 + ,4 + ,3 + ,3 + ,6 + ,1 + 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,dimnames=list(c('Age' + ,'Use_hands' + ,'Hand_on_hips' + ,'Quiet_FirstMeeting' + ,'Outgoing_individual' + ,'Cry_Sad') + ,1:164)) > y <- array(NA,dim=c(6,164),dimnames=list(c('Age','Use_hands','Hand_on_hips','Quiet_FirstMeeting','Outgoing_individual','Cry_Sad'),1:164)) > 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' > #'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 Cry_Sad Age Use_hands Hand_on_hips Quiet_FirstMeeting Outgoing_individual 1 7 7 5 1 6 5 2 3 5 2 1 6 2 3 3 5 6 3 6 6 4 6 5 6 2 4 4 5 2 8 6 3 2 6 6 3 6 5 2 7 3 7 1 6 5 2 6 5 8 2 4 6 2 5 3 9 5 5 6 4 6 5 10 1 5 5 4 7 4 11 6 5 5 1 7 1 12 1 6 5 2 4 6 13 1 7 6 1 1 6 14 2 7 5 3 6 6 15 1 6 5 2 4 4 16 3 7 6 5 5 6 17 2 7 6 2 5 5 18 2 5 4 5 6 3 19 2 8 5 4 4 5 20 2 7 5 2 6 4 21 2 5 5 2 3 5 22 2 7 6 5 3 6 23 1 5 5 1 5 3 24 3 10 7 4 5 4 25 2 5 6 1 5 5 26 3 4 6 3 5 4 27 4 4 6 2 5 5 28 5 5 6 2 2 6 29 2 5 4 1 6 7 30 5 6 5 3 7 2 31 5 5 6 4 2 4 32 1 5 4 3 3 6 33 6 8 5 5 6 5 34 3 5 5 2 5 5 35 4 5 5 1 7 5 36 6 5 7 2 5 6 37 5 5 7 5 6 6 38 5 5 6 1 5 1 39 3 5 7 3 3 4 40 3 7 6 2 7 2 41 5 7 5 3 5 3 42 2 7 6 2 5 4 43 2 4 4 2 6 5 44 3 5 6 3 2 4 45 5 5 5 3 7 4 46 2 4 5 5 3 3 47 4 5 6 3 6 4 48 5 5 6 2 7 6 49 2 6 5 1 5 4 50 2 5 6 6 4 5 51 5 5 5 6 6 4 52 6 6 5 3 7 5 53 6 6 5 5 2 6 54 5 4 6 4 2 6 55 4 6 6 3 2 4 56 3 6 5 2 5 4 57 7 5 7 7 2 6 58 7 5 6 2 5 4 59 5 5 5 2 6 2 60 2 7 5 2 2 6 61 6 6 6 2 4 5 62 6 8 5 3 6 6 63 4 7 5 5 4 6 64 5 5 6 2 3 5 65 2 6 6 5 3 5 66 6 6 3 2 3 5 67 3 5 5 1 6 5 68 2 5 5 3 6 3 69 2 5 6 4 5 4 70 5 5 5 2 3 1 71 3 4 5 4 3 5 72 4 6 4 4 2 2 73 5 6 5 3 3 6 74 7 6 5 2 3 5 75 2 6 2 1 5 2 76 5 7 6 5 3 6 77 6 7 6 2 5 5 78 4 5 6 4 2 6 79 3 7 6 4 5 3 80 6 5 5 4 6 4 81 5 5 5 2 6 4 82 2 5 6 2 5 4 83 5 8 5 2 2 4 84 3 8 5 2 6 5 85 6 5 6 3 7 2 86 5 4 3 5 5 3 87 1 6 6 1 5 5 88 5 4 3 2 2 6 89 2 5 5 2 5 5 90 1 5 5 2 6 6 91 4 5 6 5 5 3 92 2 6 5 2 5 4 93 3 6 6 1 4 4 94 5 6 6 2 5 3 95 6 5 6 1 4 4 96 4 6 7 6 2 4 97 4 5 5 2 3 4 98 5 5 3 1 5 2 99 1 7 4 1 2 6 100 6 6 7 6 2 3 101 2 6 6 1 4 5 102 3 6 6 2 3 5 103 5 7 5 2 5 5 104 2 5 4 1 5 5 105 2 6 6 2 2 4 106 3 6 6 1 5 2 107 2 5 6 1 2 5 108 6 4 5 3 6 3 109 3 5 6 5 2 6 110 2 5 6 2 1 6 111 1 9 2 1 6 1 112 1 6 6 3 2 7 113 1 5 5 2 3 5 114 4 6 5 4 5 6 115 1 5 3 2 4 6 116 1 6 4 5 4 6 117 1 5 6 1 6 3 118 5 7 5 2 2 6 119 5 6 6 2 7 7 120 2 7 4 1 2 6 121 3 5 6 2 5 5 122 5 6 4 2 3 5 123 2 9 3 5 3 5 124 2 4 6 2 5 5 125 4 6 5 5 5 4 126 1 6 5 2 2 6 127 5 6 7 5 4 4 128 1 6 6 1 3 6 129 2 5 6 3 2 6 130 2 5 5 2 6 4 131 6 5 6 1 6 3 132 2 7 6 2 3 5 133 1 5 5 1 2 7 134 3 4 2 2 6 3 135 4 5 5 2 6 4 136 6 6 3 2 2 2 137 5 7 6 4 5 4 138 6 5 5 5 6 4 139 6 7 5 2 5 3 140 1 7 5 3 3 2 141 6 6 2 2 7 5 142 2 8 5 1 5 5 143 2 5 5 2 4 4 144 7 5 6 2 5 6 145 2 6 6 2 3 5 146 2 4 5 2 2 1 147 6 5 5 2 5 5 148 1 5 3 4 6 6 149 2 5 5 2 5 5 150 3 7 6 4 2 5 151 4 5 6 5 3 5 152 5 6 6 3 2 5 153 5 7 6 4 6 4 154 6 8 6 4 6 7 155 3 10 5 2 2 6 156 1 5 7 3 2 5 157 3 6 6 2 3 6 158 2 4 6 1 4 3 159 3 6 6 2 6 5 160 7 7 7 3 2 6 161 3 5 1 3 7 1 162 4 7 6 2 2 6 163 6 6 5 5 2 4 164 2 6 6 1 4 5 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Age Use_hands 1.558187 0.009709 0.216489 Hand_on_hips Quiet_FirstMeeting Outgoing_individual 0.273494 0.148458 -0.138792 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -3.2672 -1.3455 -0.4475 1.4355 4.0027 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.558187 1.156205 1.348 0.17969 Age 0.009709 0.118536 0.082 0.93483 Use_hands 0.216489 0.129833 1.667 0.09741 . Hand_on_hips 0.273494 0.099789 2.741 0.00684 ** Quiet_FirstMeeting 0.148458 0.086712 1.712 0.08884 . Outgoing_individual -0.138792 0.103965 -1.335 0.18380 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 1.745 on 158 degrees of freedom Multiple R-squared: 0.08696, Adjusted R-squared: 0.05807 F-statistic: 3.01 on 5 and 158 DF, p-value: 0.01268 > 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,] 0.9749961 0.05000787 0.02500393 [2,] 0.9565357 0.08692856 0.04346428 [3,] 0.9346631 0.13067373 0.06533686 [4,] 0.9251839 0.14963216 0.07481608 [5,] 0.9153859 0.16922818 0.08461409 [6,] 0.8762173 0.24756532 0.12378266 [7,] 0.8587362 0.28252758 0.14126379 [8,] 0.8295524 0.34089529 0.17044765 [9,] 0.8264505 0.34709910 0.17354955 [10,] 0.7801269 0.43974626 0.21987313 [11,] 0.7224752 0.55504951 0.27752476 [12,] 0.7077740 0.58445209 0.29222604 [13,] 0.6426485 0.71470290 0.35735145 [14,] 0.5920876 0.81582475 0.40791237 [15,] 0.6398064 0.72038715 0.36019357 [16,] 0.5938158 0.81236835 0.40618418 [17,] 0.5555015 0.88899702 0.44449851 [18,] 0.4895553 0.97911051 0.51044474 [19,] 0.4467575 0.89351496 0.55324252 [20,] 0.5602980 0.87940399 0.43970200 [21,] 0.4981496 0.99629913 0.50185044 [22,] 0.4769166 0.95383328 0.52308336 [23,] 0.5054169 0.98916616 0.49458308 [24,] 0.4609340 0.92186791 0.53906605 [25,] 0.6069787 0.78604256 0.39302128 [26,] 0.5510211 0.89795779 0.44897890 [27,] 0.5072860 0.98542797 0.49271398 [28,] 0.5477333 0.90453334 0.45226667 [29,] 0.4977464 0.99549280 0.50225360 [30,] 0.4529310 0.90586208 0.54706896 [31,] 0.4131008 0.82620165 0.58689917 [32,] 0.3958978 0.79179564 0.60410218 [33,] 0.3995754 0.79915072 0.60042464 [34,] 0.3894702 0.77894037 0.61052981 [35,] 0.3494414 0.69888288 0.65055856 [36,] 0.3012964 0.60259276 0.69870362 [37,] 0.2808591 0.56171830 0.71914085 [38,] 0.2643572 0.52871450 0.73564275 [39,] 0.2230007 0.44600148 0.77699926 [40,] 0.2007974 0.40159478 0.79920261 [41,] 0.1775758 0.35515150 0.82242425 [42,] 0.1816391 0.36327823 0.81836089 [43,] 0.1708900 0.34177995 0.82911002 [44,] 0.2016125 0.40322503 0.79838749 [45,] 0.3409381 0.68187628 0.65906186 [46,] 0.3458395 0.69167907 0.65416046 [47,] 0.3132787 0.62655748 0.68672126 [48,] 0.2721454 0.54429083 0.72785458 [49,] 0.3209729 0.64194583 0.67902709 [50,] 0.4365371 0.87307428 0.56346286 [51,] 0.4123740 0.82474795 0.58762603 [52,] 0.3702471 0.74049412 0.62975294 [53,] 0.4292622 0.85852435 0.57073783 [54,] 0.4965970 0.99319406 0.50340297 [55,] 0.4551552 0.91031038 0.54484481 [56,] 0.4536535 0.90730694 0.54634653 [57,] 0.4647988 0.92959766 0.53520117 [58,] 0.6379540 0.72409193 0.36204596 [59,] 0.5944566 0.81108680 0.40554340 [60,] 0.6019696 0.79606089 0.39803044 [61,] 0.6253038 0.74939250 0.37469625 [62,] 0.6166775 0.76664492 0.38332246 [63,] 0.5752200 0.84956000 0.42478000 [64,] 0.5359650 0.92806993 0.46403496 [65,] 0.5402191 0.91956173 0.45978086 [66,] 0.7123267 0.57534657 0.28767328 [67,] 0.6782809 0.64343819 0.32171909 [68,] 0.6517041 0.69659172 0.34829586 [69,] 0.6861484 0.62770316 0.31385158 [70,] 0.6475270 0.70494597 0.35247299 [71,] 0.6313411 0.73731777 0.36865888 [72,] 0.6404937 0.71901251 0.35950626 [73,] 0.6247251 0.75054988 0.37527494 [74,] 0.6217204 0.75655913 0.37827956 [75,] 0.6297874 0.74042526 0.37021263 [76,] 0.5896127 0.82077454 0.41038727 [77,] 0.5783325 0.84333505 0.42166752 [78,] 0.5528462 0.89430766 0.44715383 [79,] 0.5846819 0.83063610 0.41531805 [80,] 0.6619898 0.67602042 0.33801021 [81,] 0.6431300 0.71373995 0.35686998 [82,] 0.6765965 0.64680700 0.32340350 [83,] 0.6421490 0.71570208 0.35785104 [84,] 0.6320379 0.73592417 0.36796208 [85,] 0.5889857 0.82202862 0.41101431 [86,] 0.5597639 0.88047220 0.44023610 [87,] 0.6283207 0.74335868 0.37167934 [88,] 0.5892427 0.82151451 0.41075725 [89,] 0.5602300 0.87953995 0.43976998 [90,] 0.5885928 0.82281438 0.41140719 [91,] 0.5644802 0.87103963 0.43551982 [92,] 0.5411151 0.91776979 0.45888489 [93,] 0.5128169 0.97436617 0.48718308 [94,] 0.4666936 0.93338718 0.53330641 [95,] 0.4578511 0.91570222 0.54214889 [96,] 0.4184974 0.83699474 0.58150263 [97,] 0.3913584 0.78271678 0.60864161 [98,] 0.3522498 0.70449956 0.64775022 [99,] 0.3160774 0.63215480 0.68392260 [100,] 0.3329680 0.66593597 0.66703201 [101,] 0.2954233 0.59084654 0.70457673 [102,] 0.2601321 0.52026420 0.73986790 [103,] 0.3018330 0.60366599 0.69816700 [104,] 0.3054517 0.61090336 0.69454832 [105,] 0.3038825 0.60776490 0.69611755 [106,] 0.2623730 0.52474609 0.73762696 [107,] 0.2459790 0.49195795 0.75402102 [108,] 0.3070745 0.61414904 0.69292548 [109,] 0.3618770 0.72375410 0.63812295 [110,] 0.3955807 0.79116144 0.60441928 [111,] 0.3654591 0.73091828 0.63454086 [112,] 0.3173203 0.63464055 0.68267973 [113,] 0.2755958 0.55119167 0.72440417 [114,] 0.3114547 0.62290935 0.68854533 [115,] 0.3286030 0.65720599 0.67139700 [116,] 0.3035809 0.60716181 0.69641910 [117,] 0.2690815 0.53816303 0.73091849 [118,] 0.2557350 0.51147007 0.74426497 [119,] 0.2138222 0.42764448 0.78617776 [120,] 0.2070437 0.41408746 0.79295627 [121,] 0.1814811 0.36296224 0.81851888 [122,] 0.1789741 0.35794820 0.82102590 [123,] 0.2145799 0.42915971 0.78542015 [124,] 0.1974873 0.39497453 0.80251273 [125,] 0.1821290 0.36425796 0.81787102 [126,] 0.1450456 0.29009127 0.85495437 [127,] 0.1143023 0.22860467 0.88569766 [128,] 0.2238821 0.44776418 0.77611791 [129,] 0.1806415 0.36128299 0.81935851 [130,] 0.1545192 0.30903835 0.84548083 [131,] 0.2119827 0.42396549 0.78801726 [132,] 0.2192779 0.43855579 0.78072210 [133,] 0.3261546 0.65230923 0.67384539 [134,] 0.2873880 0.57477607 0.71261196 [135,] 0.2407500 0.48150001 0.75925000 [136,] 0.4840650 0.96812993 0.51593503 [137,] 0.4369926 0.87398522 0.56300739 [138,] 0.3674987 0.73499747 0.63250126 [139,] 0.6584122 0.68317555 0.34158777 [140,] 0.6658021 0.66839571 0.33419785 [141,] 0.5903097 0.81938056 0.40969028 [142,] 0.6035256 0.79294878 0.39647439 [143,] 0.5717044 0.85659111 0.42829555 [144,] 0.4941028 0.98820568 0.50589716 [145,] 0.3749922 0.74998445 0.62500777 [146,] 0.2586099 0.51721979 0.74139011 [147,] 0.5419511 0.91609775 0.45804888 > postscript(file="/var/www/html/freestat/rcomp/tmp/14g3z1290455807.ps",horizontal=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/24g3z1290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3fp2k1290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4fp2k1290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5fp2k1290455807.ps",horizontal=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 = 164 Frequency = 1 1 2 3 4 5 6 3.82112403 0.07363233 -0.78414485 2.50868190 -1.21943733 -0.86870429 7 8 9 10 11 12 -2.44266186 -1.76885994 0.80356866 -3.26719251 2.13691445 -2.00695325 13 14 15 16 17 18 -1.51428175 -1.58707269 -2.28453742 -1.20209241 -1.52040129 -2.31453155 19 20 21 22 23 24 -1.71215116 -1.59116246 -0.98757857 -1.90517589 -2.28858486 -1.45179688 25 26 27 28 29 30 -1.22748987 -0.90356225 0.50872424 2.08318260 -0.66538560 0.71900922 31 32 33 34 35 36 1.25860962 -1.90579171 1.71743791 -0.28449509 0.69208279 2.42131863 37 38 39 40 41 42 0.45237716 1.21734179 -0.83284342 -1.23369407 1.14500932 -1.65919337 43 44 45 46 47 48 -1.20675567 -0.46789598 1.00630190 -2.07593744 -0.06172902 1.34089129 49 50 51 52 53 54 -1.15950128 -2.44650362 0.33427695 2.13538547 2.46948006 1.54590230 55 56 57 58 59 60 0.52239552 -0.43299569 2.49922140 3.36022364 1.15067039 -0.71974524 61 62 63 64 65 66 2.63776548 2.40321880 0.16285503 1.79593225 -2.03425947 3.43569128 67 68 69 70 71 72 -0.15945895 -1.98403193 -2.18676516 1.45725309 -0.52485887 0.40429530 73 74 75 76 77 78 1.86801061 4.00271292 -0.78761791 1.09482411 2.47959871 0.53619379 79 80 81 82 83 84 -1.34497427 1.88126575 1.42825456 -1.63977636 1.99296208 -0.46207888 85 86 87 88 89 90 1.51222854 1.06012440 -2.23719838 2.74235865 -1.28449509 -2.29416127 91 92 93 94 95 96 -0.59905165 -1.43299569 -0.22753220 1.21172305 2.78217631 -0.51457687 97 98 99 100 101 102 0.87362935 2.00560142 -1.22976165 1.34663104 -1.08874012 -0.21377626 103 104 105 106 107 108 1.69608789 -0.79451151 -1.20411008 -0.65357463 -0.78211508 2.02567658 109 110 111 112 113 114 -0.73730061 -0.76835914 -2.10399378 -2.06122823 -1.98757857 0.29759968 115 116 117 118 119 120 -1.56426638 -2.61094728 -2.65353230 2.28025476 1.46997487 -0.22976165 121 122 123 124 125 126 -0.50098427 2.21920210 -1.41391745 -1.49127576 -0.25347889 -1.71003673 127 128 129 130 131 132 0.46200101 -1.80148977 -1.19031180 -1.57174544 2.34646770 -1.22348476 133 134 135 136 137 138 -1.28804173 -0.05136148 0.42825456 3.16777329 0.79381782 1.60777135 139 140 141 142 143 144 2.41850372 -2.69686624 3.05834742 -1.04012621 -1.27482892 3.63780781 145 146 147 148 149 150 -1.21377626 -1.38458014 2.71550491 -2.40817171 -1.28449509 -0.62201531 151 152 153 154 155 156 -0.02455096 1.66118760 0.64535956 2.05202731 0.25112924 -2.54559307 157 158 159 160 161 162 -0.07498417 -1.34690727 -0.65915104 3.57378200 -0.54411764 1.06376558 163 164 2.19189589 -1.08874012 > postscript(file="/var/www/html/freestat/rcomp/tmp/6py151290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 164 Frequency = 1 lag(myerror, k = 1) myerror 0 3.82112403 NA 1 0.07363233 3.82112403 2 -0.78414485 0.07363233 3 2.50868190 -0.78414485 4 -1.21943733 2.50868190 5 -0.86870429 -1.21943733 6 -2.44266186 -0.86870429 7 -1.76885994 -2.44266186 8 0.80356866 -1.76885994 9 -3.26719251 0.80356866 10 2.13691445 -3.26719251 11 -2.00695325 2.13691445 12 -1.51428175 -2.00695325 13 -1.58707269 -1.51428175 14 -2.28453742 -1.58707269 15 -1.20209241 -2.28453742 16 -1.52040129 -1.20209241 17 -2.31453155 -1.52040129 18 -1.71215116 -2.31453155 19 -1.59116246 -1.71215116 20 -0.98757857 -1.59116246 21 -1.90517589 -0.98757857 22 -2.28858486 -1.90517589 23 -1.45179688 -2.28858486 24 -1.22748987 -1.45179688 25 -0.90356225 -1.22748987 26 0.50872424 -0.90356225 27 2.08318260 0.50872424 28 -0.66538560 2.08318260 29 0.71900922 -0.66538560 30 1.25860962 0.71900922 31 -1.90579171 1.25860962 32 1.71743791 -1.90579171 33 -0.28449509 1.71743791 34 0.69208279 -0.28449509 35 2.42131863 0.69208279 36 0.45237716 2.42131863 37 1.21734179 0.45237716 38 -0.83284342 1.21734179 39 -1.23369407 -0.83284342 40 1.14500932 -1.23369407 41 -1.65919337 1.14500932 42 -1.20675567 -1.65919337 43 -0.46789598 -1.20675567 44 1.00630190 -0.46789598 45 -2.07593744 1.00630190 46 -0.06172902 -2.07593744 47 1.34089129 -0.06172902 48 -1.15950128 1.34089129 49 -2.44650362 -1.15950128 50 0.33427695 -2.44650362 51 2.13538547 0.33427695 52 2.46948006 2.13538547 53 1.54590230 2.46948006 54 0.52239552 1.54590230 55 -0.43299569 0.52239552 56 2.49922140 -0.43299569 57 3.36022364 2.49922140 58 1.15067039 3.36022364 59 -0.71974524 1.15067039 60 2.63776548 -0.71974524 61 2.40321880 2.63776548 62 0.16285503 2.40321880 63 1.79593225 0.16285503 64 -2.03425947 1.79593225 65 3.43569128 -2.03425947 66 -0.15945895 3.43569128 67 -1.98403193 -0.15945895 68 -2.18676516 -1.98403193 69 1.45725309 -2.18676516 70 -0.52485887 1.45725309 71 0.40429530 -0.52485887 72 1.86801061 0.40429530 73 4.00271292 1.86801061 74 -0.78761791 4.00271292 75 1.09482411 -0.78761791 76 2.47959871 1.09482411 77 0.53619379 2.47959871 78 -1.34497427 0.53619379 79 1.88126575 -1.34497427 80 1.42825456 1.88126575 81 -1.63977636 1.42825456 82 1.99296208 -1.63977636 83 -0.46207888 1.99296208 84 1.51222854 -0.46207888 85 1.06012440 1.51222854 86 -2.23719838 1.06012440 87 2.74235865 -2.23719838 88 -1.28449509 2.74235865 89 -2.29416127 -1.28449509 90 -0.59905165 -2.29416127 91 -1.43299569 -0.59905165 92 -0.22753220 -1.43299569 93 1.21172305 -0.22753220 94 2.78217631 1.21172305 95 -0.51457687 2.78217631 96 0.87362935 -0.51457687 97 2.00560142 0.87362935 98 -1.22976165 2.00560142 99 1.34663104 -1.22976165 100 -1.08874012 1.34663104 101 -0.21377626 -1.08874012 102 1.69608789 -0.21377626 103 -0.79451151 1.69608789 104 -1.20411008 -0.79451151 105 -0.65357463 -1.20411008 106 -0.78211508 -0.65357463 107 2.02567658 -0.78211508 108 -0.73730061 2.02567658 109 -0.76835914 -0.73730061 110 -2.10399378 -0.76835914 111 -2.06122823 -2.10399378 112 -1.98757857 -2.06122823 113 0.29759968 -1.98757857 114 -1.56426638 0.29759968 115 -2.61094728 -1.56426638 116 -2.65353230 -2.61094728 117 2.28025476 -2.65353230 118 1.46997487 2.28025476 119 -0.22976165 1.46997487 120 -0.50098427 -0.22976165 121 2.21920210 -0.50098427 122 -1.41391745 2.21920210 123 -1.49127576 -1.41391745 124 -0.25347889 -1.49127576 125 -1.71003673 -0.25347889 126 0.46200101 -1.71003673 127 -1.80148977 0.46200101 128 -1.19031180 -1.80148977 129 -1.57174544 -1.19031180 130 2.34646770 -1.57174544 131 -1.22348476 2.34646770 132 -1.28804173 -1.22348476 133 -0.05136148 -1.28804173 134 0.42825456 -0.05136148 135 3.16777329 0.42825456 136 0.79381782 3.16777329 137 1.60777135 0.79381782 138 2.41850372 1.60777135 139 -2.69686624 2.41850372 140 3.05834742 -2.69686624 141 -1.04012621 3.05834742 142 -1.27482892 -1.04012621 143 3.63780781 -1.27482892 144 -1.21377626 3.63780781 145 -1.38458014 -1.21377626 146 2.71550491 -1.38458014 147 -2.40817171 2.71550491 148 -1.28449509 -2.40817171 149 -0.62201531 -1.28449509 150 -0.02455096 -0.62201531 151 1.66118760 -0.02455096 152 0.64535956 1.66118760 153 2.05202731 0.64535956 154 0.25112924 2.05202731 155 -2.54559307 0.25112924 156 -0.07498417 -2.54559307 157 -1.34690727 -0.07498417 158 -0.65915104 -1.34690727 159 3.57378200 -0.65915104 160 -0.54411764 3.57378200 161 1.06376558 -0.54411764 162 2.19189589 1.06376558 163 -1.08874012 2.19189589 164 NA -1.08874012 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.07363233 3.82112403 [2,] -0.78414485 0.07363233 [3,] 2.50868190 -0.78414485 [4,] -1.21943733 2.50868190 [5,] -0.86870429 -1.21943733 [6,] -2.44266186 -0.86870429 [7,] -1.76885994 -2.44266186 [8,] 0.80356866 -1.76885994 [9,] -3.26719251 0.80356866 [10,] 2.13691445 -3.26719251 [11,] -2.00695325 2.13691445 [12,] -1.51428175 -2.00695325 [13,] -1.58707269 -1.51428175 [14,] -2.28453742 -1.58707269 [15,] -1.20209241 -2.28453742 [16,] -1.52040129 -1.20209241 [17,] -2.31453155 -1.52040129 [18,] -1.71215116 -2.31453155 [19,] -1.59116246 -1.71215116 [20,] -0.98757857 -1.59116246 [21,] -1.90517589 -0.98757857 [22,] -2.28858486 -1.90517589 [23,] -1.45179688 -2.28858486 [24,] -1.22748987 -1.45179688 [25,] -0.90356225 -1.22748987 [26,] 0.50872424 -0.90356225 [27,] 2.08318260 0.50872424 [28,] -0.66538560 2.08318260 [29,] 0.71900922 -0.66538560 [30,] 1.25860962 0.71900922 [31,] -1.90579171 1.25860962 [32,] 1.71743791 -1.90579171 [33,] -0.28449509 1.71743791 [34,] 0.69208279 -0.28449509 [35,] 2.42131863 0.69208279 [36,] 0.45237716 2.42131863 [37,] 1.21734179 0.45237716 [38,] -0.83284342 1.21734179 [39,] -1.23369407 -0.83284342 [40,] 1.14500932 -1.23369407 [41,] -1.65919337 1.14500932 [42,] -1.20675567 -1.65919337 [43,] -0.46789598 -1.20675567 [44,] 1.00630190 -0.46789598 [45,] -2.07593744 1.00630190 [46,] -0.06172902 -2.07593744 [47,] 1.34089129 -0.06172902 [48,] -1.15950128 1.34089129 [49,] -2.44650362 -1.15950128 [50,] 0.33427695 -2.44650362 [51,] 2.13538547 0.33427695 [52,] 2.46948006 2.13538547 [53,] 1.54590230 2.46948006 [54,] 0.52239552 1.54590230 [55,] -0.43299569 0.52239552 [56,] 2.49922140 -0.43299569 [57,] 3.36022364 2.49922140 [58,] 1.15067039 3.36022364 [59,] -0.71974524 1.15067039 [60,] 2.63776548 -0.71974524 [61,] 2.40321880 2.63776548 [62,] 0.16285503 2.40321880 [63,] 1.79593225 0.16285503 [64,] -2.03425947 1.79593225 [65,] 3.43569128 -2.03425947 [66,] -0.15945895 3.43569128 [67,] -1.98403193 -0.15945895 [68,] -2.18676516 -1.98403193 [69,] 1.45725309 -2.18676516 [70,] -0.52485887 1.45725309 [71,] 0.40429530 -0.52485887 [72,] 1.86801061 0.40429530 [73,] 4.00271292 1.86801061 [74,] -0.78761791 4.00271292 [75,] 1.09482411 -0.78761791 [76,] 2.47959871 1.09482411 [77,] 0.53619379 2.47959871 [78,] -1.34497427 0.53619379 [79,] 1.88126575 -1.34497427 [80,] 1.42825456 1.88126575 [81,] -1.63977636 1.42825456 [82,] 1.99296208 -1.63977636 [83,] -0.46207888 1.99296208 [84,] 1.51222854 -0.46207888 [85,] 1.06012440 1.51222854 [86,] -2.23719838 1.06012440 [87,] 2.74235865 -2.23719838 [88,] -1.28449509 2.74235865 [89,] -2.29416127 -1.28449509 [90,] -0.59905165 -2.29416127 [91,] -1.43299569 -0.59905165 [92,] -0.22753220 -1.43299569 [93,] 1.21172305 -0.22753220 [94,] 2.78217631 1.21172305 [95,] -0.51457687 2.78217631 [96,] 0.87362935 -0.51457687 [97,] 2.00560142 0.87362935 [98,] -1.22976165 2.00560142 [99,] 1.34663104 -1.22976165 [100,] -1.08874012 1.34663104 [101,] -0.21377626 -1.08874012 [102,] 1.69608789 -0.21377626 [103,] -0.79451151 1.69608789 [104,] -1.20411008 -0.79451151 [105,] -0.65357463 -1.20411008 [106,] -0.78211508 -0.65357463 [107,] 2.02567658 -0.78211508 [108,] -0.73730061 2.02567658 [109,] -0.76835914 -0.73730061 [110,] -2.10399378 -0.76835914 [111,] -2.06122823 -2.10399378 [112,] -1.98757857 -2.06122823 [113,] 0.29759968 -1.98757857 [114,] -1.56426638 0.29759968 [115,] -2.61094728 -1.56426638 [116,] -2.65353230 -2.61094728 [117,] 2.28025476 -2.65353230 [118,] 1.46997487 2.28025476 [119,] -0.22976165 1.46997487 [120,] -0.50098427 -0.22976165 [121,] 2.21920210 -0.50098427 [122,] -1.41391745 2.21920210 [123,] -1.49127576 -1.41391745 [124,] -0.25347889 -1.49127576 [125,] -1.71003673 -0.25347889 [126,] 0.46200101 -1.71003673 [127,] -1.80148977 0.46200101 [128,] -1.19031180 -1.80148977 [129,] -1.57174544 -1.19031180 [130,] 2.34646770 -1.57174544 [131,] -1.22348476 2.34646770 [132,] -1.28804173 -1.22348476 [133,] -0.05136148 -1.28804173 [134,] 0.42825456 -0.05136148 [135,] 3.16777329 0.42825456 [136,] 0.79381782 3.16777329 [137,] 1.60777135 0.79381782 [138,] 2.41850372 1.60777135 [139,] -2.69686624 2.41850372 [140,] 3.05834742 -2.69686624 [141,] -1.04012621 3.05834742 [142,] -1.27482892 -1.04012621 [143,] 3.63780781 -1.27482892 [144,] -1.21377626 3.63780781 [145,] -1.38458014 -1.21377626 [146,] 2.71550491 -1.38458014 [147,] -2.40817171 2.71550491 [148,] -1.28449509 -2.40817171 [149,] -0.62201531 -1.28449509 [150,] -0.02455096 -0.62201531 [151,] 1.66118760 -0.02455096 [152,] 0.64535956 1.66118760 [153,] 2.05202731 0.64535956 [154,] 0.25112924 2.05202731 [155,] -2.54559307 0.25112924 [156,] -0.07498417 -2.54559307 [157,] -1.34690727 -0.07498417 [158,] -0.65915104 -1.34690727 [159,] 3.57378200 -0.65915104 [160,] -0.54411764 3.57378200 [161,] 1.06376558 -0.54411764 [162,] 2.19189589 1.06376558 [163,] -1.08874012 2.19189589 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.07363233 3.82112403 2 -0.78414485 0.07363233 3 2.50868190 -0.78414485 4 -1.21943733 2.50868190 5 -0.86870429 -1.21943733 6 -2.44266186 -0.86870429 7 -1.76885994 -2.44266186 8 0.80356866 -1.76885994 9 -3.26719251 0.80356866 10 2.13691445 -3.26719251 11 -2.00695325 2.13691445 12 -1.51428175 -2.00695325 13 -1.58707269 -1.51428175 14 -2.28453742 -1.58707269 15 -1.20209241 -2.28453742 16 -1.52040129 -1.20209241 17 -2.31453155 -1.52040129 18 -1.71215116 -2.31453155 19 -1.59116246 -1.71215116 20 -0.98757857 -1.59116246 21 -1.90517589 -0.98757857 22 -2.28858486 -1.90517589 23 -1.45179688 -2.28858486 24 -1.22748987 -1.45179688 25 -0.90356225 -1.22748987 26 0.50872424 -0.90356225 27 2.08318260 0.50872424 28 -0.66538560 2.08318260 29 0.71900922 -0.66538560 30 1.25860962 0.71900922 31 -1.90579171 1.25860962 32 1.71743791 -1.90579171 33 -0.28449509 1.71743791 34 0.69208279 -0.28449509 35 2.42131863 0.69208279 36 0.45237716 2.42131863 37 1.21734179 0.45237716 38 -0.83284342 1.21734179 39 -1.23369407 -0.83284342 40 1.14500932 -1.23369407 41 -1.65919337 1.14500932 42 -1.20675567 -1.65919337 43 -0.46789598 -1.20675567 44 1.00630190 -0.46789598 45 -2.07593744 1.00630190 46 -0.06172902 -2.07593744 47 1.34089129 -0.06172902 48 -1.15950128 1.34089129 49 -2.44650362 -1.15950128 50 0.33427695 -2.44650362 51 2.13538547 0.33427695 52 2.46948006 2.13538547 53 1.54590230 2.46948006 54 0.52239552 1.54590230 55 -0.43299569 0.52239552 56 2.49922140 -0.43299569 57 3.36022364 2.49922140 58 1.15067039 3.36022364 59 -0.71974524 1.15067039 60 2.63776548 -0.71974524 61 2.40321880 2.63776548 62 0.16285503 2.40321880 63 1.79593225 0.16285503 64 -2.03425947 1.79593225 65 3.43569128 -2.03425947 66 -0.15945895 3.43569128 67 -1.98403193 -0.15945895 68 -2.18676516 -1.98403193 69 1.45725309 -2.18676516 70 -0.52485887 1.45725309 71 0.40429530 -0.52485887 72 1.86801061 0.40429530 73 4.00271292 1.86801061 74 -0.78761791 4.00271292 75 1.09482411 -0.78761791 76 2.47959871 1.09482411 77 0.53619379 2.47959871 78 -1.34497427 0.53619379 79 1.88126575 -1.34497427 80 1.42825456 1.88126575 81 -1.63977636 1.42825456 82 1.99296208 -1.63977636 83 -0.46207888 1.99296208 84 1.51222854 -0.46207888 85 1.06012440 1.51222854 86 -2.23719838 1.06012440 87 2.74235865 -2.23719838 88 -1.28449509 2.74235865 89 -2.29416127 -1.28449509 90 -0.59905165 -2.29416127 91 -1.43299569 -0.59905165 92 -0.22753220 -1.43299569 93 1.21172305 -0.22753220 94 2.78217631 1.21172305 95 -0.51457687 2.78217631 96 0.87362935 -0.51457687 97 2.00560142 0.87362935 98 -1.22976165 2.00560142 99 1.34663104 -1.22976165 100 -1.08874012 1.34663104 101 -0.21377626 -1.08874012 102 1.69608789 -0.21377626 103 -0.79451151 1.69608789 104 -1.20411008 -0.79451151 105 -0.65357463 -1.20411008 106 -0.78211508 -0.65357463 107 2.02567658 -0.78211508 108 -0.73730061 2.02567658 109 -0.76835914 -0.73730061 110 -2.10399378 -0.76835914 111 -2.06122823 -2.10399378 112 -1.98757857 -2.06122823 113 0.29759968 -1.98757857 114 -1.56426638 0.29759968 115 -2.61094728 -1.56426638 116 -2.65353230 -2.61094728 117 2.28025476 -2.65353230 118 1.46997487 2.28025476 119 -0.22976165 1.46997487 120 -0.50098427 -0.22976165 121 2.21920210 -0.50098427 122 -1.41391745 2.21920210 123 -1.49127576 -1.41391745 124 -0.25347889 -1.49127576 125 -1.71003673 -0.25347889 126 0.46200101 -1.71003673 127 -1.80148977 0.46200101 128 -1.19031180 -1.80148977 129 -1.57174544 -1.19031180 130 2.34646770 -1.57174544 131 -1.22348476 2.34646770 132 -1.28804173 -1.22348476 133 -0.05136148 -1.28804173 134 0.42825456 -0.05136148 135 3.16777329 0.42825456 136 0.79381782 3.16777329 137 1.60777135 0.79381782 138 2.41850372 1.60777135 139 -2.69686624 2.41850372 140 3.05834742 -2.69686624 141 -1.04012621 3.05834742 142 -1.27482892 -1.04012621 143 3.63780781 -1.27482892 144 -1.21377626 3.63780781 145 -1.38458014 -1.21377626 146 2.71550491 -1.38458014 147 -2.40817171 2.71550491 148 -1.28449509 -2.40817171 149 -0.62201531 -1.28449509 150 -0.02455096 -0.62201531 151 1.66118760 -0.02455096 152 0.64535956 1.66118760 153 2.05202731 0.64535956 154 0.25112924 2.05202731 155 -2.54559307 0.25112924 156 -0.07498417 -2.54559307 157 -1.34690727 -0.07498417 158 -0.65915104 -1.34690727 159 3.57378200 -0.65915104 160 -0.54411764 3.57378200 161 1.06376558 -0.54411764 162 2.19189589 1.06376558 163 -1.08874012 2.19189589 > 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/70qi81290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/80qi81290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/90qi81290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10tz0t1290455807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11wzyy1290455807.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/120ixn1290455807.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/13escd1290455807.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/14zstj1290455807.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/152t9p1290455807.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/166tqd1290455807.tab") + } > try(system("convert tmp/14g3z1290455807.ps tmp/14g3z1290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/24g3z1290455807.ps tmp/24g3z1290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/3fp2k1290455807.ps tmp/3fp2k1290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/4fp2k1290455807.ps tmp/4fp2k1290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/5fp2k1290455807.ps tmp/5fp2k1290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/6py151290455807.ps tmp/6py151290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/70qi81290455807.ps tmp/70qi81290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/80qi81290455807.ps tmp/80qi81290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/90qi81290455807.ps tmp/90qi81290455807.png",intern=TRUE)) character(0) > try(system("convert tmp/10tz0t1290455807.ps tmp/10tz0t1290455807.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.904 2.715 10.712