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 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,0 + ,1 + ,1 + ,4 + ,1 + ,1 + ,1 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,1 + ,0 + ,4 + ,1 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + 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,2 + ,1 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,1 + ,0 + ,1 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,1 + ,1 + ,0 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,1 + ,1 + ,0 + ,0 + ,2 + ,1 + ,1 + ,1 + ,1 + ,0 + ,2 + ,1 + ,1 + ,0 + ,0 + ,0) + ,dim=c(6 + ,154) + ,dimnames=list(c('Weeks' + ,'USELIMIT' + ,'Used' + ,'CorrectAN' + ,'Useful' + ,'Outcome') + ,1:154)) > y <- array(NA,dim=c(6,154),dimnames=list(c('Weeks','USELIMIT','Used','CorrectAN','Useful','Outcome'),1:154)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '6' > par3 <- 'Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '6' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Outcome Weeks USELIMIT Used CorrectAN Useful t 1 1 4 1 0 0 0 1 2 0 4 0 0 0 0 2 3 0 4 0 0 0 0 3 4 0 4 0 0 0 0 4 5 0 4 0 0 0 0 5 6 1 4 1 0 0 1 6 7 0 4 0 0 0 0 7 8 0 4 0 0 0 0 8 9 1 4 0 0 0 0 9 10 0 4 1 0 0 0 10 11 0 4 1 0 0 0 11 12 0 4 0 0 0 0 12 13 0 4 0 1 0 1 13 14 0 4 1 0 0 0 14 15 1 4 0 1 0 1 15 16 1 4 0 1 0 1 16 17 0 4 1 1 1 1 17 18 0 4 1 0 0 0 18 19 1 4 0 0 0 0 19 20 1 4 0 1 1 1 20 21 0 4 1 0 0 1 21 22 1 4 1 1 0 1 22 23 1 4 0 0 0 1 23 24 1 4 1 0 0 1 24 25 1 4 0 1 0 0 25 26 0 4 0 1 0 1 26 27 1 4 1 0 0 0 27 28 0 4 0 1 0 0 28 29 1 4 0 0 0 0 29 30 0 4 0 0 0 1 30 31 0 4 0 0 0 0 31 32 0 4 1 0 0 0 32 33 0 4 1 0 0 1 33 34 1 4 0 0 0 0 34 35 0 4 0 0 0 0 35 36 0 4 0 0 0 0 36 37 0 4 1 1 0 1 37 38 1 4 0 1 0 0 38 39 1 4 0 0 0 1 39 40 0 4 0 0 0 1 40 41 1 4 0 1 1 1 41 42 1 4 0 1 0 0 42 43 1 4 1 0 0 1 43 44 0 4 1 0 0 0 44 45 0 4 0 0 0 1 45 46 1 4 0 0 0 1 46 47 0 4 0 0 0 0 47 48 1 4 0 0 0 0 48 49 1 4 0 0 0 1 49 50 0 4 0 0 0 0 50 51 0 4 0 1 0 0 51 52 0 4 1 1 1 1 52 53 1 4 0 0 0 0 53 54 0 4 0 1 1 0 54 55 0 4 0 0 0 0 55 56 1 4 0 1 0 0 56 57 1 4 0 1 0 1 57 58 1 4 0 0 0 0 58 59 1 4 0 0 0 0 59 60 1 4 1 1 1 1 60 61 1 4 1 0 0 0 61 62 0 4 0 1 0 1 62 63 0 4 0 0 0 0 63 64 1 4 1 0 0 0 64 65 0 4 0 0 0 0 65 66 0 4 0 0 0 0 66 67 0 4 0 1 1 1 67 68 0 4 1 0 0 0 68 69 1 4 0 0 0 0 69 70 0 4 0 1 0 0 70 71 0 4 0 0 0 0 71 72 1 4 0 0 0 0 72 73 1 4 0 1 0 0 73 74 0 4 1 1 0 0 74 75 1 4 0 0 0 0 75 76 1 4 0 0 0 1 76 77 1 4 0 0 0 0 77 78 1 4 0 1 0 1 78 79 1 4 0 1 1 0 79 80 0 4 0 0 0 1 80 81 0 4 0 0 0 0 81 82 1 4 1 1 0 0 82 83 0 4 0 0 0 0 83 84 0 4 0 1 1 0 84 85 1 4 0 0 0 1 85 86 0 4 1 0 0 0 86 87 1 2 1 0 0 0 87 88 1 2 1 1 0 0 88 89 0 2 0 0 0 0 89 90 1 2 0 0 0 0 90 91 0 2 0 0 0 1 91 92 0 2 1 0 0 0 92 93 0 2 1 0 0 1 93 94 0 2 0 0 0 0 94 95 0 2 0 0 0 0 95 96 1 2 0 0 0 0 96 97 0 2 1 0 0 0 97 98 0 2 0 0 0 0 98 99 0 2 1 0 0 0 99 100 1 2 0 0 0 0 100 101 1 2 1 0 0 0 101 102 0 2 0 0 0 0 102 103 0 2 0 0 0 0 103 104 0 2 0 0 0 0 104 105 0 2 0 1 0 0 105 106 0 2 0 0 0 0 106 107 0 2 0 0 0 0 107 108 0 2 1 1 0 0 108 109 0 2 0 0 0 0 109 110 0 2 1 0 0 0 110 111 0 2 1 1 0 1 111 112 0 2 0 0 0 0 112 113 0 2 0 1 0 0 113 114 0 2 1 1 0 0 114 115 0 2 1 0 0 0 115 116 0 2 0 0 0 0 116 117 1 2 1 0 0 0 117 118 0 2 1 0 0 0 118 119 0 2 0 0 0 0 119 120 1 2 0 0 0 0 120 121 0 2 1 0 0 0 121 122 0 2 0 0 0 0 122 123 0 2 1 1 0 0 123 124 1 2 0 1 0 1 124 125 1 2 0 0 0 0 125 126 0 2 0 0 0 0 126 127 0 2 0 0 0 1 127 128 1 2 0 0 0 0 128 129 0 2 0 0 0 0 129 130 1 2 0 0 0 0 130 131 0 2 1 0 0 0 131 132 1 2 1 0 0 0 132 133 0 2 1 1 0 0 133 134 0 2 0 0 0 0 134 135 0 2 0 0 0 0 135 136 0 2 0 0 0 0 136 137 1 2 1 1 0 1 137 138 1 2 1 1 0 1 138 139 0 2 0 0 0 0 139 140 0 2 0 0 0 0 140 141 1 2 0 1 1 0 141 142 1 2 0 1 0 0 142 143 0 2 1 0 0 0 143 144 1 2 0 0 0 1 144 145 0 2 0 0 0 1 145 146 1 2 0 0 0 0 146 147 0 2 0 1 0 0 147 148 0 2 0 0 0 0 148 149 0 2 1 0 0 0 149 150 1 2 0 0 0 1 150 151 1 2 0 0 0 0 151 152 0 2 1 1 1 0 152 153 0 2 1 1 1 1 153 154 0 2 1 1 0 0 154 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Weeks USELIMIT Used CorrectAN Useful -0.220056 0.137632 -0.071160 0.076674 -0.141203 0.163922 t 0.002003 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.6953 -0.3729 -0.2655 0.5137 0.8417 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.220056 0.377984 -0.582 0.5613 Weeks 0.137632 0.080338 1.713 0.0888 . USELIMIT -0.071160 0.085046 -0.837 0.4041 Used 0.076674 0.098844 0.776 0.4392 CorrectAN -0.141203 0.165823 -0.852 0.3959 Useful 0.163922 0.093771 1.748 0.0825 . t 0.002003 0.001770 1.132 0.2596 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.484 on 147 degrees of freedom Multiple R-squared: 0.06527, Adjusted R-squared: 0.02711 F-statistic: 1.711 on 6 and 147 DF, p-value: 0.1224 > 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,] 0.8681104 0.2637792 0.1318896 [2,] 0.8029007 0.3941986 0.1970993 [3,] 0.6976187 0.6047627 0.3023813 [4,] 0.5874150 0.8251700 0.4125850 [5,] 0.4788193 0.9576386 0.5211807 [6,] 0.6066338 0.7867325 0.3933662 [7,] 0.5827472 0.8345056 0.4172528 [8,] 0.4904052 0.9808105 0.5095948 [9,] 0.4016247 0.8032493 0.5983753 [10,] 0.5775513 0.8448974 0.4224487 [11,] 0.6034755 0.7930491 0.3965245 [12,] 0.6972625 0.6054749 0.3027375 [13,] 0.6677771 0.6644457 0.3322229 [14,] 0.6229750 0.7540499 0.3770250 [15,] 0.5807983 0.8384034 0.4192017 [16,] 0.5693660 0.8612679 0.4306340 [17,] 0.6978773 0.6042454 0.3021227 [18,] 0.7036072 0.5927857 0.2963928 [19,] 0.7073709 0.5852581 0.2926291 [20,] 0.6912430 0.6175141 0.3087570 [21,] 0.7639811 0.4720378 0.2360189 [22,] 0.7530825 0.4938350 0.2469175 [23,] 0.7334874 0.5330252 0.2665126 [24,] 0.7384927 0.5230145 0.2615073 [25,] 0.7596081 0.4807837 0.2403919 [26,] 0.7422956 0.5154088 0.2577044 [27,] 0.7189764 0.5620472 0.2810236 [28,] 0.7311444 0.5377111 0.2688556 [29,] 0.7371694 0.5256613 0.2628306 [30,] 0.7261101 0.5477797 0.2738899 [31,] 0.7360276 0.5279448 0.2639724 [32,] 0.7171934 0.5656131 0.2828066 [33,] 0.7065793 0.5868414 0.2934207 [34,] 0.7040587 0.5918826 0.2959413 [35,] 0.6856856 0.6286289 0.3143144 [36,] 0.6973167 0.6053666 0.3026833 [37,] 0.6866456 0.6267089 0.3133544 [38,] 0.6738475 0.6523051 0.3261525 [39,] 0.6860844 0.6278312 0.3139156 [40,] 0.6678853 0.6642293 0.3321147 [41,] 0.6610897 0.6778205 0.3389103 [42,] 0.6687103 0.6625793 0.3312897 [43,] 0.6719502 0.6560995 0.3280498 [44,] 0.6849311 0.6301377 0.3150689 [45,] 0.6647869 0.6704261 0.3352131 [46,] 0.6530017 0.6939967 0.3469983 [47,] 0.6496766 0.7006469 0.3503234 [48,] 0.6173797 0.7652406 0.3826203 [49,] 0.6261225 0.7477549 0.3738775 [50,] 0.6305423 0.7389155 0.3694577 [51,] 0.6312665 0.7374670 0.3687335 [52,] 0.6455526 0.7088948 0.3544474 [53,] 0.7000499 0.5999002 0.2999501 [54,] 0.6995418 0.6009164 0.3004582 [55,] 0.7139035 0.5721930 0.2860965 [56,] 0.7126079 0.5747842 0.2873921 [57,] 0.7093097 0.5813807 0.2906903 [58,] 0.7218635 0.5562731 0.2781365 [59,] 0.7098897 0.5802207 0.2901103 [60,] 0.7146444 0.5707113 0.2853556 [61,] 0.7267508 0.5464984 0.2732492 [62,] 0.7246320 0.5507360 0.2753680 [63,] 0.7274621 0.5450758 0.2725379 [64,] 0.7164845 0.5670311 0.2835155 [65,] 0.7179154 0.5641693 0.2820846 [66,] 0.7193175 0.5613650 0.2806825 [67,] 0.6976750 0.6046500 0.3023250 [68,] 0.7049201 0.5901599 0.2950799 [69,] 0.6789630 0.6420739 0.3210370 [70,] 0.7055872 0.5888256 0.2944128 [71,] 0.7255536 0.5488928 0.2744464 [72,] 0.7185117 0.5629766 0.2814883 [73,] 0.7359805 0.5280389 0.2640195 [74,] 0.7231600 0.5536799 0.2768400 [75,] 0.7072718 0.5854564 0.2927282 [76,] 0.6996445 0.6007110 0.3003555 [77,] 0.6726160 0.6547679 0.3273840 [78,] 0.7092948 0.5814104 0.2907052 [79,] 0.7521069 0.4957863 0.2478931 [80,] 0.7571457 0.4857087 0.2428543 [81,] 0.7952295 0.4095410 0.2047705 [82,] 0.8053853 0.3892294 0.1946147 [83,] 0.7832705 0.4334591 0.2167295 [84,] 0.7708058 0.4583884 0.2291942 [85,] 0.7441563 0.5116875 0.2558437 [86,] 0.7147882 0.5704236 0.2852118 [87,] 0.7706120 0.4587760 0.2293880 [88,] 0.7375752 0.5248495 0.2624248 [89,] 0.7061263 0.5877474 0.2938737 [90,] 0.6670964 0.6658072 0.3329036 [91,] 0.7350427 0.5299146 0.2649573 [92,] 0.8332355 0.3335290 0.1667645 [93,] 0.8062773 0.3874454 0.1937227 [94,] 0.7760746 0.4478508 0.2239254 [95,] 0.7428952 0.5142097 0.2571048 [96,] 0.7147805 0.5704391 0.2852195 [97,] 0.6773097 0.6453807 0.3226903 [98,] 0.6386165 0.7227670 0.3613835 [99,] 0.5969233 0.8061533 0.4030767 [100,] 0.5569759 0.8860481 0.4430241 [101,] 0.5069610 0.9860780 0.4930390 [102,] 0.4945730 0.9891460 0.5054270 [103,] 0.4585803 0.9171606 0.5414197 [104,] 0.4423864 0.8847727 0.5576136 [105,] 0.4084499 0.8168998 0.5915501 [106,] 0.3625891 0.7251783 0.6374109 [107,] 0.3425275 0.6850550 0.6574725 [108,] 0.4375085 0.8750170 0.5624915 [109,] 0.3846310 0.7692619 0.6153690 [110,] 0.3625142 0.7250285 0.6374858 [111,] 0.3965383 0.7930766 0.6034617 [112,] 0.3431909 0.6863818 0.6568091 [113,] 0.3189672 0.6379343 0.6810328 [114,] 0.2954333 0.5908666 0.7045667 [115,] 0.2555336 0.5110671 0.7444664 [116,] 0.2793596 0.5587191 0.7206404 [117,] 0.2546364 0.5092729 0.7453636 [118,] 0.3177224 0.6354448 0.6822776 [119,] 0.3295885 0.6591769 0.6704115 [120,] 0.3156112 0.6312224 0.6843888 [121,] 0.3329987 0.6659974 0.6670013 [122,] 0.2773305 0.5546611 0.7226695 [123,] 0.4599503 0.9199006 0.5400497 [124,] 0.3976122 0.7952244 0.6023878 [125,] 0.3457858 0.6915715 0.6542142 [126,] 0.3071052 0.6142105 0.6928948 [127,] 0.2908845 0.5817689 0.7091155 [128,] 0.2455569 0.4911137 0.7544431 [129,] 0.3079113 0.6158226 0.6920887 [130,] 0.2876447 0.5752893 0.7123553 [131,] 0.3295650 0.6591301 0.6704350 [132,] 0.2593626 0.5187252 0.7406374 [133,] 0.3550612 0.7101225 0.6449388 [134,] 0.2458746 0.4917491 0.7541254 [135,] 0.3120095 0.6240190 0.6879905 > postscript(file="/var/fisher/rcomp/tmp/1kr211355685340.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2lvef1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3tv0u1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4spy51355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/56ms21355685340.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 0.7386834 -0.3344797 -0.3364828 -0.3384858 -0.3404889 0.5647462 -0.3444950 8 9 10 11 12 13 14 -0.3464980 0.6514989 -0.2793440 -0.2813471 -0.3545102 -0.5971092 -0.2873562 15 16 17 18 19 20 21 0.3988847 0.3968816 -0.3927584 -0.2953684 0.6314685 0.5300723 -0.4652995 22 23 24 25 26 27 28 0.4560234 0.4595343 0.5286913 0.5427761 -0.6231489 0.6866042 -0.4632330 29 30 31 32 33 34 35 0.6114380 -0.5544871 -0.3925681 -0.3234111 -0.4893361 0.6014227 -0.4005803 36 37 38 39 40 41 42 -0.4025834 -0.5740223 0.5167365 0.4274855 -0.5745175 0.4880083 0.5087243 43 44 45 46 47 48 49 0.4906334 -0.3474477 -0.5845328 0.4134642 -0.4246169 0.5733800 0.4074550 50 51 52 53 54 55 56 -0.4306261 -0.5093031 -0.4628651 0.5633648 -0.3741094 -0.4406413 0.4806816 57 58 59 60 61 62 63 0.3147566 0.5533495 0.5513465 0.5211105 0.6185005 -0.6952586 -0.4566657 64 65 66 67 68 69 70 0.6124914 -0.4606718 -0.4626748 -0.5640710 -0.3955208 0.5313160 -0.5473611 71 72 73 74 75 76 77 -0.4726901 0.5253069 0.4466298 -0.4842131 0.5192977 0.3533727 0.5152916 78 79 80 81 82 83 84 0.2726926 0.5758144 -0.6546395 -0.4927206 0.4997625 -0.4967267 -0.4342008 85 86 87 88 89 90 91 0.3353453 -0.4315757 0.8416862 0.7630091 -0.2334800 0.7645169 -0.4014081 92 93 94 95 96 97 98 -0.1683291 -0.3342541 -0.2434953 -0.2454983 0.7524986 -0.1783443 -0.2515075 99 100 101 102 103 104 105 -0.1823504 0.7444865 0.8136435 -0.2595196 -0.2615227 -0.2635257 -0.3422028 106 107 108 109 110 111 112 -0.2675318 -0.2695349 -0.2770519 -0.2735410 -0.2043839 -0.4469830 -0.2795501 113 114 115 116 117 118 119 -0.3582272 -0.2890701 -0.2143992 -0.2875623 0.7815947 -0.2204083 -0.2935715 120 121 122 123 124 125 126 0.7044255 -0.2264175 -0.2995806 -0.3070976 0.4558173 0.6944102 -0.3075928 127 128 129 130 131 132 133 -0.4735178 0.6884011 -0.3136020 0.6843950 -0.2464480 0.7515490 -0.3271281 134 135 136 137 138 139 140 -0.3236172 -0.3256203 -0.3276233 0.5009378 0.4989347 -0.3336325 -0.3356355 141 142 143 144 145 146 147 0.7268904 0.5836844 -0.2704845 0.4924303 -0.5095727 0.6523462 -0.4263309 148 149 150 151 152 153 154 -0.3516599 -0.2825028 0.4804120 0.6423310 -0.2239831 -0.3899081 -0.3691921 > postscript(file="/var/fisher/rcomp/tmp/6ybf11355685340.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 0.7386834 NA 1 -0.3344797 0.7386834 2 -0.3364828 -0.3344797 3 -0.3384858 -0.3364828 4 -0.3404889 -0.3384858 5 0.5647462 -0.3404889 6 -0.3444950 0.5647462 7 -0.3464980 -0.3444950 8 0.6514989 -0.3464980 9 -0.2793440 0.6514989 10 -0.2813471 -0.2793440 11 -0.3545102 -0.2813471 12 -0.5971092 -0.3545102 13 -0.2873562 -0.5971092 14 0.3988847 -0.2873562 15 0.3968816 0.3988847 16 -0.3927584 0.3968816 17 -0.2953684 -0.3927584 18 0.6314685 -0.2953684 19 0.5300723 0.6314685 20 -0.4652995 0.5300723 21 0.4560234 -0.4652995 22 0.4595343 0.4560234 23 0.5286913 0.4595343 24 0.5427761 0.5286913 25 -0.6231489 0.5427761 26 0.6866042 -0.6231489 27 -0.4632330 0.6866042 28 0.6114380 -0.4632330 29 -0.5544871 0.6114380 30 -0.3925681 -0.5544871 31 -0.3234111 -0.3925681 32 -0.4893361 -0.3234111 33 0.6014227 -0.4893361 34 -0.4005803 0.6014227 35 -0.4025834 -0.4005803 36 -0.5740223 -0.4025834 37 0.5167365 -0.5740223 38 0.4274855 0.5167365 39 -0.5745175 0.4274855 40 0.4880083 -0.5745175 41 0.5087243 0.4880083 42 0.4906334 0.5087243 43 -0.3474477 0.4906334 44 -0.5845328 -0.3474477 45 0.4134642 -0.5845328 46 -0.4246169 0.4134642 47 0.5733800 -0.4246169 48 0.4074550 0.5733800 49 -0.4306261 0.4074550 50 -0.5093031 -0.4306261 51 -0.4628651 -0.5093031 52 0.5633648 -0.4628651 53 -0.3741094 0.5633648 54 -0.4406413 -0.3741094 55 0.4806816 -0.4406413 56 0.3147566 0.4806816 57 0.5533495 0.3147566 58 0.5513465 0.5533495 59 0.5211105 0.5513465 60 0.6185005 0.5211105 61 -0.6952586 0.6185005 62 -0.4566657 -0.6952586 63 0.6124914 -0.4566657 64 -0.4606718 0.6124914 65 -0.4626748 -0.4606718 66 -0.5640710 -0.4626748 67 -0.3955208 -0.5640710 68 0.5313160 -0.3955208 69 -0.5473611 0.5313160 70 -0.4726901 -0.5473611 71 0.5253069 -0.4726901 72 0.4466298 0.5253069 73 -0.4842131 0.4466298 74 0.5192977 -0.4842131 75 0.3533727 0.5192977 76 0.5152916 0.3533727 77 0.2726926 0.5152916 78 0.5758144 0.2726926 79 -0.6546395 0.5758144 80 -0.4927206 -0.6546395 81 0.4997625 -0.4927206 82 -0.4967267 0.4997625 83 -0.4342008 -0.4967267 84 0.3353453 -0.4342008 85 -0.4315757 0.3353453 86 0.8416862 -0.4315757 87 0.7630091 0.8416862 88 -0.2334800 0.7630091 89 0.7645169 -0.2334800 90 -0.4014081 0.7645169 91 -0.1683291 -0.4014081 92 -0.3342541 -0.1683291 93 -0.2434953 -0.3342541 94 -0.2454983 -0.2434953 95 0.7524986 -0.2454983 96 -0.1783443 0.7524986 97 -0.2515075 -0.1783443 98 -0.1823504 -0.2515075 99 0.7444865 -0.1823504 100 0.8136435 0.7444865 101 -0.2595196 0.8136435 102 -0.2615227 -0.2595196 103 -0.2635257 -0.2615227 104 -0.3422028 -0.2635257 105 -0.2675318 -0.3422028 106 -0.2695349 -0.2675318 107 -0.2770519 -0.2695349 108 -0.2735410 -0.2770519 109 -0.2043839 -0.2735410 110 -0.4469830 -0.2043839 111 -0.2795501 -0.4469830 112 -0.3582272 -0.2795501 113 -0.2890701 -0.3582272 114 -0.2143992 -0.2890701 115 -0.2875623 -0.2143992 116 0.7815947 -0.2875623 117 -0.2204083 0.7815947 118 -0.2935715 -0.2204083 119 0.7044255 -0.2935715 120 -0.2264175 0.7044255 121 -0.2995806 -0.2264175 122 -0.3070976 -0.2995806 123 0.4558173 -0.3070976 124 0.6944102 0.4558173 125 -0.3075928 0.6944102 126 -0.4735178 -0.3075928 127 0.6884011 -0.4735178 128 -0.3136020 0.6884011 129 0.6843950 -0.3136020 130 -0.2464480 0.6843950 131 0.7515490 -0.2464480 132 -0.3271281 0.7515490 133 -0.3236172 -0.3271281 134 -0.3256203 -0.3236172 135 -0.3276233 -0.3256203 136 0.5009378 -0.3276233 137 0.4989347 0.5009378 138 -0.3336325 0.4989347 139 -0.3356355 -0.3336325 140 0.7268904 -0.3356355 141 0.5836844 0.7268904 142 -0.2704845 0.5836844 143 0.4924303 -0.2704845 144 -0.5095727 0.4924303 145 0.6523462 -0.5095727 146 -0.4263309 0.6523462 147 -0.3516599 -0.4263309 148 -0.2825028 -0.3516599 149 0.4804120 -0.2825028 150 0.6423310 0.4804120 151 -0.2239831 0.6423310 152 -0.3899081 -0.2239831 153 -0.3691921 -0.3899081 154 NA -0.3691921 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.3344797 0.7386834 [2,] -0.3364828 -0.3344797 [3,] -0.3384858 -0.3364828 [4,] -0.3404889 -0.3384858 [5,] 0.5647462 -0.3404889 [6,] -0.3444950 0.5647462 [7,] -0.3464980 -0.3444950 [8,] 0.6514989 -0.3464980 [9,] -0.2793440 0.6514989 [10,] -0.2813471 -0.2793440 [11,] -0.3545102 -0.2813471 [12,] -0.5971092 -0.3545102 [13,] -0.2873562 -0.5971092 [14,] 0.3988847 -0.2873562 [15,] 0.3968816 0.3988847 [16,] -0.3927584 0.3968816 [17,] -0.2953684 -0.3927584 [18,] 0.6314685 -0.2953684 [19,] 0.5300723 0.6314685 [20,] -0.4652995 0.5300723 [21,] 0.4560234 -0.4652995 [22,] 0.4595343 0.4560234 [23,] 0.5286913 0.4595343 [24,] 0.5427761 0.5286913 [25,] -0.6231489 0.5427761 [26,] 0.6866042 -0.6231489 [27,] -0.4632330 0.6866042 [28,] 0.6114380 -0.4632330 [29,] -0.5544871 0.6114380 [30,] -0.3925681 -0.5544871 [31,] -0.3234111 -0.3925681 [32,] -0.4893361 -0.3234111 [33,] 0.6014227 -0.4893361 [34,] -0.4005803 0.6014227 [35,] -0.4025834 -0.4005803 [36,] -0.5740223 -0.4025834 [37,] 0.5167365 -0.5740223 [38,] 0.4274855 0.5167365 [39,] -0.5745175 0.4274855 [40,] 0.4880083 -0.5745175 [41,] 0.5087243 0.4880083 [42,] 0.4906334 0.5087243 [43,] -0.3474477 0.4906334 [44,] -0.5845328 -0.3474477 [45,] 0.4134642 -0.5845328 [46,] -0.4246169 0.4134642 [47,] 0.5733800 -0.4246169 [48,] 0.4074550 0.5733800 [49,] -0.4306261 0.4074550 [50,] -0.5093031 -0.4306261 [51,] -0.4628651 -0.5093031 [52,] 0.5633648 -0.4628651 [53,] -0.3741094 0.5633648 [54,] -0.4406413 -0.3741094 [55,] 0.4806816 -0.4406413 [56,] 0.3147566 0.4806816 [57,] 0.5533495 0.3147566 [58,] 0.5513465 0.5533495 [59,] 0.5211105 0.5513465 [60,] 0.6185005 0.5211105 [61,] -0.6952586 0.6185005 [62,] -0.4566657 -0.6952586 [63,] 0.6124914 -0.4566657 [64,] -0.4606718 0.6124914 [65,] -0.4626748 -0.4606718 [66,] -0.5640710 -0.4626748 [67,] -0.3955208 -0.5640710 [68,] 0.5313160 -0.3955208 [69,] -0.5473611 0.5313160 [70,] -0.4726901 -0.5473611 [71,] 0.5253069 -0.4726901 [72,] 0.4466298 0.5253069 [73,] -0.4842131 0.4466298 [74,] 0.5192977 -0.4842131 [75,] 0.3533727 0.5192977 [76,] 0.5152916 0.3533727 [77,] 0.2726926 0.5152916 [78,] 0.5758144 0.2726926 [79,] -0.6546395 0.5758144 [80,] -0.4927206 -0.6546395 [81,] 0.4997625 -0.4927206 [82,] -0.4967267 0.4997625 [83,] -0.4342008 -0.4967267 [84,] 0.3353453 -0.4342008 [85,] -0.4315757 0.3353453 [86,] 0.8416862 -0.4315757 [87,] 0.7630091 0.8416862 [88,] -0.2334800 0.7630091 [89,] 0.7645169 -0.2334800 [90,] -0.4014081 0.7645169 [91,] -0.1683291 -0.4014081 [92,] -0.3342541 -0.1683291 [93,] -0.2434953 -0.3342541 [94,] -0.2454983 -0.2434953 [95,] 0.7524986 -0.2454983 [96,] -0.1783443 0.7524986 [97,] -0.2515075 -0.1783443 [98,] -0.1823504 -0.2515075 [99,] 0.7444865 -0.1823504 [100,] 0.8136435 0.7444865 [101,] -0.2595196 0.8136435 [102,] -0.2615227 -0.2595196 [103,] -0.2635257 -0.2615227 [104,] -0.3422028 -0.2635257 [105,] -0.2675318 -0.3422028 [106,] -0.2695349 -0.2675318 [107,] -0.2770519 -0.2695349 [108,] -0.2735410 -0.2770519 [109,] -0.2043839 -0.2735410 [110,] -0.4469830 -0.2043839 [111,] -0.2795501 -0.4469830 [112,] -0.3582272 -0.2795501 [113,] -0.2890701 -0.3582272 [114,] -0.2143992 -0.2890701 [115,] -0.2875623 -0.2143992 [116,] 0.7815947 -0.2875623 [117,] -0.2204083 0.7815947 [118,] -0.2935715 -0.2204083 [119,] 0.7044255 -0.2935715 [120,] -0.2264175 0.7044255 [121,] -0.2995806 -0.2264175 [122,] -0.3070976 -0.2995806 [123,] 0.4558173 -0.3070976 [124,] 0.6944102 0.4558173 [125,] -0.3075928 0.6944102 [126,] -0.4735178 -0.3075928 [127,] 0.6884011 -0.4735178 [128,] -0.3136020 0.6884011 [129,] 0.6843950 -0.3136020 [130,] -0.2464480 0.6843950 [131,] 0.7515490 -0.2464480 [132,] -0.3271281 0.7515490 [133,] -0.3236172 -0.3271281 [134,] -0.3256203 -0.3236172 [135,] -0.3276233 -0.3256203 [136,] 0.5009378 -0.3276233 [137,] 0.4989347 0.5009378 [138,] -0.3336325 0.4989347 [139,] -0.3356355 -0.3336325 [140,] 0.7268904 -0.3356355 [141,] 0.5836844 0.7268904 [142,] -0.2704845 0.5836844 [143,] 0.4924303 -0.2704845 [144,] -0.5095727 0.4924303 [145,] 0.6523462 -0.5095727 [146,] -0.4263309 0.6523462 [147,] -0.3516599 -0.4263309 [148,] -0.2825028 -0.3516599 [149,] 0.4804120 -0.2825028 [150,] 0.6423310 0.4804120 [151,] -0.2239831 0.6423310 [152,] -0.3899081 -0.2239831 [153,] -0.3691921 -0.3899081 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.3344797 0.7386834 2 -0.3364828 -0.3344797 3 -0.3384858 -0.3364828 4 -0.3404889 -0.3384858 5 0.5647462 -0.3404889 6 -0.3444950 0.5647462 7 -0.3464980 -0.3444950 8 0.6514989 -0.3464980 9 -0.2793440 0.6514989 10 -0.2813471 -0.2793440 11 -0.3545102 -0.2813471 12 -0.5971092 -0.3545102 13 -0.2873562 -0.5971092 14 0.3988847 -0.2873562 15 0.3968816 0.3988847 16 -0.3927584 0.3968816 17 -0.2953684 -0.3927584 18 0.6314685 -0.2953684 19 0.5300723 0.6314685 20 -0.4652995 0.5300723 21 0.4560234 -0.4652995 22 0.4595343 0.4560234 23 0.5286913 0.4595343 24 0.5427761 0.5286913 25 -0.6231489 0.5427761 26 0.6866042 -0.6231489 27 -0.4632330 0.6866042 28 0.6114380 -0.4632330 29 -0.5544871 0.6114380 30 -0.3925681 -0.5544871 31 -0.3234111 -0.3925681 32 -0.4893361 -0.3234111 33 0.6014227 -0.4893361 34 -0.4005803 0.6014227 35 -0.4025834 -0.4005803 36 -0.5740223 -0.4025834 37 0.5167365 -0.5740223 38 0.4274855 0.5167365 39 -0.5745175 0.4274855 40 0.4880083 -0.5745175 41 0.5087243 0.4880083 42 0.4906334 0.5087243 43 -0.3474477 0.4906334 44 -0.5845328 -0.3474477 45 0.4134642 -0.5845328 46 -0.4246169 0.4134642 47 0.5733800 -0.4246169 48 0.4074550 0.5733800 49 -0.4306261 0.4074550 50 -0.5093031 -0.4306261 51 -0.4628651 -0.5093031 52 0.5633648 -0.4628651 53 -0.3741094 0.5633648 54 -0.4406413 -0.3741094 55 0.4806816 -0.4406413 56 0.3147566 0.4806816 57 0.5533495 0.3147566 58 0.5513465 0.5533495 59 0.5211105 0.5513465 60 0.6185005 0.5211105 61 -0.6952586 0.6185005 62 -0.4566657 -0.6952586 63 0.6124914 -0.4566657 64 -0.4606718 0.6124914 65 -0.4626748 -0.4606718 66 -0.5640710 -0.4626748 67 -0.3955208 -0.5640710 68 0.5313160 -0.3955208 69 -0.5473611 0.5313160 70 -0.4726901 -0.5473611 71 0.5253069 -0.4726901 72 0.4466298 0.5253069 73 -0.4842131 0.4466298 74 0.5192977 -0.4842131 75 0.3533727 0.5192977 76 0.5152916 0.3533727 77 0.2726926 0.5152916 78 0.5758144 0.2726926 79 -0.6546395 0.5758144 80 -0.4927206 -0.6546395 81 0.4997625 -0.4927206 82 -0.4967267 0.4997625 83 -0.4342008 -0.4967267 84 0.3353453 -0.4342008 85 -0.4315757 0.3353453 86 0.8416862 -0.4315757 87 0.7630091 0.8416862 88 -0.2334800 0.7630091 89 0.7645169 -0.2334800 90 -0.4014081 0.7645169 91 -0.1683291 -0.4014081 92 -0.3342541 -0.1683291 93 -0.2434953 -0.3342541 94 -0.2454983 -0.2434953 95 0.7524986 -0.2454983 96 -0.1783443 0.7524986 97 -0.2515075 -0.1783443 98 -0.1823504 -0.2515075 99 0.7444865 -0.1823504 100 0.8136435 0.7444865 101 -0.2595196 0.8136435 102 -0.2615227 -0.2595196 103 -0.2635257 -0.2615227 104 -0.3422028 -0.2635257 105 -0.2675318 -0.3422028 106 -0.2695349 -0.2675318 107 -0.2770519 -0.2695349 108 -0.2735410 -0.2770519 109 -0.2043839 -0.2735410 110 -0.4469830 -0.2043839 111 -0.2795501 -0.4469830 112 -0.3582272 -0.2795501 113 -0.2890701 -0.3582272 114 -0.2143992 -0.2890701 115 -0.2875623 -0.2143992 116 0.7815947 -0.2875623 117 -0.2204083 0.7815947 118 -0.2935715 -0.2204083 119 0.7044255 -0.2935715 120 -0.2264175 0.7044255 121 -0.2995806 -0.2264175 122 -0.3070976 -0.2995806 123 0.4558173 -0.3070976 124 0.6944102 0.4558173 125 -0.3075928 0.6944102 126 -0.4735178 -0.3075928 127 0.6884011 -0.4735178 128 -0.3136020 0.6884011 129 0.6843950 -0.3136020 130 -0.2464480 0.6843950 131 0.7515490 -0.2464480 132 -0.3271281 0.7515490 133 -0.3236172 -0.3271281 134 -0.3256203 -0.3236172 135 -0.3276233 -0.3256203 136 0.5009378 -0.3276233 137 0.4989347 0.5009378 138 -0.3336325 0.4989347 139 -0.3356355 -0.3336325 140 0.7268904 -0.3356355 141 0.5836844 0.7268904 142 -0.2704845 0.5836844 143 0.4924303 -0.2704845 144 -0.5095727 0.4924303 145 0.6523462 -0.5095727 146 -0.4263309 0.6523462 147 -0.3516599 -0.4263309 148 -0.2825028 -0.3516599 149 0.4804120 -0.2825028 150 0.6423310 0.4804120 151 -0.2239831 0.6423310 152 -0.3899081 -0.2239831 153 -0.3691921 -0.3899081 > 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/fisher/rcomp/tmp/741wy1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8hqob1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9rarn1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/10wpmk1355685340.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/fisher/rcomp/tmp/11dwbs1355685340.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/fisher/rcomp/tmp/12kktx1355685340.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/fisher/rcomp/tmp/135twg1355685340.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/fisher/rcomp/tmp/143i1d1355685340.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/fisher/rcomp/tmp/15ek8h1355685340.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/fisher/rcomp/tmp/16xt1u1355685340.tab") + } > > try(system("convert tmp/1kr211355685340.ps tmp/1kr211355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/2lvef1355685340.ps tmp/2lvef1355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/3tv0u1355685340.ps tmp/3tv0u1355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/4spy51355685340.ps tmp/4spy51355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/56ms21355685340.ps tmp/56ms21355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/6ybf11355685340.ps tmp/6ybf11355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/741wy1355685340.ps tmp/741wy1355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/8hqob1355685340.ps tmp/8hqob1355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/9rarn1355685340.ps tmp/9rarn1355685340.png",intern=TRUE)) character(0) > try(system("convert tmp/10wpmk1355685340.ps tmp/10wpmk1355685340.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.336 1.774 10.112