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Type 'q()' to quit R. > x <- array(list(1775 + ,0 + ,2197 + ,0 + ,2920 + ,0 + ,4240 + ,0 + ,5415 + ,0 + ,6136 + ,0 + ,6719 + ,0 + ,6234 + ,0 + ,7152 + ,0 + ,3646 + ,0 + ,2165 + ,0 + ,2803 + ,0 + ,1615 + ,0 + ,2350 + ,0 + ,3350 + ,0 + ,3536 + ,0 + ,5834 + ,0 + ,6767 + ,0 + ,5993 + ,0 + ,7276 + ,0 + ,5641 + ,0 + ,3477 + ,0 + ,2247 + ,0 + ,2466 + ,0 + ,1567 + ,0 + ,2237 + ,0 + ,2598 + ,0 + ,3729 + ,0 + ,5715 + ,0 + ,5776 + ,0 + ,5852 + ,0 + ,6878 + ,0 + ,5488 + ,0 + ,3583 + ,0 + ,2054 + ,0 + ,2282 + ,0 + ,1552 + ,0 + ,2261 + ,0 + ,2446 + ,0 + ,3519 + ,0 + ,5161 + ,0 + ,5085 + ,0 + ,5711 + ,0 + ,6057 + ,0 + ,5224 + ,0 + ,3363 + ,0 + ,1899 + ,0 + ,2115 + ,0 + ,1491 + ,0 + ,2061 + ,0 + ,2419 + ,0 + ,3430 + ,0 + ,4778 + ,0 + ,4862 + ,0 + ,6176 + ,0 + ,5664 + ,0 + ,5529 + ,0 + ,3418 + ,0 + ,1941 + ,0 + ,2402 + ,0 + ,1579 + ,0 + ,2146 + ,0 + ,2462 + ,0 + ,3695 + ,0 + ,4831 + ,0 + ,5134 + ,0 + ,6250 + ,0 + ,5760 + ,0 + ,6249 + ,0 + ,2917 + ,0 + ,1741 + ,0 + ,2359 + ,0 + ,1511 + ,0 + ,2059 + ,0 + ,2635 + ,0 + ,2867 + ,0 + ,4403 + ,0 + ,5720 + ,0 + ,4502 + ,0 + ,5749 + ,0 + ,5627 + ,0 + ,2846 + ,0 + ,1762 + ,0 + ,2429 + ,0 + ,1169 + ,0 + ,2154 + ,0 + ,2249 + ,0 + ,2687 + ,0 + ,4359 + ,0 + ,5382 + ,0 + ,4459 + ,0 + ,6398 + ,0 + ,4596 + ,0 + ,3024 + ,0 + ,1887 + ,0 + ,2070 + ,0 + ,1351 + ,0 + ,2218 + ,0 + ,2461 + ,0 + ,3028 + ,0 + ,4784 + ,0 + ,4975 + ,0 + ,4607 + ,1 + ,6249 + ,1 + ,4809 + ,1 + ,3157 + ,1 + ,1910 + ,1 + ,2228 + ,1 + ,1594 + ,1 + ,2467 + ,1 + ,2222 + ,1 + ,3607 + ,1 + ,4685 + ,1 + ,4962 + ,1 + ,5770 + ,1 + ,5480 + ,1 + ,5000 + ,1 + ,3228 + ,1 + ,1993 + ,1 + ,2288 + ,1 + ,1588 + ,1 + ,2105 + ,1 + ,2191 + ,1 + ,3591 + ,1 + ,4668 + ,1 + ,4885 + ,1 + ,5822 + ,1 + ,5599 + ,1 + ,5340 + ,1 + ,3082 + ,1 + ,2010 + ,1 + ,2301 + ,1 + ,1507 + ,1 + ,1992 + ,1 + ,2487 + ,1 + ,3490 + ,1 + ,4647 + ,1 + ,5594 + ,1 + ,5611 + ,1 + ,5788 + ,1 + ,6204 + ,1 + ,3013 + ,1 + ,1931 + ,1 + ,2549 + ,1 + ,1504 + ,1 + ,2090 + ,1 + ,2702 + ,1 + ,2939 + ,1 + ,4500 + ,1 + ,6208 + ,1 + ,6415 + ,1 + ,5657 + ,1 + ,5964 + ,1 + ,3163 + ,1 + ,1997 + ,1 + ,2422 + ,1 + ,1376 + ,1 + ,2202 + ,1 + ,2683 + ,1 + ,3303 + ,1 + ,5202 + ,1 + ,5231 + ,1 + ,4880 + ,1 + ,7998 + ,1 + ,4977 + ,1 + ,3531 + ,1 + ,2025 + ,1 + ,2205 + ,1 + ,1442 + ,1 + ,2238 + ,1 + ,2179 + ,1 + ,3218 + ,1 + ,5139 + ,1 + ,4990 + ,1 + ,4914 + ,1 + ,6084 + ,1 + ,5672 + ,1 + ,3548 + ,1 + ,1793 + ,1 + ,2086 + ,1) + ,dim=c(2 + ,180) + ,dimnames=list(c('Huwelijken' + ,'Dummy') + ,1:180)) > y <- array(NA,dim=c(2,180),dimnames=list(c('Huwelijken','Dummy'),1:180)) > 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 = 'Include Monthly 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 Huwelijken Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1 1775 0 1 0 0 0 0 0 0 0 0 0 0 2 2197 0 0 1 0 0 0 0 0 0 0 0 0 3 2920 0 0 0 1 0 0 0 0 0 0 0 0 4 4240 0 0 0 0 1 0 0 0 0 0 0 0 5 5415 0 0 0 0 0 1 0 0 0 0 0 0 6 6136 0 0 0 0 0 0 1 0 0 0 0 0 7 6719 0 0 0 0 0 0 0 1 0 0 0 0 8 6234 0 0 0 0 0 0 0 0 1 0 0 0 9 7152 0 0 0 0 0 0 0 0 0 1 0 0 10 3646 0 0 0 0 0 0 0 0 0 0 1 0 11 2165 0 0 0 0 0 0 0 0 0 0 0 1 12 2803 0 0 0 0 0 0 0 0 0 0 0 0 13 1615 0 1 0 0 0 0 0 0 0 0 0 0 14 2350 0 0 1 0 0 0 0 0 0 0 0 0 15 3350 0 0 0 1 0 0 0 0 0 0 0 0 16 3536 0 0 0 0 1 0 0 0 0 0 0 0 17 5834 0 0 0 0 0 1 0 0 0 0 0 0 18 6767 0 0 0 0 0 0 1 0 0 0 0 0 19 5993 0 0 0 0 0 0 0 1 0 0 0 0 20 7276 0 0 0 0 0 0 0 0 1 0 0 0 21 5641 0 0 0 0 0 0 0 0 0 1 0 0 22 3477 0 0 0 0 0 0 0 0 0 0 1 0 23 2247 0 0 0 0 0 0 0 0 0 0 0 1 24 2466 0 0 0 0 0 0 0 0 0 0 0 0 25 1567 0 1 0 0 0 0 0 0 0 0 0 0 26 2237 0 0 1 0 0 0 0 0 0 0 0 0 27 2598 0 0 0 1 0 0 0 0 0 0 0 0 28 3729 0 0 0 0 1 0 0 0 0 0 0 0 29 5715 0 0 0 0 0 1 0 0 0 0 0 0 30 5776 0 0 0 0 0 0 1 0 0 0 0 0 31 5852 0 0 0 0 0 0 0 1 0 0 0 0 32 6878 0 0 0 0 0 0 0 0 1 0 0 0 33 5488 0 0 0 0 0 0 0 0 0 1 0 0 34 3583 0 0 0 0 0 0 0 0 0 0 1 0 35 2054 0 0 0 0 0 0 0 0 0 0 0 1 36 2282 0 0 0 0 0 0 0 0 0 0 0 0 37 1552 0 1 0 0 0 0 0 0 0 0 0 0 38 2261 0 0 1 0 0 0 0 0 0 0 0 0 39 2446 0 0 0 1 0 0 0 0 0 0 0 0 40 3519 0 0 0 0 1 0 0 0 0 0 0 0 41 5161 0 0 0 0 0 1 0 0 0 0 0 0 42 5085 0 0 0 0 0 0 1 0 0 0 0 0 43 5711 0 0 0 0 0 0 0 1 0 0 0 0 44 6057 0 0 0 0 0 0 0 0 1 0 0 0 45 5224 0 0 0 0 0 0 0 0 0 1 0 0 46 3363 0 0 0 0 0 0 0 0 0 0 1 0 47 1899 0 0 0 0 0 0 0 0 0 0 0 1 48 2115 0 0 0 0 0 0 0 0 0 0 0 0 49 1491 0 1 0 0 0 0 0 0 0 0 0 0 50 2061 0 0 1 0 0 0 0 0 0 0 0 0 51 2419 0 0 0 1 0 0 0 0 0 0 0 0 52 3430 0 0 0 0 1 0 0 0 0 0 0 0 53 4778 0 0 0 0 0 1 0 0 0 0 0 0 54 4862 0 0 0 0 0 0 1 0 0 0 0 0 55 6176 0 0 0 0 0 0 0 1 0 0 0 0 56 5664 0 0 0 0 0 0 0 0 1 0 0 0 57 5529 0 0 0 0 0 0 0 0 0 1 0 0 58 3418 0 0 0 0 0 0 0 0 0 0 1 0 59 1941 0 0 0 0 0 0 0 0 0 0 0 1 60 2402 0 0 0 0 0 0 0 0 0 0 0 0 61 1579 0 1 0 0 0 0 0 0 0 0 0 0 62 2146 0 0 1 0 0 0 0 0 0 0 0 0 63 2462 0 0 0 1 0 0 0 0 0 0 0 0 64 3695 0 0 0 0 1 0 0 0 0 0 0 0 65 4831 0 0 0 0 0 1 0 0 0 0 0 0 66 5134 0 0 0 0 0 0 1 0 0 0 0 0 67 6250 0 0 0 0 0 0 0 1 0 0 0 0 68 5760 0 0 0 0 0 0 0 0 1 0 0 0 69 6249 0 0 0 0 0 0 0 0 0 1 0 0 70 2917 0 0 0 0 0 0 0 0 0 0 1 0 71 1741 0 0 0 0 0 0 0 0 0 0 0 1 72 2359 0 0 0 0 0 0 0 0 0 0 0 0 73 1511 0 1 0 0 0 0 0 0 0 0 0 0 74 2059 0 0 1 0 0 0 0 0 0 0 0 0 75 2635 0 0 0 1 0 0 0 0 0 0 0 0 76 2867 0 0 0 0 1 0 0 0 0 0 0 0 77 4403 0 0 0 0 0 1 0 0 0 0 0 0 78 5720 0 0 0 0 0 0 1 0 0 0 0 0 79 4502 0 0 0 0 0 0 0 1 0 0 0 0 80 5749 0 0 0 0 0 0 0 0 1 0 0 0 81 5627 0 0 0 0 0 0 0 0 0 1 0 0 82 2846 0 0 0 0 0 0 0 0 0 0 1 0 83 1762 0 0 0 0 0 0 0 0 0 0 0 1 84 2429 0 0 0 0 0 0 0 0 0 0 0 0 85 1169 0 1 0 0 0 0 0 0 0 0 0 0 86 2154 0 0 1 0 0 0 0 0 0 0 0 0 87 2249 0 0 0 1 0 0 0 0 0 0 0 0 88 2687 0 0 0 0 1 0 0 0 0 0 0 0 89 4359 0 0 0 0 0 1 0 0 0 0 0 0 90 5382 0 0 0 0 0 0 1 0 0 0 0 0 91 4459 0 0 0 0 0 0 0 1 0 0 0 0 92 6398 0 0 0 0 0 0 0 0 1 0 0 0 93 4596 0 0 0 0 0 0 0 0 0 1 0 0 94 3024 0 0 0 0 0 0 0 0 0 0 1 0 95 1887 0 0 0 0 0 0 0 0 0 0 0 1 96 2070 0 0 0 0 0 0 0 0 0 0 0 0 97 1351 0 1 0 0 0 0 0 0 0 0 0 0 98 2218 0 0 1 0 0 0 0 0 0 0 0 0 99 2461 0 0 0 1 0 0 0 0 0 0 0 0 100 3028 0 0 0 0 1 0 0 0 0 0 0 0 101 4784 0 0 0 0 0 1 0 0 0 0 0 0 102 4975 0 0 0 0 0 0 1 0 0 0 0 0 103 4607 1 0 0 0 0 0 0 1 0 0 0 0 104 6249 1 0 0 0 0 0 0 0 1 0 0 0 105 4809 1 0 0 0 0 0 0 0 0 1 0 0 106 3157 1 0 0 0 0 0 0 0 0 0 1 0 107 1910 1 0 0 0 0 0 0 0 0 0 0 1 108 2228 1 0 0 0 0 0 0 0 0 0 0 0 109 1594 1 1 0 0 0 0 0 0 0 0 0 0 110 2467 1 0 1 0 0 0 0 0 0 0 0 0 111 2222 1 0 0 1 0 0 0 0 0 0 0 0 112 3607 1 0 0 0 1 0 0 0 0 0 0 0 113 4685 1 0 0 0 0 1 0 0 0 0 0 0 114 4962 1 0 0 0 0 0 1 0 0 0 0 0 115 5770 1 0 0 0 0 0 0 1 0 0 0 0 116 5480 1 0 0 0 0 0 0 0 1 0 0 0 117 5000 1 0 0 0 0 0 0 0 0 1 0 0 118 3228 1 0 0 0 0 0 0 0 0 0 1 0 119 1993 1 0 0 0 0 0 0 0 0 0 0 1 120 2288 1 0 0 0 0 0 0 0 0 0 0 0 121 1588 1 1 0 0 0 0 0 0 0 0 0 0 122 2105 1 0 1 0 0 0 0 0 0 0 0 0 123 2191 1 0 0 1 0 0 0 0 0 0 0 0 124 3591 1 0 0 0 1 0 0 0 0 0 0 0 125 4668 1 0 0 0 0 1 0 0 0 0 0 0 126 4885 1 0 0 0 0 0 1 0 0 0 0 0 127 5822 1 0 0 0 0 0 0 1 0 0 0 0 128 5599 1 0 0 0 0 0 0 0 1 0 0 0 129 5340 1 0 0 0 0 0 0 0 0 1 0 0 130 3082 1 0 0 0 0 0 0 0 0 0 1 0 131 2010 1 0 0 0 0 0 0 0 0 0 0 1 132 2301 1 0 0 0 0 0 0 0 0 0 0 0 133 1507 1 1 0 0 0 0 0 0 0 0 0 0 134 1992 1 0 1 0 0 0 0 0 0 0 0 0 135 2487 1 0 0 1 0 0 0 0 0 0 0 0 136 3490 1 0 0 0 1 0 0 0 0 0 0 0 137 4647 1 0 0 0 0 1 0 0 0 0 0 0 138 5594 1 0 0 0 0 0 1 0 0 0 0 0 139 5611 1 0 0 0 0 0 0 1 0 0 0 0 140 5788 1 0 0 0 0 0 0 0 1 0 0 0 141 6204 1 0 0 0 0 0 0 0 0 1 0 0 142 3013 1 0 0 0 0 0 0 0 0 0 1 0 143 1931 1 0 0 0 0 0 0 0 0 0 0 1 144 2549 1 0 0 0 0 0 0 0 0 0 0 0 145 1504 1 1 0 0 0 0 0 0 0 0 0 0 146 2090 1 0 1 0 0 0 0 0 0 0 0 0 147 2702 1 0 0 1 0 0 0 0 0 0 0 0 148 2939 1 0 0 0 1 0 0 0 0 0 0 0 149 4500 1 0 0 0 0 1 0 0 0 0 0 0 150 6208 1 0 0 0 0 0 1 0 0 0 0 0 151 6415 1 0 0 0 0 0 0 1 0 0 0 0 152 5657 1 0 0 0 0 0 0 0 1 0 0 0 153 5964 1 0 0 0 0 0 0 0 0 1 0 0 154 3163 1 0 0 0 0 0 0 0 0 0 1 0 155 1997 1 0 0 0 0 0 0 0 0 0 0 1 156 2422 1 0 0 0 0 0 0 0 0 0 0 0 157 1376 1 1 0 0 0 0 0 0 0 0 0 0 158 2202 1 0 1 0 0 0 0 0 0 0 0 0 159 2683 1 0 0 1 0 0 0 0 0 0 0 0 160 3303 1 0 0 0 1 0 0 0 0 0 0 0 161 5202 1 0 0 0 0 1 0 0 0 0 0 0 162 5231 1 0 0 0 0 0 1 0 0 0 0 0 163 4880 1 0 0 0 0 0 0 1 0 0 0 0 164 7998 1 0 0 0 0 0 0 0 1 0 0 0 165 4977 1 0 0 0 0 0 0 0 0 1 0 0 166 3531 1 0 0 0 0 0 0 0 0 0 1 0 167 2025 1 0 0 0 0 0 0 0 0 0 0 1 168 2205 1 0 0 0 0 0 0 0 0 0 0 0 169 1442 1 1 0 0 0 0 0 0 0 0 0 0 170 2238 1 0 1 0 0 0 0 0 0 0 0 0 171 2179 1 0 0 1 0 0 0 0 0 0 0 0 172 3218 1 0 0 0 1 0 0 0 0 0 0 0 173 5139 1 0 0 0 0 1 0 0 0 0 0 0 174 4990 1 0 0 0 0 0 1 0 0 0 0 0 175 4914 1 0 0 0 0 0 0 1 0 0 0 0 176 6084 1 0 0 0 0 0 0 0 1 0 0 0 177 5672 1 0 0 0 0 0 0 0 0 1 0 0 178 3548 1 0 0 0 0 0 0 0 0 0 1 0 179 1793 1 0 0 0 0 0 0 0 0 0 0 1 180 2086 1 0 0 0 0 0 0 0 0 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy M1 M2 M3 M4 2392.6 -126.4 -834.0 -157.0 191.5 1049.8 M5 M6 M7 M8 M9 M10 2599.3 3105.0 3245.1 3857.7 3231.1 932.7 M11 -376.7 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1178.699 -209.442 -5.465 174.057 1873.989 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2392.6 118.8 20.149 < 2e-16 *** Dummy -126.3 66.9 -1.889 0.0606 . M1 -834.0 162.1 -5.145 7.42e-07 *** M2 -157.0 162.1 -0.968 0.3343 M3 191.5 162.1 1.182 0.2391 M4 1049.8 162.1 6.477 1.00e-09 *** M5 2599.3 162.1 16.036 < 2e-16 *** M6 3105.0 162.1 19.156 < 2e-16 *** M7 3245.1 162.0 20.028 < 2e-16 *** M8 3857.7 162.0 23.809 < 2e-16 *** M9 3231.1 162.0 19.942 < 2e-16 *** M10 932.7 162.0 5.757 4.02e-08 *** M11 -376.7 162.0 -2.325 0.0213 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 443.7 on 167 degrees of freedom Multiple R-squared: 0.9349, Adjusted R-squared: 0.9302 F-statistic: 199.9 on 12 and 167 DF, p-value: < 2.2e-16 > 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,] 0.44456533 0.88913066 0.55543467 [2,] 0.38377644 0.76755289 0.61622356 [3,] 0.46768111 0.93536222 0.53231889 [4,] 0.55367205 0.89265589 0.44632795 [5,] 0.78822128 0.42355744 0.21177872 [6,] 0.96655509 0.06688982 0.03344491 [7,] 0.94754800 0.10490399 0.05245200 [8,] 0.92125376 0.15749247 0.07874624 [9,] 0.89549670 0.20900661 0.10450330 [10,] 0.85519355 0.28961290 0.14480645 [11,] 0.80427752 0.39144496 0.19572248 [12,] 0.80160361 0.39679278 0.19839639 [13,] 0.75662926 0.48674147 0.24337074 [14,] 0.73456500 0.53087000 0.26543500 [15,] 0.77847400 0.44305201 0.22152600 [16,] 0.77901922 0.44196156 0.22098078 [17,] 0.76131358 0.47737283 0.23868642 [18,] 0.84356243 0.31287514 0.15643757 [19,] 0.80868488 0.38263024 0.19131512 [20,] 0.76696343 0.46607314 0.23303657 [21,] 0.73770406 0.52459188 0.26229594 [22,] 0.68696474 0.62607052 0.31303526 [23,] 0.63109564 0.73780872 0.36890436 [24,] 0.63217063 0.73565873 0.36782937 [25,] 0.60236681 0.79526637 0.39763319 [26,] 0.61356726 0.77286549 0.38643274 [27,] 0.79767014 0.40465971 0.20232986 [28,] 0.79508706 0.40982588 0.20491294 [29,] 0.82625765 0.34748471 0.17374235 [30,] 0.87246716 0.25506568 0.12753284 [31,] 0.84850838 0.30298324 0.15149162 [32,] 0.82179530 0.35640940 0.17820470 [33,] 0.80460678 0.39078645 0.19539322 [34,] 0.76845736 0.46308528 0.23154264 [35,] 0.73202795 0.53594409 0.26797205 [36,] 0.71277540 0.57444920 0.28722460 [37,] 0.68732492 0.62535017 0.31267508 [38,] 0.72663796 0.54672407 0.27336204 [39,] 0.83259233 0.33481535 0.16740767 [40,] 0.84496097 0.31007806 0.15503903 [41,] 0.89290458 0.21419083 0.10709542 [42,] 0.87806089 0.24387822 0.12193911 [43,] 0.85773760 0.28452480 0.14226240 [44,] 0.83083789 0.33832422 0.16916211 [45,] 0.80023050 0.39953900 0.19976950 [46,] 0.76722657 0.46554687 0.23277343 [47,] 0.72919463 0.54161073 0.27080537 [48,] 0.69913430 0.60173140 0.30086570 [49,] 0.68380717 0.63238566 0.31619283 [50,] 0.68397861 0.63204278 0.31602139 [51,] 0.68619513 0.62760974 0.31380487 [52,] 0.75419987 0.49160026 0.24580013 [53,] 0.76794252 0.46411497 0.23205748 [54,] 0.83074272 0.33851456 0.16925728 [55,] 0.83018567 0.33962865 0.16981433 [56,] 0.80823279 0.38353443 0.19176721 [57,] 0.77932674 0.44134651 0.22067326 [58,] 0.74846982 0.50306036 0.25153018 [59,] 0.71259522 0.57480956 0.28740478 [60,] 0.68810520 0.62378960 0.31189480 [61,] 0.72884787 0.54230427 0.27115213 [62,] 0.77301933 0.45396135 0.22698067 [63,] 0.77030268 0.45939465 0.22969732 [64,] 0.92816667 0.14366666 0.07183333 [65,] 0.92538680 0.14922639 0.07461320 [66,] 0.92158709 0.15682581 0.07841291 [67,] 0.91727433 0.16545135 0.08272567 [68,] 0.90101717 0.19796565 0.09898283 [69,] 0.88727236 0.22545528 0.11272764 [70,] 0.87370915 0.25258170 0.12629085 [71,] 0.85056765 0.29886471 0.14943235 [72,] 0.83488388 0.33023224 0.16511612 [73,] 0.86447627 0.27104746 0.13552373 [74,] 0.87615743 0.24768515 0.12384257 [75,] 0.86093757 0.27812487 0.13906243 [76,] 0.94398243 0.11203514 0.05601757 [77,] 0.93888810 0.12222379 0.06111190 [78,] 0.96922547 0.06154905 0.03077453 [79,] 0.96189492 0.07621017 0.03810508 [80,] 0.95159314 0.09681372 0.04840686 [81,] 0.94167779 0.11664442 0.05832221 [82,] 0.92780639 0.14438722 0.07219361 [83,] 0.91202206 0.17595587 0.08797794 [84,] 0.89636170 0.20727659 0.10363830 [85,] 0.88199298 0.23601405 0.11800702 [86,] 0.86393435 0.27213131 0.13606565 [87,] 0.85435530 0.29128941 0.14564470 [88,] 0.89131071 0.21737858 0.10868929 [89,] 0.89082492 0.21835015 0.10917508 [90,] 0.90280803 0.19438394 0.09719197 [91,] 0.88879331 0.22241338 0.11120669 [92,] 0.87146419 0.25707163 0.12853581 [93,] 0.84823152 0.30353696 0.15176848 [94,] 0.82775697 0.34448606 0.17224303 [95,] 0.82036902 0.35926197 0.17963098 [96,] 0.79305878 0.41388244 0.20694122 [97,] 0.77536615 0.44926770 0.22463385 [98,] 0.74068496 0.51863008 0.25931504 [99,] 0.72626903 0.54746194 0.27373097 [100,] 0.70025173 0.59949655 0.29974827 [101,] 0.73984147 0.52031706 0.26015853 [102,] 0.75178920 0.49642160 0.24821080 [103,] 0.71338538 0.57322924 0.28661462 [104,] 0.67399190 0.65201620 0.32600810 [105,] 0.62937903 0.74124195 0.37062097 [106,] 0.58826984 0.82346031 0.41173016 [107,] 0.53928192 0.92143616 0.46071808 [108,] 0.50485712 0.99028576 0.49514288 [109,] 0.47928917 0.95857833 0.52071083 [110,] 0.43516454 0.87032908 0.56483546 [111,] 0.44645468 0.89290936 0.55354532 [112,] 0.42387362 0.84774725 0.57612638 [113,] 0.46952286 0.93904572 0.53047714 [114,] 0.43686490 0.87372980 0.56313510 [115,] 0.39284699 0.78569397 0.60715301 [116,] 0.34612764 0.69225528 0.65387236 [117,] 0.29876726 0.59753452 0.70123274 [118,] 0.25510916 0.51021832 0.74489084 [119,] 0.21670096 0.43340193 0.78329904 [120,] 0.17913067 0.35826135 0.82086933 [121,] 0.15595206 0.31190411 0.84404794 [122,] 0.13199099 0.26398198 0.86800901 [123,] 0.10796007 0.21592015 0.89203993 [124,] 0.08650459 0.17300918 0.91349541 [125,] 0.10076813 0.20153626 0.89923187 [126,] 0.12183130 0.24366261 0.87816870 [127,] 0.10513406 0.21026813 0.89486594 [128,] 0.08038038 0.16076076 0.91961962 [129,] 0.06635462 0.13270924 0.93364538 [130,] 0.04909790 0.09819580 0.95090210 [131,] 0.03556865 0.07113729 0.96443135 [132,] 0.02693559 0.05387118 0.97306441 [133,] 0.02085035 0.04170070 0.97914965 [134,] 0.02086338 0.04172676 0.97913662 [135,] 0.04695554 0.09391108 0.95304446 [136,] 0.21428215 0.42856431 0.78571785 [137,] 0.52844797 0.94310407 0.47155203 [138,] 0.56200384 0.87599233 0.43799616 [139,] 0.51742466 0.96515068 0.48257534 [140,] 0.43494649 0.86989297 0.56505351 [141,] 0.37044366 0.74088732 0.62955634 [142,] 0.28914461 0.57828921 0.71085539 [143,] 0.21493114 0.42986227 0.78506886 [144,] 0.18288344 0.36576687 0.81711656 [145,] 0.12345065 0.24690130 0.87654935 [146,] 0.07848710 0.15697419 0.92151290 [147,] 0.04727449 0.09454898 0.95272551 [148,] 0.02587263 0.05174526 0.97412737 [149,] 0.72437268 0.55125465 0.27562732 > postscript(file="/var/www/html/rcomp/tmp/1honc1293454152.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2sx4x1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3sx4x1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4sx4x1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5sx4x1293454152.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 = 180 Frequency = 1 1 2 3 4 5 6 216.391515 -38.675152 335.858182 797.524848 423.058182 638.324848 7 8 9 10 11 12 1081.301212 -16.365455 1528.234545 320.634545 149.034545 410.367879 13 14 15 16 17 18 56.391515 114.324848 765.858182 93.524848 842.058182 1269.324848 19 20 21 22 23 24 355.301212 1025.634545 17.234545 151.634545 231.034545 73.367879 25 26 27 28 29 30 8.391515 1.324848 13.858182 286.524848 723.058182 278.324848 31 32 33 34 35 36 214.301212 627.634545 -135.765455 257.634545 38.034545 -110.632121 37 38 39 40 41 42 -6.608485 25.324848 -138.141818 76.524848 169.058182 -412.675152 43 44 45 46 47 48 73.301212 -193.365455 -399.765455 37.634545 -116.965455 -277.632121 49 50 51 52 53 54 -67.608485 -174.675152 -165.141818 -12.475152 -213.941818 -635.675152 55 56 57 58 59 60 538.301212 -586.365455 -94.765455 92.634545 -74.965455 9.367879 61 62 63 64 65 66 20.391515 -89.675152 -122.141818 252.524848 -160.941818 -363.675152 67 68 69 70 71 72 612.301212 -490.365455 625.234545 -408.365455 -274.965455 -33.632121 73 74 75 76 77 78 -47.608485 -176.675152 50.858182 -575.475152 -588.941818 222.324848 79 80 81 82 83 84 -1135.698788 -501.365455 3.234545 -479.365455 -253.965455 36.367879 85 86 87 88 89 90 -389.608485 -81.675152 -335.141818 -755.475152 -632.941818 -115.675152 91 92 93 94 95 96 -1178.698788 147.634545 -1027.765455 -301.365455 -128.965455 -322.632121 97 98 99 100 101 102 -207.608485 -17.675152 -123.141818 -414.475152 -207.941818 -522.675152 103 104 105 106 107 108 -904.344242 124.989091 -688.410909 -42.010909 20.389091 -38.277576 109 110 111 112 113 114 161.746061 357.679394 -235.787273 290.879394 -180.587273 -409.320606 115 116 117 118 119 120 258.655758 -644.010909 -497.410909 28.989091 103.389091 21.722424 121 122 123 124 125 126 155.746061 -4.320606 -266.787273 274.879394 -197.587273 -486.320606 127 128 129 130 131 132 310.655758 -525.010909 -157.410909 -117.010909 120.389091 34.722424 133 134 135 136 137 138 74.746061 -117.320606 29.212727 173.879394 -218.587273 222.679394 139 140 141 142 143 144 99.655758 -336.010909 706.589091 -186.010909 41.389091 282.722424 145 146 147 148 149 150 71.746061 -19.320606 244.212727 -377.120606 -365.587273 836.679394 151 152 153 154 155 156 903.655758 -467.010909 466.589091 -36.010909 107.389091 155.722424 157 158 159 160 161 162 -56.253939 92.679394 225.212727 -13.120606 336.412727 -140.320606 163 164 165 166 167 168 -631.344242 1873.989091 -520.410909 331.989091 135.389091 -61.277576 169 170 171 172 173 174 9.746061 128.679394 -278.787273 -98.120606 273.412727 -381.320606 175 176 177 178 179 180 -597.344242 -40.010909 174.589091 348.989091 -96.610909 -180.277576 > postscript(file="/var/www/html/rcomp/tmp/6kpli1293454152.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 = 180 Frequency = 1 lag(myerror, k = 1) myerror 0 216.391515 NA 1 -38.675152 216.391515 2 335.858182 -38.675152 3 797.524848 335.858182 4 423.058182 797.524848 5 638.324848 423.058182 6 1081.301212 638.324848 7 -16.365455 1081.301212 8 1528.234545 -16.365455 9 320.634545 1528.234545 10 149.034545 320.634545 11 410.367879 149.034545 12 56.391515 410.367879 13 114.324848 56.391515 14 765.858182 114.324848 15 93.524848 765.858182 16 842.058182 93.524848 17 1269.324848 842.058182 18 355.301212 1269.324848 19 1025.634545 355.301212 20 17.234545 1025.634545 21 151.634545 17.234545 22 231.034545 151.634545 23 73.367879 231.034545 24 8.391515 73.367879 25 1.324848 8.391515 26 13.858182 1.324848 27 286.524848 13.858182 28 723.058182 286.524848 29 278.324848 723.058182 30 214.301212 278.324848 31 627.634545 214.301212 32 -135.765455 627.634545 33 257.634545 -135.765455 34 38.034545 257.634545 35 -110.632121 38.034545 36 -6.608485 -110.632121 37 25.324848 -6.608485 38 -138.141818 25.324848 39 76.524848 -138.141818 40 169.058182 76.524848 41 -412.675152 169.058182 42 73.301212 -412.675152 43 -193.365455 73.301212 44 -399.765455 -193.365455 45 37.634545 -399.765455 46 -116.965455 37.634545 47 -277.632121 -116.965455 48 -67.608485 -277.632121 49 -174.675152 -67.608485 50 -165.141818 -174.675152 51 -12.475152 -165.141818 52 -213.941818 -12.475152 53 -635.675152 -213.941818 54 538.301212 -635.675152 55 -586.365455 538.301212 56 -94.765455 -586.365455 57 92.634545 -94.765455 58 -74.965455 92.634545 59 9.367879 -74.965455 60 20.391515 9.367879 61 -89.675152 20.391515 62 -122.141818 -89.675152 63 252.524848 -122.141818 64 -160.941818 252.524848 65 -363.675152 -160.941818 66 612.301212 -363.675152 67 -490.365455 612.301212 68 625.234545 -490.365455 69 -408.365455 625.234545 70 -274.965455 -408.365455 71 -33.632121 -274.965455 72 -47.608485 -33.632121 73 -176.675152 -47.608485 74 50.858182 -176.675152 75 -575.475152 50.858182 76 -588.941818 -575.475152 77 222.324848 -588.941818 78 -1135.698788 222.324848 79 -501.365455 -1135.698788 80 3.234545 -501.365455 81 -479.365455 3.234545 82 -253.965455 -479.365455 83 36.367879 -253.965455 84 -389.608485 36.367879 85 -81.675152 -389.608485 86 -335.141818 -81.675152 87 -755.475152 -335.141818 88 -632.941818 -755.475152 89 -115.675152 -632.941818 90 -1178.698788 -115.675152 91 147.634545 -1178.698788 92 -1027.765455 147.634545 93 -301.365455 -1027.765455 94 -128.965455 -301.365455 95 -322.632121 -128.965455 96 -207.608485 -322.632121 97 -17.675152 -207.608485 98 -123.141818 -17.675152 99 -414.475152 -123.141818 100 -207.941818 -414.475152 101 -522.675152 -207.941818 102 -904.344242 -522.675152 103 124.989091 -904.344242 104 -688.410909 124.989091 105 -42.010909 -688.410909 106 20.389091 -42.010909 107 -38.277576 20.389091 108 161.746061 -38.277576 109 357.679394 161.746061 110 -235.787273 357.679394 111 290.879394 -235.787273 112 -180.587273 290.879394 113 -409.320606 -180.587273 114 258.655758 -409.320606 115 -644.010909 258.655758 116 -497.410909 -644.010909 117 28.989091 -497.410909 118 103.389091 28.989091 119 21.722424 103.389091 120 155.746061 21.722424 121 -4.320606 155.746061 122 -266.787273 -4.320606 123 274.879394 -266.787273 124 -197.587273 274.879394 125 -486.320606 -197.587273 126 310.655758 -486.320606 127 -525.010909 310.655758 128 -157.410909 -525.010909 129 -117.010909 -157.410909 130 120.389091 -117.010909 131 34.722424 120.389091 132 74.746061 34.722424 133 -117.320606 74.746061 134 29.212727 -117.320606 135 173.879394 29.212727 136 -218.587273 173.879394 137 222.679394 -218.587273 138 99.655758 222.679394 139 -336.010909 99.655758 140 706.589091 -336.010909 141 -186.010909 706.589091 142 41.389091 -186.010909 143 282.722424 41.389091 144 71.746061 282.722424 145 -19.320606 71.746061 146 244.212727 -19.320606 147 -377.120606 244.212727 148 -365.587273 -377.120606 149 836.679394 -365.587273 150 903.655758 836.679394 151 -467.010909 903.655758 152 466.589091 -467.010909 153 -36.010909 466.589091 154 107.389091 -36.010909 155 155.722424 107.389091 156 -56.253939 155.722424 157 92.679394 -56.253939 158 225.212727 92.679394 159 -13.120606 225.212727 160 336.412727 -13.120606 161 -140.320606 336.412727 162 -631.344242 -140.320606 163 1873.989091 -631.344242 164 -520.410909 1873.989091 165 331.989091 -520.410909 166 135.389091 331.989091 167 -61.277576 135.389091 168 9.746061 -61.277576 169 128.679394 9.746061 170 -278.787273 128.679394 171 -98.120606 -278.787273 172 273.412727 -98.120606 173 -381.320606 273.412727 174 -597.344242 -381.320606 175 -40.010909 -597.344242 176 174.589091 -40.010909 177 348.989091 174.589091 178 -96.610909 348.989091 179 -180.277576 -96.610909 180 NA -180.277576 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -38.675152 216.391515 [2,] 335.858182 -38.675152 [3,] 797.524848 335.858182 [4,] 423.058182 797.524848 [5,] 638.324848 423.058182 [6,] 1081.301212 638.324848 [7,] -16.365455 1081.301212 [8,] 1528.234545 -16.365455 [9,] 320.634545 1528.234545 [10,] 149.034545 320.634545 [11,] 410.367879 149.034545 [12,] 56.391515 410.367879 [13,] 114.324848 56.391515 [14,] 765.858182 114.324848 [15,] 93.524848 765.858182 [16,] 842.058182 93.524848 [17,] 1269.324848 842.058182 [18,] 355.301212 1269.324848 [19,] 1025.634545 355.301212 [20,] 17.234545 1025.634545 [21,] 151.634545 17.234545 [22,] 231.034545 151.634545 [23,] 73.367879 231.034545 [24,] 8.391515 73.367879 [25,] 1.324848 8.391515 [26,] 13.858182 1.324848 [27,] 286.524848 13.858182 [28,] 723.058182 286.524848 [29,] 278.324848 723.058182 [30,] 214.301212 278.324848 [31,] 627.634545 214.301212 [32,] -135.765455 627.634545 [33,] 257.634545 -135.765455 [34,] 38.034545 257.634545 [35,] -110.632121 38.034545 [36,] -6.608485 -110.632121 [37,] 25.324848 -6.608485 [38,] -138.141818 25.324848 [39,] 76.524848 -138.141818 [40,] 169.058182 76.524848 [41,] -412.675152 169.058182 [42,] 73.301212 -412.675152 [43,] -193.365455 73.301212 [44,] -399.765455 -193.365455 [45,] 37.634545 -399.765455 [46,] -116.965455 37.634545 [47,] -277.632121 -116.965455 [48,] -67.608485 -277.632121 [49,] -174.675152 -67.608485 [50,] -165.141818 -174.675152 [51,] -12.475152 -165.141818 [52,] -213.941818 -12.475152 [53,] -635.675152 -213.941818 [54,] 538.301212 -635.675152 [55,] -586.365455 538.301212 [56,] -94.765455 -586.365455 [57,] 92.634545 -94.765455 [58,] -74.965455 92.634545 [59,] 9.367879 -74.965455 [60,] 20.391515 9.367879 [61,] -89.675152 20.391515 [62,] -122.141818 -89.675152 [63,] 252.524848 -122.141818 [64,] -160.941818 252.524848 [65,] -363.675152 -160.941818 [66,] 612.301212 -363.675152 [67,] -490.365455 612.301212 [68,] 625.234545 -490.365455 [69,] -408.365455 625.234545 [70,] -274.965455 -408.365455 [71,] -33.632121 -274.965455 [72,] -47.608485 -33.632121 [73,] -176.675152 -47.608485 [74,] 50.858182 -176.675152 [75,] -575.475152 50.858182 [76,] -588.941818 -575.475152 [77,] 222.324848 -588.941818 [78,] -1135.698788 222.324848 [79,] -501.365455 -1135.698788 [80,] 3.234545 -501.365455 [81,] -479.365455 3.234545 [82,] -253.965455 -479.365455 [83,] 36.367879 -253.965455 [84,] -389.608485 36.367879 [85,] -81.675152 -389.608485 [86,] -335.141818 -81.675152 [87,] -755.475152 -335.141818 [88,] -632.941818 -755.475152 [89,] -115.675152 -632.941818 [90,] -1178.698788 -115.675152 [91,] 147.634545 -1178.698788 [92,] -1027.765455 147.634545 [93,] -301.365455 -1027.765455 [94,] -128.965455 -301.365455 [95,] -322.632121 -128.965455 [96,] -207.608485 -322.632121 [97,] -17.675152 -207.608485 [98,] -123.141818 -17.675152 [99,] -414.475152 -123.141818 [100,] -207.941818 -414.475152 [101,] -522.675152 -207.941818 [102,] -904.344242 -522.675152 [103,] 124.989091 -904.344242 [104,] -688.410909 124.989091 [105,] -42.010909 -688.410909 [106,] 20.389091 -42.010909 [107,] -38.277576 20.389091 [108,] 161.746061 -38.277576 [109,] 357.679394 161.746061 [110,] -235.787273 357.679394 [111,] 290.879394 -235.787273 [112,] -180.587273 290.879394 [113,] -409.320606 -180.587273 [114,] 258.655758 -409.320606 [115,] -644.010909 258.655758 [116,] -497.410909 -644.010909 [117,] 28.989091 -497.410909 [118,] 103.389091 28.989091 [119,] 21.722424 103.389091 [120,] 155.746061 21.722424 [121,] -4.320606 155.746061 [122,] -266.787273 -4.320606 [123,] 274.879394 -266.787273 [124,] -197.587273 274.879394 [125,] -486.320606 -197.587273 [126,] 310.655758 -486.320606 [127,] -525.010909 310.655758 [128,] -157.410909 -525.010909 [129,] -117.010909 -157.410909 [130,] 120.389091 -117.010909 [131,] 34.722424 120.389091 [132,] 74.746061 34.722424 [133,] -117.320606 74.746061 [134,] 29.212727 -117.320606 [135,] 173.879394 29.212727 [136,] -218.587273 173.879394 [137,] 222.679394 -218.587273 [138,] 99.655758 222.679394 [139,] -336.010909 99.655758 [140,] 706.589091 -336.010909 [141,] -186.010909 706.589091 [142,] 41.389091 -186.010909 [143,] 282.722424 41.389091 [144,] 71.746061 282.722424 [145,] -19.320606 71.746061 [146,] 244.212727 -19.320606 [147,] -377.120606 244.212727 [148,] -365.587273 -377.120606 [149,] 836.679394 -365.587273 [150,] 903.655758 836.679394 [151,] -467.010909 903.655758 [152,] 466.589091 -467.010909 [153,] -36.010909 466.589091 [154,] 107.389091 -36.010909 [155,] 155.722424 107.389091 [156,] -56.253939 155.722424 [157,] 92.679394 -56.253939 [158,] 225.212727 92.679394 [159,] -13.120606 225.212727 [160,] 336.412727 -13.120606 [161,] -140.320606 336.412727 [162,] -631.344242 -140.320606 [163,] 1873.989091 -631.344242 [164,] -520.410909 1873.989091 [165,] 331.989091 -520.410909 [166,] 135.389091 331.989091 [167,] -61.277576 135.389091 [168,] 9.746061 -61.277576 [169,] 128.679394 9.746061 [170,] -278.787273 128.679394 [171,] -98.120606 -278.787273 [172,] 273.412727 -98.120606 [173,] -381.320606 273.412727 [174,] -597.344242 -381.320606 [175,] -40.010909 -597.344242 [176,] 174.589091 -40.010909 [177,] 348.989091 174.589091 [178,] -96.610909 348.989091 [179,] -180.277576 -96.610909 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -38.675152 216.391515 2 335.858182 -38.675152 3 797.524848 335.858182 4 423.058182 797.524848 5 638.324848 423.058182 6 1081.301212 638.324848 7 -16.365455 1081.301212 8 1528.234545 -16.365455 9 320.634545 1528.234545 10 149.034545 320.634545 11 410.367879 149.034545 12 56.391515 410.367879 13 114.324848 56.391515 14 765.858182 114.324848 15 93.524848 765.858182 16 842.058182 93.524848 17 1269.324848 842.058182 18 355.301212 1269.324848 19 1025.634545 355.301212 20 17.234545 1025.634545 21 151.634545 17.234545 22 231.034545 151.634545 23 73.367879 231.034545 24 8.391515 73.367879 25 1.324848 8.391515 26 13.858182 1.324848 27 286.524848 13.858182 28 723.058182 286.524848 29 278.324848 723.058182 30 214.301212 278.324848 31 627.634545 214.301212 32 -135.765455 627.634545 33 257.634545 -135.765455 34 38.034545 257.634545 35 -110.632121 38.034545 36 -6.608485 -110.632121 37 25.324848 -6.608485 38 -138.141818 25.324848 39 76.524848 -138.141818 40 169.058182 76.524848 41 -412.675152 169.058182 42 73.301212 -412.675152 43 -193.365455 73.301212 44 -399.765455 -193.365455 45 37.634545 -399.765455 46 -116.965455 37.634545 47 -277.632121 -116.965455 48 -67.608485 -277.632121 49 -174.675152 -67.608485 50 -165.141818 -174.675152 51 -12.475152 -165.141818 52 -213.941818 -12.475152 53 -635.675152 -213.941818 54 538.301212 -635.675152 55 -586.365455 538.301212 56 -94.765455 -586.365455 57 92.634545 -94.765455 58 -74.965455 92.634545 59 9.367879 -74.965455 60 20.391515 9.367879 61 -89.675152 20.391515 62 -122.141818 -89.675152 63 252.524848 -122.141818 64 -160.941818 252.524848 65 -363.675152 -160.941818 66 612.301212 -363.675152 67 -490.365455 612.301212 68 625.234545 -490.365455 69 -408.365455 625.234545 70 -274.965455 -408.365455 71 -33.632121 -274.965455 72 -47.608485 -33.632121 73 -176.675152 -47.608485 74 50.858182 -176.675152 75 -575.475152 50.858182 76 -588.941818 -575.475152 77 222.324848 -588.941818 78 -1135.698788 222.324848 79 -501.365455 -1135.698788 80 3.234545 -501.365455 81 -479.365455 3.234545 82 -253.965455 -479.365455 83 36.367879 -253.965455 84 -389.608485 36.367879 85 -81.675152 -389.608485 86 -335.141818 -81.675152 87 -755.475152 -335.141818 88 -632.941818 -755.475152 89 -115.675152 -632.941818 90 -1178.698788 -115.675152 91 147.634545 -1178.698788 92 -1027.765455 147.634545 93 -301.365455 -1027.765455 94 -128.965455 -301.365455 95 -322.632121 -128.965455 96 -207.608485 -322.632121 97 -17.675152 -207.608485 98 -123.141818 -17.675152 99 -414.475152 -123.141818 100 -207.941818 -414.475152 101 -522.675152 -207.941818 102 -904.344242 -522.675152 103 124.989091 -904.344242 104 -688.410909 124.989091 105 -42.010909 -688.410909 106 20.389091 -42.010909 107 -38.277576 20.389091 108 161.746061 -38.277576 109 357.679394 161.746061 110 -235.787273 357.679394 111 290.879394 -235.787273 112 -180.587273 290.879394 113 -409.320606 -180.587273 114 258.655758 -409.320606 115 -644.010909 258.655758 116 -497.410909 -644.010909 117 28.989091 -497.410909 118 103.389091 28.989091 119 21.722424 103.389091 120 155.746061 21.722424 121 -4.320606 155.746061 122 -266.787273 -4.320606 123 274.879394 -266.787273 124 -197.587273 274.879394 125 -486.320606 -197.587273 126 310.655758 -486.320606 127 -525.010909 310.655758 128 -157.410909 -525.010909 129 -117.010909 -157.410909 130 120.389091 -117.010909 131 34.722424 120.389091 132 74.746061 34.722424 133 -117.320606 74.746061 134 29.212727 -117.320606 135 173.879394 29.212727 136 -218.587273 173.879394 137 222.679394 -218.587273 138 99.655758 222.679394 139 -336.010909 99.655758 140 706.589091 -336.010909 141 -186.010909 706.589091 142 41.389091 -186.010909 143 282.722424 41.389091 144 71.746061 282.722424 145 -19.320606 71.746061 146 244.212727 -19.320606 147 -377.120606 244.212727 148 -365.587273 -377.120606 149 836.679394 -365.587273 150 903.655758 836.679394 151 -467.010909 903.655758 152 466.589091 -467.010909 153 -36.010909 466.589091 154 107.389091 -36.010909 155 155.722424 107.389091 156 -56.253939 155.722424 157 92.679394 -56.253939 158 225.212727 92.679394 159 -13.120606 225.212727 160 336.412727 -13.120606 161 -140.320606 336.412727 162 -631.344242 -140.320606 163 1873.989091 -631.344242 164 -520.410909 1873.989091 165 331.989091 -520.410909 166 135.389091 331.989091 167 -61.277576 135.389091 168 9.746061 -61.277576 169 128.679394 9.746061 170 -278.787273 128.679394 171 -98.120606 -278.787273 172 273.412727 -98.120606 173 -381.320606 273.412727 174 -597.344242 -381.320606 175 -40.010909 -597.344242 176 174.589091 -40.010909 177 348.989091 174.589091 178 -96.610909 348.989091 179 -180.277576 -96.610909 > 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/rcomp/tmp/7dy2l1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8dy2l1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9dy2l1293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/106pk61293454152.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/11970u1293454152.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/rcomp/tmp/12c8zi1293454152.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/rcomp/tmp/1380e91293454152.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/rcomp/tmp/14u0dw1293454152.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/rcomp/tmp/155suz1293454152.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/rcomp/tmp/16jks81293454152.tab") + } > > try(system("convert tmp/1honc1293454152.ps tmp/1honc1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/2sx4x1293454152.ps tmp/2sx4x1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/3sx4x1293454152.ps tmp/3sx4x1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/4sx4x1293454152.ps tmp/4sx4x1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/5sx4x1293454152.ps tmp/5sx4x1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/6kpli1293454152.ps tmp/6kpli1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/7dy2l1293454152.ps tmp/7dy2l1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/8dy2l1293454152.ps tmp/8dy2l1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/9dy2l1293454152.ps tmp/9dy2l1293454152.png",intern=TRUE)) character(0) > try(system("convert tmp/106pk61293454152.ps tmp/106pk61293454152.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.524 1.787 9.877