R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-redhat-linux-gnu (64-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(4831 + ,0 + ,3695 + ,2462 + ,2146 + ,1579 + ,5134 + ,0 + ,4831 + ,3695 + ,2462 + ,2146 + ,6250 + ,0 + ,5134 + ,4831 + ,3695 + ,2462 + ,5760 + ,0 + ,6250 + ,5134 + ,4831 + ,3695 + ,6249 + ,0 + ,5760 + ,6250 + ,5134 + ,4831 + ,2917 + ,0 + ,6249 + ,5760 + ,6250 + ,5134 + ,1741 + ,0 + ,2917 + ,6249 + ,5760 + ,6250 + ,2359 + ,0 + ,1741 + ,2917 + ,6249 + ,5760 + ,1511 + ,1 + ,2359 + ,1741 + ,2917 + ,6249 + ,2059 + ,0 + ,1511 + ,2359 + ,1741 + ,2917 + ,2635 + ,0 + ,2059 + ,1511 + ,2359 + ,1741 + ,2867 + ,0 + ,2635 + ,2059 + ,1511 + ,2359 + ,4403 + ,0 + ,2867 + ,2635 + ,2059 + ,1511 + ,5720 + ,0 + ,4403 + ,2867 + ,2635 + ,2059 + ,4502 + ,0 + ,5720 + ,4403 + ,2867 + ,2635 + ,5749 + ,0 + ,4502 + ,5720 + ,4403 + ,2867 + ,5627 + ,0 + ,5749 + ,4502 + ,5720 + ,4403 + ,2846 + ,0 + ,5627 + ,5749 + ,4502 + ,5720 + ,1762 + ,0 + ,2846 + ,5627 + ,5749 + ,4502 + ,2429 + ,0 + ,1762 + ,2846 + ,5627 + ,5749 + ,1169 + ,0 + ,2429 + ,1762 + ,2846 + ,5627 + ,2154 + ,1 + 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,2939 + ,5964 + ,0 + ,5657 + ,6415 + ,6208 + ,4500 + ,3163 + ,0 + ,5964 + ,5657 + ,6415 + ,6208 + ,1997 + ,0 + ,3163 + ,5964 + ,5657 + ,6415 + ,2422 + ,0 + ,1997 + ,3163 + ,5964 + ,5657 + ,1376 + ,0 + ,2422 + ,1997 + ,3163 + ,5964 + ,2202 + ,0 + ,1376 + ,2422 + ,1997 + ,3163 + ,2683 + ,0 + ,2202 + ,1376 + ,2422 + ,1997 + ,3303 + ,0 + ,2683 + ,2202 + ,1376 + ,2422 + ,5202 + ,0 + ,3303 + ,2683 + ,2202 + ,1376 + ,5231 + ,0 + ,5202 + ,3303 + ,2683 + ,2202 + ,4880 + ,0 + ,5231 + ,5202 + ,3303 + ,2683 + ,7998 + ,1 + ,4880 + ,5231 + ,5202 + ,3303 + ,4977 + ,0 + ,7998 + ,4880 + ,5231 + ,5202 + ,3531 + ,0 + ,4977 + ,7998 + ,4880 + ,5231 + ,2025 + ,0 + ,3531 + ,4977 + ,7998 + ,4880 + ,2205 + ,0 + ,2025 + ,3531 + ,4977 + ,7998 + ,1442 + ,0 + ,2205 + ,2025 + ,3531 + ,4977 + ,2238 + ,0 + ,1442 + ,2205 + ,2025 + ,3531 + ,2179 + ,0 + ,2238 + ,1442 + ,2205 + ,2025 + ,3218 + ,0 + ,2179 + ,2238 + ,1442 + ,2205 + ,5139 + ,0 + ,3218 + ,2179 + ,2238 + ,1442 + ,4990 + ,0 + ,5139 + ,3218 + ,2179 + ,2238 + ,4914 + ,0 + ,4990 + ,5139 + ,3218 + ,2179 + ,6084 + ,0 + ,4914 + ,4990 + ,5139 + ,3218 + ,5672 + ,1 + ,6084 + ,4914 + ,4990 + ,5139 + ,3548 + ,0 + ,5672 + ,6084 + ,4914 + ,4990 + ,1793 + ,0 + ,3548 + ,5672 + ,6084 + ,4914 + ,2086 + ,0 + ,1793 + ,3548 + ,5672 + ,6084) + ,dim=c(6 + ,116) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2' + ,'Y3' + ,'Y4') + ,1:116)) > y <- array(NA,dim=c(6,116),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:116)) > 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 > 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 Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1 4831 0 3695 2462 2146 1579 1 0 0 0 0 0 0 0 0 0 0 2 5134 0 4831 3695 2462 2146 0 1 0 0 0 0 0 0 0 0 0 3 6250 0 5134 4831 3695 2462 0 0 1 0 0 0 0 0 0 0 0 4 5760 0 6250 5134 4831 3695 0 0 0 1 0 0 0 0 0 0 0 5 6249 0 5760 6250 5134 4831 0 0 0 0 1 0 0 0 0 0 0 6 2917 0 6249 5760 6250 5134 0 0 0 0 0 1 0 0 0 0 0 7 1741 0 2917 6249 5760 6250 0 0 0 0 0 0 1 0 0 0 0 8 2359 0 1741 2917 6249 5760 0 0 0 0 0 0 0 1 0 0 0 9 1511 1 2359 1741 2917 6249 0 0 0 0 0 0 0 0 1 0 0 10 2059 0 1511 2359 1741 2917 0 0 0 0 0 0 0 0 0 1 0 11 2635 0 2059 1511 2359 1741 0 0 0 0 0 0 0 0 0 0 1 12 2867 0 2635 2059 1511 2359 0 0 0 0 0 0 0 0 0 0 0 13 4403 0 2867 2635 2059 1511 1 0 0 0 0 0 0 0 0 0 0 14 5720 0 4403 2867 2635 2059 0 1 0 0 0 0 0 0 0 0 0 15 4502 0 5720 4403 2867 2635 0 0 1 0 0 0 0 0 0 0 0 16 5749 0 4502 5720 4403 2867 0 0 0 1 0 0 0 0 0 0 0 17 5627 0 5749 4502 5720 4403 0 0 0 0 1 0 0 0 0 0 0 18 2846 0 5627 5749 4502 5720 0 0 0 0 0 1 0 0 0 0 0 19 1762 0 2846 5627 5749 4502 0 0 0 0 0 0 1 0 0 0 0 20 2429 0 1762 2846 5627 5749 0 0 0 0 0 0 0 1 0 0 0 21 1169 0 2429 1762 2846 5627 0 0 0 0 0 0 0 0 1 0 0 22 2154 1 1169 2429 1762 2846 0 0 0 0 0 0 0 0 0 1 0 23 2249 0 2154 1169 2429 1762 0 0 0 0 0 0 0 0 0 0 1 24 2687 0 2249 2154 1169 2429 0 0 0 0 0 0 0 0 0 0 0 25 4359 0 2687 2249 2154 1169 1 0 0 0 0 0 0 0 0 0 0 26 5382 0 4359 2687 2249 2154 0 1 0 0 0 0 0 0 0 0 0 27 4459 0 5382 4359 2687 2249 0 0 1 0 0 0 0 0 0 0 0 28 6398 0 4459 5382 4359 2687 0 0 0 1 0 0 0 0 0 0 0 29 4596 0 6398 4459 5382 4359 0 0 0 0 1 0 0 0 0 0 0 30 3024 0 4596 6398 4459 5382 0 0 0 0 0 1 0 0 0 0 0 31 1887 0 3024 4596 6398 4459 0 0 0 0 0 0 1 0 0 0 0 32 2070 0 1887 3024 4596 6398 0 0 0 0 0 0 0 1 0 0 0 33 1351 0 2070 1887 3024 4596 0 0 0 0 0 0 0 0 1 0 0 34 2218 0 1351 2070 1887 3024 0 0 0 0 0 0 0 0 0 1 0 35 2461 1 2218 1351 2070 1887 0 0 0 0 0 0 0 0 0 0 1 36 3028 0 2461 2218 1351 2070 0 0 0 0 0 0 0 0 0 0 0 37 4784 0 3028 2461 2218 1351 1 0 0 0 0 0 0 0 0 0 0 38 4975 0 4784 3028 2461 2218 0 1 0 0 0 0 0 0 0 0 0 39 4607 0 4975 4784 3028 2461 0 0 1 0 0 0 0 0 0 0 0 40 6249 0 4607 4975 4784 3028 0 0 0 1 0 0 0 0 0 0 0 41 4809 0 6249 4607 4975 4784 0 0 0 0 1 0 0 0 0 0 0 42 3157 0 4809 6249 4607 4975 0 0 0 0 0 1 0 0 0 0 0 43 1910 0 3157 4809 6249 4607 0 0 0 0 0 0 1 0 0 0 0 44 2228 0 1910 3157 4809 6249 0 0 0 0 0 0 0 1 0 0 0 45 1594 0 2228 1910 3157 4809 0 0 0 0 0 0 0 0 1 0 0 46 2467 0 1594 2228 1910 3157 0 0 0 0 0 0 0 0 0 1 0 47 2222 0 2467 1594 2228 1910 0 0 0 0 0 0 0 0 0 0 1 48 3607 1 2222 2467 1594 2228 0 0 0 0 0 0 0 0 0 0 0 49 4685 0 3607 2222 2467 1594 1 0 0 0 0 0 0 0 0 0 0 50 4962 0 4685 3607 2222 2467 0 1 0 0 0 0 0 0 0 0 0 51 5770 0 4962 4685 3607 2222 0 0 1 0 0 0 0 0 0 0 0 52 5480 0 5770 4962 4685 3607 0 0 0 1 0 0 0 0 0 0 0 53 5000 0 5480 5770 4962 4685 0 0 0 0 1 0 0 0 0 0 0 54 3228 0 5000 5480 5770 4962 0 0 0 0 0 1 0 0 0 0 0 55 1993 0 3228 5000 5480 5770 0 0 0 0 0 0 1 0 0 0 0 56 2288 0 1993 3228 5000 5480 0 0 0 0 0 0 0 1 0 0 0 57 1580 0 2288 1993 3228 5000 0 0 0 0 0 0 0 0 1 0 0 58 2111 0 1580 2288 1993 3228 0 0 0 0 0 0 0 0 0 1 0 59 2192 0 2111 1580 2288 1993 0 0 0 0 0 0 0 0 0 0 1 60 3601 0 2192 2111 1580 2288 0 0 0 0 0 0 0 0 0 0 0 61 4665 1 3601 2192 2111 1580 1 0 0 0 0 0 0 0 0 0 0 62 4876 0 4665 3601 2192 2111 0 1 0 0 0 0 0 0 0 0 0 63 5813 0 4876 4665 3601 2192 0 0 1 0 0 0 0 0 0 0 0 64 5589 0 5813 4876 4665 3601 0 0 0 1 0 0 0 0 0 0 0 65 5331 0 5589 5813 4876 4665 0 0 0 0 1 0 0 0 0 0 0 66 3075 0 5331 5589 5813 4876 0 0 0 0 0 1 0 0 0 0 0 67 2002 0 3075 5331 5589 5813 0 0 0 0 0 0 1 0 0 0 0 68 2306 0 2002 3075 5331 5589 0 0 0 0 0 0 0 1 0 0 0 69 1507 0 2306 2002 3075 5331 0 0 0 0 0 0 0 0 1 0 0 70 1992 0 1507 2306 2002 3075 0 0 0 0 0 0 0 0 0 1 0 71 2487 0 1992 1507 2306 2002 0 0 0 0 0 0 0 0 0 0 1 72 3490 0 2487 1992 1507 2306 0 0 0 0 0 0 0 0 0 0 0 73 4647 0 3490 2487 1992 1507 1 0 0 0 0 0 0 0 0 0 0 74 5594 1 4647 3490 2487 1992 0 1 0 0 0 0 0 0 0 0 0 75 5611 0 5594 4647 3490 2487 0 0 1 0 0 0 0 0 0 0 0 76 5788 0 5611 5594 4647 3490 0 0 0 1 0 0 0 0 0 0 0 77 6204 0 5788 5611 5594 4647 0 0 0 0 1 0 0 0 0 0 0 78 3013 0 6204 5788 5611 5594 0 0 0 0 0 1 0 0 0 0 0 79 1931 0 3013 6204 5788 5611 0 0 0 0 0 0 1 0 0 0 0 80 2549 0 1931 3013 6204 5788 0 0 0 0 0 0 0 1 0 0 0 81 1504 0 2549 1931 3013 6204 0 0 0 0 0 0 0 0 1 0 0 82 2090 0 1504 2549 1931 3013 0 0 0 0 0 0 0 0 0 1 0 83 2702 0 2090 1504 2549 1931 0 0 0 0 0 0 0 0 0 0 1 84 2939 0 2702 2090 1504 2549 0 0 0 0 0 0 0 0 0 0 0 85 4500 0 2939 2702 2090 1504 1 0 0 0 0 0 0 0 0 0 0 86 6208 0 4500 2939 2702 2090 0 1 0 0 0 0 0 0 0 0 0 87 6415 1 6208 4500 2939 2702 0 0 1 0 0 0 0 0 0 0 0 88 5657 0 6415 6208 4500 2939 0 0 0 1 0 0 0 0 0 0 0 89 5964 0 5657 6415 6208 4500 0 0 0 0 1 0 0 0 0 0 0 90 3163 0 5964 5657 6415 6208 0 0 0 0 0 1 0 0 0 0 0 91 1997 0 3163 5964 5657 6415 0 0 0 0 0 0 1 0 0 0 0 92 2422 0 1997 3163 5964 5657 0 0 0 0 0 0 0 1 0 0 0 93 1376 0 2422 1997 3163 5964 0 0 0 0 0 0 0 0 1 0 0 94 2202 0 1376 2422 1997 3163 0 0 0 0 0 0 0 0 0 1 0 95 2683 0 2202 1376 2422 1997 0 0 0 0 0 0 0 0 0 0 1 96 3303 0 2683 2202 1376 2422 0 0 0 0 0 0 0 0 0 0 0 97 5202 0 3303 2683 2202 1376 1 0 0 0 0 0 0 0 0 0 0 98 5231 0 5202 3303 2683 2202 0 1 0 0 0 0 0 0 0 0 0 99 4880 0 5231 5202 3303 2683 0 0 1 0 0 0 0 0 0 0 0 100 7998 1 4880 5231 5202 3303 0 0 0 1 0 0 0 0 0 0 0 101 4977 0 7998 4880 5231 5202 0 0 0 0 1 0 0 0 0 0 0 102 3531 0 4977 7998 4880 5231 0 0 0 0 0 1 0 0 0 0 0 103 2025 0 3531 4977 7998 4880 0 0 0 0 0 0 1 0 0 0 0 104 2205 0 2025 3531 4977 7998 0 0 0 0 0 0 0 1 0 0 0 105 1442 0 2205 2025 3531 4977 0 0 0 0 0 0 0 0 1 0 0 106 2238 0 1442 2205 2025 3531 0 0 0 0 0 0 0 0 0 1 0 107 2179 0 2238 1442 2205 2025 0 0 0 0 0 0 0 0 0 0 1 108 3218 0 2179 2238 1442 2205 0 0 0 0 0 0 0 0 0 0 0 109 5139 0 3218 2179 2238 1442 1 0 0 0 0 0 0 0 0 0 0 110 4990 0 5139 3218 2179 2238 0 1 0 0 0 0 0 0 0 0 0 111 4914 0 4990 5139 3218 2179 0 0 1 0 0 0 0 0 0 0 0 112 6084 0 4914 4990 5139 3218 0 0 0 1 0 0 0 0 0 0 0 113 5672 1 6084 4914 4990 5139 0 0 0 0 1 0 0 0 0 0 0 114 3548 0 5672 6084 4914 4990 0 0 0 0 0 1 0 0 0 0 0 115 1793 0 3548 5672 6084 4914 0 0 0 0 0 0 1 0 0 0 0 116 2086 0 1793 3548 5672 6084 0 0 0 0 0 0 0 1 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 Y3 Y4 2.811e+03 5.367e+02 -2.707e-01 1.470e-01 3.823e-01 4.569e-02 M1 M2 M3 M4 M5 M6 1.482e+03 2.217e+03 1.849e+03 1.918e+03 1.196e+03 -1.358e+03 M7 M8 M9 M10 M11 -3.420e+03 -2.823e+03 -2.512e+03 -1.524e+03 -1.046e+03 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -679.71 -221.98 -23.83 170.52 1144.88 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.811e+03 3.913e+02 7.184 1.28e-10 *** X 5.367e+02 1.244e+02 4.314 3.79e-05 *** Y1 -2.707e-01 9.177e-02 -2.950 0.003965 ** Y2 1.470e-01 8.889e-02 1.653 0.101423 Y3 3.824e-01 8.934e-02 4.280 4.33e-05 *** Y4 4.569e-02 9.288e-02 0.492 0.623833 M1 1.482e+03 2.114e+02 7.013 2.91e-10 *** M2 2.217e+03 3.112e+02 7.123 1.72e-10 *** M3 1.849e+03 4.493e+02 4.115 8.01e-05 *** M4 1.918e+03 5.471e+02 3.505 0.000687 *** M5 1.196e+03 6.320e+02 1.892 0.061418 . M6 -1.358e+03 6.685e+02 -2.031 0.044931 * M7 -3.420e+03 6.540e+02 -5.230 9.47e-07 *** M8 -2.823e+03 6.044e+02 -4.671 9.46e-06 *** M9 -2.512e+03 3.974e+02 -6.321 7.49e-09 *** M10 -1.524e+03 2.219e+02 -6.869 5.78e-10 *** M11 -1.046e+03 1.901e+02 -5.505 2.91e-07 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 350.5 on 99 degrees of freedom Multiple R-squared: 0.9602, Adjusted R-squared: 0.9538 F-statistic: 149.3 on 16 and 99 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,] 0.98798502 0.02402995 0.01201498 [2,] 0.97229500 0.05541000 0.02770500 [3,] 0.95602706 0.08794589 0.04397294 [4,] 0.92982221 0.14035558 0.07017779 [5,] 0.89630481 0.20739037 0.10369519 [6,] 0.86902431 0.26195139 0.13097569 [7,] 0.82152754 0.35694491 0.17847246 [8,] 0.84276278 0.31447445 0.15723722 [9,] 0.86055202 0.27889595 0.13944798 [10,] 0.90251552 0.19496897 0.09748448 [11,] 0.86819971 0.26360058 0.13180029 [12,] 0.85421694 0.29156613 0.14578306 [13,] 0.82925771 0.34148458 0.17074229 [14,] 0.77658309 0.44683382 0.22341691 [15,] 0.71864065 0.56271870 0.28135935 [16,] 0.68934521 0.62130958 0.31065479 [17,] 0.64242647 0.71514706 0.35757353 [18,] 0.58182636 0.83634728 0.41817364 [19,] 0.54965832 0.90068337 0.45034168 [20,] 0.70194363 0.59611273 0.29805637 [21,] 0.64157120 0.71685760 0.35842880 [22,] 0.61929651 0.76140698 0.38070349 [23,] 0.56122885 0.87754229 0.43877115 [24,] 0.52322275 0.95355450 0.47677725 [25,] 0.47289653 0.94579306 0.52710347 [26,] 0.41479810 0.82959619 0.58520190 [27,] 0.40958752 0.81917504 0.59041248 [28,] 0.35326375 0.70652750 0.64673625 [29,] 0.35529457 0.71058913 0.64470543 [30,] 0.30440512 0.60881023 0.69559488 [31,] 0.28980348 0.57960695 0.71019652 [32,] 0.27193981 0.54387962 0.72806019 [33,] 0.25970445 0.51940890 0.74029555 [34,] 0.33781500 0.67563001 0.66218500 [35,] 0.30444478 0.60888956 0.69555522 [36,] 0.32072841 0.64145683 0.67927159 [37,] 0.28114246 0.56228491 0.71885754 [38,] 0.23265404 0.46530808 0.76734596 [39,] 0.18947843 0.37895685 0.81052157 [40,] 0.16917283 0.33834565 0.83082717 [41,] 0.16453439 0.32906878 0.83546561 [42,] 0.23075587 0.46151175 0.76924413 [43,] 0.22334465 0.44668931 0.77665535 [44,] 0.21132251 0.42264502 0.78867749 [45,] 0.19368436 0.38736871 0.80631564 [46,] 0.16263546 0.32527091 0.83736454 [47,] 0.15880810 0.31761619 0.84119190 [48,] 0.13077466 0.26154932 0.86922534 [49,] 0.10057879 0.20115759 0.89942121 [50,] 0.07551357 0.15102714 0.92448643 [51,] 0.06030783 0.12061567 0.93969217 [52,] 0.04356768 0.08713536 0.95643232 [53,] 0.04170457 0.08340914 0.95829543 [54,] 0.03184032 0.06368064 0.96815968 [55,] 0.07415233 0.14830466 0.92584767 [56,] 0.09689509 0.19379019 0.90310491 [57,] 0.07681551 0.15363102 0.92318449 [58,] 0.18582527 0.37165054 0.81417473 [59,] 0.15261511 0.30523022 0.84738489 [60,] 0.11765108 0.23530215 0.88234892 [61,] 0.09388077 0.18776155 0.90611923 [62,] 0.07257241 0.14514482 0.92742759 [63,] 0.05210565 0.10421130 0.94789435 [64,] 0.03764049 0.07528099 0.96235951 [65,] 0.02853768 0.05707537 0.97146232 [66,] 0.04906132 0.09812264 0.95093868 [67,] 0.24737715 0.49475429 0.75262285 [68,] 0.49090429 0.98180858 0.50909571 [69,] 0.69239447 0.61521106 0.30760553 [70,] 0.95216023 0.09567953 0.04783977 [71,] 0.97293176 0.05413649 0.02706824 [72,] 0.98692501 0.02614998 0.01307499 [73,] 0.97623568 0.04752864 0.02376432 [74,] 0.95263099 0.09473802 0.04736901 [75,] 0.90025287 0.19949426 0.09974713 [76,] 0.97685581 0.04628838 0.02314419 [77,] 0.95758523 0.08482953 0.04241477 > postscript(file="/var/www/wessaorg/rcomp/tmp/1pj5o1293789345.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/2dfhy1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/wessaorg/rcomp/tmp/330da1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/4c9kz1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/565tu1293789345.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 = 116 Frequency = 1 1 2 3 4 5 6 283.2064308 -168.5612069 744.3608111 -47.3616880 699.2726766 -315.4992693 7 8 9 10 11 12 -266.5945697 -238.8895040 -342.9152950 35.1062261 224.0722528 -218.9760817 13 14 15 16 17 18 -358.0174855 361.0864893 -473.4063243 -416.2536820 126.7044826 88.2842649 19 20 21 22 23 24 -89.3195857 85.5531157 -76.8284597 -514.2113014 -113.6671929 -389.8785563 25 26 27 28 29 30 -414.7138710 180.8738470 -514.9876032 295.8296330 -591.0246028 -76.3434078 31 32 33 34 35 36 -10.7782122 98.7772268 -31.3403310 132.5515718 -316.1914873 -54.0714176 37 38 39 40 41 42 38.6622204 -245.1629691 -679.7076768 68.6370177 -303.9214248 98.2326921 43 44 45 46 47 48 67.1313156 168.8255779 190.4704488 409.2473268 -48.3013535 -213.1562511 49 50 51 52 53 54 25.2364009 -290.0599590 283.8654918 -372.1918332 -482.5515732 -110.1100295 55 56 57 58 59 60 382.1631205 202.9727976 144.6415681 5.6595994 -199.3590922 364.3079038 61 62 63 64 65 66 -391.8767194 -352.8550659 310.1865973 -230.9894878 -94.5655027 -202.0276471 67 68 69 70 71 72 257.4521054 114.3587543 118.5660608 -132.1994039 66.8588516 377.7533999 73 74 75 76 77 78 102.2027045 -267.4218421 334.1807529 -180.2498019 588.2970371 -12.4978562 79 80 81 82 83 84 -25.4968667 4.3670643 175.6036984 -40.7461889 219.1660085 -139.3985367 85 86 87 88 89 90 -262.9045370 837.7320894 990.2129142 -102.4365060 -33.3786068 -243.6842544 91 92 93 94 95 96 129.7355212 -29.0610430 -42.8650936 23.1760277 294.8429873 257.7401898 97 98 99 100 101 102 503.4618504 -0.5626393 -514.1232985 1144.8830939 180.4906258 144.5833217 103 104 105 106 107 108 -422.5035538 -22.1620061 -135.3325968 81.4161424 -127.4209743 15.6793499 109 110 111 112 113 114 474.7430058 -55.0687433 -480.5816646 -159.8667456 -89.3231118 629.0621857 115 116 -21.7892745 -384.7419834 > postscript(file="/var/www/wessaorg/rcomp/tmp/67ydo1293789345.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 = 116 Frequency = 1 lag(myerror, k = 1) myerror 0 283.2064308 NA 1 -168.5612069 283.2064308 2 744.3608111 -168.5612069 3 -47.3616880 744.3608111 4 699.2726766 -47.3616880 5 -315.4992693 699.2726766 6 -266.5945697 -315.4992693 7 -238.8895040 -266.5945697 8 -342.9152950 -238.8895040 9 35.1062261 -342.9152950 10 224.0722528 35.1062261 11 -218.9760817 224.0722528 12 -358.0174855 -218.9760817 13 361.0864893 -358.0174855 14 -473.4063243 361.0864893 15 -416.2536820 -473.4063243 16 126.7044826 -416.2536820 17 88.2842649 126.7044826 18 -89.3195857 88.2842649 19 85.5531157 -89.3195857 20 -76.8284597 85.5531157 21 -514.2113014 -76.8284597 22 -113.6671929 -514.2113014 23 -389.8785563 -113.6671929 24 -414.7138710 -389.8785563 25 180.8738470 -414.7138710 26 -514.9876032 180.8738470 27 295.8296330 -514.9876032 28 -591.0246028 295.8296330 29 -76.3434078 -591.0246028 30 -10.7782122 -76.3434078 31 98.7772268 -10.7782122 32 -31.3403310 98.7772268 33 132.5515718 -31.3403310 34 -316.1914873 132.5515718 35 -54.0714176 -316.1914873 36 38.6622204 -54.0714176 37 -245.1629691 38.6622204 38 -679.7076768 -245.1629691 39 68.6370177 -679.7076768 40 -303.9214248 68.6370177 41 98.2326921 -303.9214248 42 67.1313156 98.2326921 43 168.8255779 67.1313156 44 190.4704488 168.8255779 45 409.2473268 190.4704488 46 -48.3013535 409.2473268 47 -213.1562511 -48.3013535 48 25.2364009 -213.1562511 49 -290.0599590 25.2364009 50 283.8654918 -290.0599590 51 -372.1918332 283.8654918 52 -482.5515732 -372.1918332 53 -110.1100295 -482.5515732 54 382.1631205 -110.1100295 55 202.9727976 382.1631205 56 144.6415681 202.9727976 57 5.6595994 144.6415681 58 -199.3590922 5.6595994 59 364.3079038 -199.3590922 60 -391.8767194 364.3079038 61 -352.8550659 -391.8767194 62 310.1865973 -352.8550659 63 -230.9894878 310.1865973 64 -94.5655027 -230.9894878 65 -202.0276471 -94.5655027 66 257.4521054 -202.0276471 67 114.3587543 257.4521054 68 118.5660608 114.3587543 69 -132.1994039 118.5660608 70 66.8588516 -132.1994039 71 377.7533999 66.8588516 72 102.2027045 377.7533999 73 -267.4218421 102.2027045 74 334.1807529 -267.4218421 75 -180.2498019 334.1807529 76 588.2970371 -180.2498019 77 -12.4978562 588.2970371 78 -25.4968667 -12.4978562 79 4.3670643 -25.4968667 80 175.6036984 4.3670643 81 -40.7461889 175.6036984 82 219.1660085 -40.7461889 83 -139.3985367 219.1660085 84 -262.9045370 -139.3985367 85 837.7320894 -262.9045370 86 990.2129142 837.7320894 87 -102.4365060 990.2129142 88 -33.3786068 -102.4365060 89 -243.6842544 -33.3786068 90 129.7355212 -243.6842544 91 -29.0610430 129.7355212 92 -42.8650936 -29.0610430 93 23.1760277 -42.8650936 94 294.8429873 23.1760277 95 257.7401898 294.8429873 96 503.4618504 257.7401898 97 -0.5626393 503.4618504 98 -514.1232985 -0.5626393 99 1144.8830939 -514.1232985 100 180.4906258 1144.8830939 101 144.5833217 180.4906258 102 -422.5035538 144.5833217 103 -22.1620061 -422.5035538 104 -135.3325968 -22.1620061 105 81.4161424 -135.3325968 106 -127.4209743 81.4161424 107 15.6793499 -127.4209743 108 474.7430058 15.6793499 109 -55.0687433 474.7430058 110 -480.5816646 -55.0687433 111 -159.8667456 -480.5816646 112 -89.3231118 -159.8667456 113 629.0621857 -89.3231118 114 -21.7892745 629.0621857 115 -384.7419834 -21.7892745 116 NA -384.7419834 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -168.5612069 283.2064308 [2,] 744.3608111 -168.5612069 [3,] -47.3616880 744.3608111 [4,] 699.2726766 -47.3616880 [5,] -315.4992693 699.2726766 [6,] -266.5945697 -315.4992693 [7,] -238.8895040 -266.5945697 [8,] -342.9152950 -238.8895040 [9,] 35.1062261 -342.9152950 [10,] 224.0722528 35.1062261 [11,] -218.9760817 224.0722528 [12,] -358.0174855 -218.9760817 [13,] 361.0864893 -358.0174855 [14,] -473.4063243 361.0864893 [15,] -416.2536820 -473.4063243 [16,] 126.7044826 -416.2536820 [17,] 88.2842649 126.7044826 [18,] -89.3195857 88.2842649 [19,] 85.5531157 -89.3195857 [20,] -76.8284597 85.5531157 [21,] -514.2113014 -76.8284597 [22,] -113.6671929 -514.2113014 [23,] -389.8785563 -113.6671929 [24,] -414.7138710 -389.8785563 [25,] 180.8738470 -414.7138710 [26,] -514.9876032 180.8738470 [27,] 295.8296330 -514.9876032 [28,] -591.0246028 295.8296330 [29,] -76.3434078 -591.0246028 [30,] -10.7782122 -76.3434078 [31,] 98.7772268 -10.7782122 [32,] -31.3403310 98.7772268 [33,] 132.5515718 -31.3403310 [34,] -316.1914873 132.5515718 [35,] -54.0714176 -316.1914873 [36,] 38.6622204 -54.0714176 [37,] -245.1629691 38.6622204 [38,] -679.7076768 -245.1629691 [39,] 68.6370177 -679.7076768 [40,] -303.9214248 68.6370177 [41,] 98.2326921 -303.9214248 [42,] 67.1313156 98.2326921 [43,] 168.8255779 67.1313156 [44,] 190.4704488 168.8255779 [45,] 409.2473268 190.4704488 [46,] -48.3013535 409.2473268 [47,] -213.1562511 -48.3013535 [48,] 25.2364009 -213.1562511 [49,] -290.0599590 25.2364009 [50,] 283.8654918 -290.0599590 [51,] -372.1918332 283.8654918 [52,] -482.5515732 -372.1918332 [53,] -110.1100295 -482.5515732 [54,] 382.1631205 -110.1100295 [55,] 202.9727976 382.1631205 [56,] 144.6415681 202.9727976 [57,] 5.6595994 144.6415681 [58,] -199.3590922 5.6595994 [59,] 364.3079038 -199.3590922 [60,] -391.8767194 364.3079038 [61,] -352.8550659 -391.8767194 [62,] 310.1865973 -352.8550659 [63,] -230.9894878 310.1865973 [64,] -94.5655027 -230.9894878 [65,] -202.0276471 -94.5655027 [66,] 257.4521054 -202.0276471 [67,] 114.3587543 257.4521054 [68,] 118.5660608 114.3587543 [69,] -132.1994039 118.5660608 [70,] 66.8588516 -132.1994039 [71,] 377.7533999 66.8588516 [72,] 102.2027045 377.7533999 [73,] -267.4218421 102.2027045 [74,] 334.1807529 -267.4218421 [75,] -180.2498019 334.1807529 [76,] 588.2970371 -180.2498019 [77,] -12.4978562 588.2970371 [78,] -25.4968667 -12.4978562 [79,] 4.3670643 -25.4968667 [80,] 175.6036984 4.3670643 [81,] -40.7461889 175.6036984 [82,] 219.1660085 -40.7461889 [83,] -139.3985367 219.1660085 [84,] -262.9045370 -139.3985367 [85,] 837.7320894 -262.9045370 [86,] 990.2129142 837.7320894 [87,] -102.4365060 990.2129142 [88,] -33.3786068 -102.4365060 [89,] -243.6842544 -33.3786068 [90,] 129.7355212 -243.6842544 [91,] -29.0610430 129.7355212 [92,] -42.8650936 -29.0610430 [93,] 23.1760277 -42.8650936 [94,] 294.8429873 23.1760277 [95,] 257.7401898 294.8429873 [96,] 503.4618504 257.7401898 [97,] -0.5626393 503.4618504 [98,] -514.1232985 -0.5626393 [99,] 1144.8830939 -514.1232985 [100,] 180.4906258 1144.8830939 [101,] 144.5833217 180.4906258 [102,] -422.5035538 144.5833217 [103,] -22.1620061 -422.5035538 [104,] -135.3325968 -22.1620061 [105,] 81.4161424 -135.3325968 [106,] -127.4209743 81.4161424 [107,] 15.6793499 -127.4209743 [108,] 474.7430058 15.6793499 [109,] -55.0687433 474.7430058 [110,] -480.5816646 -55.0687433 [111,] -159.8667456 -480.5816646 [112,] -89.3231118 -159.8667456 [113,] 629.0621857 -89.3231118 [114,] -21.7892745 629.0621857 [115,] -384.7419834 -21.7892745 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -168.5612069 283.2064308 2 744.3608111 -168.5612069 3 -47.3616880 744.3608111 4 699.2726766 -47.3616880 5 -315.4992693 699.2726766 6 -266.5945697 -315.4992693 7 -238.8895040 -266.5945697 8 -342.9152950 -238.8895040 9 35.1062261 -342.9152950 10 224.0722528 35.1062261 11 -218.9760817 224.0722528 12 -358.0174855 -218.9760817 13 361.0864893 -358.0174855 14 -473.4063243 361.0864893 15 -416.2536820 -473.4063243 16 126.7044826 -416.2536820 17 88.2842649 126.7044826 18 -89.3195857 88.2842649 19 85.5531157 -89.3195857 20 -76.8284597 85.5531157 21 -514.2113014 -76.8284597 22 -113.6671929 -514.2113014 23 -389.8785563 -113.6671929 24 -414.7138710 -389.8785563 25 180.8738470 -414.7138710 26 -514.9876032 180.8738470 27 295.8296330 -514.9876032 28 -591.0246028 295.8296330 29 -76.3434078 -591.0246028 30 -10.7782122 -76.3434078 31 98.7772268 -10.7782122 32 -31.3403310 98.7772268 33 132.5515718 -31.3403310 34 -316.1914873 132.5515718 35 -54.0714176 -316.1914873 36 38.6622204 -54.0714176 37 -245.1629691 38.6622204 38 -679.7076768 -245.1629691 39 68.6370177 -679.7076768 40 -303.9214248 68.6370177 41 98.2326921 -303.9214248 42 67.1313156 98.2326921 43 168.8255779 67.1313156 44 190.4704488 168.8255779 45 409.2473268 190.4704488 46 -48.3013535 409.2473268 47 -213.1562511 -48.3013535 48 25.2364009 -213.1562511 49 -290.0599590 25.2364009 50 283.8654918 -290.0599590 51 -372.1918332 283.8654918 52 -482.5515732 -372.1918332 53 -110.1100295 -482.5515732 54 382.1631205 -110.1100295 55 202.9727976 382.1631205 56 144.6415681 202.9727976 57 5.6595994 144.6415681 58 -199.3590922 5.6595994 59 364.3079038 -199.3590922 60 -391.8767194 364.3079038 61 -352.8550659 -391.8767194 62 310.1865973 -352.8550659 63 -230.9894878 310.1865973 64 -94.5655027 -230.9894878 65 -202.0276471 -94.5655027 66 257.4521054 -202.0276471 67 114.3587543 257.4521054 68 118.5660608 114.3587543 69 -132.1994039 118.5660608 70 66.8588516 -132.1994039 71 377.7533999 66.8588516 72 102.2027045 377.7533999 73 -267.4218421 102.2027045 74 334.1807529 -267.4218421 75 -180.2498019 334.1807529 76 588.2970371 -180.2498019 77 -12.4978562 588.2970371 78 -25.4968667 -12.4978562 79 4.3670643 -25.4968667 80 175.6036984 4.3670643 81 -40.7461889 175.6036984 82 219.1660085 -40.7461889 83 -139.3985367 219.1660085 84 -262.9045370 -139.3985367 85 837.7320894 -262.9045370 86 990.2129142 837.7320894 87 -102.4365060 990.2129142 88 -33.3786068 -102.4365060 89 -243.6842544 -33.3786068 90 129.7355212 -243.6842544 91 -29.0610430 129.7355212 92 -42.8650936 -29.0610430 93 23.1760277 -42.8650936 94 294.8429873 23.1760277 95 257.7401898 294.8429873 96 503.4618504 257.7401898 97 -0.5626393 503.4618504 98 -514.1232985 -0.5626393 99 1144.8830939 -514.1232985 100 180.4906258 1144.8830939 101 144.5833217 180.4906258 102 -422.5035538 144.5833217 103 -22.1620061 -422.5035538 104 -135.3325968 -22.1620061 105 81.4161424 -135.3325968 106 -127.4209743 81.4161424 107 15.6793499 -127.4209743 108 474.7430058 15.6793499 109 -55.0687433 474.7430058 110 -480.5816646 -55.0687433 111 -159.8667456 -480.5816646 112 -89.3231118 -159.8667456 113 629.0621857 -89.3231118 114 -21.7892745 629.0621857 115 -384.7419834 -21.7892745 > 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/wessaorg/rcomp/tmp/7pwco1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/8pspo1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/9keh91293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/wessaorg/rcomp/tmp/10igpx1293789345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/wessaorg/rcomp/tmp/112bxm1293789345.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/wessaorg/rcomp/tmp/12vkgj1293789345.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/wessaorg/rcomp/tmp/134gid1293789345.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/wessaorg/rcomp/tmp/14zeve1293789345.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/wessaorg/rcomp/tmp/15jlvo1293789345.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/wessaorg/rcomp/tmp/161g2y1293789345.tab") + } > > try(system("convert tmp/1pj5o1293789345.ps tmp/1pj5o1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/2dfhy1293789345.ps tmp/2dfhy1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/330da1293789345.ps tmp/330da1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/4c9kz1293789345.ps tmp/4c9kz1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/565tu1293789345.ps tmp/565tu1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/67ydo1293789345.ps tmp/67ydo1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/7pwco1293789345.ps tmp/7pwco1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/8pspo1293789345.ps tmp/8pspo1293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/9keh91293789345.ps tmp/9keh91293789345.png",intern=TRUE)) character(0) > try(system("convert tmp/10igpx1293789345.ps tmp/10igpx1293789345.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.320 0.330 4.857