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Type 'q()' to quit R. > x <- array(list(3.7 + ,0 + ,3.7 + ,3.93 + ,4.15 + ,4.24 + ,0 + ,0 + ,0 + ,3.65 + ,0 + ,3.7 + ,3.7 + ,3.93 + ,4.15 + ,0 + ,0 + ,0 + ,3.55 + ,0 + ,3.65 + ,3.7 + ,3.7 + ,3.93 + ,0 + ,0 + ,0 + ,3.43 + ,0 + ,3.55 + ,3.65 + ,3.7 + ,3.7 + ,0 + ,0 + ,0 + ,3.47 + ,0 + ,3.43 + ,3.55 + ,3.65 + ,3.7 + ,0 + ,0 + ,0 + ,3.58 + ,0 + ,3.47 + ,3.43 + ,3.55 + ,3.65 + ,0 + ,0 + ,0 + ,3.67 + ,0 + ,3.58 + ,3.47 + ,3.43 + ,3.55 + ,0 + ,0 + ,0 + ,3.72 + ,0 + ,3.67 + ,3.58 + ,3.47 + ,3.43 + ,0 + ,0 + ,0 + ,3.8 + ,0 + ,3.72 + ,3.67 + ,3.58 + ,3.47 + ,0 + ,0 + ,0 + ,3.76 + ,0 + ,3.8 + ,3.72 + ,3.67 + ,3.58 + ,0 + ,0 + ,0 + ,3.63 + ,0 + ,3.76 + ,3.8 + ,3.72 + ,3.67 + ,0 + ,0 + ,0 + ,3.48 + ,0 + ,3.63 + ,3.76 + ,3.8 + ,3.72 + ,0 + ,0 + ,0 + ,3.41 + ,0 + ,3.48 + ,3.63 + ,3.76 + ,3.8 + ,0 + ,0 + ,0 + ,3.43 + ,0 + ,3.41 + ,3.48 + ,3.63 + ,3.76 + ,0 + ,0 + ,0 + ,3.5 + ,0 + ,3.43 + ,3.41 + ,3.48 + ,3.63 + ,0 + ,0 + ,0 + ,3.62 + ,0 + ,3.5 + ,3.43 + ,3.41 + ,3.48 + ,0 + ,0 + ,0 + ,3.58 + ,0 + ,3.62 + ,3.5 + ,3.43 + ,3.41 + ,0 + ,0 + ,0 + ,3.52 + ,0 + ,3.58 + ,3.62 + ,3.5 + ,3.43 + ,0 + ,0 + ,0 + ,3.45 + ,0 + ,3.52 + ,3.58 + ,3.62 + ,3.5 + ,0 + ,0 + ,0 + ,3.36 + ,0 + ,3.45 + ,3.52 + ,3.58 + ,3.62 + ,0 + ,0 + ,0 + ,3.27 + ,0 + ,3.36 + ,3.45 + ,3.52 + ,3.58 + ,0 + ,0 + ,0 + ,3.21 + ,0 + ,3.27 + ,3.36 + ,3.45 + ,3.52 + ,0 + ,0 + ,0 + ,3.19 + ,0 + ,3.21 + ,3.27 + ,3.36 + ,3.45 + ,0 + ,0 + ,0 + ,3.16 + ,0 + ,3.19 + ,3.21 + ,3.27 + ,3.36 + ,0 + ,0 + ,0 + ,3.12 + ,0 + ,3.16 + ,3.19 + ,3.21 + ,3.27 + ,0 + ,0 + ,0 + ,3.06 + ,0 + ,3.12 + ,3.16 + ,3.19 + ,3.21 + ,0 + ,0 + ,0 + ,3.01 + ,0 + ,3.06 + ,3.12 + ,3.16 + ,3.19 + ,0 + ,0 + ,0 + ,2.98 + ,0 + ,3.01 + ,3.06 + ,3.12 + ,3.16 + ,0 + ,0 + ,0 + ,2.97 + ,0 + ,2.98 + ,3.01 + ,3.06 + ,3.12 + ,0 + ,0 + ,0 + ,3.02 + ,0 + ,2.97 + ,2.98 + ,3.01 + ,3.06 + ,0 + ,0 + ,0 + ,3.07 + ,0 + ,3.02 + ,2.97 + ,2.98 + ,3.01 + ,0 + ,0 + ,0 + ,3.18 + ,0 + ,3.07 + ,3.02 + ,2.97 + ,2.98 + ,0 + ,0 + ,0 + ,3.29 + ,1 + ,3.18 + ,3.07 + ,3.02 + ,2.97 + ,0 + ,0 + ,0 + ,3.43 + ,1 + ,3.29 + ,3.18 + ,3.07 + ,3.02 + ,0 + ,0 + ,0 + ,3.61 + ,1 + ,3.43 + ,3.29 + ,3.18 + ,3.07 + ,0 + ,0 + ,0 + ,3.74 + ,1 + ,3.61 + ,3.43 + ,3.29 + ,3.18 + ,0 + ,0 + ,0 + ,3.87 + ,1 + ,3.74 + ,3.61 + ,3.43 + ,3.29 + ,0 + ,0 + ,0 + ,3.88 + ,1 + ,3.87 + ,3.74 + ,3.61 + ,3.43 + ,0 + ,0 + ,0 + ,4.09 + ,1 + ,3.88 + ,3.87 + ,3.74 + ,3.61 + ,0 + ,0 + ,0 + ,4.19 + ,1 + ,4.09 + ,3.88 + ,3.87 + ,3.74 + ,0 + ,0 + ,0 + ,4.2 + ,1 + ,4.19 + ,4.09 + ,3.88 + ,3.87 + ,0 + ,0 + ,0 + ,4.29 + ,1 + ,4.2 + ,4.19 + ,4.09 + ,3.88 + ,0 + ,0 + ,0 + ,4.37 + ,1 + ,4.29 + ,4.2 + ,4.19 + ,4.09 + ,0 + ,0 + ,0 + ,4.47 + ,1 + ,4.37 + ,4.29 + ,4.2 + ,4.19 + ,0 + ,0 + ,0 + ,4.61 + ,1 + ,4.47 + ,4.37 + ,4.29 + ,4.2 + ,0 + ,0 + ,0 + ,4.65 + ,1 + ,4.61 + ,4.47 + ,4.37 + ,4.29 + ,0 + ,0 + ,0 + ,4.69 + ,1 + ,4.65 + ,4.61 + ,4.47 + ,4.37 + ,0 + ,0 + ,0 + ,4.82 + ,1 + ,4.69 + ,4.65 + ,4.61 + ,4.47 + ,0 + ,0 + ,0 + ,4.86 + ,1 + ,4.82 + ,4.69 + ,4.65 + ,4.61 + ,0 + ,0 + ,0 + ,4.87 + ,1 + ,4.86 + ,4.82 + ,4.69 + ,4.65 + ,0 + ,0 + ,0 + ,5.01 + ,1 + ,4.87 + ,4.86 + ,4.82 + ,4.69 + ,0 + ,0 + ,0 + ,5.03 + ,1 + ,5.01 + ,4.87 + ,4.86 + ,4.82 + ,0 + ,0 + ,0 + ,5.13 + ,1 + ,5.03 + ,5.01 + ,4.87 + ,4.86 + ,0 + ,0 + ,0 + ,5.18 + ,1 + ,5.13 + ,5.03 + ,5.01 + ,4.87 + ,0 + ,0 + ,0 + ,5.21 + ,1 + ,5.18 + ,5.13 + ,5.03 + ,5.01 + ,0 + ,0 + ,0 + ,5.26 + ,1 + ,5.21 + ,5.18 + ,5.13 + ,5.03 + ,0 + ,0 + ,0 + ,5.25 + ,1 + ,5.26 + ,5.21 + ,5.18 + ,5.13 + ,0 + ,0 + ,0 + ,5.2 + ,1 + ,5.25 + ,5.26 + ,5.21 + ,5.18 + ,0 + ,0 + ,0 + ,5.16 + ,1 + ,5.2 + ,5.25 + ,5.26 + ,5.21 + ,0 + ,0 + ,0 + ,5.19 + ,1 + ,5.16 + ,5.2 + ,5.25 + ,5.26 + ,0 + ,0 + ,0 + ,5.39 + ,1 + ,5.19 + ,5.16 + ,5.2 + ,5.25 + ,0 + ,0 + ,0 + ,5.58 + ,1 + ,5.39 + ,5.19 + ,5.16 + ,5.2 + ,0 + ,0 + ,0 + ,5.76 + ,1 + ,5.58 + ,5.39 + ,5.19 + ,5.16 + ,0 + ,0 + ,0 + ,5.89 + ,1 + ,5.76 + ,5.58 + ,5.39 + ,5.19 + ,0 + ,0 + ,1 + ,5.98 + ,1 + ,5.89 + ,5.76 + ,5.58 + ,5.39 + ,0 + ,1 + ,0 + ,6.02 + ,1 + ,5.98 + ,5.89 + ,5.76 + ,5.58 + ,1 + ,0 + ,0 + ,5.62 + ,1 + ,6.02 + ,5.98 + ,5.89 + ,5.76 + ,0 + ,0 + ,0 + ,4.87 + ,1 + ,5.62 + ,6.02 + ,5.98 + ,5.89 + ,0 + ,0 + ,0) + ,dim=c(9 + ,68) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2' + ,'Y3' + ,'Y4' + ,'O1' + ,'O2' + ,'O3') + ,1:68)) > y <- array(NA,dim=c(9,68),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4','O1','O2','O3'),1:68)) > 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 = '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 Y X Y1 Y2 Y3 Y4 O1 O2 O3 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 3.70 0 3.70 3.93 4.15 4.24 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 2 3.65 0 3.70 3.70 3.93 4.15 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 3 3.55 0 3.65 3.70 3.70 3.93 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 4 3.43 0 3.55 3.65 3.70 3.70 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 5 3.47 0 3.43 3.55 3.65 3.70 0 0 0 0 0 0 0 1 0 0 0 0 0 0 5 6 3.58 0 3.47 3.43 3.55 3.65 0 0 0 0 0 0 0 0 1 0 0 0 0 0 6 7 3.67 0 3.58 3.47 3.43 3.55 0 0 0 0 0 0 0 0 0 1 0 0 0 0 7 8 3.72 0 3.67 3.58 3.47 3.43 0 0 0 0 0 0 0 0 0 0 1 0 0 0 8 9 3.80 0 3.72 3.67 3.58 3.47 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 10 3.76 0 3.80 3.72 3.67 3.58 0 0 0 0 0 0 0 0 0 0 0 0 1 0 10 11 3.63 0 3.76 3.80 3.72 3.67 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 12 3.48 0 3.63 3.76 3.80 3.72 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 13 3.41 0 3.48 3.63 3.76 3.80 0 0 0 1 0 0 0 0 0 0 0 0 0 0 13 14 3.43 0 3.41 3.48 3.63 3.76 0 0 0 0 1 0 0 0 0 0 0 0 0 0 14 15 3.50 0 3.43 3.41 3.48 3.63 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15 16 3.62 0 3.50 3.43 3.41 3.48 0 0 0 0 0 0 1 0 0 0 0 0 0 0 16 17 3.58 0 3.62 3.50 3.43 3.41 0 0 0 0 0 0 0 1 0 0 0 0 0 0 17 18 3.52 0 3.58 3.62 3.50 3.43 0 0 0 0 0 0 0 0 1 0 0 0 0 0 18 19 3.45 0 3.52 3.58 3.62 3.50 0 0 0 0 0 0 0 0 0 1 0 0 0 0 19 20 3.36 0 3.45 3.52 3.58 3.62 0 0 0 0 0 0 0 0 0 0 1 0 0 0 20 21 3.27 0 3.36 3.45 3.52 3.58 0 0 0 0 0 0 0 0 0 0 0 1 0 0 21 22 3.21 0 3.27 3.36 3.45 3.52 0 0 0 0 0 0 0 0 0 0 0 0 1 0 22 23 3.19 0 3.21 3.27 3.36 3.45 0 0 0 0 0 0 0 0 0 0 0 0 0 1 23 24 3.16 0 3.19 3.21 3.27 3.36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 25 3.12 0 3.16 3.19 3.21 3.27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 25 26 3.06 0 3.12 3.16 3.19 3.21 0 0 0 0 1 0 0 0 0 0 0 0 0 0 26 27 3.01 0 3.06 3.12 3.16 3.19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 27 28 2.98 0 3.01 3.06 3.12 3.16 0 0 0 0 0 0 1 0 0 0 0 0 0 0 28 29 2.97 0 2.98 3.01 3.06 3.12 0 0 0 0 0 0 0 1 0 0 0 0 0 0 29 30 3.02 0 2.97 2.98 3.01 3.06 0 0 0 0 0 0 0 0 1 0 0 0 0 0 30 31 3.07 0 3.02 2.97 2.98 3.01 0 0 0 0 0 0 0 0 0 1 0 0 0 0 31 32 3.18 0 3.07 3.02 2.97 2.98 0 0 0 0 0 0 0 0 0 0 1 0 0 0 32 33 3.29 1 3.18 3.07 3.02 2.97 0 0 0 0 0 0 0 0 0 0 0 1 0 0 33 34 3.43 1 3.29 3.18 3.07 3.02 0 0 0 0 0 0 0 0 0 0 0 0 1 0 34 35 3.61 1 3.43 3.29 3.18 3.07 0 0 0 0 0 0 0 0 0 0 0 0 0 1 35 36 3.74 1 3.61 3.43 3.29 3.18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 37 3.87 1 3.74 3.61 3.43 3.29 0 0 0 1 0 0 0 0 0 0 0 0 0 0 37 38 3.88 1 3.87 3.74 3.61 3.43 0 0 0 0 1 0 0 0 0 0 0 0 0 0 38 39 4.09 1 3.88 3.87 3.74 3.61 0 0 0 0 0 1 0 0 0 0 0 0 0 0 39 40 4.19 1 4.09 3.88 3.87 3.74 0 0 0 0 0 0 1 0 0 0 0 0 0 0 40 41 4.20 1 4.19 4.09 3.88 3.87 0 0 0 0 0 0 0 1 0 0 0 0 0 0 41 42 4.29 1 4.20 4.19 4.09 3.88 0 0 0 0 0 0 0 0 1 0 0 0 0 0 42 43 4.37 1 4.29 4.20 4.19 4.09 0 0 0 0 0 0 0 0 0 1 0 0 0 0 43 44 4.47 1 4.37 4.29 4.20 4.19 0 0 0 0 0 0 0 0 0 0 1 0 0 0 44 45 4.61 1 4.47 4.37 4.29 4.20 0 0 0 0 0 0 0 0 0 0 0 1 0 0 45 46 4.65 1 4.61 4.47 4.37 4.29 0 0 0 0 0 0 0 0 0 0 0 0 1 0 46 47 4.69 1 4.65 4.61 4.47 4.37 0 0 0 0 0 0 0 0 0 0 0 0 0 1 47 48 4.82 1 4.69 4.65 4.61 4.47 0 0 0 0 0 0 0 0 0 0 0 0 0 0 48 49 4.86 1 4.82 4.69 4.65 4.61 0 0 0 1 0 0 0 0 0 0 0 0 0 0 49 50 4.87 1 4.86 4.82 4.69 4.65 0 0 0 0 1 0 0 0 0 0 0 0 0 0 50 51 5.01 1 4.87 4.86 4.82 4.69 0 0 0 0 0 1 0 0 0 0 0 0 0 0 51 52 5.03 1 5.01 4.87 4.86 4.82 0 0 0 0 0 0 1 0 0 0 0 0 0 0 52 53 5.13 1 5.03 5.01 4.87 4.86 0 0 0 0 0 0 0 1 0 0 0 0 0 0 53 54 5.18 1 5.13 5.03 5.01 4.87 0 0 0 0 0 0 0 0 1 0 0 0 0 0 54 55 5.21 1 5.18 5.13 5.03 5.01 0 0 0 0 0 0 0 0 0 1 0 0 0 0 55 56 5.26 1 5.21 5.18 5.13 5.03 0 0 0 0 0 0 0 0 0 0 1 0 0 0 56 57 5.25 1 5.26 5.21 5.18 5.13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 57 58 5.20 1 5.25 5.26 5.21 5.18 0 0 0 0 0 0 0 0 0 0 0 0 1 0 58 59 5.16 1 5.20 5.25 5.26 5.21 0 0 0 0 0 0 0 0 0 0 0 0 0 1 59 60 5.19 1 5.16 5.20 5.25 5.26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60 61 5.39 1 5.19 5.16 5.20 5.25 0 0 0 1 0 0 0 0 0 0 0 0 0 0 61 62 5.58 1 5.39 5.19 5.16 5.20 0 0 0 0 1 0 0 0 0 0 0 0 0 0 62 63 5.76 1 5.58 5.39 5.19 5.16 0 0 0 0 0 1 0 0 0 0 0 0 0 0 63 64 5.89 1 5.76 5.58 5.39 5.19 0 0 1 0 0 0 1 0 0 0 0 0 0 0 64 65 5.98 1 5.89 5.76 5.58 5.39 0 1 0 0 0 0 0 1 0 0 0 0 0 0 65 66 6.02 1 5.98 5.89 5.76 5.58 1 0 0 0 0 0 0 0 1 0 0 0 0 0 66 67 5.62 1 6.02 5.98 5.89 5.76 0 0 0 0 0 0 0 0 0 1 0 0 0 0 67 68 4.87 1 5.62 6.02 5.98 5.89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 68 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 Y3 Y4 0.2057026 0.1127320 2.0113964 -1.4959688 0.3491965 0.0804554 O1 O2 O3 M1 M2 M3 0.0525626 0.0942235 0.1473695 0.0334034 -0.0510167 0.0589097 M4 M5 M6 M7 M8 M9 -0.0626460 0.0066517 0.0244183 -0.0680214 -0.0260023 -0.0090469 M10 M11 t -0.0453841 -0.0001017 -0.0007973 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.259896 -0.045571 0.003107 0.058051 0.133051 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.2057026 0.0911777 2.256 0.0288 * X 0.1127320 0.0626107 1.801 0.0782 . Y1 2.0113964 0.1698601 11.841 1.04e-15 *** Y2 -1.4959688 0.3393943 -4.408 6.03e-05 *** Y3 0.3491965 0.3803620 0.918 0.3633 Y4 0.0804554 0.2092979 0.384 0.7024 O1 0.0525626 0.1128683 0.466 0.6436 O2 0.0942235 0.1161697 0.811 0.4214 O3 0.1473695 0.1155369 1.276 0.2084 M1 0.0334034 0.0589822 0.566 0.5739 M2 -0.0510167 0.0599731 -0.851 0.3993 M3 0.0589097 0.0611491 0.963 0.3403 M4 -0.0626460 0.0618923 -1.012 0.3166 M5 0.0066517 0.0640051 0.104 0.9177 M6 0.0244183 0.0615229 0.397 0.6932 M7 -0.0680214 0.0597748 -1.138 0.2609 M8 -0.0260023 0.0606276 -0.429 0.6700 M9 -0.0090469 0.0612088 -0.148 0.8831 M10 -0.0453841 0.0614815 -0.738 0.4641 M11 -0.0001017 0.0615389 -0.002 0.9987 t -0.0007973 0.0014625 -0.545 0.5882 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.09613 on 47 degrees of freedom Multiple R-squared: 0.9919, Adjusted R-squared: 0.9885 F-statistic: 288.1 on 20 and 47 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,] 0.72219960 0.55560080 0.2778004 [2,] 0.67261261 0.65477478 0.3273874 [3,] 0.52684594 0.94630812 0.4731541 [4,] 0.52346845 0.95306311 0.4765316 [5,] 0.40281268 0.80562537 0.5971873 [6,] 0.31332412 0.62664824 0.6866759 [7,] 0.26850135 0.53700270 0.7314987 [8,] 0.18488199 0.36976398 0.8151180 [9,] 0.15199510 0.30399020 0.8480049 [10,] 0.11293977 0.22587954 0.8870602 [11,] 0.08892208 0.17784417 0.9110779 [12,] 0.06589214 0.13178428 0.9341079 [13,] 0.05619029 0.11238058 0.9438097 [14,] 0.03523949 0.07047898 0.9647605 [15,] 0.01869531 0.03739062 0.9813047 [16,] 0.03660117 0.07320233 0.9633988 [17,] 0.02277970 0.04555941 0.9772203 [18,] 0.04103896 0.08207793 0.9589610 [19,] 0.02794827 0.05589655 0.9720517 [20,] 0.01333440 0.02666880 0.9866656 [21,] 0.02026638 0.04053276 0.9797336 > postscript(file="/var/www/html/rcomp/tmp/180ls1293571155.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/280ls1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ia3v1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4ia3v1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5ia3v1293571155.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 = 68 Frequency = 1 1 2 3 4 5 1.083856e-01 -1.164056e-01 -1.269494e-01 2.024952e-02 1.009796e-01 6 7 8 9 10 -2.701939e-02 4.475194e-02 3.274778e-02 8.902726e-02 -4.022925e-02 11 12 13 14 15 -3.928184e-02 -1.890190e-02 -6.743030e-03 6.349061e-02 -5.774553e-02 16 17 18 19 20 1.102412e-01 -1.362611e-01 2.068887e-02 5.723553e-02 -1.863346e-02 21 22 23 24 25 -2.431365e-02 2.848046e-02 -1.289854e-02 -5.306443e-02 -6.705522e-02 26 27 28 29 30 5.550268e-03 -8.064876e-02 3.889747e-02 -2.988953e-02 6.632393e-04 31 32 33 34 35 4.286947e-02 9.178189e-02 -9.021866e-02 8.736246e-03 -1.522222e-02 36 37 38 39 40 -8.440401e-02 -3.695485e-02 -8.286212e-02 1.324933e-01 -1.084420e-01 41 42 43 44 45 -6.787983e-02 6.049799e-02 1.585380e-02 3.681995e-02 4.696751e-02 46 47 48 49 50 -4.307327e-02 4.006527e-02 9.321076e-02 -1.262697e-01 6.578174e-02 51 52 53 54 55 8.776370e-02 -6.094615e-02 1.330509e-01 -5.483070e-02 9.918575e-02 56 57 58 59 60 8.589172e-02 -2.146246e-02 4.608582e-02 2.733732e-02 6.315958e-02 61 62 63 64 65 1.286372e-01 6.444507e-02 4.508676e-02 6.418477e-17 3.989864e-17 66 67 68 -2.255141e-17 -2.598965e-01 -2.286079e-01 > postscript(file="/var/www/html/rcomp/tmp/6b1ky1293571155.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 = 68 Frequency = 1 lag(myerror, k = 1) myerror 0 1.083856e-01 NA 1 -1.164056e-01 1.083856e-01 2 -1.269494e-01 -1.164056e-01 3 2.024952e-02 -1.269494e-01 4 1.009796e-01 2.024952e-02 5 -2.701939e-02 1.009796e-01 6 4.475194e-02 -2.701939e-02 7 3.274778e-02 4.475194e-02 8 8.902726e-02 3.274778e-02 9 -4.022925e-02 8.902726e-02 10 -3.928184e-02 -4.022925e-02 11 -1.890190e-02 -3.928184e-02 12 -6.743030e-03 -1.890190e-02 13 6.349061e-02 -6.743030e-03 14 -5.774553e-02 6.349061e-02 15 1.102412e-01 -5.774553e-02 16 -1.362611e-01 1.102412e-01 17 2.068887e-02 -1.362611e-01 18 5.723553e-02 2.068887e-02 19 -1.863346e-02 5.723553e-02 20 -2.431365e-02 -1.863346e-02 21 2.848046e-02 -2.431365e-02 22 -1.289854e-02 2.848046e-02 23 -5.306443e-02 -1.289854e-02 24 -6.705522e-02 -5.306443e-02 25 5.550268e-03 -6.705522e-02 26 -8.064876e-02 5.550268e-03 27 3.889747e-02 -8.064876e-02 28 -2.988953e-02 3.889747e-02 29 6.632393e-04 -2.988953e-02 30 4.286947e-02 6.632393e-04 31 9.178189e-02 4.286947e-02 32 -9.021866e-02 9.178189e-02 33 8.736246e-03 -9.021866e-02 34 -1.522222e-02 8.736246e-03 35 -8.440401e-02 -1.522222e-02 36 -3.695485e-02 -8.440401e-02 37 -8.286212e-02 -3.695485e-02 38 1.324933e-01 -8.286212e-02 39 -1.084420e-01 1.324933e-01 40 -6.787983e-02 -1.084420e-01 41 6.049799e-02 -6.787983e-02 42 1.585380e-02 6.049799e-02 43 3.681995e-02 1.585380e-02 44 4.696751e-02 3.681995e-02 45 -4.307327e-02 4.696751e-02 46 4.006527e-02 -4.307327e-02 47 9.321076e-02 4.006527e-02 48 -1.262697e-01 9.321076e-02 49 6.578174e-02 -1.262697e-01 50 8.776370e-02 6.578174e-02 51 -6.094615e-02 8.776370e-02 52 1.330509e-01 -6.094615e-02 53 -5.483070e-02 1.330509e-01 54 9.918575e-02 -5.483070e-02 55 8.589172e-02 9.918575e-02 56 -2.146246e-02 8.589172e-02 57 4.608582e-02 -2.146246e-02 58 2.733732e-02 4.608582e-02 59 6.315958e-02 2.733732e-02 60 1.286372e-01 6.315958e-02 61 6.444507e-02 1.286372e-01 62 4.508676e-02 6.444507e-02 63 6.418477e-17 4.508676e-02 64 3.989864e-17 6.418477e-17 65 -2.255141e-17 3.989864e-17 66 -2.598965e-01 -2.255141e-17 67 -2.286079e-01 -2.598965e-01 68 NA -2.286079e-01 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1.164056e-01 1.083856e-01 [2,] -1.269494e-01 -1.164056e-01 [3,] 2.024952e-02 -1.269494e-01 [4,] 1.009796e-01 2.024952e-02 [5,] -2.701939e-02 1.009796e-01 [6,] 4.475194e-02 -2.701939e-02 [7,] 3.274778e-02 4.475194e-02 [8,] 8.902726e-02 3.274778e-02 [9,] -4.022925e-02 8.902726e-02 [10,] -3.928184e-02 -4.022925e-02 [11,] -1.890190e-02 -3.928184e-02 [12,] -6.743030e-03 -1.890190e-02 [13,] 6.349061e-02 -6.743030e-03 [14,] -5.774553e-02 6.349061e-02 [15,] 1.102412e-01 -5.774553e-02 [16,] -1.362611e-01 1.102412e-01 [17,] 2.068887e-02 -1.362611e-01 [18,] 5.723553e-02 2.068887e-02 [19,] -1.863346e-02 5.723553e-02 [20,] -2.431365e-02 -1.863346e-02 [21,] 2.848046e-02 -2.431365e-02 [22,] -1.289854e-02 2.848046e-02 [23,] -5.306443e-02 -1.289854e-02 [24,] -6.705522e-02 -5.306443e-02 [25,] 5.550268e-03 -6.705522e-02 [26,] -8.064876e-02 5.550268e-03 [27,] 3.889747e-02 -8.064876e-02 [28,] -2.988953e-02 3.889747e-02 [29,] 6.632393e-04 -2.988953e-02 [30,] 4.286947e-02 6.632393e-04 [31,] 9.178189e-02 4.286947e-02 [32,] -9.021866e-02 9.178189e-02 [33,] 8.736246e-03 -9.021866e-02 [34,] -1.522222e-02 8.736246e-03 [35,] -8.440401e-02 -1.522222e-02 [36,] -3.695485e-02 -8.440401e-02 [37,] -8.286212e-02 -3.695485e-02 [38,] 1.324933e-01 -8.286212e-02 [39,] -1.084420e-01 1.324933e-01 [40,] -6.787983e-02 -1.084420e-01 [41,] 6.049799e-02 -6.787983e-02 [42,] 1.585380e-02 6.049799e-02 [43,] 3.681995e-02 1.585380e-02 [44,] 4.696751e-02 3.681995e-02 [45,] -4.307327e-02 4.696751e-02 [46,] 4.006527e-02 -4.307327e-02 [47,] 9.321076e-02 4.006527e-02 [48,] -1.262697e-01 9.321076e-02 [49,] 6.578174e-02 -1.262697e-01 [50,] 8.776370e-02 6.578174e-02 [51,] -6.094615e-02 8.776370e-02 [52,] 1.330509e-01 -6.094615e-02 [53,] -5.483070e-02 1.330509e-01 [54,] 9.918575e-02 -5.483070e-02 [55,] 8.589172e-02 9.918575e-02 [56,] -2.146246e-02 8.589172e-02 [57,] 4.608582e-02 -2.146246e-02 [58,] 2.733732e-02 4.608582e-02 [59,] 6.315958e-02 2.733732e-02 [60,] 1.286372e-01 6.315958e-02 [61,] 6.444507e-02 1.286372e-01 [62,] 4.508676e-02 6.444507e-02 [63,] 6.418477e-17 4.508676e-02 [64,] 3.989864e-17 6.418477e-17 [65,] -2.255141e-17 3.989864e-17 [66,] -2.598965e-01 -2.255141e-17 [67,] -2.286079e-01 -2.598965e-01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1.164056e-01 1.083856e-01 2 -1.269494e-01 -1.164056e-01 3 2.024952e-02 -1.269494e-01 4 1.009796e-01 2.024952e-02 5 -2.701939e-02 1.009796e-01 6 4.475194e-02 -2.701939e-02 7 3.274778e-02 4.475194e-02 8 8.902726e-02 3.274778e-02 9 -4.022925e-02 8.902726e-02 10 -3.928184e-02 -4.022925e-02 11 -1.890190e-02 -3.928184e-02 12 -6.743030e-03 -1.890190e-02 13 6.349061e-02 -6.743030e-03 14 -5.774553e-02 6.349061e-02 15 1.102412e-01 -5.774553e-02 16 -1.362611e-01 1.102412e-01 17 2.068887e-02 -1.362611e-01 18 5.723553e-02 2.068887e-02 19 -1.863346e-02 5.723553e-02 20 -2.431365e-02 -1.863346e-02 21 2.848046e-02 -2.431365e-02 22 -1.289854e-02 2.848046e-02 23 -5.306443e-02 -1.289854e-02 24 -6.705522e-02 -5.306443e-02 25 5.550268e-03 -6.705522e-02 26 -8.064876e-02 5.550268e-03 27 3.889747e-02 -8.064876e-02 28 -2.988953e-02 3.889747e-02 29 6.632393e-04 -2.988953e-02 30 4.286947e-02 6.632393e-04 31 9.178189e-02 4.286947e-02 32 -9.021866e-02 9.178189e-02 33 8.736246e-03 -9.021866e-02 34 -1.522222e-02 8.736246e-03 35 -8.440401e-02 -1.522222e-02 36 -3.695485e-02 -8.440401e-02 37 -8.286212e-02 -3.695485e-02 38 1.324933e-01 -8.286212e-02 39 -1.084420e-01 1.324933e-01 40 -6.787983e-02 -1.084420e-01 41 6.049799e-02 -6.787983e-02 42 1.585380e-02 6.049799e-02 43 3.681995e-02 1.585380e-02 44 4.696751e-02 3.681995e-02 45 -4.307327e-02 4.696751e-02 46 4.006527e-02 -4.307327e-02 47 9.321076e-02 4.006527e-02 48 -1.262697e-01 9.321076e-02 49 6.578174e-02 -1.262697e-01 50 8.776370e-02 6.578174e-02 51 -6.094615e-02 8.776370e-02 52 1.330509e-01 -6.094615e-02 53 -5.483070e-02 1.330509e-01 54 9.918575e-02 -5.483070e-02 55 8.589172e-02 9.918575e-02 56 -2.146246e-02 8.589172e-02 57 4.608582e-02 -2.146246e-02 58 2.733732e-02 4.608582e-02 59 6.315958e-02 2.733732e-02 60 1.286372e-01 6.315958e-02 61 6.444507e-02 1.286372e-01 62 4.508676e-02 6.444507e-02 63 6.418477e-17 4.508676e-02 64 3.989864e-17 6.418477e-17 65 -2.255141e-17 3.989864e-17 66 -2.598965e-01 -2.255141e-17 67 -2.286079e-01 -2.598965e-01 > 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/7ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') Warning messages: 1: Not plotting observations with leverage one: 64, 65, 66 2: Not plotting observations with leverage one: 64, 65, 66 > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10e1141293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11au251293571156.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/12ec0b1293571156.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/13a4y11293571156.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/14d5xp1293571156.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/15z5vd1293571156.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/1626bj1293571156.tab") + } > > try(system("convert tmp/180ls1293571155.ps tmp/180ls1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/280ls1293571155.ps tmp/280ls1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/3ia3v1293571155.ps tmp/3ia3v1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/4ia3v1293571155.ps tmp/4ia3v1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/5ia3v1293571155.ps tmp/5ia3v1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/6b1ky1293571155.ps tmp/6b1ky1293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/7ma111293571155.ps tmp/7ma111293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/8ma111293571155.ps tmp/8ma111293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/9ma111293571155.ps tmp/9ma111293571155.png",intern=TRUE)) character(0) > try(system("convert tmp/10e1141293571155.ps tmp/10e1141293571155.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.572 1.613 5.858