R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,3 + ,5 + ,0 + ,0 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,1 + ,8 + ,2 + ,1 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,1 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,3 + ,5 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,3 + ,5 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,3 + ,5 + ,0 + ,1 + ,8 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,5 + ,0 + ,0 + ,8 + ,2 + ,1 + ,3 + ,5 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,3 + ,5 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,5 + ,0 + ,1 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,1 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,5 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,5 + ,0 + ,1 + ,7 + ,2 + ,1 + ,3 + ,5 + ,0 + ,1 + ,7 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,5 + ,1 + ,0 + ,7 + ,2 + ,0 + ,3 + ,5 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,1 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,1 + ,8 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,7 + ,2 + ,0 + ,3 + ,5 + ,0 + ,0 + ,8 + ,2 + ,0 + ,3 + ,6 + ,0 + ,0 + ,8 + ,2 + ,1 + ,4 + ,6 + ,0 + ,0 + ,8 + ,2 + ,0 + ,4 + ,6 + ,0 + ,1 + ,7 + ,2 + ,0 + ,4 + ,6 + ,0 + ,0 + ,7 + ,2 + ,1 + ,4 + ,5 + ,1 + ,0 + ,8 + ,2 + ,1 + ,4 + ,5 + ,1 + ,1 + ,8 + ,2 + ,1 + ,4 + ,5 + ,0 + ,0 + ,8) + ,dim=c(7 + ,68) + ,dimnames=list(c('Weeks' + ,'UseLimit' + ,'T20' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome') + ,1:68)) > y <- array(NA,dim=c(7,68),dimnames=list(c('Weeks','UseLimit','T20','Used','CorrectAnalysis','Useful','Outcome'),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 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '5' > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x CorrectAnalysis Weeks UseLimit T20 Used Useful Outcome 1 0 2 1 4 6 0 7 2 0 2 1 3 5 0 7 3 0 2 0 4 6 0 8 4 0 2 0 4 6 0 7 5 0 2 0 4 6 1 8 6 0 2 1 3 6 0 8 7 0 2 1 4 6 1 8 8 0 2 0 4 6 0 8 9 0 2 0 3 6 0 8 10 0 2 0 4 6 0 7 11 0 2 1 3 6 0 8 12 0 2 0 4 6 0 8 13 0 2 1 4 6 0 8 14 0 2 0 4 6 0 7 15 0 2 1 4 6 0 7 16 0 2 0 4 6 0 8 17 0 2 0 4 6 0 8 18 0 2 0 4 6 0 8 19 0 2 0 3 5 0 8 20 0 2 0 4 6 0 8 21 0 2 0 4 6 0 8 22 0 2 1 3 5 0 8 23 0 2 0 4 6 0 8 24 0 2 1 4 6 0 8 25 0 2 1 3 5 1 8 26 0 2 0 3 6 0 8 27 0 2 0 4 5 0 8 28 0 2 1 3 5 0 8 29 0 2 1 4 6 0 8 30 0 2 0 4 6 0 8 31 0 2 1 4 6 0 7 32 0 2 1 4 6 0 8 33 0 2 0 4 6 0 8 34 0 2 0 4 6 0 7 35 0 2 1 4 6 0 8 36 0 2 0 4 6 0 8 37 0 2 1 3 5 0 8 38 0 2 0 4 5 1 7 39 0 2 0 4 6 0 7 40 0 2 0 3 6 0 8 41 0 2 0 4 6 1 8 42 0 2 0 4 6 0 7 43 0 2 0 4 6 0 8 44 0 2 0 4 6 0 7 45 0 2 1 4 6 0 8 46 0 2 1 4 6 0 7 47 0 2 1 4 5 0 8 48 0 2 0 4 6 0 8 49 0 2 0 4 6 0 8 50 0 2 0 4 6 0 8 51 0 2 1 4 5 1 7 52 0 2 1 3 5 1 7 53 0 2 0 3 6 0 8 54 0 2 0 4 6 0 8 55 1 2 0 4 5 0 7 56 0 2 0 3 5 0 7 57 0 2 1 4 6 0 8 58 0 2 0 4 6 1 7 59 0 2 0 4 6 1 8 60 0 2 0 3 6 0 7 61 0 2 0 3 5 0 8 62 0 2 0 3 6 0 8 63 0 2 1 4 6 0 8 64 0 2 0 4 6 1 7 65 0 2 0 4 6 0 7 66 1 2 1 4 5 0 8 67 1 2 1 4 5 1 8 68 0 2 1 4 5 0 8 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Weeks UseLimit T20 Used Useful 0.6930594 NA 0.0005804 0.1487291 -0.2345955 -0.0103240 Outcome 0.0186833 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.26504 -0.03045 -0.02987 -0.01119 0.75422 Coefficients: (1 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 0.6930594 0.5153239 1.345 0.183557 Weeks NA NA NA NA UseLimit 0.0005804 0.0501236 0.012 0.990798 T20 0.1487291 0.0583749 2.548 0.013333 * Used -0.2345955 0.0621132 -3.777 0.000358 *** Useful -0.0103240 0.0651772 -0.158 0.874657 Outcome 0.0186833 0.0508163 0.368 0.714376 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.1898 on 62 degrees of freedom Multiple R-squared: 0.2208, Adjusted R-squared: 0.158 F-statistic: 3.514 on 5 and 62 DF, p-value: 0.007341 > 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,] 0.000000e+00 0.000000e+00 1.0000000 [2,] 0.000000e+00 0.000000e+00 1.0000000 [3,] 0.000000e+00 0.000000e+00 1.0000000 [4,] 0.000000e+00 0.000000e+00 1.0000000 [5,] 0.000000e+00 0.000000e+00 1.0000000 [6,] 0.000000e+00 0.000000e+00 1.0000000 [7,] 0.000000e+00 0.000000e+00 1.0000000 [8,] 0.000000e+00 0.000000e+00 1.0000000 [9,] 0.000000e+00 0.000000e+00 1.0000000 [10,] 0.000000e+00 0.000000e+00 1.0000000 [11,] 0.000000e+00 0.000000e+00 1.0000000 [12,] 0.000000e+00 0.000000e+00 1.0000000 [13,] 0.000000e+00 0.000000e+00 1.0000000 [14,] 0.000000e+00 0.000000e+00 1.0000000 [15,] 0.000000e+00 0.000000e+00 1.0000000 [16,] 0.000000e+00 0.000000e+00 1.0000000 [17,] 0.000000e+00 0.000000e+00 1.0000000 [18,] 0.000000e+00 0.000000e+00 1.0000000 [19,] 0.000000e+00 0.000000e+00 1.0000000 [20,] 0.000000e+00 0.000000e+00 1.0000000 [21,] 0.000000e+00 0.000000e+00 1.0000000 [22,] 0.000000e+00 0.000000e+00 1.0000000 [23,] 0.000000e+00 0.000000e+00 1.0000000 [24,] 0.000000e+00 0.000000e+00 1.0000000 [25,] 0.000000e+00 0.000000e+00 1.0000000 [26,] 0.000000e+00 0.000000e+00 1.0000000 [27,] 0.000000e+00 0.000000e+00 1.0000000 [28,] 0.000000e+00 0.000000e+00 1.0000000 [29,] 0.000000e+00 0.000000e+00 1.0000000 [30,] 0.000000e+00 0.000000e+00 1.0000000 [31,] 0.000000e+00 0.000000e+00 1.0000000 [32,] 0.000000e+00 0.000000e+00 1.0000000 [33,] 0.000000e+00 0.000000e+00 1.0000000 [34,] 0.000000e+00 0.000000e+00 1.0000000 [35,] 0.000000e+00 0.000000e+00 1.0000000 [36,] 0.000000e+00 0.000000e+00 1.0000000 [37,] 0.000000e+00 0.000000e+00 1.0000000 [38,] 0.000000e+00 0.000000e+00 1.0000000 [39,] 0.000000e+00 0.000000e+00 1.0000000 [40,] 0.000000e+00 0.000000e+00 1.0000000 [41,] 0.000000e+00 0.000000e+00 1.0000000 [42,] 0.000000e+00 0.000000e+00 1.0000000 [43,] 0.000000e+00 0.000000e+00 1.0000000 [44,] 0.000000e+00 0.000000e+00 1.0000000 [45,] 0.000000e+00 0.000000e+00 1.0000000 [46,] 8.720411e-06 1.744082e-05 0.9999913 [47,] 8.353127e-06 1.670625e-05 0.9999916 [48,] 3.145476e-06 6.290952e-06 0.9999969 [49,] 1.010087e-06 2.020174e-06 0.9999990 > postscript(file="/var/wessaorg/rcomp/tmp/1lusd1356170124.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/wessaorg/rcomp/tmp/2d0671356170124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3hhr11356170124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4eswl1356170124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5c6yj1356170124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 -0.0117661523 -0.0976325499 -0.0298690287 -0.0111857445 -0.0195449973 6 7 8 9 10 0.1182797046 -0.0201254051 -0.0298690287 0.1188601125 -0.0111857445 11 12 13 14 15 0.1182797046 -0.0298690287 -0.0304494365 -0.0111857445 -0.0117661523 16 17 18 19 20 -0.0298690287 -0.0298690287 -0.0298690287 -0.1157354263 -0.0298690287 21 22 23 24 25 -0.0298690287 -0.1163158341 -0.0298690287 -0.0304494365 -0.1059918027 26 27 28 29 30 0.1188601125 -0.2644645674 -0.1163158341 -0.0304494365 -0.0298690287 31 32 33 34 35 -0.0117661523 -0.0304494365 -0.0298690287 -0.0111857445 -0.0304494365 36 37 38 39 40 -0.0298690287 -0.1163158341 -0.2354572519 -0.0111857445 0.1188601125 41 42 43 44 45 -0.0195449973 -0.0111857445 -0.0298690287 -0.0111857445 -0.0304494365 46 47 48 49 50 -0.0117661523 -0.2650449753 -0.0298690287 -0.0298690287 -0.0298690287 51 52 53 54 55 -0.2360376597 -0.0873085185 0.1188601125 -0.0298690287 0.7542187168 56 57 58 59 60 -0.0970521421 -0.0304494365 -0.0008617131 -0.0195449973 0.1375433967 61 62 63 64 65 -0.1157354263 0.1188601125 -0.0304494365 -0.0008617131 -0.0111857445 66 67 68 0.7349550247 0.7452790561 -0.2650449753 > postscript(file="/var/wessaorg/rcomp/tmp/6m5fi1356170124.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 -0.0117661523 NA 1 -0.0976325499 -0.0117661523 2 -0.0298690287 -0.0976325499 3 -0.0111857445 -0.0298690287 4 -0.0195449973 -0.0111857445 5 0.1182797046 -0.0195449973 6 -0.0201254051 0.1182797046 7 -0.0298690287 -0.0201254051 8 0.1188601125 -0.0298690287 9 -0.0111857445 0.1188601125 10 0.1182797046 -0.0111857445 11 -0.0298690287 0.1182797046 12 -0.0304494365 -0.0298690287 13 -0.0111857445 -0.0304494365 14 -0.0117661523 -0.0111857445 15 -0.0298690287 -0.0117661523 16 -0.0298690287 -0.0298690287 17 -0.0298690287 -0.0298690287 18 -0.1157354263 -0.0298690287 19 -0.0298690287 -0.1157354263 20 -0.0298690287 -0.0298690287 21 -0.1163158341 -0.0298690287 22 -0.0298690287 -0.1163158341 23 -0.0304494365 -0.0298690287 24 -0.1059918027 -0.0304494365 25 0.1188601125 -0.1059918027 26 -0.2644645674 0.1188601125 27 -0.1163158341 -0.2644645674 28 -0.0304494365 -0.1163158341 29 -0.0298690287 -0.0304494365 30 -0.0117661523 -0.0298690287 31 -0.0304494365 -0.0117661523 32 -0.0298690287 -0.0304494365 33 -0.0111857445 -0.0298690287 34 -0.0304494365 -0.0111857445 35 -0.0298690287 -0.0304494365 36 -0.1163158341 -0.0298690287 37 -0.2354572519 -0.1163158341 38 -0.0111857445 -0.2354572519 39 0.1188601125 -0.0111857445 40 -0.0195449973 0.1188601125 41 -0.0111857445 -0.0195449973 42 -0.0298690287 -0.0111857445 43 -0.0111857445 -0.0298690287 44 -0.0304494365 -0.0111857445 45 -0.0117661523 -0.0304494365 46 -0.2650449753 -0.0117661523 47 -0.0298690287 -0.2650449753 48 -0.0298690287 -0.0298690287 49 -0.0298690287 -0.0298690287 50 -0.2360376597 -0.0298690287 51 -0.0873085185 -0.2360376597 52 0.1188601125 -0.0873085185 53 -0.0298690287 0.1188601125 54 0.7542187168 -0.0298690287 55 -0.0970521421 0.7542187168 56 -0.0304494365 -0.0970521421 57 -0.0008617131 -0.0304494365 58 -0.0195449973 -0.0008617131 59 0.1375433967 -0.0195449973 60 -0.1157354263 0.1375433967 61 0.1188601125 -0.1157354263 62 -0.0304494365 0.1188601125 63 -0.0008617131 -0.0304494365 64 -0.0111857445 -0.0008617131 65 0.7349550247 -0.0111857445 66 0.7452790561 0.7349550247 67 -0.2650449753 0.7452790561 68 NA -0.2650449753 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.0976325499 -0.0117661523 [2,] -0.0298690287 -0.0976325499 [3,] -0.0111857445 -0.0298690287 [4,] -0.0195449973 -0.0111857445 [5,] 0.1182797046 -0.0195449973 [6,] -0.0201254051 0.1182797046 [7,] -0.0298690287 -0.0201254051 [8,] 0.1188601125 -0.0298690287 [9,] -0.0111857445 0.1188601125 [10,] 0.1182797046 -0.0111857445 [11,] -0.0298690287 0.1182797046 [12,] -0.0304494365 -0.0298690287 [13,] -0.0111857445 -0.0304494365 [14,] -0.0117661523 -0.0111857445 [15,] -0.0298690287 -0.0117661523 [16,] -0.0298690287 -0.0298690287 [17,] -0.0298690287 -0.0298690287 [18,] -0.1157354263 -0.0298690287 [19,] -0.0298690287 -0.1157354263 [20,] -0.0298690287 -0.0298690287 [21,] -0.1163158341 -0.0298690287 [22,] -0.0298690287 -0.1163158341 [23,] -0.0304494365 -0.0298690287 [24,] -0.1059918027 -0.0304494365 [25,] 0.1188601125 -0.1059918027 [26,] -0.2644645674 0.1188601125 [27,] -0.1163158341 -0.2644645674 [28,] -0.0304494365 -0.1163158341 [29,] -0.0298690287 -0.0304494365 [30,] -0.0117661523 -0.0298690287 [31,] -0.0304494365 -0.0117661523 [32,] -0.0298690287 -0.0304494365 [33,] -0.0111857445 -0.0298690287 [34,] -0.0304494365 -0.0111857445 [35,] -0.0298690287 -0.0304494365 [36,] -0.1163158341 -0.0298690287 [37,] -0.2354572519 -0.1163158341 [38,] -0.0111857445 -0.2354572519 [39,] 0.1188601125 -0.0111857445 [40,] -0.0195449973 0.1188601125 [41,] -0.0111857445 -0.0195449973 [42,] -0.0298690287 -0.0111857445 [43,] -0.0111857445 -0.0298690287 [44,] -0.0304494365 -0.0111857445 [45,] -0.0117661523 -0.0304494365 [46,] -0.2650449753 -0.0117661523 [47,] -0.0298690287 -0.2650449753 [48,] -0.0298690287 -0.0298690287 [49,] -0.0298690287 -0.0298690287 [50,] -0.2360376597 -0.0298690287 [51,] -0.0873085185 -0.2360376597 [52,] 0.1188601125 -0.0873085185 [53,] -0.0298690287 0.1188601125 [54,] 0.7542187168 -0.0298690287 [55,] -0.0970521421 0.7542187168 [56,] -0.0304494365 -0.0970521421 [57,] -0.0008617131 -0.0304494365 [58,] -0.0195449973 -0.0008617131 [59,] 0.1375433967 -0.0195449973 [60,] -0.1157354263 0.1375433967 [61,] 0.1188601125 -0.1157354263 [62,] -0.0304494365 0.1188601125 [63,] -0.0008617131 -0.0304494365 [64,] -0.0111857445 -0.0008617131 [65,] 0.7349550247 -0.0111857445 [66,] 0.7452790561 0.7349550247 [67,] -0.2650449753 0.7452790561 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.0976325499 -0.0117661523 2 -0.0298690287 -0.0976325499 3 -0.0111857445 -0.0298690287 4 -0.0195449973 -0.0111857445 5 0.1182797046 -0.0195449973 6 -0.0201254051 0.1182797046 7 -0.0298690287 -0.0201254051 8 0.1188601125 -0.0298690287 9 -0.0111857445 0.1188601125 10 0.1182797046 -0.0111857445 11 -0.0298690287 0.1182797046 12 -0.0304494365 -0.0298690287 13 -0.0111857445 -0.0304494365 14 -0.0117661523 -0.0111857445 15 -0.0298690287 -0.0117661523 16 -0.0298690287 -0.0298690287 17 -0.0298690287 -0.0298690287 18 -0.1157354263 -0.0298690287 19 -0.0298690287 -0.1157354263 20 -0.0298690287 -0.0298690287 21 -0.1163158341 -0.0298690287 22 -0.0298690287 -0.1163158341 23 -0.0304494365 -0.0298690287 24 -0.1059918027 -0.0304494365 25 0.1188601125 -0.1059918027 26 -0.2644645674 0.1188601125 27 -0.1163158341 -0.2644645674 28 -0.0304494365 -0.1163158341 29 -0.0298690287 -0.0304494365 30 -0.0117661523 -0.0298690287 31 -0.0304494365 -0.0117661523 32 -0.0298690287 -0.0304494365 33 -0.0111857445 -0.0298690287 34 -0.0304494365 -0.0111857445 35 -0.0298690287 -0.0304494365 36 -0.1163158341 -0.0298690287 37 -0.2354572519 -0.1163158341 38 -0.0111857445 -0.2354572519 39 0.1188601125 -0.0111857445 40 -0.0195449973 0.1188601125 41 -0.0111857445 -0.0195449973 42 -0.0298690287 -0.0111857445 43 -0.0111857445 -0.0298690287 44 -0.0304494365 -0.0111857445 45 -0.0117661523 -0.0304494365 46 -0.2650449753 -0.0117661523 47 -0.0298690287 -0.2650449753 48 -0.0298690287 -0.0298690287 49 -0.0298690287 -0.0298690287 50 -0.2360376597 -0.0298690287 51 -0.0873085185 -0.2360376597 52 0.1188601125 -0.0873085185 53 -0.0298690287 0.1188601125 54 0.7542187168 -0.0298690287 55 -0.0970521421 0.7542187168 56 -0.0304494365 -0.0970521421 57 -0.0008617131 -0.0304494365 58 -0.0195449973 -0.0008617131 59 0.1375433967 -0.0195449973 60 -0.1157354263 0.1375433967 61 0.1188601125 -0.1157354263 62 -0.0304494365 0.1188601125 63 -0.0008617131 -0.0304494365 64 -0.0111857445 -0.0008617131 65 0.7349550247 -0.0111857445 66 0.7452790561 0.7349550247 67 -0.2650449753 0.7452790561 > 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/wessaorg/rcomp/tmp/7czky1356170124.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/wessaorg/rcomp/tmp/8lft01356170124.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/wessaorg/rcomp/tmp/9l45w1356170124.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/wessaorg/rcomp/tmp/10zqbi1356170124.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/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='') + } + } Error: subscript out of bounds Execution halted