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Type 'q()' to quit R. > x <- array(list(38 + ,39 + ,13 + ,12 + ,15 + ,11 + ,89 + ,54 + ,37 + ,38 + ,16 + ,14 + ,15 + ,8 + ,76 + ,47 + ,33 + ,31 + ,15 + ,13 + ,15 + ,11 + ,73 + ,45 + ,31 + ,33 + ,16 + ,15 + ,13 + ,11 + ,79 + ,47 + ,39 + ,32 + ,15 + ,10 + ,17 + ,8 + ,90 + ,55 + ,44 + ,39 + ,17 + ,11 + ,17 + ,10 + ,74 + ,44 + ,33 + ,36 + ,15 + ,9 + ,19 + ,11 + ,81 + ,53 + ,35 + ,33 + ,12 + ,11 + ,15 + ,13 + ,72 + ,44 + ,32 + ,33 + ,16 + ,10 + ,13 + ,11 + ,71 + ,42 + ,28 + ,32 + ,10 + ,11 + ,9 + ,20 + ,66 + ,40 + ,40 + ,37 + ,16 + ,8 + ,15 + ,10 + ,77 + ,46 + ,27 + ,30 + ,12 + ,11 + ,15 + ,15 + ,65 + ,40 + ,37 + ,38 + ,14 + ,12 + ,15 + ,12 + ,74 + ,46 + ,32 + ,29 + ,15 + ,12 + ,16 + ,14 + ,82 + ,53 + ,28 + ,22 + ,13 + ,9 + ,11 + ,23 + ,54 + ,33 + ,34 + ,35 + ,15 + ,11 + ,14 + ,14 + ,63 + ,42 + ,30 + ,35 + ,11 + ,10 + ,11 + ,16 + ,54 + ,35 + ,35 + ,34 + ,12 + ,8 + ,15 + ,11 + ,64 + ,40 + ,31 + ,35 + ,8 + ,9 + ,13 + ,12 + ,69 + ,41 + ,32 + ,34 + ,16 + ,8 + ,15 + ,10 + ,54 + ,33 + ,30 + ,34 + ,15 + ,9 + ,16 + ,14 + ,84 + ,51 + ,30 + ,35 + ,17 + ,15 + ,14 + ,12 + ,86 + ,53 + ,31 + ,23 + ,16 + ,11 + ,15 + ,12 + ,77 + ,46 + ,40 + ,31 + ,10 + ,8 + ,16 + ,11 + ,89 + ,55 + ,32 + ,27 + ,18 + ,13 + ,16 + ,12 + ,76 + ,47 + ,36 + ,36 + ,13 + ,12 + ,11 + ,13 + ,60 + ,38 + ,32 + ,31 + ,16 + ,12 + ,12 + ,11 + ,75 + ,46 + ,35 + ,32 + ,13 + ,9 + ,9 + ,19 + ,73 + ,46 + ,38 + ,39 + ,10 + ,7 + ,16 + ,12 + ,85 + ,53 + ,42 + ,37 + ,15 + ,13 + ,13 + ,17 + ,79 + ,47 + ,34 + ,38 + ,16 + ,9 + ,16 + ,9 + ,71 + ,41 + ,35 + ,39 + ,16 + ,6 + ,12 + ,12 + ,72 + ,44 + ,35 + ,34 + ,14 + ,8 + ,9 + ,19 + ,69 + ,43 + ,33 + ,31 + ,10 + ,8 + ,13 + ,18 + ,78 + ,51 + ,36 + ,32 + ,17 + ,15 + ,13 + ,15 + ,54 + ,33 + ,32 + ,37 + ,13 + ,6 + ,14 + ,14 + ,69 + ,43 + ,33 + ,36 + ,15 + ,9 + ,19 + ,11 + ,81 + ,53 + ,34 + ,32 + ,16 + ,11 + ,13 + ,9 + ,84 + ,51 + ,32 + ,35 + ,12 + ,8 + ,12 + ,18 + ,84 + ,50 + ,34 + ,36 + ,13 + ,8 + ,13 + ,16 + ,69 + ,46) + ,dim=c(8 + ,40) + ,dimnames=list(c('Connected' + ,'Separate' + ,'Learning' + ,'Software' + ,'Happiness' + ,'Depression' + ,'Belonging' + ,'Belonging_Final') + ,1:40)) > y <- array(NA,dim=c(8,40),dimnames=list(c('Connected','Separate','Learning','Software','Happiness','Depression','Belonging','Belonging_Final'),1:40)) > 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 = '1' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal 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, 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 Connected Separate Learning Software Happiness Depression Belonging 1 38 39 13 12 15 11 89 2 37 38 16 14 15 8 76 3 33 31 15 13 15 11 73 4 31 33 16 15 13 11 79 5 39 32 15 10 17 8 90 6 44 39 17 11 17 10 74 7 33 36 15 9 19 11 81 8 35 33 12 11 15 13 72 9 32 33 16 10 13 11 71 10 28 32 10 11 9 20 66 11 40 37 16 8 15 10 77 12 27 30 12 11 15 15 65 13 37 38 14 12 15 12 74 14 32 29 15 12 16 14 82 15 28 22 13 9 11 23 54 16 34 35 15 11 14 14 63 17 30 35 11 10 11 16 54 18 35 34 12 8 15 11 64 19 31 35 8 9 13 12 69 20 32 34 16 8 15 10 54 21 30 34 15 9 16 14 84 22 30 35 17 15 14 12 86 23 31 23 16 11 15 12 77 24 40 31 10 8 16 11 89 25 32 27 18 13 16 12 76 26 36 36 13 12 11 13 60 27 32 31 16 12 12 11 75 28 35 32 13 9 9 19 73 29 38 39 10 7 16 12 85 30 42 37 15 13 13 17 79 31 34 38 16 9 16 9 71 32 35 39 16 6 12 12 72 33 35 34 14 8 9 19 69 34 33 31 10 8 13 18 78 35 36 32 17 15 13 15 54 36 32 37 13 6 14 14 69 37 33 36 15 9 19 11 81 38 34 32 16 11 13 9 84 39 32 35 12 8 12 18 84 40 34 36 13 8 13 16 69 Belonging_Final 1 54 2 47 3 45 4 47 5 55 6 44 7 53 8 44 9 42 10 40 11 46 12 40 13 46 14 53 15 33 16 42 17 35 18 40 19 41 20 33 21 51 22 53 23 46 24 55 25 47 26 38 27 46 28 46 29 53 30 47 31 41 32 44 33 43 34 51 35 33 36 43 37 53 38 51 39 50 40 46 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Separate Learning Software 10.975844 0.434970 0.137589 -0.002754 Happiness Depression Belonging Belonging_Final 0.116676 -0.033594 0.199185 -0.207011 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -5.8861 -2.6551 0.1711 1.5669 6.4729 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 10.975844 11.937658 0.919 0.36475 Separate 0.434970 0.153055 2.842 0.00774 ** Learning 0.137589 0.277041 0.497 0.62284 Software -0.002754 0.259035 -0.011 0.99158 Happiness 0.116676 0.345407 0.338 0.73772 Depression -0.033594 0.254622 -0.132 0.89586 Belonging 0.199185 0.236953 0.841 0.40680 Belonging_Final -0.207011 0.386635 -0.535 0.59606 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.364 on 32 degrees of freedom Multiple R-squared: 0.3439, Adjusted R-squared: 0.2004 F-statistic: 2.396 on 7 and 32 DF, p-value: 0.04329 > 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,] 0.4214705 0.84294102 0.57852949 [2,] 0.5968403 0.80631937 0.40315968 [3,] 0.4590259 0.91805181 0.54097409 [4,] 0.5009056 0.99818887 0.49909444 [5,] 0.4698762 0.93975242 0.53012379 [6,] 0.4260556 0.85211118 0.57394441 [7,] 0.3819453 0.76389065 0.61805468 [8,] 0.2900068 0.58001352 0.70999324 [9,] 0.3817070 0.76341395 0.61829303 [10,] 0.3545284 0.70905683 0.64547159 [11,] 0.5769830 0.84603393 0.42301696 [12,] 0.7859040 0.42819209 0.21409605 [13,] 0.6901043 0.61979146 0.30989573 [14,] 0.9597617 0.08047669 0.04023834 [15,] 0.9382993 0.12340136 0.06170068 [16,] 0.9597718 0.08045634 0.04022817 [17,] 0.9540771 0.09184587 0.04592293 [18,] 0.9027687 0.19446266 0.09723133 [19,] 0.7937201 0.41255972 0.20627986 > postscript(file="/var/wessaorg/rcomp/tmp/1een21352115767.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2eq5o1352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3zivq1352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4ehv51352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5hfpo1352115767.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 = 40 Frequency = 1 1 2 3 4 5 6 0.37528207 0.44253495 -0.09352902 -3.64328212 3.81307827 6.47288522 7 8 9 10 11 12 -2.68348726 1.50315032 -2.09863029 -3.48442515 3.52197295 -4.55850505 13 14 15 16 17 18 1.03793726 -0.37881126 1.25556503 0.74935426 -1.94224481 1.75816391 19 20 21 22 23 24 -2.64566296 -1.28301596 -5.37431349 -5.88611868 0.68699930 6.34712550 25 26 27 28 29 30 -0.03303003 2.67826052 -1.07520045 2.91148187 1.28092309 5.95048159 31 32 33 34 35 36 -2.90046094 -1.35435701 2.07690484 1.29529686 3.86993358 -2.84727421 37 38 39 40 -2.68348726 -0.45439391 -3.00520206 0.39810055 > postscript(file="/var/wessaorg/rcomp/tmp/6374r1352115767.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 = 40 Frequency = 1 lag(myerror, k = 1) myerror 0 0.37528207 NA 1 0.44253495 0.37528207 2 -0.09352902 0.44253495 3 -3.64328212 -0.09352902 4 3.81307827 -3.64328212 5 6.47288522 3.81307827 6 -2.68348726 6.47288522 7 1.50315032 -2.68348726 8 -2.09863029 1.50315032 9 -3.48442515 -2.09863029 10 3.52197295 -3.48442515 11 -4.55850505 3.52197295 12 1.03793726 -4.55850505 13 -0.37881126 1.03793726 14 1.25556503 -0.37881126 15 0.74935426 1.25556503 16 -1.94224481 0.74935426 17 1.75816391 -1.94224481 18 -2.64566296 1.75816391 19 -1.28301596 -2.64566296 20 -5.37431349 -1.28301596 21 -5.88611868 -5.37431349 22 0.68699930 -5.88611868 23 6.34712550 0.68699930 24 -0.03303003 6.34712550 25 2.67826052 -0.03303003 26 -1.07520045 2.67826052 27 2.91148187 -1.07520045 28 1.28092309 2.91148187 29 5.95048159 1.28092309 30 -2.90046094 5.95048159 31 -1.35435701 -2.90046094 32 2.07690484 -1.35435701 33 1.29529686 2.07690484 34 3.86993358 1.29529686 35 -2.84727421 3.86993358 36 -2.68348726 -2.84727421 37 -0.45439391 -2.68348726 38 -3.00520206 -0.45439391 39 0.39810055 -3.00520206 40 NA 0.39810055 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.44253495 0.37528207 [2,] -0.09352902 0.44253495 [3,] -3.64328212 -0.09352902 [4,] 3.81307827 -3.64328212 [5,] 6.47288522 3.81307827 [6,] -2.68348726 6.47288522 [7,] 1.50315032 -2.68348726 [8,] -2.09863029 1.50315032 [9,] -3.48442515 -2.09863029 [10,] 3.52197295 -3.48442515 [11,] -4.55850505 3.52197295 [12,] 1.03793726 -4.55850505 [13,] -0.37881126 1.03793726 [14,] 1.25556503 -0.37881126 [15,] 0.74935426 1.25556503 [16,] -1.94224481 0.74935426 [17,] 1.75816391 -1.94224481 [18,] -2.64566296 1.75816391 [19,] -1.28301596 -2.64566296 [20,] -5.37431349 -1.28301596 [21,] -5.88611868 -5.37431349 [22,] 0.68699930 -5.88611868 [23,] 6.34712550 0.68699930 [24,] -0.03303003 6.34712550 [25,] 2.67826052 -0.03303003 [26,] -1.07520045 2.67826052 [27,] 2.91148187 -1.07520045 [28,] 1.28092309 2.91148187 [29,] 5.95048159 1.28092309 [30,] -2.90046094 5.95048159 [31,] -1.35435701 -2.90046094 [32,] 2.07690484 -1.35435701 [33,] 1.29529686 2.07690484 [34,] 3.86993358 1.29529686 [35,] -2.84727421 3.86993358 [36,] -2.68348726 -2.84727421 [37,] -0.45439391 -2.68348726 [38,] -3.00520206 -0.45439391 [39,] 0.39810055 -3.00520206 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.44253495 0.37528207 2 -0.09352902 0.44253495 3 -3.64328212 -0.09352902 4 3.81307827 -3.64328212 5 6.47288522 3.81307827 6 -2.68348726 6.47288522 7 1.50315032 -2.68348726 8 -2.09863029 1.50315032 9 -3.48442515 -2.09863029 10 3.52197295 -3.48442515 11 -4.55850505 3.52197295 12 1.03793726 -4.55850505 13 -0.37881126 1.03793726 14 1.25556503 -0.37881126 15 0.74935426 1.25556503 16 -1.94224481 0.74935426 17 1.75816391 -1.94224481 18 -2.64566296 1.75816391 19 -1.28301596 -2.64566296 20 -5.37431349 -1.28301596 21 -5.88611868 -5.37431349 22 0.68699930 -5.88611868 23 6.34712550 0.68699930 24 -0.03303003 6.34712550 25 2.67826052 -0.03303003 26 -1.07520045 2.67826052 27 2.91148187 -1.07520045 28 1.28092309 2.91148187 29 5.95048159 1.28092309 30 -2.90046094 5.95048159 31 -1.35435701 -2.90046094 32 2.07690484 -1.35435701 33 1.29529686 2.07690484 34 3.86993358 1.29529686 35 -2.84727421 3.86993358 36 -2.68348726 -2.84727421 37 -0.45439391 -2.68348726 38 -3.00520206 -0.45439391 39 0.39810055 -3.00520206 > 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/7hcjq1352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/80em31352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9oqhg1352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/1049z81352115767.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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='') + } + } > 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/wessaorg/rcomp/tmp/11m3p01352115767.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/wessaorg/rcomp/tmp/12fbty1352115767.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/wessaorg/rcomp/tmp/138y9c1352115767.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/wessaorg/rcomp/tmp/14kqow1352115767.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/wessaorg/rcomp/tmp/15bvo71352115767.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/wessaorg/rcomp/tmp/1656j81352115767.tab") + } > > try(system("convert tmp/1een21352115767.ps tmp/1een21352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/2eq5o1352115767.ps tmp/2eq5o1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/3zivq1352115767.ps tmp/3zivq1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/4ehv51352115767.ps tmp/4ehv51352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/5hfpo1352115767.ps tmp/5hfpo1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/6374r1352115767.ps tmp/6374r1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/7hcjq1352115767.ps tmp/7hcjq1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/80em31352115767.ps tmp/80em31352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/9oqhg1352115767.ps tmp/9oqhg1352115767.png",intern=TRUE)) character(0) > try(system("convert tmp/1049z81352115767.ps tmp/1049z81352115767.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.080 1.147 7.243