x <- array(list(1 ,1911 , 61 ,17 ,  2 ,2599 , 74 ,19 ,  3 ,2145 , 57 ,18 ,  4 ,1331 , 50 ,15 ,  5 ,7375 ,  3 ,12 ,  6 ,1445 , 48 ,15 ,  7 ,1595 , 62 ,14 ,  8 ,1134 , 41 ,15 ,  9 ,1235 , 31 ,20 , 10 ,1552 , 12 ,12 , 11 ,2110 , 46 ,13 , 12 ,1430 , 27 ,13 , 13 ,1726 , 47 ,15 , 14 ,1348 , 31 ,17 , 15 ,1569 , 16 ,13 , 16 ,1534 , 60 ,15 , 17 ,1515 , 37 ,13 , 18 , 843 , 49 ,10 , 19 ,1075 , 33 ,12 , 20 ,1600 , 28 ,12 , 21 ,1233 , 56 ,16 , 22 , 945 , 41 ,15 , 23 ,1149 , 71 ,12 , 24 ,1360 , 30 ,12 , 25 ,1758 , 28 ,12 , 26 ,1313 , 40 ,15 , 27 ,1318 , 28 ,12 , 28 ,1276 , 56 ,12 , 29 ,1553 , 37 ,13 , 30 ,1180 , 36 ,12 , 31 , 868 , 32 ,15 , 32 ,1098 , 19 , 9 , 33 ,1487 , 25 , 8 , 34 ,1071 , 58 ,13 , 35 , 968 , 29 ,15 , 36 ,1066 , 26 , 9 , 37 ,1254 , 54 ,12 , 38 ,1508 , 41 ,12 , 39 ,1367 , 39 ,12 , 40 ,1428 , 29 ,12 , 41 ,1290 , 19 ,14 , 42 ,1216 , 32 ,12 , 43 , 863 , 26 ,12 , 44 , 903 , 42 ,16 , 45 , 826 , 10 ,12 , 46 ,1470 , 57 ,12 , 47 ,1065 , 48 ,15 , 48 ,1218 , 43 ,12 , 49 , 923 , 37 ,12 , 50 , 874 , 49 ,15 , 51 ,1491 , 28 ,13 , 52 , 853 , 55 ,12 , 53 ,1016 , 13 , 9 , 54 , 713 , 17 ,15 , 55 ,1218 , 36 ,13 , 56 , 983 , 22 ,13 , 57 ,1672 , 37 ,13 , 58 ,1231 , 29 ,14 , 59 ,1107 ,  3 ,13 , 60 ,1132 , 15 ,13 , 61 , 804 , 38 ,15 , 62 , 775 , 19 ,12 , 63 ,1206 , 35 ,14 , 64 ,1233 , 38 ,15 , 65 , 988 , 23 ,12 , 66 , 614 , 27 ,14 , 67 ,1172 , 43 ,12 , 68 ,1216 , 32 ,16 , 69 , 619 , 37 ,12 , 70 , 934 ,  7 , 9 , 71 , 874 , 62 ,12 , 72 , 713 , 17 ,10 , 73 , 932 , 39 ,12 ,74 , 706 , 18 ,13 , 75 , 760 , 30 ,13 , 76 , 828 , 18 ,16 , 77 , 792 ,  0 ,12 , 78 , 844 , 34 ,12 , 79 , 918 , 37 ,10 , 80 , 796 , 33 ,12 , 81 ,1061 , 35 ,15 , 82 , 847 , 17 ,14 , 83 , 575 , 25 ,12 , 84 , 707 , 21 ,13 , 85 , 548 , 26 ,15 , 86 , 835 , 40 ,12 , 87 , 563 , 29 , 8 , 88 , 487 , 40 ,12 , 89 , 504 , 13 ,13 , 90 , 641 ,  9 ,16 , 91 , 862 , 54 ,12 , 92 , 715 , 29 ,12 , 93 , 872 , 25 ,12 , 94 , 564 ,  9 , 8 , 95 , 997 , 32 ,13 , 96 , 476 ,  4 , 8 , 97 , 646 , 17 ,16 , 98 , 637 , 28 ,12 , 99 , 598 ,  4 ,13 ,100 , 960 , 18 ,11 ,101 , 959 , 17 ,12 ,102 , 563 , 15 , 8 ,103 , 500 , 16 ,15 ,104 , 694 , 25 ,13 ,105 , 620 ,  1 , 4 ,106 , 831 , 10 ,12 ,107 , 791 , 10 ,12 ,108 , 428 , 10 ,11 ,109 , 573 ,  7 ,12 ,110 , 623 , 25 ,12 ,111 , 590 , 27 ,14 ,112 , 584 , 16 ,16 ,113 , 533 , 11 ,13 ,114 , 508 , 16 , 9 ,115 , 488 ,  0 , 5 ,116 , 723 , 15 ,10 ,117 , 476 , 36 ,13 ,118 , 387 ,  5 ,13 ,119 , 511 , 14 ,12 ,120 , 585 , 43 ,13 ,121 , 581 , 10 ,12 ,122 , 413 ,  8 ,12 ,123 , 496 , 12 ,12 ,124 , 350 , 39 , 5 ,125 , 427 ,  0 ,12 ,126 , 267 ,  0 , 9 ,127 , 350 , 10 , 9 ,128 , 335 ,  7 , 6 ,129 , 229 ,  0 ,11 ,130 , 470 ,  8 ,15 ,131 , 310 ,  3 ,12 ,132 , 242 ,  1 , 8 ,133 , 244 ,  8 , 0 ,134 , 431 ,  8 , 3 ,135 , 352 ,  0 ,12 ,136 , 285 ,  5 , 9 ,137 , 291 ,  0 ,14 ,138 , 242 ,  0 , 4 ,139 , 211 ,  3 , 1 ,140 , 136 ,  0 , 0 ,141 , 231 ,  0 , 0 ,142 , 268 ,  0 , 6 ,143 , 126 ,  0 , 6 ,144 ,  44 ,  0 , 0 ,145 , 340 ,  0 , 0 ,146 , 143 ,  2 , 2 ,147 , 104 ,  0 , 0 ,148 ,  25 ,  0 , 0 ,149 ,  11 ,  0 , 0) ,dim=c(4 ,149) ,dimnames=list(c('(aantallogins ,aantalpeerreviews ,aantalcompendiums ,aantalhoures)') ,1:149)) y <- array(NA,dim=c(4,149),dimnames=list(c('(aantallogins,aantalpeerreviews,aantalcompendiums,aantalhoures)'),1:149)) 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 = '' par3 <- 'No Linear Trend' par2 <- 'Do not include Seasonal Dummies' par1 <- '' #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ #Source of accompanying publication: Office for Research, Development, and Education #Technical description: Write here your technical program description (don't use hard returns!) library(lattice) library(lmtest) n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test par1 <- as.numeric(par1) x <- t(y) k <- length(x[1,]) n <- length(x[,1]) x1 <- cbind(x[,par1], x[,1:k!=par1]) mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) colnames(x1) <- mycolnames #colnames(x)[par1] x <- x1 if (par3 == 'First Differences'){ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) for (i in 1:n-1) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 } if (par2 == 'Include Monthly Dummies'){ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) for (i in 1:11){ x2[seq(i,n,12),i] <- 1 } x <- cbind(x, x2) } if (par2 == 'Include Quarterly Dummies'){ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) for (i in 1:3){ x2[seq(i,n,4),i] <- 1 } x <- cbind(x, x2) } k <- length(x[1,]) if (par3 == 'Linear Trend'){ x <- cbind(x, c(1:n)) colnames(x)[k+1] <- 't' } x k <- length(x[1,]) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) if (n > n25) { kp3 <- k + 3 nmkm3 <- n - k - 3 gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) numgqtests <- 0 numsignificant1 <- 0 numsignificant5 <- 0 numsignificant10 <- 0 for (mypoint in kp3:nmkm3) { j <- 0 numgqtests <- numgqtests + 1 for (myalt in c('greater', 'two.sided', 'less')) { j <- j + 1 gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$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 } postscript(file="/var/fisher/rcomp/tmp/13erm1352151839.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$resid) grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/27qcy1352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/3tojl1352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/4pb811352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() postscript(file="/var/fisher/rcomp/tmp/5dbqu1352151839.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() (myerror <- as.ts(mysum$resid)) postscript(file="/var/fisher/rcomp/tmp/65wvw1352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) z plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') lines(lowess(z)) abline(lm(z)) grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/7y6591352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/8dswz1352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/9ugtq1352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { postscript(file="/var/fisher/rcomp/tmp/10z7b11352151839.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab load(file="/var/fisher/rcomp/createtable") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) a<-table.row.end(a) myeq <- colnames(x)[1] myeq <- paste(myeq, '[t] = ', sep='') for (i in 1:k){ if (mysum$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/fisher/rcomp/tmp/119bxm1352151839.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/fisher/rcomp/tmp/12z8q31352151839.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/fisher/rcomp/tmp/13m3uz1352151839.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/fisher/rcomp/tmp/14lt9e1352151839.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/fisher/rcomp/tmp/15drtd1352151839.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/fisher/rcomp/tmp/16xz1l1352151839.tab") } try(system("convert tmp/13erm1352151839.ps tmp/13erm1352151839.png",intern=TRUE)) try(system("convert tmp/27qcy1352151839.ps tmp/27qcy1352151839.png",intern=TRUE)) try(system("convert tmp/3tojl1352151839.ps tmp/3tojl1352151839.png",intern=TRUE)) try(system("convert tmp/4pb811352151839.ps tmp/4pb811352151839.png",intern=TRUE)) try(system("convert tmp/5dbqu1352151839.ps tmp/5dbqu1352151839.png",intern=TRUE)) try(system("convert tmp/65wvw1352151839.ps tmp/65wvw1352151839.png",intern=TRUE)) try(system("convert tmp/7y6591352151839.ps tmp/7y6591352151839.png",intern=TRUE)) try(system("convert tmp/8dswz1352151839.ps tmp/8dswz1352151839.png",intern=TRUE)) try(system("convert tmp/9ugtq1352151839.ps tmp/9ugtq1352151839.png",intern=TRUE)) try(system("convert tmp/10z7b11352151839.ps tmp/10z7b11352151839.png",intern=TRUE))