x <- array(list(9190 ,2514 ,2550 ,1512 ,1591 ,472 ,551 ,9251 ,2537 ,2572 ,1517 ,1595 ,476 ,554 ,9328 ,2564 ,2597 ,1525 ,1602 ,483 ,558 ,9428 ,2595 ,2623 ,1540 ,1613 ,493 ,565 ,9499 ,2617 ,2647 ,1547 ,1622 ,498 ,568 ,9556 ,2638 ,2670 ,1547 ,1627 ,502 ,572 ,9606 ,2657 ,2690 ,1547 ,1632 ,504 ,575 ,9632 ,2668 ,2705 ,1547 ,1634 ,503 ,574 ,9660 ,2683 ,2721 ,1546 ,1637 ,501 ,572 ,9651 ,2687 ,2729 ,1533 ,1627 ,502 ,573 ,9695 ,2705 ,2747 ,1538 ,1632 ,502 ,572 ,9727 ,2717 ,2761 ,1543 ,1637 ,500 ,569 ,9757 ,2728 ,2773 ,1549 ,1643 ,498 ,566 ,9788 ,2741 ,2786 ,1556 ,1650 ,495 ,560 ,9813 ,2752 ,2796 ,1559 ,1654 ,494 ,557 ,9823 ,2759 ,2807 ,1559 ,1656 ,490 ,552 ,9837 ,2767 ,2817 ,1563 ,1661 ,484 ,545 ,9842 ,2774 ,2827 ,1563 ,1662 ,477 ,539 ,9855 ,2781 ,2838 ,1564 ,1664 ,474 ,535 ,9863 ,2788 ,2847 ,1564 ,1665 ,469 ,531 ,9855 ,2789 ,2853 ,1557 ,1661 ,466 ,528 ,9858 ,2795 ,2860 ,1554 ,1659 ,464 ,526 ,9853 ,2798 ,2864 ,1552 ,1656 ,460 ,523 ,9858 ,2801 ,2869 ,1552 ,1656 ,458 ,521 ,9859 ,2803 ,2873 ,1551 ,1655 ,457 ,519 ,9865 ,2808 ,2877 ,1552 ,1654 ,456 ,517 ,9876 ,2813 ,2883 ,1554 ,1656 ,455 ,515 ,9928 ,2826 ,2896 ,1567 ,1668 ,456 ,514 ,9948 ,2835 ,2905 ,1572 ,1672 ,453 ,511 ,9987 ,2849 ,2919 ,1579 ,1680 ,453 ,508 ,10022 ,2862 ,2933 ,1588 ,1688 ,449 ,502 ,10068 ,2877 ,2948 ,1597 ,1696 ,449 ,501 ,10101 ,2888 ,2959 ,1603 ,1702 ,449 ,500 ,10131 ,2897 ,2969 ,1607 ,1706 ,452 ,500 ,10143 ,2902 ,2978 ,1607 ,1708 ,450 ,498 ,10170 ,2911 ,2988 ,1609 ,1711 ,452 ,499 ,10192 ,2917 ,2996 ,1612 ,1714 ,454 ,499 ,10214 ,2924 ,3003 ,1615 ,1717 ,455 ,500 ,10239 ,2930 ,3011 ,1619 ,1721 ,458 ,501 ,10263 ,2935 ,3018 ,1622 ,1724 ,461 ,503 ,10310 ,2945 ,3028 ,1628 ,1730 ,469 ,510 ,10355 ,2957 ,3038 ,1634 ,1735 ,477 ,515 ,10396 ,2967 ,3049 ,1640 ,1740 ,480 ,520 ,10446 ,2980 ,3063 ,1648 ,1748 ,484 ,523 ,10511 ,2997 ,3081 ,1657 ,1757 ,490 ,529 ,10585 ,3017 ,3100 ,1668 ,1768 ,497 ,534 ,10667 ,3040 ,3122 ,1678 ,1778 ,506 ,543 ,10753 ,3064 ,3145 ,1687 ,1789 ,516 ,553 ,10840 ,3085 ,3167 ,1700 ,1798 ,527 ,563 ,10951 ,3113 ,3193 ,1714 ,1811 ,542 ,577) ,dim=c(7 ,50) ,dimnames=list(c('totaal' ,'vlaams_man' ,'vlaams_vrouw' ,'waals_man' ,'waals_vrouw' ,'brussel_man' ,'brussel_vrouw') ,1:50)) y <- array(NA,dim=c(7,50),dimnames=list(c('totaal','vlaams_man','vlaams_vrouw','waals_man','waals_vrouw','brussel_man','brussel_vrouw'),1:50)) 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' 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)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } postscript(file="/var/wessaorg/rcomp/tmp/1rpsm1351870971.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() postscript(file="/var/wessaorg/rcomp/tmp/25alx1351870971.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() postscript(file="/var/wessaorg/rcomp/tmp/3jo0i1351870971.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() postscript(file="/var/wessaorg/rcomp/tmp/4osjo1351870971.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() postscript(file="/var/wessaorg/rcomp/tmp/5kxhb1351870971.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') qqline(mysum$resid) grid() dev.off() (myerror <- as.ts(mysum$resid)) postscript(file="/var/wessaorg/rcomp/tmp/6cpi31351870971.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/wessaorg/rcomp/tmp/7rpro1351870971.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/wessaorg/rcomp/tmp/8gszg1351870971.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/wessaorg/rcomp/tmp/9z2c81351870971.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/wessaorg/rcomp/tmp/10zvtx1351870971.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/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/1109we1351870972.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/122rfi1351870972.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a, sqrt(mysum$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$sigma) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a, sum(myerror*myerror)) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/13orpw1351870972.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]-mysum$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/14k4yj1351870972.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/15e0s11351870972.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/16jblh1351870972.tab") } try(system("convert tmp/1rpsm1351870971.ps tmp/1rpsm1351870971.png",intern=TRUE)) try(system("convert tmp/25alx1351870971.ps tmp/25alx1351870971.png",intern=TRUE)) try(system("convert tmp/3jo0i1351870971.ps tmp/3jo0i1351870971.png",intern=TRUE)) try(system("convert tmp/4osjo1351870971.ps tmp/4osjo1351870971.png",intern=TRUE)) try(system("convert tmp/5kxhb1351870971.ps tmp/5kxhb1351870971.png",intern=TRUE)) try(system("convert tmp/6cpi31351870971.ps tmp/6cpi31351870971.png",intern=TRUE)) try(system("convert tmp/7rpro1351870971.ps tmp/7rpro1351870971.png",intern=TRUE)) try(system("convert tmp/8gszg1351870971.ps tmp/8gszg1351870971.png",intern=TRUE)) try(system("convert tmp/9z2c81351870971.ps tmp/9z2c81351870971.png",intern=TRUE)) try(system("convert tmp/10zvtx1351870971.ps tmp/10zvtx1351870971.png",intern=TRUE))