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Type 'q()' to quit R. > x <- array(list(1235,1019,162,30,12,4,8,1298,1093,162,12,13,8,10,1334,1119,146,29,20,3,17,1180,1015,114,17,22,3,9,1163,988,114,32,1,5,23,1066,900,140,9,6,4,7,1090,937,101,18,16,2,16,1082,907,140,9,5,2,19,993,839,115,10,8,1,20,987,830,128,9,1,5,14,1028,909,75,16,8,3,17,804,696,74,11,6,3,14,750,649,55,10,10,1,25,730,637,72,8,4,1,8,709,614,73,5,2,3,12,677,583,56,10,11,2,15,644,576,50,4,3,0,11),dim=c(7,17),dimnames=list(c('Ongevallen','Droog','Regen','Mist','Sneeuw','Wind','Andere'),1:17)) > y <- array(NA,dim=c(7,17),dimnames=list(c('Ongevallen','Droog','Regen','Mist','Sneeuw','Wind','Andere'),1:17)) > 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' > #'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 > 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 Ongevallen Droog Regen Mist Sneeuw Wind Andere 1 1235 1019 162 30 12 4 8 2 1298 1093 162 12 13 8 10 3 1334 1119 146 29 20 3 17 4 1180 1015 114 17 22 3 9 5 1163 988 114 32 1 5 23 6 1066 900 140 9 6 4 7 7 1090 937 101 18 16 2 16 8 1082 907 140 9 5 2 19 9 993 839 115 10 8 1 20 10 987 830 128 9 1 5 14 11 1028 909 75 16 8 3 17 12 804 696 74 11 6 3 14 13 750 649 55 10 10 1 25 14 730 637 72 8 4 1 8 15 709 614 73 5 2 3 12 16 677 583 56 10 11 2 15 17 644 576 50 4 3 0 11 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Droog Regen Mist Sneeuw Wind -1.533e-13 1.000e+00 1.000e+00 1.000e+00 1.000e+00 1.000e+00 Andere 1.000e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.842e-13 -4.808e-14 1.243e-14 4.971e-14 1.387e-13 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.533e-13 1.820e-13 -8.420e-01 0.419 Droog 1.000e+00 4.530e-16 2.207e+15 <2e-16 *** Regen 1.000e+00 1.590e-15 6.291e+14 <2e-16 *** Mist 1.000e+00 4.437e-15 2.254e+14 <2e-16 *** Sneeuw 1.000e+00 5.747e-15 1.740e+14 <2e-16 *** Wind 1.000e+00 1.919e-14 5.210e+13 <2e-16 *** Andere 1.000e+00 5.509e-15 1.815e+14 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 9.963e-14 on 10 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 1.379e+31 on 6 and 10 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 + } > postscript(file="/var/wessaorg/rcomp/tmp/1e2521322150241.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2egja1322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/32riu1322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/419rr1322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5ln3o1322150241.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 = 17 Frequency = 1 1 2 3 4 5 -1.842254e-13 -6.187463e-14 1.387100e-13 4.104783e-14 7.328696e-14 6 7 8 9 10 8.140988e-14 -1.325966e-14 -9.887293e-15 -2.207665e-14 3.848126e-14 11 12 13 14 15 -9.875584e-14 1.243444e-14 -8.177616e-14 6.836746e-14 1.649030e-14 16 17 4.970837e-14 -4.808096e-14 > postscript(file="/var/wessaorg/rcomp/tmp/6fw651322150241.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 = 17 Frequency = 1 lag(myerror, k = 1) myerror 0 -1.842254e-13 NA 1 -6.187463e-14 -1.842254e-13 2 1.387100e-13 -6.187463e-14 3 4.104783e-14 1.387100e-13 4 7.328696e-14 4.104783e-14 5 8.140988e-14 7.328696e-14 6 -1.325966e-14 8.140988e-14 7 -9.887293e-15 -1.325966e-14 8 -2.207665e-14 -9.887293e-15 9 3.848126e-14 -2.207665e-14 10 -9.875584e-14 3.848126e-14 11 1.243444e-14 -9.875584e-14 12 -8.177616e-14 1.243444e-14 13 6.836746e-14 -8.177616e-14 14 1.649030e-14 6.836746e-14 15 4.970837e-14 1.649030e-14 16 -4.808096e-14 4.970837e-14 17 NA -4.808096e-14 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -6.187463e-14 -1.842254e-13 [2,] 1.387100e-13 -6.187463e-14 [3,] 4.104783e-14 1.387100e-13 [4,] 7.328696e-14 4.104783e-14 [5,] 8.140988e-14 7.328696e-14 [6,] -1.325966e-14 8.140988e-14 [7,] -9.887293e-15 -1.325966e-14 [8,] -2.207665e-14 -9.887293e-15 [9,] 3.848126e-14 -2.207665e-14 [10,] -9.875584e-14 3.848126e-14 [11,] 1.243444e-14 -9.875584e-14 [12,] -8.177616e-14 1.243444e-14 [13,] 6.836746e-14 -8.177616e-14 [14,] 1.649030e-14 6.836746e-14 [15,] 4.970837e-14 1.649030e-14 [16,] -4.808096e-14 4.970837e-14 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -6.187463e-14 -1.842254e-13 2 1.387100e-13 -6.187463e-14 3 4.104783e-14 1.387100e-13 4 7.328696e-14 4.104783e-14 5 8.140988e-14 7.328696e-14 6 -1.325966e-14 8.140988e-14 7 -9.887293e-15 -1.325966e-14 8 -2.207665e-14 -9.887293e-15 9 3.848126e-14 -2.207665e-14 10 -9.875584e-14 3.848126e-14 11 1.243444e-14 -9.875584e-14 12 -8.177616e-14 1.243444e-14 13 6.836746e-14 -8.177616e-14 14 1.649030e-14 6.836746e-14 15 4.970837e-14 1.649030e-14 16 -4.808096e-14 4.970837e-14 > 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/7mfs21322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/84qxi1322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9s2k71322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10j4il1322150241.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11v0fw1322150241.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/12a6ov1322150241.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/13urk91322150241.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/14oqea1322150241.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/1556da1322150241.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/16xasq1322150241.tab") + } > > try(system("convert tmp/1e2521322150241.ps tmp/1e2521322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/2egja1322150241.ps tmp/2egja1322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/32riu1322150241.ps tmp/32riu1322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/419rr1322150241.ps tmp/419rr1322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/5ln3o1322150241.ps tmp/5ln3o1322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/6fw651322150241.ps tmp/6fw651322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/7mfs21322150241.ps tmp/7mfs21322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/84qxi1322150241.ps tmp/84qxi1322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/9s2k71322150241.ps tmp/9s2k71322150241.png",intern=TRUE)) character(0) > try(system("convert tmp/10j4il1322150241.ps tmp/10j4il1322150241.png",intern=TRUE)) convert: unable to open image `tmp/10j4il1322150241.ps': No such file or directory @ blob.c/OpenBlob/2480. convert: missing an image filename `tmp/10j4il1322150241.png' @ convert.c/ConvertImageCommand/2838. character(0) Warning message: running command 'convert tmp/10j4il1322150241.ps tmp/10j4il1322150241.png' had status 1 > > > proc.time() user system elapsed 2.607 0.631 3.818