x <- c(19.4,19.4,19.4,19.5,19.5,19.5,28.7,28.7,28.7,21.8,21.8,21.8,20,20,20,22.6,22.6,22.6,22.4,22.4,22.4,18.6,18.6,18.6,16.2,16.2,16.2,13.8,13.8,13.8,24.1,24.1,24.1,19.9,19.9,19.9,22.3,22.3,22.3,20.9,20.9,20.9,23.5,23.5,23.5,23.1,23.1,23.1,25.7,25.7,25.7,19.7,19.7,19.7,23.1,23.1,23.1,20.7,20.7,20.7,18,18,18,16.9,16.9,16.9,24.4,24.4,24.4,15.5,15.5,15.5,18.4,18.4,18.4,16.2,16.2,16.2,20.6,20.6,20.6,19.8,19.8,19.8) par3 = 'additive' par2 = 'Single' par1 = '12' par3 <- 'additive' par2 <- 'Single' par1 <- '12' #'GNU S' R Code compiled by R2WASP v. 1.2.327 () #Author: root #To cite this work: Wessa P., (2013), Exponential Smoothing (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_exponentialsmoothing.wasp/ #Source of accompanying publication: # par1 <- as.numeric(par1) if (par2 == 'Single') K <- 1 if (par2 == 'Double') K <- 2 if (par2 == 'Triple') K <- par1 nx <- length(x) nxmK <- nx - K x <- ts(x, frequency = par1) if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F) if (par2 == 'Double') fit <- HoltWinters(x, gamma=F) if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) fit myresid <- x - fit$fitted[,'xhat'] postscript(file="/var/wessaorg/rcomp/tmp/19n3g1386833744.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) op <- par(mfrow=c(2,1)) plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing') plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors') par(op) dev.off() postscript(file="/var/wessaorg/rcomp/tmp/28ftk1386833744.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) p <- predict(fit, par1, prediction.interval=TRUE) np <- length(p[,1]) plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing') dev.off() postscript(file="/var/wessaorg/rcomp/tmp/3dor41386833744.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) op <- par(mfrow = c(2,2)) acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF') spectrum(myresid,main='Residals Periodogram') cpgram(myresid,main='Residal Cumulative Periodogram') qqnorm(myresid,main='Residual Normal QQ Plot') qqline(myresid) par(op) 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,'Estimated Parameters of Exponential Smoothing',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,fit$alpha) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,fit$beta) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'gamma',header=TRUE) a<-table.element(a,fit$gamma) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/4ffxa1386833744.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observed',header=TRUE) a<-table.element(a,'Fitted',header=TRUE) a<-table.element(a,'Residuals',header=TRUE) a<-table.row.end(a) for (i in 1:nxmK) { a<-table.row.start(a) a<-table.element(a,i+K,header=TRUE) a<-table.element(a,x[i+K]) a<-table.element(a,fit$fitted[i,'xhat']) a<-table.element(a,myresid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/5qetq1386833744.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,'Extrapolation Forecasts of Exponential Smoothing',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Forecast',header=TRUE) a<-table.element(a,'95% Lower Bound',header=TRUE) a<-table.element(a,'95% Upper Bound',header=TRUE) a<-table.row.end(a) for (i in 1:np) { a<-table.row.start(a) a<-table.element(a,nx+i,header=TRUE) a<-table.element(a,p[i,'fit']) a<-table.element(a,p[i,'lwr']) a<-table.element(a,p[i,'upr']) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/wessaorg/rcomp/tmp/6bkxd1386833745.tab") try(system("convert tmp/19n3g1386833744.ps tmp/19n3g1386833744.png",intern=TRUE)) try(system("convert tmp/28ftk1386833744.ps tmp/28ftk1386833744.png",intern=TRUE)) try(system("convert tmp/3dor41386833744.ps tmp/3dor41386833744.png",intern=TRUE))