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Type 'q()' to quit R. > x <- c(3722.7,3707.1,3697.4,3691.4,3679.4,3660.6,3647.5,3639,3623.5,3612.2,3604.2,3596.9,3603.9,3606.9,3607.7,3611.4,3611.9,3618.4,3629.5,3640.6,3646.8,3647.3,3649.5,3649.7,3652.5,3665.8,3674.3,3705.8,3735.8,3735.4,3747.7,3765.5,3779.7,3795.5,3813.1,3826.9,3833.3,3844.8,3851.3,3851.8,3854.1,3858.4,3861.6,3856.3,3855.8,3860.4,3855.1,3839.5,3833,3833.6,3826.8,3818.2,3811.4,3806.8,3810.3,3818.2,3858.7,3868.7,3872.6,3872.4,3876.4,3883.2,3883.4,3881.8,3887.1,3893.3,3902.8,3914.7,3929.8,3947.3,3971.8,3991.3,3993,3997.2,4016.2,4041.7,4060.5,4076.7,4102.7,4125.8,4140.1,4146.7,4157.9,4154.7,4145.3,4149,4142.4,4141,4146.1,4147.6,4142.7,4148.1,4159,4167,4178.5,4192.5,4209.2,4223.7,4231.6,4236.9,4253,4270.5,4285.7,4302.8,4321.5,4340.3,4356.5) > par3 = 'multiplicative' > par2 = 'Single' > par1 = '12' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > if (par2 == 'Single') K <- 1 > if (par2 == 'Double') K <- 2 > if (par2 == 'Triple') K <- par1 > nx <- length(x) > nxmK <- nx - K > x <- ts(x, frequency = par1) > if (par2 == 'Single') fit <- HoltWinters(x, gamma=0, beta=0) > if (par2 == 'Double') fit <- HoltWinters(x, gamma=0) > if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) > fit Holt-Winters exponential smoothing without trend and without seasonal component. Call: HoltWinters(x = x, beta = 0, gamma = 0) Smoothing parameters: alpha: 1 beta : 0 gamma: 0 Coefficients: [,1] a 4356.5 > myresid <- x - fit$fitted[,'xhat'] > postscript(file="/var/www/html/rcomp/tmp/1hl6z1211793798.ps",horizontal=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() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2c24g1211793798.ps",horizontal=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() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3ydgr1211793798.ps",horizontal=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() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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$gamma) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4eefq1211793798.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Residuals',header=TRUE) > a<-table.row.end(a) > for (i in 1:nxmK) { + a<-table.row.start(a) + a<-table.element(a,i+K,header=TRUE) + a<-table.element(a,x[i+K]) + a<-table.element(a,fit$fitted[i,'xhat']) + a<-table.element(a,myresid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/5psj11211793798.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/www/html/rcomp/tmp/66q1j1211793798.tab") > > system("convert tmp/1hl6z1211793798.ps tmp/1hl6z1211793798.png") > system("convert tmp/2c24g1211793798.ps tmp/2c24g1211793798.png") > system("convert tmp/3ydgr1211793798.ps tmp/3ydgr1211793798.png") > > > proc.time() user system elapsed 1.173 0.520 7.803