R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(2443.6,2460.2,2448.2,2470.4,2484.7,2466.8,2487.9,2508.4,2510.5,2497.4,2532.5,2556.8,2561,2547.3,2541.5,2558.5,2587.9,2580.5,2579.6,2589.3,2595,2595.6,2588.8,2591.7,2601.7,2585.4,2573.3,2597.4,2600.6,2570.6,2569.4,2584.9,2608.8,2617.2,2621,2540.5,2554.5,2601.9,2623,2640.7,2640.7,2619.8,2624.2,2638.2,2645.7,2679.6,2669,2664.6,2663.3,2667.4,2653.2,2630.8,2626.6,2641.9,2625.8,2606,2594.4,2583.6,2588.7,2600.3,2579.5,2576.6,2597.8,2595.6,2599,2621.7,2645.6,2644.2,2625.6,2624.6,2596.2,2599.5,2584.1,2570.8,2555,2574.5,2576.7,2579,2588.7,2601.1,2575.7,2559.5,2561.1,2528.3,2514.7,2558.5,2553.3,2577.1,2566,2549.5,2527.8,2540.9,2534.2,2538,2559,2554.9,2575.5,2546.5,2561.6,2546.6,2502.9,2463.1,2472.6,2463.5,2446.3,2456.2,2471.5,2447.5,2428.6,2420.2,2414.9,2420.2,2423.8,2407,2388.7,2409.6,2392,2380.2,2423.3,2451.6,2440.8,2432.9,2413.6,2391.6,2358.1,2345.4,2384.4,2384.4,2384.4,2418.7,2420,2493.1,2493.1,2492.8)
> par3 = 'additive'
> par2 = 'Double'
> par1 = '12'
> par3 <- 'additive'
> par2 <- 'Double'
> 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
Holt-Winters exponential smoothing with trend and without seasonal component.

Call:
HoltWinters(x = x, gamma = F)

Smoothing parameters:
 alpha: 1
 beta : 0.06010695
 gamma: FALSE

Coefficients:
         [,1]
a 2492.800000
b    3.227046
> myresid <- x - fit$fitted[,'xhat']
> postscript(file="/var/fisher/rcomp/tmp/1g2bu1376838007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing')
> plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/2lmc41376838007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> p <- predict(fit, par1, prediction.interval=TRUE)
> np <- length(p[,1])
> plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3ku4p1376838007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF')
> spectrum(myresid,main='Residals Periodogram')
> cpgram(myresid,main='Residal Cumulative Periodogram')
> qqnorm(myresid,main='Residual Normal QQ Plot')
> qqline(myresid)
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'Value',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,fit$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/fisher/rcomp/tmp/4opse1376838007.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/fisher/rcomp/tmp/503l01376838007.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/fisher/rcomp/tmp/6dw3v1376838007.tab") 
> 
> try(system("convert tmp/1g2bu1376838007.ps tmp/1g2bu1376838007.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lmc41376838007.ps tmp/2lmc41376838007.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ku4p1376838007.ps tmp/3ku4p1376838007.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.746   0.813   5.527