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aantal bezoekers aan Hawai

*Unverified author*
R Software Module: /rwasp_exponentialsmoothing.wasp (opens new window with default values)
Title produced by software: Exponential Smoothing
Date of computation: Sun, 24 Jan 2010 07:22:10 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g.htm/, Retrieved Sun, 24 Jan 2010 15:24:04 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W62
 
Dataseries X:
» Textbox « » Textfile « » CSV «
6715 7703 9856 8326 9269 7035 10342 11682 10304 11385 9777 8882 7897 6930 9545 9110 7459 7320 10017 12307 11072 10749 9589 9080 7384 8062 8511 8684 8306 7643 10577 13747 11783 11611 9946 8693 7303 7609 9423 8584 7586 6843 11811 13414 12103 11501 8213 7982 7687 7180 7862 8043 8340 6692 10065 12684 11587 9843 8110 7940 6475 6121 9669 7778 7826 7403 10741 14023 11519 10236 8075 8157
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.105565855420786
beta0
gamma0.649886178771197


Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
1378978049.3170405983-152.317040598293
1469307046.48421109652-116.48421109652
1595459583.89243822658-38.8924382265832
1691109132.03337389994-22.0333738999434
1774597505.78738445388-46.7873844538753
1873207354.17821670858-34.1782167085821
191001710291.0668132091-274.066813209136
201230711577.8396981477729.160301852255
211107210314.7274450025757.272554997526
221074911448.7078859083-699.70788590829
2395899802.33927357186-213.339273571859
2490808941.10624651321138.893753486787
2573847876.64309174713-492.643091747132
2680626858.712372583511203.28762741649
2785119580.54601867563-1069.54601867563
2886849029.68497094595-345.684970945955
2983067354.8834029306951.116597069407
3076437315.94828454679327.051715453214
311057710151.5278912971425.472108702919
321374712095.30444800681651.69555199322
331178310945.9215191251837.078480874921
341161111241.4125843075369.587415692478
3599469990.64158105826-44.6415810582585
3686939351.96342098732-658.963420987318
3773037836.17380841848-533.173808418475
3876097799.77569658483-190.775696584833
3994239053.29023083748369.709769162524
4085849075.13168247993-491.131682479934
4175868138.78122705509-552.78122705509
4268437578.32917164003-735.329171640026
431181110358.96747567461452.03252432537
441341413123.8934001608290.106599839155
451210311357.2522413304745.747758669617
461150111371.3585127622129.641487237841
4782139854.47422021005-1641.47422021005
4879828690.13181891705-708.131818917054
4976877242.27073720966444.729262790337
5071807508.13510703508-328.135107035082
5178629072.94838683614-1210.94838683614
5280438427.53605476578-384.536054765782
5383407466.60278675041873.397213249588
5466926950.59493824193-258.594938241931
551006511053.0305555986-988.030555598592
561268412884.9643811143-200.964381114252
571158711331.3381638754255.6618361246
58984310935.5776029209-1092.57760292092
5981108260.15388030792-150.153880307920
6079407795.77761992109144.222380078911
6164757108.0315756788-633.031575678803
6261216810.87029959265-689.870299592649
6396697824.334648203071844.66535179693
6477787981.86807563744-203.868075637438
6578267771.2191159778554.7808840221469
6674036510.78849694748892.211503052522
671074110310.7033617456430.296638254384
681402312749.87024233441273.12975766564
691151911617.2858987291-98.285898729071
701023610400.4553976088-164.455397608761
7180758370.82211703647-295.822117036469
7281578062.1834116001694.8165883998354


Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
736917.419321421425530.465254901418304.37338794142
746654.045329618325259.384463079838048.70619615681
759213.61229434517811.2869816336110615.9376070566
767985.63973963726575.691643894349395.58783538005
777946.859855501066529.329967736299364.38974326583
787167.428241062035742.356898032538592.49958409154
7910604.65398331449172.0808847461412037.2270818826
8013488.318594194612048.282819375514928.3543690137
8111424.15819327599976.6982170498612871.6181695020
8210179.24029512298724.3940033126511634.0865869331
838090.606991588166628.411695873049552.8022873033
848040.267619402686570.760071674889509.77516713047
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/140mo1264342928.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/140mo1264342928.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/2i7oo1264342928.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/2i7oo1264342928.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/3f91s1264342928.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Jan/24/t1264343040sd44hnhdv00vx5g/3f91s1264342928.ps (open in new window)


 
Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = additive ;
 
Parameters (R input):
par1 = 12 ; par2 = Triple ; par3 = additive ;
 
R code (references can be found in the software module):
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$fitted[,'xhat']
bitmap(file='test1.png')
op <- par(mfrow=c(2,1))
plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing')
plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors')
par(op)
dev.off()
bitmap(file='test2.png')
p <- predict(fit, par1, prediction.interval=TRUE)
np <- length(p[,1])
plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing')
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF')
spectrum(myresid,main='Residals Periodogram')
cpgram(myresid,main='Residal Cumulative Periodogram')
qqnorm(myresid,main='Residual Normal QQ Plot')
qqline(myresid)
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,fit$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='mytable.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='mytable1.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='mytable2.tab')
 





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Software written by Ed van Stee & Patrick Wessa


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