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Exponential Smoothing

*The author of this computation has been verified*
R Software Module: /rwasp_exponentialsmoothing.wasp (opens new window with default values)
Title produced by software: Exponential Smoothing
Date of computation: Tue, 14 Dec 2010 14:19:11 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c.htm/, Retrieved Tue, 14 Dec 2010 15:17:58 +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/Dec/14/t1292336278r7iwkh5a7dkf82c.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1.3866 1.3582 1.3332 1.3595 1.3617 1.3684 1.3394 1.3262 1.3173 1.3085 1.327 1.3182 1.293 1.291 1.2984 1.2795 1.299 1.3174 1.326 1.3111 1.2816 1.276 1.2849 1.2818 1.2829 1.2796 1.3008 1.2967 1.2938 1.2833 1.2823 1.2765 1.2634 1.2596 1.2705 1.2591 1.2798 1.2763 1.2795 1.2782 1.2644 1.2596 1.2615 1.2555 1.2555 1.2658 1.2565 1.2783 1.2786 1.2782 1.2905 1.3042 1.2942 1.313 1.3671 1.3549 1.3558 1.3507 1.3494 1.3607 1.3295 1.3193 1.3308 1.3246 1.3392 1.3425 1.3496 1.3255 1.3231 1.3273 1.3276 1.3173 1.3196 1.3058 1.2966 1.2932 1.2947 1.305 1.3232 1.3125 1.2992 1.3266 1.3275 1.3223 1.3403 1.3322 1.3363 1.3425 1.3574 1.3683 1.3623 1.3563 1.3518 1.3494 1.3612 1.369 1.3771 1.3972 1.401 1.3908 1.3901 1.3856 1.4098 1.422 1.4238 1.4207 1.4095 1.4177 1.3866 1.3959 1.4102 1.3969 1.4004 1.385 1.389 1.384 1.392 1.3932 1.3858 1.3978 1.4029 1.394 1.4096 1.4058 1.4134 1.4096 1.4049 1.4009 1.3897 1.4019 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.994202437987405
betaFALSE
gammaFALSE


Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
21.35821.3866-0.0284
31.33321.35836465076116-0.0251646507611578
41.35951.333345893623310.0261541063766868
51.36171.359348369946400.00235163005360284
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81.32621.33956790364155-0.0133679036415528
91.31731.32627750125034-0.00897750125034036
101.30851.31735204762022-0.00885204762021696
111.3271.308551320295020.0184486797049832
121.31821.32689304263536-0.00869304263535975
131.2931.31825039845376-0.0252503984537567
141.2911.29314639075088-0.0021463907508783
151.29841.291012443833480.00738755616651865
161.27951.29835717018500-0.0188571701850031
171.2991.279609325613530.0193906743864702
181.31741.298887581362780.0185124186372216
191.3261.317292673104950.0087073268950526
201.31111.32594951873236-0.0148495187323621
211.28161.31118609100571-0.029586091005708
221.2761.28177152719732-0.005771527197316
231.28491.276033460786830.00886653921316616
241.28181.28484859568907-0.00304859568907445
251.28291.281817674422560.00108232557744103
261.27961.28289372515035-0.00329372515034687
271.30081.279619095575810.0211809044241884
281.29671.30067720239312-0.00397720239311794
291.29381.29672305807751-0.00292305807751059
301.28331.29381694661047-0.0105169466104706
311.28231.28336097265016-0.00106097265015737
321.27651.28230615105473-0.00580615105473292
331.26341.27653366152079-0.0131336615207942
341.25961.26347614321712-0.00387614321711927
351.27051.259622472180670.0108775278193289
361.25911.27043693685792-0.0113369368579235
371.27981.259165726594470.0206342734055334
381.27631.27968037152035-0.00338037152034665
391.27951.276319597913510.00318040208648518
401.27821.27948156142168-0.00128156142167879
411.26441.27820742993182-0.0138074299318152
421.25961.26448004943126-0.00488004943126419
431.26151.259628292389200.00187170761079769
441.25551.26148914865906-0.00598914865905686
451.25551.25553472246075-3.47224607535335e-05
461.26581.255500201305620.0102997986943805
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491.27861.278173923730090.000426076269910647
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551.36711.312891339267860.0542086607321424
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641.32461.33073367694352-0.00613367694351674
651.33921.324635560372450.0145644396275546
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1111.41021.395847126412710.0143528735872889
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1151.3891.385089167389460.00391083261054104
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1301.40191.389765068061560.0121349319384438
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1341.39751.390151301443270.00734869855673304
1351.39911.397457395464410.00164260453559462
1361.40891.399090476898340.00980952310165728
1371.4131.408843128681500.00415687131849585
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1821.47121.467065047206800.00413495279319509
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1851.4781.465827271263900.0121727287360951
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1881.4671.47680868388745-0.00980868388744938
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1901.45491.46501192481081-0.0101119248108135
1911.46431.454958624511160.0093413754888425
1921.45391.46424584279632-0.0103458427963206
1931.45371.45395998066518-0.000259980665184179
1941.46161.453701507254030.00789849274597154
1951.47221.46155420799850.0106457920015008
1961.46941.47213828036070-0.00273828036069812
1971.47631.46941587535020.00688412464980082
1981.4751.47626008886044-0.00126008886044016
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2001.48641.476491346010740.00990865398925833
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2861.35721.37181282020543-0.0146128202054270
2871.36071.357284718731320.00341528126868029
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3141.33381.35187243270595-0.0180724327059480
3151.33561.333904776049330.00169522395066868
3161.33531.33559017183402-0.000290171834020692
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3191.34791.34819322611997-0.000293226119972401
3201.34681.34790169999661-0.00110169999661425
3211.33961.34680638717405-0.00720638717404976
3221.3341.33964177947653-0.00564177947652822
3231.32961.33403270856638-0.00443270856637668
3241.33841.329625698902800.00877430109720279
3251.35851.338349130445270.0201508695547281
3261.35831.35838317408415-8.31740841487072e-05
3271.36151.358300482206910.00319951779308925
3281.35441.36148145059718-0.00708145059718412
3291.35351.35444105514898-0.000941055148976355
3301.34321.35350545582558-0.0103054558255835
3311.34861.343259746519220.00534025348078315
3321.33731.34856903954928-0.0112690395492823
3331.33391.33736533295561-0.00346533295560914
3341.33111.33392009048270-0.00282009048270448
3351.33211.331116349649450.000983650350545595
3361.3291.33209429722609-0.00309429722609411
3371.32451.32901793938005-0.00451793938005363
3381.32561.324526193033730.00107380696627479
3391.33151.325593774537520.00590622546247666
3401.32381.33146575829162-0.00766575829162064
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3441.27461.272814769477280.00178523052271995
3451.29691.274589650015340.0223103499846622
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3511.24281.234983226378880.00781677362112299
3521.2271.24275468177019-0.015754681770193
3531.23341.227091338744550.0063086612554486
3541.24971.233363425145160.0163365748548450
3551.2361.24960528769421-0.0136052876942057
3561.22231.23607887749911-0.0137788774991063
3571.23091.222379883896760.00852011610323511
3581.22551.23085060409854-0.00535060409853716
3591.23841.225531020459070.0128689795409338
3601.23071.23832539129307-0.0076253912930726
3611.21551.23074420867889-0.0152442086788918
3621.22181.215588379245150.00621162075485127
3631.22681.221763987743470.00503601225652495
3641.2061.22677080340665-0.0207708034066465
3651.19591.20612042002080-0.0102204200208014
3661.19421.19595925351887-0.0017592535188653
3671.2011.194210199381370.00678980061862866
3681.20451.200960635709860.00353936429013957
3691.21271.204479480316040.00822051968395732
3701.22491.212652341027360.0122476589726437
3711.22581.224828993437600.000971006562402899
3721.22771.225794370529240.00190562947076023
3731.23631.227688951994970.00861104800502965
3741.23721.236250076915200.000949923084802684
3751.23911.237194492762010.00190550723799143
3761.22581.23908895270362-0.0132889527036224
3771.22711.225877043527380.00122295647261850
3781.22621.22709290983401-0.000892909834011357
3791.22941.226205176700130.00319482329986576
3801.23391.22938147781380.0045185221862003
3811.21981.23387380358742-0.0140738035874202
3821.22711.219881593749050.00721840625094905
3831.23281.227058150842130.00574184915787179
3841.25481.232766711273440.0220332887265597
3851.25311.25467226064227-0.00157226064226612
3861.25791.253109115278570.00479088472142641
3871.25671.25787222454873-0.00117222454873245
3881.2661.256706796044510.00929320395548605
3891.26371.26594612207377-0.00224612207377239
3901.25721.26371302203201-0.00651302203201043
3911.25691.25723775964912-0.000337759649120084
3921.27031.256901958182510.0133980418174890
3931.28281.270222324021720.0125776759782841
3941.31.282727080143540.0172729198564585
3951.29571.29989985917599-0.00419985917599353
3961.28441.29572434894402-0.0113243489440171
3971.28171.28446565361526-0.00276565361525516
3981.2851.281716034048340.00328396595166014
3991.28971.284980961003750.00471903899625215
4001.29311.289672641078780.00342735892122037
4011.30331.293080129674110.0102198703258851
4021.29921.30324074966802-0.00404074966802503
4031.30691.299223426496780.00767657350322226
4041.30281.30685549458907-0.00405549458907073
4051.30731.302823511981370.0044764880186281
4061.32211.307274047283110.0148259527168868
4071.32061.32201404561973-0.00141404561972802
4081.31841.32060819801717-0.00220819801716909
4091.31761.31841280216494-0.000812802164940507
4101.32531.317604712270960.0076952877290446
4111.31331.32525538609219-0.0119553860921862
4121.30161.31336931209225-0.0117693120922537
4131.2791.3016682333167-0.0226682333167005
4141.27991.279131420488370.000768579511630563
4151.2821.279895544112620.00210445588738017
4161.2861.281987799286490.00401220071350994
4171.2881.285976739017560.00202326098244354
4181.28361.28798827001899-0.00438827001898656
4191.27111.28362544126756-0.0125254412675633
4201.27041.27117261702248-0.000772617022483768
4211.26111.2704044792951-0.00930447929509981
4221.26131.261153943295710.000146056704291686
4231.26931.26129915322720.00800084677280055
4241.27131.269253614594680.00204638540531854
4251.271.27128813595371-0.00128813595371113
4261.2681.27000746804807-0.00200746804807239
4271.281.268011638420500.0119883615795031
4281.28181.279930496730310.00186950326968649
4291.28341.281789161438860.00161083856113886
4301.28741.283390661063550.00400933893645039
4311.27441.28737675560889-0.0129767556088864
4321.26971.27447523354536-0.0047752335453648
4331.27151.269727684712600.00177231528739608
4341.27251.271489724892220.00101027510778451
4351.28011.272494142867410.00760585713258721
4361.2851.280055904571610.00494409542838503
4371.29891.284971336300160.0139286636998424
4381.30781.298819247708450.0089807522915526
4391.3061.30774793353167-0.00174793353166991
4401.30741.306010133753040.00138986624695603
4411.3121.307391942164240.00460805783575613
4421.33641.311973284498940.0244267155010605
4431.33231.33625838460212-0.0039583846021185
4441.34121.33232294898020.00887705101979952
4451.34771.341148534746220.00655146525377615
4461.3461.34766201747392-0.0016620174739177
4471.36111.346009635649370.0150903643506288
4481.36481.361012512676880.0037874873231154
4491.37261.364778041807370.00782195819262776
4501.37051.37255465171232-0.00205465171231833
4511.3781.370511911970720.00748808802928336
4521.38561.377956587345290.00764341265470558
4531.3971.385555686841150.0114443131588535
4541.38741.39693365088477-0.0095336508847701
4551.39361.387455271932210.0061447280677891
4561.38331.39356437555798-0.0102643755579765
4571.39581.383359508353820.012440491646182
4581.41011.395727875478210.0143721245217858
4591.40891.41001667671683-0.00111667671683202
4601.38961.40890647400251-0.0193064740025140
4611.38591.38971193048027-0.00381193048027417
4621.38611.385922099903350.000177900096653083
4631.40161.386098968613160.0155010313868422
4641.39341.40151013180928-0.00811013180927556
4651.40311.393447018992090.00965298100790535
4661.39121.403044036244-0.0118440362440002
4671.38031.39126866653460-0.0109686665346038
4681.38571.380363591524430.00533640847557004
4691.38571.385669061840943.09381590617441e-05
4701.39261.385699820634100.00690017936589582
4711.40181.392559995782230.0092400042177716
4721.40141.40174643050255-0.000346430502550898
4731.42441.401402008452320.0229979915476786
4741.40841.42426666771784-0.0158666677178372
4751.39171.40849198799003-0.0167919879900276
4761.39451.391797352591690.00270264740831316
4771.3771.39448433123405-0.0174843312340522
4781.371.37710136649458-0.00710136649457804
4791.37111.370041170612630.00105882938737345
4801.36261.37109386137097-0.00849386137096597
4811.36121.36264924368802-0.00144924368802468
4821.34811.36120840208015-0.0131084020801526
4831.36471.348175996773950.0165240032260543
4841.36741.36460420106660.00279579893339932
4851.36471.36738379118231-0.00268379118230877
4861.34961.36471555944581-0.0151155594458083
4871.33391.34968763339324-0.0157876333932419
4881.33211.33399152978363-0.00189152978362950
4891.32251.33211096626122-0.00961096626121938
4901.31461.3225557201729-0.00795572017290036
4911.29981.31464612378106-0.0148461237810571


Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
4921.299886071323271.279708864933651.32006327771289
4931.299886071323271.271433788524721.32833835412182
4941.299886071323271.265073068936111.33469907371042
4951.299886071323271.259706998736071.34006514391047
4961.299886071323271.254977602047121.34479454059942
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/1h2cp1292336343.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/1h2cp1292336343.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/2stcs1292336343.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/2stcs1292336343.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/3stcs1292336343.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/14/t1292336278r7iwkh5a7dkf82c/3stcs1292336343.ps (open in new window)


 
Parameters (Session):
par1 = 5 ; par2 = Single ; par3 = additive ;
 
Parameters (R input):
par1 = 5 ; par2 = Single ; par3 = additive ;
 
R code (references can be found in the software module):
par1 <- 5
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')
 





Copyright

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Software written by Ed van Stee & Patrick Wessa


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