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Structurele tijdreeksanalyse

*The author of this computation has been verified*

R Software Module: /rwasp_structuraltimeseries.wasp (opens new window with default values)

Title produced by software: Structural Time Series Models

Date of computation: Fri, 11 Dec 2009 09:03:21 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c.htm/, Retrieved Fri, 11 Dec 2009 17:04:35 +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/2009/Dec/11/t126054746818e0rf5ajsih91c.htm/},
    year = {2009},
}
@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 = {2009},
    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 «

8.3 8.2 8 7.9 7.6 7.6 8.3 8.4 8.4 8.4 8.4 8.6 8.9 8.8 8.3 7.5 7.2 7.4 8.8 9.3 9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8 8.2 8.1 8.1 8 7.9 7.9 8 8 7.9 8 7.7 7.2 7.5 7.3 7 7 7 7.2 7.3 7.1 6.8 6.4 6.1 6.5 7.7 7.9 7.5 6.9 6.6 6.9

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	8.3	8.3	0	0	0
2	8.2	8.20150794324155	-0.0986166801562142	-0.00150794324155027	-0.309040537073739
3	8	8.00283057750846	-0.194512078765493	-0.00283057750846062	-0.304377034984027
4	7.9	7.89619813771343	-0.110992221924477	0.00380186228657122	0.259490908910541
5	7.6	7.60710290313238	-0.280349045317253	-0.00710290313238139	-0.526922252594266
6	7.6	7.5894352782938	-0.0305154718711783	0.0105647217062059	0.777236677085165
7	8.3	8.27756350033823	0.652962934568876	0.0224364996617669	2.12631693214153
8	8.4	8.42411465087286	0.171335733221709	-0.0241146508728594	-1.49835286505826
9	8.4	8.4022979407693	-0.0123638970675732	-0.00229794076929965	-0.571493612201239
10	8.4	8.398118670039	-0.00457981959493595	0.00188132996100493	0.0242164371391531
11	8.4	8.39997964959871	0.00154577143125055	2.03504012858244e-05	0.0190568491318921
12	8.6	8.5935302527941	0.184154019187659	0.00646974720590753	0.568098296613493
13	8.9	8.89723721118891	0.297819721661505	0.00276278881108751	0.353780641744862
14	8.8	8.81254857887911	-0.0661567648095394	-0.0125485788791144	-1.13787364407034
15	8.3	8.33210551744682	-0.449554428603814	-0.03210551744682	-1.20575176823243
16	7.5	7.49654751038298	-0.806802769014652	0.00345248961702379	-1.10993647895224
17	7.2	7.16825468178275	-0.364379268571575	0.0317453182172476	1.37659020782180
18	7.4	7.41110637072932	0.197272316466894	-0.0111063707293208	1.74730949268202
19	8.8	8.70778685475634	1.21417115830365	0.0922131452436654	3.16359846568683
20	9.3	9.35828957297884	0.692818917212127	-0.0582895729788386	-1.62193836112218
21	9.3	9.3372457913932	0.0325503854806996	-0.0372457913932058	-2.05411002973329
22	8.7	8.71867517045162	-0.569688907524338	-0.0186751704516244	-1.87357979531947
23	8.2	8.1937878995701	-0.528250175480331	0.00621210042989475	0.128916898298164
24	8.3	8.27565012816473	0.0360448863597018	0.0243498718352705	1.75553885567322
25	8.5	8.48681074620486	0.197960409513843	0.0131892537951403	0.504014491173652
26	8.6	8.60659322134047	0.125609684135195	-0.00659322134047034	-0.225515294382770
27	8.5	8.50279066740803	-0.0836346857588167	-0.00279066740803013	-0.654241362504792
28	8.2	8.21530980336555	-0.269995115243943	-0.0153098033655529	-0.579478181871975
29	8.1	8.06084726067879	-0.164543540171458	0.0391527393212141	0.328054018511747
30	7.9	8.00679015783698	-0.0636579506010582	-0.106790157836976	0.313866338946917
31	8.6	8.46458888621165	0.412516487516675	0.135411113788350	1.48138602867508
32	8.7	8.74466765072423	0.291582226359057	-0.0446676507242307	-0.376229419108265
33	8.7	8.70697815706679	-0.00908476219982657	-0.00697815706678867	-0.935381666329714
34	8.5	8.50706404644173	-0.183337772839505	-0.00706404644173238	-0.542105007729224
35	8.4	8.42349551328738	-0.0922336519816608	-0.0234955132873816	0.283427940059473
36	8.5	8.48254528853028	0.0458976874389169	0.017454711469724	0.429732441604963
37	8.7	8.68209057628563	0.18615973347711	0.0179094237143697	0.436660402369008
38	8.7	8.70667633812932	0.038598811591521	-0.00667633812932111	-0.459289685022563
39	8.6	8.59138376215762	-0.100862298851671	0.0086162378423773	-0.434927081496445
40	8.5	8.51385208004961	-0.0796716143642026	-0.0138520800496118	0.0659285991504954
41	8.3	8.25890553924152	-0.238637913414801	0.0410944607584801	-0.494452744334046
42	8	8.14993461344097	-0.121006421414725	-0.149934613440969	0.365974353648347
43	8.2	8.06582710542257	-0.0875285544851058	0.134172894577431	0.104149836040597
44	8.1	8.11617540989993	0.0375638170478271	-0.0161754098999275	0.389165448216263
45	8.1	8.09088508707781	-0.0194612456731615	0.00911491292219052	-0.177406231052720
46	8	8.01186461406146	-0.0734975032603589	-0.0118646140614547	-0.168108093818893
47	7.9	7.93121085797819	-0.0799901770160099	-0.0312108579781895	-0.0201989406438855
48	7.9	7.89963440230783	-0.0360718985378237	0.000365597692166885	0.136634123441552
49	8	7.9667647257953	0.0575441566034415	0.0332352742046941	0.291437152539457
50	8	7.99601296231887	0.0318777967430105	0.00398703768113005	-0.0798466092202058
51	7.9	7.90736032468487	-0.0769665872681344	-0.00736032468486671	-0.339061405531233
52	8	7.98313596091908	0.0612094154316495	0.0168640390809208	0.430003205562517
53	7.7	7.68911191307443	-0.259801448256619	0.0108880869255737	-0.998402009993685
54	7.2	7.352599876354	-0.329126626078210	-0.152599876353997	-0.215684513089949
55	7.5	7.36012550557213	-0.0248394618827552	0.139874494427866	0.946641438144736
56	7.3	7.3141494166909	-0.0439441485933053	-0.0141494166908954	-0.059435064635252
57	7	7.00270763400846	-0.285723114504312	-0.00270763400845993	-0.752179878351502
58	7	6.9915471819148	-0.0375567928908624	0.00845281808519224	0.772052556840845
59	7	7.02693270980818	0.0283719342405384	-0.0269327098081753	0.205106003491748
60	7.2	7.20239137752213	0.161294440603718	-0.00239137752212999	0.4135480595682
61	7.3	7.2728868319794	0.0792318669164984	0.0271131680205903	-0.2554448349319
62	7.1	7.09985318516729	-0.148686133361820	0.000146814832710113	-0.70892621824615
63	6.8	6.84291559765728	-0.24621877452675	-0.0429155976572829	-0.303662639828411
64	6.4	6.36032599414731	-0.459465531724917	0.0396740058526884	-0.663676077715483
65	6.1	6.05897452667951	-0.316922618916431	0.0410254733204924	0.44332999844042
66	6.5	6.63522708060232	0.488227690252844	-0.135227080602317	2.50494243221914
67	7.7	7.54067407657017	0.864392092635254	0.159325923429828	1.17026054465987
68	7.9	7.91056574167231	0.418541277665396	-0.0105657416723083	-1.38704799283956
69	7.5	7.5732063271842	-0.262988181540286	-0.073206327184208	-2.12025519382940
70	6.9	6.91661774716365	-0.617863481089187	-0.0166177471636463	-1.10402931056326
71	6.6	6.62313661158964	-0.325406663450460	-0.0231366115896357	0.909837401592211
72	6.9	6.86707424260515	0.187822973769178	0.0329257573948542	1.59680928356641

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/100s21260547397.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/100s21260547397.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/2crip1260547397.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/2crip1260547397.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/3vwg01260547397.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/3vwg01260547397.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/4km8j1260547397.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/4km8j1260547397.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/50esj1260547397.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t126054746818e0rf5ajsih91c/50esj1260547397.ps (open in new window)

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)

nx <- length(x)

x <- ts(x,frequency=par1)

m <- StructTS(x,type='BSM')

m$coef

m$fitted

m$resid

mylevel <- as.numeric(m$fitted[,'level'])

myslope <- as.numeric(m$fitted[,'slope'])

myseas <- as.numeric(m$fitted[,'sea'])

myresid <- as.numeric(m$resid)

myfit <- mylevel+myseas

mylagmax <- nx/2

bitmap(file='test2.png')

op <- par(mfrow = c(2,2))

acf(as.numeric(x),lag.max = mylagmax,main='Observed')

acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')

acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')

acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')

par(op)

dev.off()

bitmap(file='test3.png')

op <- par(mfrow = c(2,2))

spectrum(as.numeric(x),main='Observed')

spectrum(mylevel,main='Level')

spectrum(myseas,main='Seasonal')

spectrum(myresid,main='Standardized Residals')

par(op)

dev.off()

bitmap(file='test4.png')

op <- par(mfrow = c(2,2))

cpgram(as.numeric(x),main='Observed')

cpgram(mylevel,main='Level')

cpgram(myseas,main='Seasonal')

cpgram(myresid,main='Standardized Residals')

par(op)

dev.off()

bitmap(file='test1.png')

plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')

grid()

dev.off()

bitmap(file='test5.png')

op <- par(mfrow = c(2,2))

hist(m$resid,main='Residual Histogram')

plot(density(m$resid),main='Residual Kernel Density')

qqnorm(m$resid,main='Residual Normal QQ Plot')

qqline(m$resid)

plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit')

par(op)

dev.off()

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Structural Time Series Model',6,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,'Level',header=TRUE)

a<-table.element(a,'Slope',header=TRUE)

a<-table.element(a,'Seasonal',header=TRUE)

a<-table.element(a,'Stand. Residuals',header=TRUE)

a<-table.row.end(a)

for (i in 1:nx) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,x[i])

a<-table.element(a,mylevel[i])

a<-table.element(a,myslope[i])

a<-table.element(a,myseas[i])

a<-table.element(a,myresid[i])

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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