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*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: Sun, 19 Dec 2010 17:18:58 +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/19/t1292778991v2a5c5vetudhjhp.htm/, Retrieved Sun, 19 Dec 2010 18:16:33 +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/19/t1292778991v2a5c5vetudhjhp.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 «

41,85 41,75 41,75 41,75 41,58 41,61 41,42 41,37 41,37 41,33 41,37 41,34 41,33 41,29 41,29 41,27 41,04 40,90 40,89 40,72 40,72 40,58 40,24 40,07 40,12 40,10 40,10 40,08 40,06 39,99 40,05 39,66 39,66 39,67 39,56 39,64 39,73 39,70 39,70 39,68 39,76 40,00 39,96 40,01 40,01 40,01 40,00 39,91 39,86 39,79 39,79 39,80 39,64 39,55 39,36 39,28

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	41.85	41.85	0	0	0
2	41.75	41.7562066210638	-0.0065553124913993	-0.00511075876723255	-0.61157554965322
3	41.75	41.7549293310928	-0.00611880030325368	-0.00509238564705291	0.05512048631084
4	41.75	41.7549006548992	-0.00542960596175323	-0.00508223033860989	0.0623942577348153
5	41.58	41.5899273756818	-0.0272834162103662	-0.00530433967981116	-1.61054141317511
6	41.61	41.6137934117889	-0.0193904508997543	-0.00524428569938085	0.51065660381463
7	41.42	41.4299975197799	-0.0467618215237257	-0.00540492067399878	-1.62835288439185
8	41.37	41.3756214929032	-0.0480930062245208	-0.00541105014653086	-0.0749965969536968
9	41.37	41.3741024961183	-0.0396888198675224	-0.00538037049466777	0.456988108410448
10	41.33	41.3353541870175	-0.0395155883299458	-0.00537986584236436	0.00920458601168563
11	41.37	41.3732397749297	-0.0250679142824497	-0.00534613862050466	0.756197181506416
12	41.34	41.3454217860621	-0.0255857061126666	-0.00534710983358388	-0.0268366330650689
13	41.33	41.2866304499283	-0.0315349549944941	0.0442367032332191	-0.379472745287853
14	41.29	41.2924523769974	-0.0245981513681806	-0.00316262073635268	0.30718206069518
15	41.29	41.2924932016727	-0.0199060513396933	-0.00316016636394246	0.240024650589459
16	41.27	41.2731453597386	-0.0197995537619999	-0.0031604526808434	0.00543303450087765
17	41.04	41.0486067124392	-0.0588955580630466	-0.00307166391677844	-1.99266394346721
18	40.9	40.9053233476935	-0.07501943528306	-0.00304205230068141	-0.821335942029
19	40.89	40.8914075502777	-0.0633397589181768	-0.00305936976826737	0.594729161605545
20	40.72	40.7258005645861	-0.0828929751436773	-0.00303596358724405	-0.995406373780797
21	40.72	40.7209408838964	-0.0679704515706822	-0.00305038575273346	0.759548032383008
22	40.58	40.584880935154	-0.0809930601853865	-0.0030402238764905	-0.662774533557788
23	40.24	40.2498765743218	-0.12957887687454	-0.00300961263811978	-2.47256603372478
24	40.07	40.074250005569	-0.138387163676504	-0.00300513175741117	-0.448240041566728
25	40.12	40.0580117723527	-0.115378181635299	0.0587519071097328	1.29182115715795
26	40.1	40.0995831856281	-0.0859718846523846	-0.00301741916449247	1.38099087616352
27	40.1	40.1006658976651	-0.069316744924702	-0.00301951449875203	0.847468612686639
28	40.08	40.0816799407282	-0.0596852524074713	-0.00303995420800641	0.48973876224505
29	40.06	40.0619731689419	-0.0520358959661575	-0.00305356694032228	0.389041153149987
30	39.99	39.9934934700151	-0.0551819318808214	-0.0030490392240099	-0.160032460579175
31	40.05	40.0500535702964	-0.0338043730721001	-0.00307388392220129	1.08755401532798
32	39.66	39.672309155526	-0.0996027090958257	-0.00301213673390254	-3.34764306168403
33	39.66	39.6606476456903	-0.082779016086571	-0.00302488478620099	0.85598491682344
34	39.67	39.6705307872641	-0.06505216507212	-0.003035730814851	0.901965164401479
35	39.56	39.5641491185908	-0.0729587950225451	-0.00303182470087589	-0.40230767202018
36	39.64	39.6390459238431	-0.0446727744001233	-0.00304310805438549	1.43927720668671
37	39.73	39.6820643601204	-0.0280567372809125	0.0455963015402111	0.90311589298975
38	39.7	39.7024882658352	-0.0189263548958714	-0.00361426754759397	0.438957996625694
39	39.7	39.7030868391148	-0.0151907805904221	-0.00361471412272284	0.190072979452948
40	39.68	39.6837261335673	-0.0159887224179164	-0.00361344086647369	-0.0405798182735179
41	39.76	39.761113618057	0.00187739870114834	-0.00363733500949657	0.908756363295003
42	40	39.9973511872504	0.0467155761240067	-0.00368582901278298	2.28098674910422
43	39.96	39.9657886926001	0.031739844058584	-0.00367274976794332	-0.761904628319648
44	40.01	40.0132498863858	0.034747512134722	-0.00367487080253303	0.153026648064286
45	40.01	40.0145747520173	0.0283534337762807	-0.00367122986019488	-0.32533527697936
46	40.01	40.0144389015728	0.0229031579474176	-0.00366872392676351	-0.27732060894897
47	40	40.0045528351555	0.0166302431348601	-0.00366639511793735	-0.319183088499056
48	39.91	39.9164907405033	-0.00339856641637932	-0.00366039124057445	-1.01913112631678
49	39.86	39.8304526815677	-0.0190965970453849	0.0317594691201597	-0.83955993266865
50	39.79	39.7934720734949	-0.022475658488028	-0.0030426351700077	-0.164529041217416
51	39.79	39.7924626686976	-0.0183686811146941	-0.00304303188038616	0.20897249038329
52	39.8	39.8022878726012	-0.0129738145812875	-0.00304988158238495	0.274390633366302
53	39.64	39.6468710139236	-0.0402276741106775	-0.00302088063079823	-1.38636948088415
54	39.55	39.5544238270231	-0.0502183701235838	-0.00301228352088342	-0.508267825735278
55	39.36	39.3667107916579	-0.0765232218571488	-0.00299400490547728	-1.33832870702638
56	39.28	39.2831826190994	-0.0778633576636562	-0.00299325297617586	-0.06818602114093

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/1arn21292779133.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/1arn21292779133.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/2qlbt1292779133.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/2qlbt1292779133.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/3w9l81292779133.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/3w9l81292779133.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/4w9l81292779133.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/4w9l81292779133.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/56j3b1292779133.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292778991v2a5c5vetudhjhp/56j3b1292779133.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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