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ws9(2)

*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: Wed, 02 Dec 2009 14:48:13 -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/02/t12597905434m8sc32a2xgf2js.htm/, Retrieved Wed, 02 Dec 2009 22:49:22 +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/02/t12597905434m8sc32a2xgf2js.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 «

216234 213587 209465 204045 200237 203666 241476 260307 243324 244460 233575 237217 235243 230354 227184 221678 217142 219452 256446 265845 248624 241114 229245 231805 219277 219313 212610 214771 211142 211457 240048 240636 230580 208795 197922 194596 194581 185686 178106 172608 167302 168053 202300 202388 182516 173476 166444 171297 169701 164182 161914 159612 151001 158114 186530 187069 174330 169362 166827 178037 186412 189226 191563 188906 186005 195309 223532 226899 214126

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	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	216234	216234	0	0	0
2	213587	214477.181578230	-1830.38714480497	-890.18157823028	-0.39479893349566
3	209465	209827.776322188	-3680.183873355	-362.776322187599	-0.33994872187352
4	204045	204418.526126059	-4877.81228434098	-373.526126059336	-0.224145044258044
5	200237	199912.724765473	-4623.02694404524	324.275234526576	0.0447853618394943
6	203666	201577.920789916	-375.522213058505	2088.07921008387	0.754017126473183
7	241476	231683.748183663	20286.0819432127	9792.25181633744	3.67433989511235
8	260307	260697.084335007	26211.6813865841	-390.08433500697	1.05224332628533
9	243324	255302.858981583	4750.96165544077	-11978.8589815831	-3.81108721658072
10	244460	245969.507346691	-4810.34385832014	-1509.50734669066	-1.69798373655502
11	233575	234448.121881445	-9365.40693011369	-873.121881445027	-0.808911182158405
12	237217	233621.72911782	-3569.82500021787	3595.27088217987	1.02920968741838
13	235243	234448.999317957	-594.937579165195	794.000682043006	0.530187414592767
14	230354	231487.733683511	-2202.77240311391	-1133.73368351057	-0.290158593620246
15	227184	226389.049191915	-4111.79879594066	794.950808084671	-0.336336347303463
16	221678	220112.165410824	-5523.98720058181	1565.83458917626	-0.254681916560283
17	217142	217319.207638779	-3722.61739222962	-177.207638778539	0.321211514433398
18	219452	225574.073738568	4118.63235016086	-6122.07373856777	1.38708366320003
19	256446	246288.856012642	14948.573511286	10157.1439873585	1.92374910746258
20	265845	258827.954980479	13373.1862463137	7017.04501952103	-0.279940690474034
21	248624	259837.762918314	5281.72057677067	-11213.7629183136	-1.43681442840166
22	241114	246096.84742379	-7168.52294247772	-4982.84742379007	-2.21108948209455
23	229245	233605.498697259	-10650.5840068462	-4360.49869725849	-0.618383956824398
24	231805	227827.192949423	-7467.0254354779	3977.80705057703	0.565603424674838
25	219277	218543.624534856	-8654.23149439876	733.37546514395	-0.211501834754061
26	219313	215992.168336011	-4660.44957368118	3320.83166398932	0.71039202623335
27	212610	210179.950654399	-5407.54079978417	2430.04934560058	-0.132288676925589
28	214771	210854.180975122	-1481.96639047548	3916.81902487844	0.700184460883853
29	211142	214841.025223256	2066.75062721389	-3699.02522325568	0.632709485648814
30	211457	223122.940683899	6096.0388137432	-11665.9406838993	0.714353567549834
31	240048	230441.956830442	6886.25156294235	9606.04316955802	0.140188518068640
32	240636	231564.389106116	3161.07787052051	9071.61089388379	-0.661749836521446
33	230580	234650.384057707	3112.49731290947	-4070.38405770683	-0.00862787527067449
34	208795	218734.187169042	-9202.46609052241	-9939.18716904172	-2.18694549691350
35	197922	204202.905219426	-12649.5276759828	-6280.90521942641	-0.6121891033156
36	194596	190122.423514331	-13574.729511267	4473.5764856685	-0.164426694542214
37	194581	190251.101893247	-4707.74428196086	4329.89810675275	1.57733900903130
38	185686	182988.429579636	-6360.54182285207	2697.57042036405	-0.293491191252335
39	178106	176859.121284027	-6211.61317620413	1246.87871597260	0.0264108176182695
40	172608	170764.884649402	-6136.18965263854	1843.11535059847	0.0134191535255904
41	167302	171497.339101412	-1710.96625017192	-4195.33910141220	0.78787019449899
42	168053	178477.291490645	3891.65135072021	-10424.2914906453	0.994589206368886
43	202300	190018.106849733	8812.91568056983	12281.8931502666	0.87303164596816
44	202388	195001.089990867	6350.43488712091	7386.91000913265	-0.437232023869609
45	182516	184852.724262001	-4263.76325082504	-2336.72426200113	-1.88509875979197
46	173476	180114.036656314	-4569.38692897991	-6638.03665631371	-0.0542776617268997
47	166444	173617.799436375	-5809.12872835949	-7173.79943637479	-0.220209075636228
48	171297	170483.167250836	-4088.2521850003	813.832749164085	0.305824936134334
49	169701	164676.579226762	-5194.54535509817	5024.42077323782	-0.196622435415268
50	164182	160119.692223411	-4784.27232663496	4062.30777658860	0.0728281882559792
51	161914	158822.518977709	-2546.59072385817	3091.48102229063	0.397062001356254
52	159612	159426.398381158	-527.463891824144	185.601618842121	0.358942433469935
53	151001	159375.049523596	-221.861061375823	-8374.04952359615	0.0543642486848535
54	158114	168868.999312782	6019.4993300538	-10754.9993127818	1.10855163258835
55	186530	173678.921073125	5243.32415583226	12851.0789268747	-0.137731493842675
56	187069	175021.255775317	2742.37212010449	12047.7442246825	-0.443955593424929
57	174330	176604.202486730	1999.03500934169	-2274.20248672969	-0.132007690850250
58	169362	176282.125291881	510.600391879073	-6920.12529188148	-0.264371078849236
59	166827	175188.700349993	-518.085727951854	-8361.70034999336	-0.182749363677611
60	178037	175800.558907678	206.783287225079	2236.44109232194	0.128806519531542
61	186412	180014.072864591	2778.02452377536	6397.92713540855	0.456780487556198
62	189226	185377.119104139	4435.70815336254	3848.88089586147	0.294238190255126
63	191563	189375.194838726	4155.57241089437	2187.80516127351	-0.0497219247628187
64	188906	190385.514380267	2143.79154419358	-1479.51438026679	-0.357512665973949
65	186005	196606.222890339	4754.09175784515	-10601.2228903389	0.464137381115021
66	195309	204886.272707439	7013.35614700393	-9577.27270743905	0.401351579474383
67	223532	210211.293033849	5932.21499564619	13320.7069661513	-0.191894445648607
68	226899	214691.919209623	5003.53647514459	12207.0807903768	-0.164841281353842
69	214126	216343.388023012	2859.71232736978	-2217.38802301183	-0.380687409990829

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/1uetd1259790489.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/1uetd1259790489.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/2tyjb1259790489.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/2tyjb1259790489.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/3hskk1259790489.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/3hskk1259790489.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/4sb8i1259790489.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/4sb8i1259790489.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/5kkth1259790489.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/02/t12597905434m8sc32a2xgf2js/5kkth1259790489.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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