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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: Fri, 04 Dec 2009 12:52:00 -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/04/t1259956352pis7buhicijylj3.htm/, Retrieved Fri, 04 Dec 2009 20:52:39 +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/04/t1259956352pis7buhicijylj3.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 «

5560 3922 3759 4138 4634 3996 4308 4143 4429 5219 4929 5755 5592 4163 4962 5208 4755 4491 5732 5731 5040 6102 4904 5369 5578 4619 4731 5011 5299 4146 4625 4736 4219 5116 4205 4121 5103 4300 4578 3809 5526 4247 3830 4394 4826 4409 4569 4106 4794 3914 3793 4405 4022 4100 4788 3163 3585 3903 4178 3863 4187

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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	5560	5560	0	0	0
2	3922	4714.52536816824	-74.8634167326895	-89.9284610409174	-2.64728315184995
3	3759	4251.25320949742	-98.5977753216762	-102.876743216874	-1.39053745032720
4	4138	4188.74279278889	-97.0069197894164	-90.2626406011074	0.137511978806211
5	4634	4380.81362343875	-87.0091017883324	-76.2344691943839	1.13290461723728
6	3996	4201.35777485845	-89.7106788592938	-97.9182549126208	-0.367345084406422
7	4308	4238.67637505286	-86.3952112705153	-79.8413625465993	0.508426254575097
8	4143	4187.54215009020	-85.5422029361742	-86.1848467018173	0.141690422389103
9	4429	4285.76819498042	-81.3255527105868	-74.5169003009558	0.740123624362006
10	5219	4692.91651253572	-70.547019462021	-53.8980840992694	1.97003266688826
11	4929	4793.51145861073	-66.8859877586515	-67.9896015787631	0.690838602016055
12	5755	5214.38773771925	-56.7225666989548	-39.8752155933868	1.97015700851266
13	5592	5103.99086011032	-51.4016152985969	561.767991861081	-0.291046803469919
14	4163	4639.17502904271	-66.4555273969757	-93.6842778615573	-1.39183123962552
15	4962	4780.64246390558	-60.7121546520551	-40.0207282144515	0.779006773947029
16	5208	4968.63601110879	-55.64365659185	-43.2199308134834	0.977524372560877
17	4755	4864.98092556559	-56.4226911816121	-54.0020853803743	-0.192305125451883
18	4491	4697.80001516939	-57.9616464948569	-76.1980432749851	-0.44726681858055
19	5732	5140.71339328842	-51.6659919258776	-2.50621263754336	2.03044740077155
20	5731	5402.4316535147	-47.9698406767004	-43.9732834442245	1.2728758015702
21	5040	5244.57404946423	-49.2138586451292	-73.7482507358397	-0.446799765869881
22	6102	5607.40780423478	-44.6757425391048	3.61344654374845	1.67636959726186
23	4904	5305.69961264877	-47.4493417860724	-95.2663634307702	-1.04609018511708
24	5369	5316.26047711632	-46.8725599245558	-16.5047300099843	0.236197409956976
25	5578	5190.95106719817	-43.3708694523649	487.488997458091	-0.369495435030959
26	4619	4940.27152490031	-48.0404573935925	-108.026538709054	-0.758011313040461
27	4731	4833.81936967272	-49.1228078632079	-38.5477608553221	-0.225524952249835
28	5011	4897.7796499059	-47.5652056304162	-16.5996154998335	0.45062433377211
29	5299	5064.96142435806	-45.2109195561946	-16.8562202740689	0.866840707514142
30	4146	4682.33196206863	-48.3802891034652	-139.080584198232	-1.36962201276624
31	4625	4630.15616070899	-48.4126010086433	-0.671334903417502	-0.0154467698685278
32	4736	4665.29227494143	-47.7432752249101	-28.1963504070519	0.340469035235951
33	4219	4487.00660858808	-48.7506075698078	-113.320023689104	-0.532344429826461
34	5116	4724.32664662977	-46.5947785298817	52.5057737805362	1.16703873175352
35	4205	4520.63978480779	-47.7541620852386	-129.319074725491	-0.64102463004397
36	4121	4322.45584247464	-48.6630819708016	-22.7167990088788	-0.614191306034067
37	5103	4375.38349007507	-51.4588144426713	601.116149513449	0.455041151048605
38	4300	4363.20855680689	-50.8410477668242	-105.452504150362	0.149202273962471
39	4578	4452.50165860099	-48.846116918933	-30.5041847336747	0.548586931057211
40	3809	4162.49598431055	-51.4345106351338	-76.3579461194893	-0.96694442769165
41	5526	4716.95404162376	-46.2668391848404	103.009240550941	2.45436570254497
42	4247	4560.84837304883	-47.067647194155	-185.071471102264	-0.446916100740273
43	3830	4219.38359932978	-49.0117038349573	-43.2350544981382	-1.20033228477782
44	4394	4268.43168519634	-48.4018917925477	10.1047778128082	0.400226999998593
45	4826	4540.35518764070	-46.4798995198423	-91.8186119070737	1.30810653137723
46	4409	4437.28757644325	-46.8120342414527	38.4224059681007	-0.231157256891856
47	4569	4516.67373846962	-46.0934944827857	-96.5020132658425	0.515622131797038
48	4106	4329.46848593743	-46.6531423624850	-56.6796654507778	-0.577006050046973
49	4794	4263.10149939684	-46.2791764892355	555.031501887875	-0.0859867005905898
50	3914	4133.08375826453	-47.2578845637882	-126.904658667729	-0.325073995661583
51	3793	3959.75336934837	-48.7324425406275	-25.6541132832324	-0.497573358930957
52	4405	4175.79066231665	-46.3469022758127	-74.6660195986305	1.06523695834722
53	4022	4040.99819793884	-46.9800267750368	83.7232868883203	-0.358975354620323
54	4100	4105.32382236895	-46.3012438720444	-135.278629679864	0.453493531451737
55	4788	4395.02809415939	-44.4489142184709	-0.299451394203821	1.37142306411808
56	3163	3857.74409924823	-47.0069640074485	-117.208703688729	-2.01329649051822
57	3585	3739.52766194971	-47.363889049679	-71.0265917147828	-0.291034305330591
58	3903	3768.21924941065	-46.9911342439941	45.5643283671117	0.31092234596646
59	4178	3954.63528394172	-45.9023364173876	-50.5506899572823	0.954387983747836
60	3863	3918.67657334485	-45.8756445812152	-67.3752713736452	0.0406995181224796
61	4187	3774.58962180998	-44.5205207416207	531.193417256676	-0.421350377293246

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/1it331259956318.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/1it331259956318.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/2kqav1259956318.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/2kqav1259956318.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/34vg01259956318.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/34vg01259956318.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/467rk1259956318.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/467rk1259956318.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/5k01s1259956318.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259956352pis7buhicijylj3/5k01s1259956318.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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