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SHWWS9klasmeth3

*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: Tue, 01 Dec 2009 13:04:49 -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/01/t1259697938rib4tswsrficcb9.htm/, Retrieved Tue, 01 Dec 2009 21:05:45 +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/01/t1259697938rib4tswsrficcb9.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 «

161 149 139 135 130 127 122 117 112 113 149 157 157 147 137 132 125 123 117 114 111 112 144 150 149 134 123 116 117 111 105 102 95 93 124 130 124 115 106 105 105 101 95 93 84 87 116 120 117 109 105 107 109 109 108 107 99 103 131 137

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	161	161	0	0	0
2	149	150.652804954134	-7.54703501666725	-1.65280495413439	-1.63771582823087
3	139	138.982655708135	-10.5000705669800	0.0173442918654433	-0.526939710259491
4	135	133.864161340926	-6.58052551882916	1.13583865907379	0.668550281526714
5	130	129.954139671962	-4.65587222479019	0.0458603280378227	0.332322471049674
6	127	126.988868997811	-3.43357963074273	0.0111310021894042	0.211954297131278
7	122	122.480802464784	-4.21141819954527	-0.480802464784292	-0.134828025796281
8	117	117.299039632372	-4.91378274889712	-0.299039632372054	-0.121747720423399
9	112	112.158059721224	-5.0782043812403	-0.158059721223623	-0.0285009187671397
10	113	112.152979939957	-1.40695357739817	0.84702006004321	0.636375230284341
11	149	143.070980811444	21.9860350450926	5.92901918855637	4.05494630235283
12	157	160.047813503295	18.3609133248431	-3.04781350329533	-0.628379465082242
13	157	159.903599811193	5.10296396137905	-2.90359981119305	-2.38883808065303
14	147	149.560806664401	-5.5817287150919	-2.56080666440074	-1.81943303091513
15	137	138.245352406242	-9.49329810512953	-1.24535240624249	-0.687055826502149
16	132	130.547108147196	-8.23855085620497	1.45289185280430	0.217680474947628
17	125	124.929951269511	-6.41506099135959	0.0700487304888313	0.314266683881632
18	123	122.311131554423	-3.77713230927587	0.68886844557734	0.457086040563384
19	117	117.442464820216	-4.53720670332106	-0.442464820216143	-0.131772894658241
20	114	112.644613186522	-4.7188049990728	1.35538681347791	-0.0314766363061678
21	111	110.204986216342	-3.1308828302234	0.795013783657597	0.275251575401009
22	112	116.883620972700	3.70319077371009	-4.88362097269987	1.18467504374390
23	144	135.559334884308	14.1277381158775	8.44066511569167	1.80694466832398
24	150	150.249132854924	14.5182840473446	-0.249132854923828	0.0678343163534942
25	149	151.241416944591	5.09798096032244	-2.24141694459116	-1.64794338283718
26	134	138.216390052434	-7.37162961885366	-4.21639005243418	-2.14798335074383
27	123	125.000778753994	-11.3489070289402	-2.00077875399352	-0.692409525363189
28	116	114.706233550882	-10.6226325870103	1.29376644911757	0.126377475930886
29	117	115.506657540663	-2.75215508903027	1.49334245933688	1.35936480510199
30	111	110.708874214596	-4.15790634141863	0.291125785404126	-0.243353609475447
31	105	104.903816307861	-5.29123277787877	0.0961836921393925	-0.196488507873823
32	102	99.9516012637417	-5.0577121332045	2.04839873625832	0.0404777932819462
33	95	95.9994195843924	-4.29603794845461	-0.999419584392443	0.132029390768921
34	93	100.575947362725	1.81514406999319	-7.57594736272543	1.05934968470607
35	124	114.716730869536	10.2949290478122	9.28326913046433	1.47009361589350
36	130	127.458922979255	11.9773660584991	2.54107702074514	0.292347366832890
37	124	124.778545006160	1.88230592681973	-0.778545006160475	-1.75505818445573
38	115	118.497472376771	-3.70343843832279	-3.4974723767715	-0.965125704944754
39	106	109.174032358363	-7.52463032938233	-3.1740323583633	-0.663538604465324
40	105	105.755526274766	-4.71574222647919	-0.755526274765991	0.488514565709078
41	105	102.742947895194	-3.54856038586611	2.25705210480565	0.201972304211223
42	101	99.8632794521701	-3.09119351949751	1.13672054782987	0.0791583705697196
43	95	94.6588556491954	-4.53655741085967	0.341144350804620	-0.250532278129223
44	93	90.2396448656509	-4.45620607426935	2.76035513434908	0.0139285858809953
45	84	86.9085081809692	-3.68554823403002	-2.90850818096915	0.133585736338728
46	87	95.858702493427	4.96625720967545	-8.85870249342702	1.49970820122581
47	116	107.161890545002	9.30092899023232	8.83810945499783	0.751662415942542
48	120	114.589597038435	8.01944986891799	5.41040296156527	-0.222564300568298
49	117	116.777751253016	4.02677612580734	0.222248746983824	-0.69282149433411
50	109	112.572077361047	-1.58619846105863	-3.57207736104712	-0.971012714933745
51	105	109.467059550568	-2.61781299630844	-4.46705955056778	-0.178979442183705
52	107	108.081673612220	-1.77786881547401	-1.08167361222045	0.145955639649442
53	109	106.789387532202	-1.44627945369066	2.21061246779847	0.0574403511461303
54	109	106.601581858759	-0.588191073262772	2.39841814124124	0.148539974470227
55	108	106.71782747458	-0.108014553164348	1.28217252542003	0.0832118945730557
56	107	104.475962916450	-1.56378235106117	2.5240370835505	-0.252350865505948
57	99	104.861227371625	-0.233559643920123	-5.86122737162458	0.230580814859165
58	103	112.418024398797	5.08136494623352	-9.4180243987968	0.921317388795852
59	131	121.528368754438	7.8284185439313	9.4716312455623	0.476423357856821
60	137	130.136884001081	8.3605269039473	6.86311599891946	0.0923648662541242

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/1oexb1259697887.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/1oexb1259697887.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/2kc7f1259697887.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/2kc7f1259697887.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/32dvd1259697887.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/32dvd1259697887.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/4y5011259697887.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/4y5011259697887.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/5nwl61259697887.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259697938rib4tswsrficcb9/5nwl61259697887.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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