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Ad hoc forecasting

*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 09:16:16 -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/t1259943425zhfhxozgvk02vc2.htm/, Retrieved Fri, 04 Dec 2009 17:17:12 +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/t1259943425zhfhxozgvk02vc2.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:

Techniek 3: Structurele tijdreeksanalyse

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

462 455 461 461 463 462 456 455 456 472 472 471 465 459 465 468 467 463 460 462 461 476 476 471 453 443 442 444 438 427 424 416 406 431 434 418 412 404 409 412 406 398 397 385 390 413 413 401 397 397 409 419 424 428 430 424 433 456 459 446 441

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	462	462	0	0	0
2	455	460.646062194394	-1.8205545052069	-5.6460621943938	-1.88009699361182
3	461	457.698526489489	-2.46398202970895	3.30147351051124	-0.300541729252562
4	461	458.038149306611	-1.08217044784229	2.96185069338854	0.760951405976302
5	463	460.51887054342	0.80485904271331	2.48112945657975	1.00045279284430
6	462	462.186239454818	1.25791568112083	-0.186239454817606	0.221881565374327
7	456	459.113566745741	-0.956600442788405	-3.113566745741	-1.08772338491657
8	455	455.481012059443	-2.32140545865447	-0.481012059443217	-0.678839082309205
9	456	454.16505406102	-1.80579737885644	1.83494593898028	0.256269279788715
10	472	463.539520364408	3.94164033404217	8.46047963559172	2.84992772467317
11	472	471.637073865101	6.0785456872593	0.362926134898689	1.05939867949850
12	471	474.343424797212	4.34511588607999	-3.34342479721242	-0.859560870115967
13	465	470.766153545838	0.301071492224929	-5.76615354583835	-2.01658089000833
14	459	466.558795673856	-2.0136840651849	-7.55879567385617	-1.16715765892350
15	465	463.695204304106	-2.44725272428514	1.30479569589388	-0.213843572045822
16	468	464.497281638015	-0.834223886041891	3.50271836198460	0.79560261036034
17	467	464.101773392619	-0.61665434494083	2.89822660738079	0.109751571825025
18	463	461.225336970294	-1.75109274190509	1.77466302970630	-0.568265461506125
19	460	460.116972466473	-1.42936849750847	-0.116972466472944	0.158858310157211
20	462	462.243383656732	0.336243651513575	-0.243383656732173	0.871853394779848
21	461	464.997258044897	1.53463471638924	-3.99725804489688	0.594217921302161
22	476	468.678990807056	2.60076589512296	7.32100919294421	0.529129019599888
23	476	472.60337658608	3.25852309892395	3.39662341392034	0.326427002763428
24	471	472.55604236225	1.61585319806942	-1.55604236224991	-0.815926387932145
25	453	463.628592620051	-3.62874854372475	-10.6285926200509	-2.60872157477873
26	443	453.321331507414	-6.95540308874441	-10.3213315074138	-1.65197748224769
27	442	443.122170478797	-8.56488737997111	-1.12217047879715	-0.795516256087589
28	444	437.184225183589	-7.27113621926453	6.81577481641122	0.640253122798788
29	438	432.254846723312	-6.11951394534428	5.74515327668796	0.573898753201987
30	427	426.095239336167	-6.13932302811533	0.90476066383294	-0.00988371827844293
31	424	423.586786365758	-4.34214957331981	0.413213634241509	0.891808473602591
32	416	419.342418395631	-4.29391262760153	-3.34241839563133	0.0238493873240153
33	406	413.562856158462	-5.02407688832217	-7.56285615846179	-0.361329735448834
34	431	417.720852566978	-0.516779361089381	13.2791474330220	2.23570451393841
35	434	424.451240095645	3.04301899915843	9.54875990435546	1.76865048079695
36	418	420.058123373997	-0.614830305087467	-2.05812337399695	-1.81849994368634
37	412	417.898644517389	-1.37569205497466	-5.89864451738943	-0.377953358643656
38	404	414.327836738978	-2.45664512352714	-10.3278367389777	-0.535701299659597
39	409	411.462572617259	-2.65725230759588	-2.46257261725884	-0.099239103774605
40	412	407.187632715771	-3.44854032474732	4.81236728422908	-0.392024162503858
41	406	401.504105993392	-4.54109766141268	4.49589400660847	-0.543213720409086
42	398	397.378018517602	-4.33772425767209	0.621981482398046	0.101239213113608
43	397	394.929060723711	-3.4105759720909	2.07093927628929	0.46037296599645
44	385	390.592273491547	-3.86455274448964	-5.59227349154697	-0.224747195555188
45	390	396.472804349163	0.897024483350892	-6.472804349163	2.35628153175414
46	413	401.6170880799	2.96813169063773	11.3829119201002	1.02682414250941
47	413	402.173489446569	1.79185084019024	10.8265105534313	-0.58440508276701
48	401	402.542026441394	1.09655136965589	-1.54202644139356	-0.345655368645654
49	397	402.438408400577	0.509537602754697	-5.43840840057749	-0.291453933195374
50	397	405.023113916345	1.52390113926468	-8.02311391634487	0.502570517538001
51	409	408.798106522528	2.62158759127333	0.201893477471550	0.543311934737619
52	419	412.344182137642	3.07132063104807	6.65581786235769	0.222886485032896
53	424	417.739653232524	4.20159919202622	6.26034676747603	0.56148364593677
54	428	425.704168683342	6.0345451965337	2.29583131665758	0.911356616111277
55	430	430.711136971379	5.53335850397997	-0.711136971378974	-0.248819626196394
56	424	435.545224597256	5.19257503695732	-11.5452245972563	-0.168814523671046
57	433	440.897878509631	5.27040682539327	-7.89787850963066	0.0385307652333583
58	456	444.283829541669	4.35584110691099	11.7161704583307	-0.453358404700734
59	459	447.422724835739	3.76525120628003	11.5772751642615	-0.293295964734837
60	446	448.615892881323	2.51538326538021	-2.61589288132271	-0.621076433301036
61	441	448.762288121156	1.36302900914963	-7.76228812115596	-0.571992137434703

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/16htf1259943374.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/16htf1259943374.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/2qzsm1259943374.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/2qzsm1259943374.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/3q29y1259943374.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/3q29y1259943374.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/4ude91259943374.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/4ude91259943374.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/568lb1259943374.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943425zhfhxozgvk02vc2/568lb1259943374.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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