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Decomposition by Structural Time Series Models 1

*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, 17 Dec 2010 20:15:57 +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/17/t1292616939qoddp1muerys73t.htm/, Retrieved Fri, 17 Dec 2010 21:15:46 +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/17/t1292616939qoddp1muerys73t.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 «
126,64 126,81 125,84 126,77 124,34 124,4 120,48 118,54 117,66 116,97 120,11 119,16 116,9 116,11 114,98 113,65 115,82 117,59 118,57 118,07 114,98 114,04 115,02 114,28 115,04 116,7 119,21 118,39 116,5 115,46 117,59 117,33 116,2 116,83 118,99 118,62 121,09 122,4 123,76 125,33 123,23 122,52 123,64 124,67 124,71 122,53 124,4 125,45 125,35 124,3 127,03 128,51 128,1 128,94 129,67 129,87 131,12 132,68 132,24 133,63 129,91 127,93 131,17 130,86 133,48 134,08 136,02 132,8 132,37 133,05 132,57 130,7 130,5 129,67 127,8 126,82 126,85 128,28 128,3 126,82 125,08 128,53 130,34 131,52 132,59 131,17 132,72 133,36 132,82 132,9 130,9 129,41 128,67 129,28 130,91 131,06 130,84 131,41 133,22 132,06 132,48 134,38 135,22 134,89 136,09 136,33 136,32 137,48 136,53 136,8 138,03 137,39 137,55 136,08 134,78 133,28 133,57 134,84 133,02 133,49 133,77 134,34 134,5 134,03 135,51 136,53 135,95 134,32 132,44 133,61 13 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1126.64126.64000
2126.81126.7845000010080.02549999899239160.02549999899239160.0456027756430726
3125.84125.8387804878970.001219512103129990.00121951210313006-0.834106700275071
4126.77126.7466666675490.02333333245132490.02333333245132470.778435520428436
5124.34124.373720929098-0.0337209290976729-0.0337209290976723-2.05678670068069
6124.4124.285423731604-0.028644067098960.114576268395840-0.0542297861991129
7120.48120.74536841687-0.265368416870114-0.265368416870113-2.50565791008379
8118.54118.822812495588-0.282812495587649-0.282812495587648-1.41314830589112
9117.66117.948969067703-0.288969067702588-0.288969067702589-0.503967742922696
10116.97117.263061220010-0.293061220010142-0.293061220010142-0.338448800796201
11120.11118.661578966417-0.3621052583956981.448421033582791.54765424099336
12119.16119.473199996871-0.313199996871287-0.3131999968712870.904158717521044
13116.9117.226092711995-0.326092711995328-0.326092711995326-1.64596566891752
14116.11116.439144733597-0.329144733596726-0.329144733596727-0.392229408917871
15114.98115.314379081692-0.334379081691678-0.334379081691676-0.677130525965474
16113.65112.565029595412-0.2712426011468781.08497040458752-2.15303816359227
17115.82115.98009755981-0.160097559810012-0.1600975598100152.92483523593526
18117.59117.740728154248-0.1507281542483-0.1507281542482991.63329585694107
19118.57118.715265699437-0.145265699436564-0.1452656994365660.956861149657808
20118.07118.216971152792-0.146971152792320-0.146971152792319-0.300191898680979
21114.98114.654821430721-0.08129464231973270.325178569278934-3.00640881773292
22114.04114.131730768707-0.0917307687073761-0.0917307687073784-0.356074640035209
23115.02115.107624520575-0.0876245205750809-0.08762452057508020.907390854924872
24114.28114.370114503307-0.0901145033066781-0.0901145033066784-0.552343840684428
25115.04115.126882128788-0.0868821287878825-0.0868821287878850.719767901840413
26116.7116.277204303328-0.1056989241681040.422795696672421.08095577892683
27119.21119.255809523597-0.0458095235968611-0.0458095235968642.51014248909196
28118.39118.438259493447-0.0482594934472309-0.0482594934472294-0.655694949630902
29116.5116.554069400380-0.054069400380389-0.0540694003803871-1.55985643370403
30115.46115.517169811056-0.0571698110563472-0.0571698110563483-0.835035031113013
31117.59117.270239522375-0.07994011940616170.3197604776246491.57375815745127
32117.33117.406378378073-0.076378378073019-0.07637837807302220.177022105332933
33116.2116.279218328525-0.0792183285249163-0.079218328524915-0.892567069910402
34116.83116.907311827649-0.077311827649496-0.07731182764949760.600810776665471
35118.99119.061313672640-0.0713136726397783-0.07131367263978021.89533442602107
36118.62118.361696659077-0.06457583523078440.258303340923142-0.544292101589138
37121.09121.114235294036-0.0242352940364041-0.02423529403641152.31900676511829
38122.4122.421103286315-0.0211032863149866-0.02110328631498661.13048386603885
39123.76123.777868852401-0.0178688524005875-0.01786885240058761.17019785881898
40125.33125.344158878459-0.0141588784594226-0.01415887845942651.34539237225291
41123.23123.2510810809920.00527027024804953-0.0210810809921896-1.79617823867618
42122.52122.523999999992-0.0039999999914955-0.00399999999150092-0.605055938391251
43123.64123.641663201662-0.00166320166202477-0.001663201662026080.95248176536787
44124.67124.6695228215820.000477178417729530.0004771784177318020.874237109614733
45124.71124.7094409937950.0005590062054296370.0005590062054236840.0334919299349115
46122.53122.6020641280240.0180160320059253-0.0720641280236915-1.81750820607869
47124.4124.3622242991750.0377757008247220.03777570082471561.44343706968385
48125.45125.4103358210100.03966417898952370.03966417898952280.85785430142124
49125.35125.3105959032800.03940409672025330.0394040967202574-0.118364798508210
50124.3124.2626208179520.03737918204799760.0373791820479908-0.923266945868589
51127.03127.0963537904200.0165884476048816-0.06635379041952082.40712220842377
52128.51128.4793728814370.0306271185626810.03062711856267541.13474404528224
53128.1128.0701184433960.02988155660423630.0298815566042379-0.373461438980753
54128.94128.9087500000830.03124999991730510.03124999991730280.686631439536474
55129.67129.6375716695630.03242833043722050.03242833043721760.592239822267349
56129.87129.9910509028080.0302627257020198-0.1210509028080720.275992622726075
57131.12131.0797984497090.04020155029081590.04020155029080750.88067274994898
58132.68132.6374458205360.04255417946445240.04255417946445211.28822544744154
59132.24132.1981916538870.04180834611307330.0418083461130747-0.40902747247916
60133.63133.5861111112160.04388888878399400.04388888878398831.14276926144650
61129.91130.1709638548190.0652409637046719-0.260963854818674-2.97025622916153
62127.93127.8850857143850.04491428561497980.0449142856149784-1.95925289904613
63131.17131.1205278175130.0494721824873430.04947218248733022.70841245869366
64130.86130.8110398861480.04896011385241870.0489601138524303-0.304717937254863
65133.48133.4273826459190.05261735408093240.05261735408091312.17942529007123
66134.08134.2724339356090.0481084839021967-0.1924339356087790.679817166144036
67136.02135.9587682120450.06123178795487960.06123178795488481.36701141473039
68132.8132.7431084657240.05689153427574760.0568915342757417-2.78158135591239
69132.37132.3137516513690.05624834863069080.0562483486307065-0.412750359142824
70133.05132.9929287600100.0570712399897030.05707123998968270.528770628835974
71132.57132.8034883716290.0583720929072841-0.233488371629122-0.211307818481145
72130.7130.6580740741540.04192592584565780.041925925845658-1.8410632804114
73130.5130.4583723798580.04162762014233260.0416276201423239-0.205095802661597
74129.67129.6294458128850.04055418711458970.0405541871146107-0.738934042101253
75127.8127.7617958180310.03820418196873620.0382041819687196-1.61969924553118
76126.82126.9887816643410.0421954160851357-0.168781664340530-0.694883547511012
77126.85126.8093526012290.04064739877099050.0406473987709904-0.185332746467561
78128.28128.2377482679740.04225173202597290.04225173202595891.17788764016741
79128.3128.2577739331780.04222606682183520.0422260668218526-0.0188649429791518
80126.82126.7795276498420.04047235015802940.0404723501580159-1.29053895759297
81125.08125.2704524883550.0476131220887171-0.190452488354856-1.32651890968117
82128.53128.4617500001140.06824999988627830.06824999988627532.63120731232182
83130.34130.2698588491940.07014115080622150.07014115080620551.47669973255492
84131.52131.4486550977320.07134490226759080.07134490226760150.940966976745587
85132.59132.5175731312140.07242686878558070.07242686878556220.846686064195416
86131.17131.4789669856520.0772417464130427-0.308966985652153-0.950607394500127
87132.72132.6360717950030.08392820499670440.08392820499670410.904528575777077
88133.36133.2755020493130.08449795068742770.0844979506874130.471466180205489
89132.82132.7361412488520.08385875114830210.0838587511483201-0.52948166144456
90132.9132.8161451944050.08385480559498690.0838548055949646-0.00327165051073581
91130.9131.2622132791220.0905533197805022-0.362213279121986-1.40062988559014
92129.41129.3312912622530.07870873774722370.0787087377472302-1.69442586944564
93128.67128.5920853541410.07791464585920030.0779146458591843-0.694162236346376
94129.28129.2015697675580.07843023244191830.07843023244193550.451141799355914
95130.91130.8300677639130.07993223608693150.07993223608689891.31553762932218
96131.06131.3725643465410.0781410866353624-0.3125643465414290.395413977369115
97130.84130.765668202870.0743317971301630.0743317971301679-0.574562955867947
98131.41131.3352117864770.07478821352259650.07478821352257780.420274746311678
99133.22133.1436154554890.07638454451070640.07638454451072261.47127856559246
100132.06131.9847518383410.0752481616588670.0752481616588437-1.04832554914170
101132.48132.7705434778580.0726358694644726-0.2905434778578750.607159821757201
102134.38134.2996578948450.08034210515542390.08034210515542521.22227879824170
103135.22135.1389921122910.0810078877091860.08100788770917440.64412467677184
104134.89134.8093520141180.08064798588154350.0806479858815562-0.348499536823314
105136.09136.0083727035210.08162729647878350.08162729647875750.949115137896353
106136.33136.6486885241700.0796721310424428-0.3186885241697550.477233181373715
107136.32136.2427782427770.07722175722332890.077221757223336-0.407707821279806
108137.48137.4018729097990.07812709020109980.07812709020107950.918121508886552
109136.53136.4527318296730.07726817032732480.0772681703273484-0.871781393498462
110136.8136.7225709516850.07742904831516350.0774290483151370.163423455405556
111138.03138.3194233933750.0723558483436562-0.2894233933746151.29748403089557
112137.39137.3228000000820.06719999991756460.0671999999175819-0.89795695739168
113137.55137.4827258194270.0672741805730170.06727418057299050.0786894675497797
114136.08136.0139536742020.06604632579767710.0660463257977078-1.30352721214922
115134.78134.7150438947320.0649561052676230.064956105267605-1.15833541552635
116133.28133.5554609925750.068865248143775-0.275460992575091-1.04537035005942
117133.57133.5017011495050.06829885049448480.0682988504945038-0.103050128499738
118134.84134.7707810108010.0692189891990180.06921898919898041.01899586665944
119133.02132.9522264729180.06777352708193770.0677735270819753-1.60198474166183
120133.49133.4219189603240.06808103967555820.06808103967553030.341072614976869
121133.77134.035649546520.0664123866300156-0.2656495465200560.46568923370893
122134.34134.2728308824290.0671691175713250.06716911757135250.143564137804262
123134.5134.4327626745800.06723732542020520.06723732542015750.0787181989085241
124134.03133.9631571219550.06684287804514890.0668428780451907-0.455563546877677
125135.51135.4421203228940.06787967710633420.06787967710630041.19832151236316
126136.53136.7865337198010.0641334299503767-0.2565337198015031.08920286449103
127135.95135.8899575972380.06004240276164270.0600424027616758-0.80794862711483
128134.32134.2611511300070.05884886999259990.058848869992555-1.4331329220407
129132.44132.3825194072610.05748059273929450.05748059273935-1.64411782498075
130133.61133.5517348378630.05826516213709480.05826516213705560.94340176375025
131131.02131.2793584376580.0648396094145818-0.259358437658311-1.98817324706425
132130.05129.9907074830550.05929251694480.0592925169448303-1.13864849676671
133128.21128.1519986404410.05800135955866780.0580013595586186-1.61059544528243
134129.03128.9714809783220.05851902167800350.05851902167806130.646173147234186
135130.34130.2806313646240.05936863537592910.05936863537587411.06125332271557
136131.57131.7917058426180.0554264606545832-0.2217058426183191.23813180139149
137132.63132.5717114754690.0582885245313890.05828852453140580.609751140758977
138132.06132.0021231979610.05787680203865550.0578768020386131-0.532793675594946
139134.44134.3806024885990.05939751140058920.05939751140063631.96917939953826
140134.1134.0408638744050.05913612559495610.059136125594915-0.338692417790669
141132.49132.7407772018230.0626943004557905-0.250777201823141-1.15903059340574
142134.23134.1621265823440.06787341765566350.06787341765566691.14366533813822
143134.92134.8517330803950.06826691960490560.0682669196048750.527574316892901
144135.61135.541340075920.06865992408012910.06865992408017260.527240725764706
145134.53134.4620656981080.06793430189251770.0679343018924791-0.974084268825211
146133.86134.1357223261900.0689305815474402-0.275722326189739-0.336146225054652
147133.89133.8224770642830.06752293571649820.0675229357165053-0.32178629042022
148135.33135.2616381418730.06836185812665710.06836185812662351.16389714492851
149135.86135.7913561393430.06864386065655870.0686438606565960.391481526119749
150136.22136.1511782662430.06882173375733780.06882173375729720.247077866862362
151137.38137.6414026599750.0653506649937974-0.2614026599751781.21163052506560
152137.31137.2462899408860.06371005911373330.0637100591137513-0.387798743059609
153136.89136.8265759905960.06342400940428160.0634240094042531-0.410203107345011
154138.01137.9459515367010.06404846329887730.06404846329890620.896013680318127
155136.72136.6567513290590.0632486709408760.063248670940853-1.14828102249350
156135.77136.0295201870110.0648800467527497-0.259520187010987-0.588485568012225
157137.52137.4504412608060.06955873919393130.06955873919393771.14231077338023
158135.61135.5415750286970.06842497130304590.0684249713030423-1.67875093445898
159132.94132.8731425301100.0668574698897980.0668574698898331-2.32230251242172
160134.12134.0525057208830.06749427911700220.0674942791169610.943993041601902
161132.55132.8317687072380.0704421768095725-0.281768707238259-1.09777844515409
162134.11134.0357666667300.07423333327021250.07423333327020480.955098756063543
163134.19134.1157634648050.07423653519510140.07423653519507850.00489042415327633
164135.57135.4950388457910.07496115420937130.07496115420940611.10735342795409
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167133.61133.5381832884690.07181671153100720.0718167115310017-0.977339763190206
168134.75134.6776077586800.07239224131958570.07239224131956340.905880745195215
169133.1133.0285352720030.07146472799706350.0714647279971108-1.46068770257102
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173132.45132.3744322344930.07556776550726120.0755677655072275-0.0810900130113011
174133.33133.2540115063370.07598849366304540.07598849366308940.682210097072091
175133.57133.4939257711010.07607422889890960.0760742288988560.139092289151066
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177133.92133.8477201018370.0722798981625050.0722798981625093-0.551095728569803
178132.62132.5484181078890.07158189211107550.0715818921110567-1.16378967709484
179132.3132.2286171835840.07138281641620440.071382816416248-0.332088973494886
180133.26133.1881656504620.07183434953759930.07183434953754220.753609940620338
181132.6132.8903427417110.0725856854278557-0.290342741711385-0.31484717677124
182134.38134.3034207921370.07657920786280110.07657920786278921.13029986455746
183134.17134.0935625928340.07643740716628990.0764374071662703-0.243040966894696
184135.46135.3829624135100.07703758648969760.07703758648973731.02919351426465
185135.09135.0131833910620.07681660893845810.076816608938406-0.379121970000485
186134.96135.2658754289020.0764688572256126-0.3058754289024090.149781480655634
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442113.14113.0877561475580.0522438524425380.05224385244241510.661168587235529
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447113.85113.7972522796520.05274772034829540.05274772034815190.266924618128902
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485113.97113.9206894608450.04931053915535750.0493105391553121-0.143637245804337
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487111.28111.2314344186190.04856558138141280.04856558138137-1.28640908652069
488111.35111.3014304315610.04856956843844640.04856956843856630.0181808251875673
489110.92110.8715194346430.04848056535711790.0484805653570378-0.405926093414752
490110.73110.6815637783700.04843622162984160.0484362216297763-0.202280906077688
491109109.1983018167770.0495754541942135-0.198301816776756-1.30124941646404
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/1oikz1292616939.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/1oikz1292616939.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/2oikz1292616939.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/2oikz1292616939.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/3grjk1292616939.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/3grjk1292616939.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/49i0n1292616939.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/49i0n1292616939.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/59i0n1292616939.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/17/t1292616939qoddp1muerys73t/59i0n1292616939.ps (open in new window)


 
Parameters (Session):
par1 = additive ; par2 = 12 ;
 
Parameters (R input):
par1 = 5 ; par2 = 12 ;
 
R code (references can be found in the software module):
par1 <- 5
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')
 





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Software written by Ed van Stee & Patrick Wessa


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