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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 02 Dec 2009 14:19:07 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/02/t1259788791ptpftisy5n0sjo6.htm/, Retrieved Sun, 28 Apr 2024 05:10:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62594, Retrieved Sun, 28 Apr 2024 05:10:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Structural Time Series Models] [] [2009-11-27 15:02:30] [b98453cac15ba1066b407e146608df68]
-    D      [Structural Time Series Models] [Structural Time S...] [2009-12-02 21:19:07] [2622964eb3e61db9b0dfd11950e3a18c] [Current]
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Dataseries X:
0.0314796223103059 
-3.00870920563557 
-2.07677512619799 
-1.25010391965540 
0.817975239137125 
0.0252076485413113 
0.554937772830776 
0.230027371950115 
2.35672227418686 
1.41350455171120 
2.73311719024401 
1.31551925971717 
-2.70076272244080 
-0.721411049152714 
-0.149388576811997 
-0.118199629770334 
-0.676562489695275 
1.79699928690761 
1.79845572032988 
0.245100010770855 
1.80710848932636 
-1.75934771184948 
-0.0186697168761931 
0.189651523600062 
-1.84149562719087 
-1.07019530156943 
-0.507291477584104 
0.866365633831705 
-1.76077926699189 
-0.580719393339347 
-0.435702079860853 
-0.994868534845203 
1.63136048315789 
-1.1949403709466 
-1.00525975426991 
1.32302234837564 
-0.628357549594746 
0.632048410440518 
-2.16903155809288 
2.53779364144266 
-0.632933703679292 
-1.41749196342200 
-0.455343045381255 
0.812255211942954 
0.627897309219833 
0.650904313655623 
-1.29800419154382 
0.74391671726854 
-1.50461634127457 
-1.42734677658523 
0.263353807408564 
-0.430830854870631 
0.379576092518008 
1.70309353400146 
-3.12314448117342 
-1.32526207118689 
-0.60032490743804 
1.23607137604666 
0.738007075905376 
0.899100896289585 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62594&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62594&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
10.03147962231030590.0314796223103059000
2-3.00870920563557-0.337859984836871-0.123113202382392-0.153436759095376-2.05955749182822
3-2.07677512619799-0.709604203587071-0.185270956474344-0.185865735543112-0.995014943027091
4-1.2501039196554-0.928920685940089-0.192080061650079-0.18529031273494-0.116144616839291
50.817975239137125-0.689068229444243-0.120091308625758-0.09106833810026021.37353653543211
60.0252076485413113-0.609751814053241-0.0916044909090781-0.0912449663015250.623809170681526
70.554937772830776-0.425316061107351-0.0570994604272071-0.04478925316694840.876900194796564
80.230027371950115-0.328188351538081-0.0399631082053763-0.03752531251681910.506663681018811
92.356722274186860.1611822793987790.01297026570884730.04559116809141431.8165914954529
101.41350455171120.4018847750828810.03367319570659780.03385869034866650.820736271441635
112.733117190244010.8334070951980250.066827289407310.09022803738928961.50930109389431
121.315519259717170.9608670644772480.07149134170514940.06245324294126680.24228216916783
13-2.70076272244080.9125104685059580.0629307747282609-0.732463638908291-2.17933242704605
14-0.7214110491527140.6680856916312480.04244040462139620.00909657936452334-1.17069055337286
15-0.1493885768119970.5582536562184780.03292337711926080.0302213377362605-0.614818643709566
16-0.1181996297703340.4760929803635060.02615372694430590.00813932661654078-0.498521227947173
17-0.6765624896952750.3220200256460730.01614113351865380.0135541398248013-0.832626770711557
181.796999286907610.5366842825629670.02658971896066640.07131735316415330.973152758639384
191.798455720329880.7235443365988440.03460323571442690.05621685715897470.83006549095896
200.2451000107708550.6938262196183970.0315403141575282-0.0166323523779194-0.350703795086036
211.807108489326360.847576942055390.03709533271568570.09488906226987780.69932370728707
22-1.759347711849480.5804127851965990.0238666592559258-0.0795039836124123-1.82235595792003
23-0.01866971687619310.5268931723363540.02064223125108530.0564684343821266-0.484013558286986
240.1896515236000620.5046240429927530.01892577682729790.0349609929985976-0.280503374220937
25-1.841495627190870.389270140869540.0137611737907398-0.254724170071894-1.52794292646426
26-1.070195301569430.2460674275054140.00794769648870773-0.0183011781312519-1.0452326201295
27-0.5072914775841040.1725848236018820.005039471474699170.0104305576599460-0.555639151846882
280.8663656338317050.2425483886805570.007278233323112130.04917300289384890.461484830401469
29-1.760779266991890.06443890816345540.00109864286177167-0.114862540034759-1.37061423861296
30-0.5807193933393470.00122788551389760-0.000975862477303480.0351870300457735-0.493580940212733
31-0.435702079860853-0.0414523212142378-0.002279123235141980.0212395364642590-0.331709514079693
32-0.994868534845203-0.119441415399855-0.00457336477909578-0.093674439949029-0.623085277070507
331.631360483157890.0108240738219333-0.0006075161320109450.1797337545951891.14661034875885
34-1.1949403709466-0.0756029597806416-0.00305950234545563-0.171689005949062-0.75307597417658
35-1.00525975426991-0.154820057768571-0.005174991113302140.0176248386783926-0.688907865313166
361.32302234837564-0.0542808312175853-0.002317850095348400.1271922188122490.990379756576892
37-0.628357549594746-0.0829553485932472-0.00301144660272508-0.101866706160584-0.345612060624114
380.632048410440518-0.0344549765229294-0.001690630739313720.04134188845268780.49732768724465
39-2.16903155809288-0.186727500127953-0.00545517806095646-0.138095474337901-1.46759701218477
402.53779364144266-0.0110938868259967-0.001038378271617130.2674298369065981.81368136259316
41-0.632933703679292-0.0430496195485981-0.00177450575854533-0.189162105198873-0.3182282809543
42-1.417491963422-0.139152857514633-0.00396819720523114-0.0217179566559275-0.996947869794296
43-0.455343045381255-0.167905679693075-0.004531484136440470.0516160745682807-0.268740639518525
440.812255211942954-0.103133724382716-0.00299140770428937-0.05735716501383870.770343197484806
450.627897309219833-0.0716115302370842-0.002241112011899780.2028555810141200.392986893703714
460.650904313655623-0.0202645828473225-0.00110094053526868-0.1188486341202660.624625821615639
47-1.29800419154382-0.0947240222227177-0.00262924259443798-0.0957231302269195-0.875016785424487
480.74391671726854-0.0588193515525736-0.001842836201283250.2022862596756810.473798361432027
49-1.50461634127457-0.119992930518855-0.00302945105658321-0.208417934589222-0.920249067996743
50-1.42734677658523-0.202142045837650-0.004580817022508930.0415931699430216-1.00334328447356
510.263353807408564-0.172088230247541-0.00391476639534321-0.1198251988023250.440015640864886
52-0.430830854870631-0.203879200209112-0.004440732500366380.229128885971704-0.361218271192151
530.379576092518008-0.169737289497339-0.00372623910754898-0.09552988141009730.510410469441461
541.70309353400146-0.0743187411439252-0.001923606608258740.08540534654080921.33848623748116
55-3.12314448117342-0.229786100389650-0.00466545933392777-0.219038676757315-2.11437705674836
56-1.32526207118689-0.289519204058890-0.0056315583573543-0.0573483874067931-0.77312700438829
57-0.60032490743804-0.320613976735117-0.00607057929388660.181570918253374-0.364317983495049
581.23607137604666-0.247719439131744-0.004732187482068650.02582355489435181.15092684830282
590.738007075905376-0.198020565092148-0.00382500312337423-0.0884221861467460.808299372178697
600.899100896289585-0.160382719072617-0.003145284284965950.2564871012649820.632971369509908

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 0.0314796223103059 & 0.0314796223103059 & 0 & 0 & 0 \tabularnewline
2 & -3.00870920563557 & -0.337859984836871 & -0.123113202382392 & -0.153436759095376 & -2.05955749182822 \tabularnewline
3 & -2.07677512619799 & -0.709604203587071 & -0.185270956474344 & -0.185865735543112 & -0.995014943027091 \tabularnewline
4 & -1.2501039196554 & -0.928920685940089 & -0.192080061650079 & -0.18529031273494 & -0.116144616839291 \tabularnewline
5 & 0.817975239137125 & -0.689068229444243 & -0.120091308625758 & -0.0910683381002602 & 1.37353653543211 \tabularnewline
6 & 0.0252076485413113 & -0.609751814053241 & -0.0916044909090781 & -0.091244966301525 & 0.623809170681526 \tabularnewline
7 & 0.554937772830776 & -0.425316061107351 & -0.0570994604272071 & -0.0447892531669484 & 0.876900194796564 \tabularnewline
8 & 0.230027371950115 & -0.328188351538081 & -0.0399631082053763 & -0.0375253125168191 & 0.506663681018811 \tabularnewline
9 & 2.35672227418686 & 0.161182279398779 & 0.0129702657088473 & 0.0455911680914143 & 1.8165914954529 \tabularnewline
10 & 1.4135045517112 & 0.401884775082881 & 0.0336731957065978 & 0.0338586903486665 & 0.820736271441635 \tabularnewline
11 & 2.73311719024401 & 0.833407095198025 & 0.06682728940731 & 0.0902280373892896 & 1.50930109389431 \tabularnewline
12 & 1.31551925971717 & 0.960867064477248 & 0.0714913417051494 & 0.0624532429412668 & 0.24228216916783 \tabularnewline
13 & -2.7007627224408 & 0.912510468505958 & 0.0629307747282609 & -0.732463638908291 & -2.17933242704605 \tabularnewline
14 & -0.721411049152714 & 0.668085691631248 & 0.0424404046213962 & 0.00909657936452334 & -1.17069055337286 \tabularnewline
15 & -0.149388576811997 & 0.558253656218478 & 0.0329233771192608 & 0.0302213377362605 & -0.614818643709566 \tabularnewline
16 & -0.118199629770334 & 0.476092980363506 & 0.0261537269443059 & 0.00813932661654078 & -0.498521227947173 \tabularnewline
17 & -0.676562489695275 & 0.322020025646073 & 0.0161411335186538 & 0.0135541398248013 & -0.832626770711557 \tabularnewline
18 & 1.79699928690761 & 0.536684282562967 & 0.0265897189606664 & 0.0713173531641533 & 0.973152758639384 \tabularnewline
19 & 1.79845572032988 & 0.723544336598844 & 0.0346032357144269 & 0.0562168571589747 & 0.83006549095896 \tabularnewline
20 & 0.245100010770855 & 0.693826219618397 & 0.0315403141575282 & -0.0166323523779194 & -0.350703795086036 \tabularnewline
21 & 1.80710848932636 & 0.84757694205539 & 0.0370953327156857 & 0.0948890622698778 & 0.69932370728707 \tabularnewline
22 & -1.75934771184948 & 0.580412785196599 & 0.0238666592559258 & -0.0795039836124123 & -1.82235595792003 \tabularnewline
23 & -0.0186697168761931 & 0.526893172336354 & 0.0206422312510853 & 0.0564684343821266 & -0.484013558286986 \tabularnewline
24 & 0.189651523600062 & 0.504624042992753 & 0.0189257768272979 & 0.0349609929985976 & -0.280503374220937 \tabularnewline
25 & -1.84149562719087 & 0.38927014086954 & 0.0137611737907398 & -0.254724170071894 & -1.52794292646426 \tabularnewline
26 & -1.07019530156943 & 0.246067427505414 & 0.00794769648870773 & -0.0183011781312519 & -1.0452326201295 \tabularnewline
27 & -0.507291477584104 & 0.172584823601882 & 0.00503947147469917 & 0.0104305576599460 & -0.555639151846882 \tabularnewline
28 & 0.866365633831705 & 0.242548388680557 & 0.00727823332311213 & 0.0491730028938489 & 0.461484830401469 \tabularnewline
29 & -1.76077926699189 & 0.0644389081634554 & 0.00109864286177167 & -0.114862540034759 & -1.37061423861296 \tabularnewline
30 & -0.580719393339347 & 0.00122788551389760 & -0.00097586247730348 & 0.0351870300457735 & -0.493580940212733 \tabularnewline
31 & -0.435702079860853 & -0.0414523212142378 & -0.00227912323514198 & 0.0212395364642590 & -0.331709514079693 \tabularnewline
32 & -0.994868534845203 & -0.119441415399855 & -0.00457336477909578 & -0.093674439949029 & -0.623085277070507 \tabularnewline
33 & 1.63136048315789 & 0.0108240738219333 & -0.000607516132010945 & 0.179733754595189 & 1.14661034875885 \tabularnewline
34 & -1.1949403709466 & -0.0756029597806416 & -0.00305950234545563 & -0.171689005949062 & -0.75307597417658 \tabularnewline
35 & -1.00525975426991 & -0.154820057768571 & -0.00517499111330214 & 0.0176248386783926 & -0.688907865313166 \tabularnewline
36 & 1.32302234837564 & -0.0542808312175853 & -0.00231785009534840 & 0.127192218812249 & 0.990379756576892 \tabularnewline
37 & -0.628357549594746 & -0.0829553485932472 & -0.00301144660272508 & -0.101866706160584 & -0.345612060624114 \tabularnewline
38 & 0.632048410440518 & -0.0344549765229294 & -0.00169063073931372 & 0.0413418884526878 & 0.49732768724465 \tabularnewline
39 & -2.16903155809288 & -0.186727500127953 & -0.00545517806095646 & -0.138095474337901 & -1.46759701218477 \tabularnewline
40 & 2.53779364144266 & -0.0110938868259967 & -0.00103837827161713 & 0.267429836906598 & 1.81368136259316 \tabularnewline
41 & -0.632933703679292 & -0.0430496195485981 & -0.00177450575854533 & -0.189162105198873 & -0.3182282809543 \tabularnewline
42 & -1.417491963422 & -0.139152857514633 & -0.00396819720523114 & -0.0217179566559275 & -0.996947869794296 \tabularnewline
43 & -0.455343045381255 & -0.167905679693075 & -0.00453148413644047 & 0.0516160745682807 & -0.268740639518525 \tabularnewline
44 & 0.812255211942954 & -0.103133724382716 & -0.00299140770428937 & -0.0573571650138387 & 0.770343197484806 \tabularnewline
45 & 0.627897309219833 & -0.0716115302370842 & -0.00224111201189978 & 0.202855581014120 & 0.392986893703714 \tabularnewline
46 & 0.650904313655623 & -0.0202645828473225 & -0.00110094053526868 & -0.118848634120266 & 0.624625821615639 \tabularnewline
47 & -1.29800419154382 & -0.0947240222227177 & -0.00262924259443798 & -0.0957231302269195 & -0.875016785424487 \tabularnewline
48 & 0.74391671726854 & -0.0588193515525736 & -0.00184283620128325 & 0.202286259675681 & 0.473798361432027 \tabularnewline
49 & -1.50461634127457 & -0.119992930518855 & -0.00302945105658321 & -0.208417934589222 & -0.920249067996743 \tabularnewline
50 & -1.42734677658523 & -0.202142045837650 & -0.00458081702250893 & 0.0415931699430216 & -1.00334328447356 \tabularnewline
51 & 0.263353807408564 & -0.172088230247541 & -0.00391476639534321 & -0.119825198802325 & 0.440015640864886 \tabularnewline
52 & -0.430830854870631 & -0.203879200209112 & -0.00444073250036638 & 0.229128885971704 & -0.361218271192151 \tabularnewline
53 & 0.379576092518008 & -0.169737289497339 & -0.00372623910754898 & -0.0955298814100973 & 0.510410469441461 \tabularnewline
54 & 1.70309353400146 & -0.0743187411439252 & -0.00192360660825874 & 0.0854053465408092 & 1.33848623748116 \tabularnewline
55 & -3.12314448117342 & -0.229786100389650 & -0.00466545933392777 & -0.219038676757315 & -2.11437705674836 \tabularnewline
56 & -1.32526207118689 & -0.289519204058890 & -0.0056315583573543 & -0.0573483874067931 & -0.77312700438829 \tabularnewline
57 & -0.60032490743804 & -0.320613976735117 & -0.0060705792938866 & 0.181570918253374 & -0.364317983495049 \tabularnewline
58 & 1.23607137604666 & -0.247719439131744 & -0.00473218748206865 & 0.0258235548943518 & 1.15092684830282 \tabularnewline
59 & 0.738007075905376 & -0.198020565092148 & -0.00382500312337423 & -0.088422186146746 & 0.808299372178697 \tabularnewline
60 & 0.899100896289585 & -0.160382719072617 & -0.00314528428496595 & 0.256487101264982 & 0.632971369509908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62594&T=1

[TABLE]
[ROW][C]Structural Time Series Model[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Level[/C][C]Slope[/C][C]Seasonal[/C][C]Stand. Residuals[/C][/ROW]
[ROW][C]1[/C][C]0.0314796223103059[/C][C]0.0314796223103059[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-3.00870920563557[/C][C]-0.337859984836871[/C][C]-0.123113202382392[/C][C]-0.153436759095376[/C][C]-2.05955749182822[/C][/ROW]
[ROW][C]3[/C][C]-2.07677512619799[/C][C]-0.709604203587071[/C][C]-0.185270956474344[/C][C]-0.185865735543112[/C][C]-0.995014943027091[/C][/ROW]
[ROW][C]4[/C][C]-1.2501039196554[/C][C]-0.928920685940089[/C][C]-0.192080061650079[/C][C]-0.18529031273494[/C][C]-0.116144616839291[/C][/ROW]
[ROW][C]5[/C][C]0.817975239137125[/C][C]-0.689068229444243[/C][C]-0.120091308625758[/C][C]-0.0910683381002602[/C][C]1.37353653543211[/C][/ROW]
[ROW][C]6[/C][C]0.0252076485413113[/C][C]-0.609751814053241[/C][C]-0.0916044909090781[/C][C]-0.091244966301525[/C][C]0.623809170681526[/C][/ROW]
[ROW][C]7[/C][C]0.554937772830776[/C][C]-0.425316061107351[/C][C]-0.0570994604272071[/C][C]-0.0447892531669484[/C][C]0.876900194796564[/C][/ROW]
[ROW][C]8[/C][C]0.230027371950115[/C][C]-0.328188351538081[/C][C]-0.0399631082053763[/C][C]-0.0375253125168191[/C][C]0.506663681018811[/C][/ROW]
[ROW][C]9[/C][C]2.35672227418686[/C][C]0.161182279398779[/C][C]0.0129702657088473[/C][C]0.0455911680914143[/C][C]1.8165914954529[/C][/ROW]
[ROW][C]10[/C][C]1.4135045517112[/C][C]0.401884775082881[/C][C]0.0336731957065978[/C][C]0.0338586903486665[/C][C]0.820736271441635[/C][/ROW]
[ROW][C]11[/C][C]2.73311719024401[/C][C]0.833407095198025[/C][C]0.06682728940731[/C][C]0.0902280373892896[/C][C]1.50930109389431[/C][/ROW]
[ROW][C]12[/C][C]1.31551925971717[/C][C]0.960867064477248[/C][C]0.0714913417051494[/C][C]0.0624532429412668[/C][C]0.24228216916783[/C][/ROW]
[ROW][C]13[/C][C]-2.7007627224408[/C][C]0.912510468505958[/C][C]0.0629307747282609[/C][C]-0.732463638908291[/C][C]-2.17933242704605[/C][/ROW]
[ROW][C]14[/C][C]-0.721411049152714[/C][C]0.668085691631248[/C][C]0.0424404046213962[/C][C]0.00909657936452334[/C][C]-1.17069055337286[/C][/ROW]
[ROW][C]15[/C][C]-0.149388576811997[/C][C]0.558253656218478[/C][C]0.0329233771192608[/C][C]0.0302213377362605[/C][C]-0.614818643709566[/C][/ROW]
[ROW][C]16[/C][C]-0.118199629770334[/C][C]0.476092980363506[/C][C]0.0261537269443059[/C][C]0.00813932661654078[/C][C]-0.498521227947173[/C][/ROW]
[ROW][C]17[/C][C]-0.676562489695275[/C][C]0.322020025646073[/C][C]0.0161411335186538[/C][C]0.0135541398248013[/C][C]-0.832626770711557[/C][/ROW]
[ROW][C]18[/C][C]1.79699928690761[/C][C]0.536684282562967[/C][C]0.0265897189606664[/C][C]0.0713173531641533[/C][C]0.973152758639384[/C][/ROW]
[ROW][C]19[/C][C]1.79845572032988[/C][C]0.723544336598844[/C][C]0.0346032357144269[/C][C]0.0562168571589747[/C][C]0.83006549095896[/C][/ROW]
[ROW][C]20[/C][C]0.245100010770855[/C][C]0.693826219618397[/C][C]0.0315403141575282[/C][C]-0.0166323523779194[/C][C]-0.350703795086036[/C][/ROW]
[ROW][C]21[/C][C]1.80710848932636[/C][C]0.84757694205539[/C][C]0.0370953327156857[/C][C]0.0948890622698778[/C][C]0.69932370728707[/C][/ROW]
[ROW][C]22[/C][C]-1.75934771184948[/C][C]0.580412785196599[/C][C]0.0238666592559258[/C][C]-0.0795039836124123[/C][C]-1.82235595792003[/C][/ROW]
[ROW][C]23[/C][C]-0.0186697168761931[/C][C]0.526893172336354[/C][C]0.0206422312510853[/C][C]0.0564684343821266[/C][C]-0.484013558286986[/C][/ROW]
[ROW][C]24[/C][C]0.189651523600062[/C][C]0.504624042992753[/C][C]0.0189257768272979[/C][C]0.0349609929985976[/C][C]-0.280503374220937[/C][/ROW]
[ROW][C]25[/C][C]-1.84149562719087[/C][C]0.38927014086954[/C][C]0.0137611737907398[/C][C]-0.254724170071894[/C][C]-1.52794292646426[/C][/ROW]
[ROW][C]26[/C][C]-1.07019530156943[/C][C]0.246067427505414[/C][C]0.00794769648870773[/C][C]-0.0183011781312519[/C][C]-1.0452326201295[/C][/ROW]
[ROW][C]27[/C][C]-0.507291477584104[/C][C]0.172584823601882[/C][C]0.00503947147469917[/C][C]0.0104305576599460[/C][C]-0.555639151846882[/C][/ROW]
[ROW][C]28[/C][C]0.866365633831705[/C][C]0.242548388680557[/C][C]0.00727823332311213[/C][C]0.0491730028938489[/C][C]0.461484830401469[/C][/ROW]
[ROW][C]29[/C][C]-1.76077926699189[/C][C]0.0644389081634554[/C][C]0.00109864286177167[/C][C]-0.114862540034759[/C][C]-1.37061423861296[/C][/ROW]
[ROW][C]30[/C][C]-0.580719393339347[/C][C]0.00122788551389760[/C][C]-0.00097586247730348[/C][C]0.0351870300457735[/C][C]-0.493580940212733[/C][/ROW]
[ROW][C]31[/C][C]-0.435702079860853[/C][C]-0.0414523212142378[/C][C]-0.00227912323514198[/C][C]0.0212395364642590[/C][C]-0.331709514079693[/C][/ROW]
[ROW][C]32[/C][C]-0.994868534845203[/C][C]-0.119441415399855[/C][C]-0.00457336477909578[/C][C]-0.093674439949029[/C][C]-0.623085277070507[/C][/ROW]
[ROW][C]33[/C][C]1.63136048315789[/C][C]0.0108240738219333[/C][C]-0.000607516132010945[/C][C]0.179733754595189[/C][C]1.14661034875885[/C][/ROW]
[ROW][C]34[/C][C]-1.1949403709466[/C][C]-0.0756029597806416[/C][C]-0.00305950234545563[/C][C]-0.171689005949062[/C][C]-0.75307597417658[/C][/ROW]
[ROW][C]35[/C][C]-1.00525975426991[/C][C]-0.154820057768571[/C][C]-0.00517499111330214[/C][C]0.0176248386783926[/C][C]-0.688907865313166[/C][/ROW]
[ROW][C]36[/C][C]1.32302234837564[/C][C]-0.0542808312175853[/C][C]-0.00231785009534840[/C][C]0.127192218812249[/C][C]0.990379756576892[/C][/ROW]
[ROW][C]37[/C][C]-0.628357549594746[/C][C]-0.0829553485932472[/C][C]-0.00301144660272508[/C][C]-0.101866706160584[/C][C]-0.345612060624114[/C][/ROW]
[ROW][C]38[/C][C]0.632048410440518[/C][C]-0.0344549765229294[/C][C]-0.00169063073931372[/C][C]0.0413418884526878[/C][C]0.49732768724465[/C][/ROW]
[ROW][C]39[/C][C]-2.16903155809288[/C][C]-0.186727500127953[/C][C]-0.00545517806095646[/C][C]-0.138095474337901[/C][C]-1.46759701218477[/C][/ROW]
[ROW][C]40[/C][C]2.53779364144266[/C][C]-0.0110938868259967[/C][C]-0.00103837827161713[/C][C]0.267429836906598[/C][C]1.81368136259316[/C][/ROW]
[ROW][C]41[/C][C]-0.632933703679292[/C][C]-0.0430496195485981[/C][C]-0.00177450575854533[/C][C]-0.189162105198873[/C][C]-0.3182282809543[/C][/ROW]
[ROW][C]42[/C][C]-1.417491963422[/C][C]-0.139152857514633[/C][C]-0.00396819720523114[/C][C]-0.0217179566559275[/C][C]-0.996947869794296[/C][/ROW]
[ROW][C]43[/C][C]-0.455343045381255[/C][C]-0.167905679693075[/C][C]-0.00453148413644047[/C][C]0.0516160745682807[/C][C]-0.268740639518525[/C][/ROW]
[ROW][C]44[/C][C]0.812255211942954[/C][C]-0.103133724382716[/C][C]-0.00299140770428937[/C][C]-0.0573571650138387[/C][C]0.770343197484806[/C][/ROW]
[ROW][C]45[/C][C]0.627897309219833[/C][C]-0.0716115302370842[/C][C]-0.00224111201189978[/C][C]0.202855581014120[/C][C]0.392986893703714[/C][/ROW]
[ROW][C]46[/C][C]0.650904313655623[/C][C]-0.0202645828473225[/C][C]-0.00110094053526868[/C][C]-0.118848634120266[/C][C]0.624625821615639[/C][/ROW]
[ROW][C]47[/C][C]-1.29800419154382[/C][C]-0.0947240222227177[/C][C]-0.00262924259443798[/C][C]-0.0957231302269195[/C][C]-0.875016785424487[/C][/ROW]
[ROW][C]48[/C][C]0.74391671726854[/C][C]-0.0588193515525736[/C][C]-0.00184283620128325[/C][C]0.202286259675681[/C][C]0.473798361432027[/C][/ROW]
[ROW][C]49[/C][C]-1.50461634127457[/C][C]-0.119992930518855[/C][C]-0.00302945105658321[/C][C]-0.208417934589222[/C][C]-0.920249067996743[/C][/ROW]
[ROW][C]50[/C][C]-1.42734677658523[/C][C]-0.202142045837650[/C][C]-0.00458081702250893[/C][C]0.0415931699430216[/C][C]-1.00334328447356[/C][/ROW]
[ROW][C]51[/C][C]0.263353807408564[/C][C]-0.172088230247541[/C][C]-0.00391476639534321[/C][C]-0.119825198802325[/C][C]0.440015640864886[/C][/ROW]
[ROW][C]52[/C][C]-0.430830854870631[/C][C]-0.203879200209112[/C][C]-0.00444073250036638[/C][C]0.229128885971704[/C][C]-0.361218271192151[/C][/ROW]
[ROW][C]53[/C][C]0.379576092518008[/C][C]-0.169737289497339[/C][C]-0.00372623910754898[/C][C]-0.0955298814100973[/C][C]0.510410469441461[/C][/ROW]
[ROW][C]54[/C][C]1.70309353400146[/C][C]-0.0743187411439252[/C][C]-0.00192360660825874[/C][C]0.0854053465408092[/C][C]1.33848623748116[/C][/ROW]
[ROW][C]55[/C][C]-3.12314448117342[/C][C]-0.229786100389650[/C][C]-0.00466545933392777[/C][C]-0.219038676757315[/C][C]-2.11437705674836[/C][/ROW]
[ROW][C]56[/C][C]-1.32526207118689[/C][C]-0.289519204058890[/C][C]-0.0056315583573543[/C][C]-0.0573483874067931[/C][C]-0.77312700438829[/C][/ROW]
[ROW][C]57[/C][C]-0.60032490743804[/C][C]-0.320613976735117[/C][C]-0.0060705792938866[/C][C]0.181570918253374[/C][C]-0.364317983495049[/C][/ROW]
[ROW][C]58[/C][C]1.23607137604666[/C][C]-0.247719439131744[/C][C]-0.00473218748206865[/C][C]0.0258235548943518[/C][C]1.15092684830282[/C][/ROW]
[ROW][C]59[/C][C]0.738007075905376[/C][C]-0.198020565092148[/C][C]-0.00382500312337423[/C][C]-0.088422186146746[/C][C]0.808299372178697[/C][/ROW]
[ROW][C]60[/C][C]0.899100896289585[/C][C]-0.160382719072617[/C][C]-0.00314528428496595[/C][C]0.256487101264982[/C][C]0.632971369509908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62594&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
10.03147962231030590.0314796223103059000
2-3.00870920563557-0.337859984836871-0.123113202382392-0.153436759095376-2.05955749182822
3-2.07677512619799-0.709604203587071-0.185270956474344-0.185865735543112-0.995014943027091
4-1.2501039196554-0.928920685940089-0.192080061650079-0.18529031273494-0.116144616839291
50.817975239137125-0.689068229444243-0.120091308625758-0.09106833810026021.37353653543211
60.0252076485413113-0.609751814053241-0.0916044909090781-0.0912449663015250.623809170681526
70.554937772830776-0.425316061107351-0.0570994604272071-0.04478925316694840.876900194796564
80.230027371950115-0.328188351538081-0.0399631082053763-0.03752531251681910.506663681018811
92.356722274186860.1611822793987790.01297026570884730.04559116809141431.8165914954529
101.41350455171120.4018847750828810.03367319570659780.03385869034866650.820736271441635
112.733117190244010.8334070951980250.066827289407310.09022803738928961.50930109389431
121.315519259717170.9608670644772480.07149134170514940.06245324294126680.24228216916783
13-2.70076272244080.9125104685059580.0629307747282609-0.732463638908291-2.17933242704605
14-0.7214110491527140.6680856916312480.04244040462139620.00909657936452334-1.17069055337286
15-0.1493885768119970.5582536562184780.03292337711926080.0302213377362605-0.614818643709566
16-0.1181996297703340.4760929803635060.02615372694430590.00813932661654078-0.498521227947173
17-0.6765624896952750.3220200256460730.01614113351865380.0135541398248013-0.832626770711557
181.796999286907610.5366842825629670.02658971896066640.07131735316415330.973152758639384
191.798455720329880.7235443365988440.03460323571442690.05621685715897470.83006549095896
200.2451000107708550.6938262196183970.0315403141575282-0.0166323523779194-0.350703795086036
211.807108489326360.847576942055390.03709533271568570.09488906226987780.69932370728707
22-1.759347711849480.5804127851965990.0238666592559258-0.0795039836124123-1.82235595792003
23-0.01866971687619310.5268931723363540.02064223125108530.0564684343821266-0.484013558286986
240.1896515236000620.5046240429927530.01892577682729790.0349609929985976-0.280503374220937
25-1.841495627190870.389270140869540.0137611737907398-0.254724170071894-1.52794292646426
26-1.070195301569430.2460674275054140.00794769648870773-0.0183011781312519-1.0452326201295
27-0.5072914775841040.1725848236018820.005039471474699170.0104305576599460-0.555639151846882
280.8663656338317050.2425483886805570.007278233323112130.04917300289384890.461484830401469
29-1.760779266991890.06443890816345540.00109864286177167-0.114862540034759-1.37061423861296
30-0.5807193933393470.00122788551389760-0.000975862477303480.0351870300457735-0.493580940212733
31-0.435702079860853-0.0414523212142378-0.002279123235141980.0212395364642590-0.331709514079693
32-0.994868534845203-0.119441415399855-0.00457336477909578-0.093674439949029-0.623085277070507
331.631360483157890.0108240738219333-0.0006075161320109450.1797337545951891.14661034875885
34-1.1949403709466-0.0756029597806416-0.00305950234545563-0.171689005949062-0.75307597417658
35-1.00525975426991-0.154820057768571-0.005174991113302140.0176248386783926-0.688907865313166
361.32302234837564-0.0542808312175853-0.002317850095348400.1271922188122490.990379756576892
37-0.628357549594746-0.0829553485932472-0.00301144660272508-0.101866706160584-0.345612060624114
380.632048410440518-0.0344549765229294-0.001690630739313720.04134188845268780.49732768724465
39-2.16903155809288-0.186727500127953-0.00545517806095646-0.138095474337901-1.46759701218477
402.53779364144266-0.0110938868259967-0.001038378271617130.2674298369065981.81368136259316
41-0.632933703679292-0.0430496195485981-0.00177450575854533-0.189162105198873-0.3182282809543
42-1.417491963422-0.139152857514633-0.00396819720523114-0.0217179566559275-0.996947869794296
43-0.455343045381255-0.167905679693075-0.004531484136440470.0516160745682807-0.268740639518525
440.812255211942954-0.103133724382716-0.00299140770428937-0.05735716501383870.770343197484806
450.627897309219833-0.0716115302370842-0.002241112011899780.2028555810141200.392986893703714
460.650904313655623-0.0202645828473225-0.00110094053526868-0.1188486341202660.624625821615639
47-1.29800419154382-0.0947240222227177-0.00262924259443798-0.0957231302269195-0.875016785424487
480.74391671726854-0.0588193515525736-0.001842836201283250.2022862596756810.473798361432027
49-1.50461634127457-0.119992930518855-0.00302945105658321-0.208417934589222-0.920249067996743
50-1.42734677658523-0.202142045837650-0.004580817022508930.0415931699430216-1.00334328447356
510.263353807408564-0.172088230247541-0.00391476639534321-0.1198251988023250.440015640864886
52-0.430830854870631-0.203879200209112-0.004440732500366380.229128885971704-0.361218271192151
530.379576092518008-0.169737289497339-0.00372623910754898-0.09552988141009730.510410469441461
541.70309353400146-0.0743187411439252-0.001923606608258740.08540534654080921.33848623748116
55-3.12314448117342-0.229786100389650-0.00466545933392777-0.219038676757315-2.11437705674836
56-1.32526207118689-0.289519204058890-0.0056315583573543-0.0573483874067931-0.77312700438829
57-0.60032490743804-0.320613976735117-0.00607057929388660.181570918253374-0.364317983495049
581.23607137604666-0.247719439131744-0.004732187482068650.02582355489435181.15092684830282
590.738007075905376-0.198020565092148-0.00382500312337423-0.0884221861467460.808299372178697
600.899100896289585-0.160382719072617-0.003145284284965950.2564871012649820.632971369509908



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')