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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 13 Nov 2013 08:11:18 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/13/t1384348631nc9e3tsx48r7uc4.htm/, Retrieved Mon, 29 Apr 2024 01:00:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=224713, Retrieved Mon, 29 Apr 2024 01:00:00 +0000
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Original text written by user:Howard Van den Branden
IsPrivate?No (this computation is public)
User-defined keywordsHoward Van den Branden
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [WS8: Structurele ...] [2013-11-13 13:11:18] [c48df00dfd28bb130a7db97d228aa375] [Current]
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Dataseries X:
6.02
5.62
4.87
4.24
4.02
3.74
3.45
3.34
3.21
3.12
3.04
2.97
2.93
2.95
2.92
2.9
2.95
2.91
2.89
2.84
2.82
2.78
2.86
2.87
2.94
3.04
3.12
3.19
3.27
3.34
3.4
3.55
3.64
3.76
3.78
3.77
3.81
3.81
3.82
3.96
3.86
3.84
3.68
3.56
3.48
3.4
3.42
3.2
3.11
3.1
2.99
3.1
3
3.05
3.1
3.2
3.1
3.3
3.13
3.14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224713&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224713&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224713&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
16.026.02000
25.625.63902249731905-0.379507827721571-0.00262397924945988-3.29375650089534
34.874.88665151662148-0.721980535611364-0.00316230034074599-2.94972596212885
44.244.23628146059303-0.6560056576183150.001198648966246590.558382613560948
54.024.00168400099549-0.267677243633660.00349210619831823.28607028194219
63.743.741300966092-0.260955193603584-0.001557566822742160.0568819271593959
73.453.45183941146835-0.287225200921602-0.000836609588358994-0.22229627409808
83.343.33285861234874-0.1321802917416810.001222876573448941.31198691914182
93.213.21052623983837-0.123104982756925-0.0008726705387162870.0767950828164
103.123.11912625781161-0.0938873665881007-0.0002415784302927190.24723888268311
113.043.03995080783907-0.0803296587224081-0.000468344623629070.114725052347826
122.972.97009784905644-0.0706748978841393-0.0004663991040942060.0816983927924031
132.932.92304835914776-0.04901693790899240.006124894100545450.188642444879728
142.952.944395149749730.01116843574661520.003520302399102170.504191455884675
152.922.92250484515999-0.0190841110006302-0.00138784176723397-0.253212731050104
162.92.90403064573446-0.0185282805800915-0.004051442576596070.00469659190927528
172.952.943424871088660.03431929163113360.004592007721547420.447199628140867
182.912.91311100190711-0.0246573472743281-0.000897925598674195-0.499057421336289
192.892.89217662442133-0.0212603453813439-0.002304096426087020.0287453619579407
202.842.83986960465007-0.0495884280861040.0011934026036458-0.239711666774681
212.822.81910336133007-0.0232900344419605-9.02048024523563e-050.222536480959855
222.782.78086952235722-0.0369253753201484-0.000357858143215278-0.115381981869547
232.862.854068141108220.063558937231920.002161198647644140.850297475450988
242.872.872830286510120.022692047047269-0.00129678542457233-0.34582315538964
252.942.937629927564760.06100818095412460.0009302882036622780.330643733463874
263.043.033996309685430.09161983545980550.004928298288103510.257195089822357
273.123.120999901509280.087429960996663-0.000845943829666833-0.0352388143984156
283.193.196954323661580.0770509633570793-0.00657110126898891-0.0876757229833538
293.273.264156146350580.06813348624327680.00617422155918121-0.0754605094045429
303.343.340792124791250.0758330633416735-0.001077368038782360.0651532317533453
313.43.402049944267980.0626348541238268-0.00156098972149198-0.111682978200472
323.553.544930446805770.1352978165955990.002377605191124830.614872515230243
333.643.64091206740430.09969671401588280.000406848302126757-0.301255823916097
343.763.762312889417430.119350304225259-0.003040996755723430.166308316937793
353.783.781939863651680.02904529969412210.00140567578105217-0.764163309572634
363.773.77358552753595-0.00480654598522371-0.00233149997967898-0.286491175690176
373.813.808680298109850.0312919607348658-2.08937508987069e-050.30952748934077
383.813.80709498682040.002611127358329390.00392133160666568-0.241439875877997
393.823.820126920104890.0120106605332728-0.0004708630817869650.079300523017848
403.963.958860789421830.126011918320541-0.003032123227162970.962836035853441
413.863.86866803726534-0.0686546442320335-0.00151980625590437-1.64728168088996
423.843.83626626440859-0.03600453716023930.002534803785015720.276281706149978
433.683.69180805405583-0.133675621292478-0.00822145565247998-0.826490507704719
443.563.55580014139546-0.1357759738892530.00427698612353665-0.0177731406195365
453.483.47870714295177-0.0829287162198532-0.000647759196026850.447192452887783
463.43.40057989451172-0.0786045829266258-0.0007386819187366640.0365907726519531
473.423.411697400882130.002198967562354020.005335382711584470.683762570798741
483.23.216999195449-0.175010066102297-0.0104926034777029-1.50000452274026
493.113.10124300976071-0.1216415687060750.006791798739026640.455625077968933
503.13.08820904529097-0.02643006660045830.008398550918115480.802578219613786
512.993.00339051051648-0.0788545844104254-0.011478642042658-0.443130835437338
523.13.083295414517160.06344302896903020.01152802654220961.20174374947203
5333.01411844655346-0.0554949030465199-0.00977674429032932-1.00644501444218
543.053.037378818472380.01516058644847280.0100418170950520.597878061879382
553.13.10374545106320.0610986282268806-0.005422500432745480.388726344729772
563.23.195586366757930.08867713069140750.003406828415253020.233368724871076
573.13.11070606681847-0.0670196739276564-0.00502206309408251-1.3175032536383
583.33.291281612467240.1551058110488530.0006092834335342661.87962802118913
593.133.1358083980179-0.1235161448616740.0043632345887584-2.35769874637998
603.143.14188588388646-0.00734429553850341-0.006126465511692120.983543682872534

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 6.02 & 6.02 & 0 & 0 & 0 \tabularnewline
2 & 5.62 & 5.63902249731905 & -0.379507827721571 & -0.00262397924945988 & -3.29375650089534 \tabularnewline
3 & 4.87 & 4.88665151662148 & -0.721980535611364 & -0.00316230034074599 & -2.94972596212885 \tabularnewline
4 & 4.24 & 4.23628146059303 & -0.656005657618315 & 0.00119864896624659 & 0.558382613560948 \tabularnewline
5 & 4.02 & 4.00168400099549 & -0.26767724363366 & 0.0034921061983182 & 3.28607028194219 \tabularnewline
6 & 3.74 & 3.741300966092 & -0.260955193603584 & -0.00155756682274216 & 0.0568819271593959 \tabularnewline
7 & 3.45 & 3.45183941146835 & -0.287225200921602 & -0.000836609588358994 & -0.22229627409808 \tabularnewline
8 & 3.34 & 3.33285861234874 & -0.132180291741681 & 0.00122287657344894 & 1.31198691914182 \tabularnewline
9 & 3.21 & 3.21052623983837 & -0.123104982756925 & -0.000872670538716287 & 0.0767950828164 \tabularnewline
10 & 3.12 & 3.11912625781161 & -0.0938873665881007 & -0.000241578430292719 & 0.24723888268311 \tabularnewline
11 & 3.04 & 3.03995080783907 & -0.0803296587224081 & -0.00046834462362907 & 0.114725052347826 \tabularnewline
12 & 2.97 & 2.97009784905644 & -0.0706748978841393 & -0.000466399104094206 & 0.0816983927924031 \tabularnewline
13 & 2.93 & 2.92304835914776 & -0.0490169379089924 & 0.00612489410054545 & 0.188642444879728 \tabularnewline
14 & 2.95 & 2.94439514974973 & 0.0111684357466152 & 0.00352030239910217 & 0.504191455884675 \tabularnewline
15 & 2.92 & 2.92250484515999 & -0.0190841110006302 & -0.00138784176723397 & -0.253212731050104 \tabularnewline
16 & 2.9 & 2.90403064573446 & -0.0185282805800915 & -0.00405144257659607 & 0.00469659190927528 \tabularnewline
17 & 2.95 & 2.94342487108866 & 0.0343192916311336 & 0.00459200772154742 & 0.447199628140867 \tabularnewline
18 & 2.91 & 2.91311100190711 & -0.0246573472743281 & -0.000897925598674195 & -0.499057421336289 \tabularnewline
19 & 2.89 & 2.89217662442133 & -0.0212603453813439 & -0.00230409642608702 & 0.0287453619579407 \tabularnewline
20 & 2.84 & 2.83986960465007 & -0.049588428086104 & 0.0011934026036458 & -0.239711666774681 \tabularnewline
21 & 2.82 & 2.81910336133007 & -0.0232900344419605 & -9.02048024523563e-05 & 0.222536480959855 \tabularnewline
22 & 2.78 & 2.78086952235722 & -0.0369253753201484 & -0.000357858143215278 & -0.115381981869547 \tabularnewline
23 & 2.86 & 2.85406814110822 & 0.06355893723192 & 0.00216119864764414 & 0.850297475450988 \tabularnewline
24 & 2.87 & 2.87283028651012 & 0.022692047047269 & -0.00129678542457233 & -0.34582315538964 \tabularnewline
25 & 2.94 & 2.93762992756476 & 0.0610081809541246 & 0.000930288203662278 & 0.330643733463874 \tabularnewline
26 & 3.04 & 3.03399630968543 & 0.0916198354598055 & 0.00492829828810351 & 0.257195089822357 \tabularnewline
27 & 3.12 & 3.12099990150928 & 0.087429960996663 & -0.000845943829666833 & -0.0352388143984156 \tabularnewline
28 & 3.19 & 3.19695432366158 & 0.0770509633570793 & -0.00657110126898891 & -0.0876757229833538 \tabularnewline
29 & 3.27 & 3.26415614635058 & 0.0681334862432768 & 0.00617422155918121 & -0.0754605094045429 \tabularnewline
30 & 3.34 & 3.34079212479125 & 0.0758330633416735 & -0.00107736803878236 & 0.0651532317533453 \tabularnewline
31 & 3.4 & 3.40204994426798 & 0.0626348541238268 & -0.00156098972149198 & -0.111682978200472 \tabularnewline
32 & 3.55 & 3.54493044680577 & 0.135297816595599 & 0.00237760519112483 & 0.614872515230243 \tabularnewline
33 & 3.64 & 3.6409120674043 & 0.0996967140158828 & 0.000406848302126757 & -0.301255823916097 \tabularnewline
34 & 3.76 & 3.76231288941743 & 0.119350304225259 & -0.00304099675572343 & 0.166308316937793 \tabularnewline
35 & 3.78 & 3.78193986365168 & 0.0290452996941221 & 0.00140567578105217 & -0.764163309572634 \tabularnewline
36 & 3.77 & 3.77358552753595 & -0.00480654598522371 & -0.00233149997967898 & -0.286491175690176 \tabularnewline
37 & 3.81 & 3.80868029810985 & 0.0312919607348658 & -2.08937508987069e-05 & 0.30952748934077 \tabularnewline
38 & 3.81 & 3.8070949868204 & 0.00261112735832939 & 0.00392133160666568 & -0.241439875877997 \tabularnewline
39 & 3.82 & 3.82012692010489 & 0.0120106605332728 & -0.000470863081786965 & 0.079300523017848 \tabularnewline
40 & 3.96 & 3.95886078942183 & 0.126011918320541 & -0.00303212322716297 & 0.962836035853441 \tabularnewline
41 & 3.86 & 3.86866803726534 & -0.0686546442320335 & -0.00151980625590437 & -1.64728168088996 \tabularnewline
42 & 3.84 & 3.83626626440859 & -0.0360045371602393 & 0.00253480378501572 & 0.276281706149978 \tabularnewline
43 & 3.68 & 3.69180805405583 & -0.133675621292478 & -0.00822145565247998 & -0.826490507704719 \tabularnewline
44 & 3.56 & 3.55580014139546 & -0.135775973889253 & 0.00427698612353665 & -0.0177731406195365 \tabularnewline
45 & 3.48 & 3.47870714295177 & -0.0829287162198532 & -0.00064775919602685 & 0.447192452887783 \tabularnewline
46 & 3.4 & 3.40057989451172 & -0.0786045829266258 & -0.000738681918736664 & 0.0365907726519531 \tabularnewline
47 & 3.42 & 3.41169740088213 & 0.00219896756235402 & 0.00533538271158447 & 0.683762570798741 \tabularnewline
48 & 3.2 & 3.216999195449 & -0.175010066102297 & -0.0104926034777029 & -1.50000452274026 \tabularnewline
49 & 3.11 & 3.10124300976071 & -0.121641568706075 & 0.00679179873902664 & 0.455625077968933 \tabularnewline
50 & 3.1 & 3.08820904529097 & -0.0264300666004583 & 0.00839855091811548 & 0.802578219613786 \tabularnewline
51 & 2.99 & 3.00339051051648 & -0.0788545844104254 & -0.011478642042658 & -0.443130835437338 \tabularnewline
52 & 3.1 & 3.08329541451716 & 0.0634430289690302 & 0.0115280265422096 & 1.20174374947203 \tabularnewline
53 & 3 & 3.01411844655346 & -0.0554949030465199 & -0.00977674429032932 & -1.00644501444218 \tabularnewline
54 & 3.05 & 3.03737881847238 & 0.0151605864484728 & 0.010041817095052 & 0.597878061879382 \tabularnewline
55 & 3.1 & 3.1037454510632 & 0.0610986282268806 & -0.00542250043274548 & 0.388726344729772 \tabularnewline
56 & 3.2 & 3.19558636675793 & 0.0886771306914075 & 0.00340682841525302 & 0.233368724871076 \tabularnewline
57 & 3.1 & 3.11070606681847 & -0.0670196739276564 & -0.00502206309408251 & -1.3175032536383 \tabularnewline
58 & 3.3 & 3.29128161246724 & 0.155105811048853 & 0.000609283433534266 & 1.87962802118913 \tabularnewline
59 & 3.13 & 3.1358083980179 & -0.123516144861674 & 0.0043632345887584 & -2.35769874637998 \tabularnewline
60 & 3.14 & 3.14188588388646 & -0.00734429553850341 & -0.00612646551169212 & 0.983543682872534 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224713&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]6.02[/C][C]6.02[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]5.62[/C][C]5.63902249731905[/C][C]-0.379507827721571[/C][C]-0.00262397924945988[/C][C]-3.29375650089534[/C][/ROW]
[ROW][C]3[/C][C]4.87[/C][C]4.88665151662148[/C][C]-0.721980535611364[/C][C]-0.00316230034074599[/C][C]-2.94972596212885[/C][/ROW]
[ROW][C]4[/C][C]4.24[/C][C]4.23628146059303[/C][C]-0.656005657618315[/C][C]0.00119864896624659[/C][C]0.558382613560948[/C][/ROW]
[ROW][C]5[/C][C]4.02[/C][C]4.00168400099549[/C][C]-0.26767724363366[/C][C]0.0034921061983182[/C][C]3.28607028194219[/C][/ROW]
[ROW][C]6[/C][C]3.74[/C][C]3.741300966092[/C][C]-0.260955193603584[/C][C]-0.00155756682274216[/C][C]0.0568819271593959[/C][/ROW]
[ROW][C]7[/C][C]3.45[/C][C]3.45183941146835[/C][C]-0.287225200921602[/C][C]-0.000836609588358994[/C][C]-0.22229627409808[/C][/ROW]
[ROW][C]8[/C][C]3.34[/C][C]3.33285861234874[/C][C]-0.132180291741681[/C][C]0.00122287657344894[/C][C]1.31198691914182[/C][/ROW]
[ROW][C]9[/C][C]3.21[/C][C]3.21052623983837[/C][C]-0.123104982756925[/C][C]-0.000872670538716287[/C][C]0.0767950828164[/C][/ROW]
[ROW][C]10[/C][C]3.12[/C][C]3.11912625781161[/C][C]-0.0938873665881007[/C][C]-0.000241578430292719[/C][C]0.24723888268311[/C][/ROW]
[ROW][C]11[/C][C]3.04[/C][C]3.03995080783907[/C][C]-0.0803296587224081[/C][C]-0.00046834462362907[/C][C]0.114725052347826[/C][/ROW]
[ROW][C]12[/C][C]2.97[/C][C]2.97009784905644[/C][C]-0.0706748978841393[/C][C]-0.000466399104094206[/C][C]0.0816983927924031[/C][/ROW]
[ROW][C]13[/C][C]2.93[/C][C]2.92304835914776[/C][C]-0.0490169379089924[/C][C]0.00612489410054545[/C][C]0.188642444879728[/C][/ROW]
[ROW][C]14[/C][C]2.95[/C][C]2.94439514974973[/C][C]0.0111684357466152[/C][C]0.00352030239910217[/C][C]0.504191455884675[/C][/ROW]
[ROW][C]15[/C][C]2.92[/C][C]2.92250484515999[/C][C]-0.0190841110006302[/C][C]-0.00138784176723397[/C][C]-0.253212731050104[/C][/ROW]
[ROW][C]16[/C][C]2.9[/C][C]2.90403064573446[/C][C]-0.0185282805800915[/C][C]-0.00405144257659607[/C][C]0.00469659190927528[/C][/ROW]
[ROW][C]17[/C][C]2.95[/C][C]2.94342487108866[/C][C]0.0343192916311336[/C][C]0.00459200772154742[/C][C]0.447199628140867[/C][/ROW]
[ROW][C]18[/C][C]2.91[/C][C]2.91311100190711[/C][C]-0.0246573472743281[/C][C]-0.000897925598674195[/C][C]-0.499057421336289[/C][/ROW]
[ROW][C]19[/C][C]2.89[/C][C]2.89217662442133[/C][C]-0.0212603453813439[/C][C]-0.00230409642608702[/C][C]0.0287453619579407[/C][/ROW]
[ROW][C]20[/C][C]2.84[/C][C]2.83986960465007[/C][C]-0.049588428086104[/C][C]0.0011934026036458[/C][C]-0.239711666774681[/C][/ROW]
[ROW][C]21[/C][C]2.82[/C][C]2.81910336133007[/C][C]-0.0232900344419605[/C][C]-9.02048024523563e-05[/C][C]0.222536480959855[/C][/ROW]
[ROW][C]22[/C][C]2.78[/C][C]2.78086952235722[/C][C]-0.0369253753201484[/C][C]-0.000357858143215278[/C][C]-0.115381981869547[/C][/ROW]
[ROW][C]23[/C][C]2.86[/C][C]2.85406814110822[/C][C]0.06355893723192[/C][C]0.00216119864764414[/C][C]0.850297475450988[/C][/ROW]
[ROW][C]24[/C][C]2.87[/C][C]2.87283028651012[/C][C]0.022692047047269[/C][C]-0.00129678542457233[/C][C]-0.34582315538964[/C][/ROW]
[ROW][C]25[/C][C]2.94[/C][C]2.93762992756476[/C][C]0.0610081809541246[/C][C]0.000930288203662278[/C][C]0.330643733463874[/C][/ROW]
[ROW][C]26[/C][C]3.04[/C][C]3.03399630968543[/C][C]0.0916198354598055[/C][C]0.00492829828810351[/C][C]0.257195089822357[/C][/ROW]
[ROW][C]27[/C][C]3.12[/C][C]3.12099990150928[/C][C]0.087429960996663[/C][C]-0.000845943829666833[/C][C]-0.0352388143984156[/C][/ROW]
[ROW][C]28[/C][C]3.19[/C][C]3.19695432366158[/C][C]0.0770509633570793[/C][C]-0.00657110126898891[/C][C]-0.0876757229833538[/C][/ROW]
[ROW][C]29[/C][C]3.27[/C][C]3.26415614635058[/C][C]0.0681334862432768[/C][C]0.00617422155918121[/C][C]-0.0754605094045429[/C][/ROW]
[ROW][C]30[/C][C]3.34[/C][C]3.34079212479125[/C][C]0.0758330633416735[/C][C]-0.00107736803878236[/C][C]0.0651532317533453[/C][/ROW]
[ROW][C]31[/C][C]3.4[/C][C]3.40204994426798[/C][C]0.0626348541238268[/C][C]-0.00156098972149198[/C][C]-0.111682978200472[/C][/ROW]
[ROW][C]32[/C][C]3.55[/C][C]3.54493044680577[/C][C]0.135297816595599[/C][C]0.00237760519112483[/C][C]0.614872515230243[/C][/ROW]
[ROW][C]33[/C][C]3.64[/C][C]3.6409120674043[/C][C]0.0996967140158828[/C][C]0.000406848302126757[/C][C]-0.301255823916097[/C][/ROW]
[ROW][C]34[/C][C]3.76[/C][C]3.76231288941743[/C][C]0.119350304225259[/C][C]-0.00304099675572343[/C][C]0.166308316937793[/C][/ROW]
[ROW][C]35[/C][C]3.78[/C][C]3.78193986365168[/C][C]0.0290452996941221[/C][C]0.00140567578105217[/C][C]-0.764163309572634[/C][/ROW]
[ROW][C]36[/C][C]3.77[/C][C]3.77358552753595[/C][C]-0.00480654598522371[/C][C]-0.00233149997967898[/C][C]-0.286491175690176[/C][/ROW]
[ROW][C]37[/C][C]3.81[/C][C]3.80868029810985[/C][C]0.0312919607348658[/C][C]-2.08937508987069e-05[/C][C]0.30952748934077[/C][/ROW]
[ROW][C]38[/C][C]3.81[/C][C]3.8070949868204[/C][C]0.00261112735832939[/C][C]0.00392133160666568[/C][C]-0.241439875877997[/C][/ROW]
[ROW][C]39[/C][C]3.82[/C][C]3.82012692010489[/C][C]0.0120106605332728[/C][C]-0.000470863081786965[/C][C]0.079300523017848[/C][/ROW]
[ROW][C]40[/C][C]3.96[/C][C]3.95886078942183[/C][C]0.126011918320541[/C][C]-0.00303212322716297[/C][C]0.962836035853441[/C][/ROW]
[ROW][C]41[/C][C]3.86[/C][C]3.86866803726534[/C][C]-0.0686546442320335[/C][C]-0.00151980625590437[/C][C]-1.64728168088996[/C][/ROW]
[ROW][C]42[/C][C]3.84[/C][C]3.83626626440859[/C][C]-0.0360045371602393[/C][C]0.00253480378501572[/C][C]0.276281706149978[/C][/ROW]
[ROW][C]43[/C][C]3.68[/C][C]3.69180805405583[/C][C]-0.133675621292478[/C][C]-0.00822145565247998[/C][C]-0.826490507704719[/C][/ROW]
[ROW][C]44[/C][C]3.56[/C][C]3.55580014139546[/C][C]-0.135775973889253[/C][C]0.00427698612353665[/C][C]-0.0177731406195365[/C][/ROW]
[ROW][C]45[/C][C]3.48[/C][C]3.47870714295177[/C][C]-0.0829287162198532[/C][C]-0.00064775919602685[/C][C]0.447192452887783[/C][/ROW]
[ROW][C]46[/C][C]3.4[/C][C]3.40057989451172[/C][C]-0.0786045829266258[/C][C]-0.000738681918736664[/C][C]0.0365907726519531[/C][/ROW]
[ROW][C]47[/C][C]3.42[/C][C]3.41169740088213[/C][C]0.00219896756235402[/C][C]0.00533538271158447[/C][C]0.683762570798741[/C][/ROW]
[ROW][C]48[/C][C]3.2[/C][C]3.216999195449[/C][C]-0.175010066102297[/C][C]-0.0104926034777029[/C][C]-1.50000452274026[/C][/ROW]
[ROW][C]49[/C][C]3.11[/C][C]3.10124300976071[/C][C]-0.121641568706075[/C][C]0.00679179873902664[/C][C]0.455625077968933[/C][/ROW]
[ROW][C]50[/C][C]3.1[/C][C]3.08820904529097[/C][C]-0.0264300666004583[/C][C]0.00839855091811548[/C][C]0.802578219613786[/C][/ROW]
[ROW][C]51[/C][C]2.99[/C][C]3.00339051051648[/C][C]-0.0788545844104254[/C][C]-0.011478642042658[/C][C]-0.443130835437338[/C][/ROW]
[ROW][C]52[/C][C]3.1[/C][C]3.08329541451716[/C][C]0.0634430289690302[/C][C]0.0115280265422096[/C][C]1.20174374947203[/C][/ROW]
[ROW][C]53[/C][C]3[/C][C]3.01411844655346[/C][C]-0.0554949030465199[/C][C]-0.00977674429032932[/C][C]-1.00644501444218[/C][/ROW]
[ROW][C]54[/C][C]3.05[/C][C]3.03737881847238[/C][C]0.0151605864484728[/C][C]0.010041817095052[/C][C]0.597878061879382[/C][/ROW]
[ROW][C]55[/C][C]3.1[/C][C]3.1037454510632[/C][C]0.0610986282268806[/C][C]-0.00542250043274548[/C][C]0.388726344729772[/C][/ROW]
[ROW][C]56[/C][C]3.2[/C][C]3.19558636675793[/C][C]0.0886771306914075[/C][C]0.00340682841525302[/C][C]0.233368724871076[/C][/ROW]
[ROW][C]57[/C][C]3.1[/C][C]3.11070606681847[/C][C]-0.0670196739276564[/C][C]-0.00502206309408251[/C][C]-1.3175032536383[/C][/ROW]
[ROW][C]58[/C][C]3.3[/C][C]3.29128161246724[/C][C]0.155105811048853[/C][C]0.000609283433534266[/C][C]1.87962802118913[/C][/ROW]
[ROW][C]59[/C][C]3.13[/C][C]3.1358083980179[/C][C]-0.123516144861674[/C][C]0.0043632345887584[/C][C]-2.35769874637998[/C][/ROW]
[ROW][C]60[/C][C]3.14[/C][C]3.14188588388646[/C][C]-0.00734429553850341[/C][C]-0.00612646551169212[/C][C]0.983543682872534[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224713&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224713&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
16.026.02000
25.625.63902249731905-0.379507827721571-0.00262397924945988-3.29375650089534
34.874.88665151662148-0.721980535611364-0.00316230034074599-2.94972596212885
44.244.23628146059303-0.6560056576183150.001198648966246590.558382613560948
54.024.00168400099549-0.267677243633660.00349210619831823.28607028194219
63.743.741300966092-0.260955193603584-0.001557566822742160.0568819271593959
73.453.45183941146835-0.287225200921602-0.000836609588358994-0.22229627409808
83.343.33285861234874-0.1321802917416810.001222876573448941.31198691914182
93.213.21052623983837-0.123104982756925-0.0008726705387162870.0767950828164
103.123.11912625781161-0.0938873665881007-0.0002415784302927190.24723888268311
113.043.03995080783907-0.0803296587224081-0.000468344623629070.114725052347826
122.972.97009784905644-0.0706748978841393-0.0004663991040942060.0816983927924031
132.932.92304835914776-0.04901693790899240.006124894100545450.188642444879728
142.952.944395149749730.01116843574661520.003520302399102170.504191455884675
152.922.92250484515999-0.0190841110006302-0.00138784176723397-0.253212731050104
162.92.90403064573446-0.0185282805800915-0.004051442576596070.00469659190927528
172.952.943424871088660.03431929163113360.004592007721547420.447199628140867
182.912.91311100190711-0.0246573472743281-0.000897925598674195-0.499057421336289
192.892.89217662442133-0.0212603453813439-0.002304096426087020.0287453619579407
202.842.83986960465007-0.0495884280861040.0011934026036458-0.239711666774681
212.822.81910336133007-0.0232900344419605-9.02048024523563e-050.222536480959855
222.782.78086952235722-0.0369253753201484-0.000357858143215278-0.115381981869547
232.862.854068141108220.063558937231920.002161198647644140.850297475450988
242.872.872830286510120.022692047047269-0.00129678542457233-0.34582315538964
252.942.937629927564760.06100818095412460.0009302882036622780.330643733463874
263.043.033996309685430.09161983545980550.004928298288103510.257195089822357
273.123.120999901509280.087429960996663-0.000845943829666833-0.0352388143984156
283.193.196954323661580.0770509633570793-0.00657110126898891-0.0876757229833538
293.273.264156146350580.06813348624327680.00617422155918121-0.0754605094045429
303.343.340792124791250.0758330633416735-0.001077368038782360.0651532317533453
313.43.402049944267980.0626348541238268-0.00156098972149198-0.111682978200472
323.553.544930446805770.1352978165955990.002377605191124830.614872515230243
333.643.64091206740430.09969671401588280.000406848302126757-0.301255823916097
343.763.762312889417430.119350304225259-0.003040996755723430.166308316937793
353.783.781939863651680.02904529969412210.00140567578105217-0.764163309572634
363.773.77358552753595-0.00480654598522371-0.00233149997967898-0.286491175690176
373.813.808680298109850.0312919607348658-2.08937508987069e-050.30952748934077
383.813.80709498682040.002611127358329390.00392133160666568-0.241439875877997
393.823.820126920104890.0120106605332728-0.0004708630817869650.079300523017848
403.963.958860789421830.126011918320541-0.003032123227162970.962836035853441
413.863.86866803726534-0.0686546442320335-0.00151980625590437-1.64728168088996
423.843.83626626440859-0.03600453716023930.002534803785015720.276281706149978
433.683.69180805405583-0.133675621292478-0.00822145565247998-0.826490507704719
443.563.55580014139546-0.1357759738892530.00427698612353665-0.0177731406195365
453.483.47870714295177-0.0829287162198532-0.000647759196026850.447192452887783
463.43.40057989451172-0.0786045829266258-0.0007386819187366640.0365907726519531
473.423.411697400882130.002198967562354020.005335382711584470.683762570798741
483.23.216999195449-0.175010066102297-0.0104926034777029-1.50000452274026
493.113.10124300976071-0.1216415687060750.006791798739026640.455625077968933
503.13.08820904529097-0.02643006660045830.008398550918115480.802578219613786
512.993.00339051051648-0.0788545844104254-0.011478642042658-0.443130835437338
523.13.083295414517160.06344302896903020.01152802654220961.20174374947203
5333.01411844655346-0.0554949030465199-0.00977674429032932-1.00644501444218
543.053.037378818472380.01516058644847280.0100418170950520.597878061879382
553.13.10374545106320.0610986282268806-0.005422500432745480.388726344729772
563.23.195586366757930.08867713069140750.003406828415253020.233368724871076
573.13.11070606681847-0.0670196739276564-0.00502206309408251-1.3175032536383
583.33.291281612467240.1551058110488530.0006092834335342661.87962802118913
593.133.1358083980179-0.1235161448616740.0043632345887584-2.35769874637998
603.143.14188588388646-0.00734429553850341-0.006126465511692120.983543682872534



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')