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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 computationTue, 28 Dec 2010 18:57:19 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t1293562536jqyxhb0d4165rla.htm/, Retrieved Sun, 05 May 2024 07:24:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116485, Retrieved Sun, 05 May 2024 07:24:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [Paper] [2010-12-28 18:57:19] [d5e0edb7e0239841e94676417b2a1e2e] [Current]
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Dataseries X:
9782
9938
10111
10259
10419
10622
11173
11542
11538
11837
12060
12423
12791
12891
13098
13418
13614
13653
13980
14087
14332
14232
14226
14186
14310
14152
14127
14163
13964
13811
14440
14724
14790
14961
15117
15452
16080
16284
16524
16782
16663
16678
17448
17745
17789
17864
18079
18483
19037
19344
19590
19862
20207
20593
21253
21507
21528
21818
22205
22621
23006
23178
23358
23519
23725
23789
24472
24773
24477
24669
24827





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=116485&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=116485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116485&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
197829782000
299389918.9360577939623.554930142180419.06394220604170.857758874105988
31011110077.976054696771.418823068492433.02394530324941.03391890128237
41025910241.9844164491110.15793772200017.01558355091920.659212746247292
51041910406.5785907746133.35364531619612.42140922538770.382204322318611
61062210604.5079824549161.00472137439817.49201754512720.455522951897839
71117311096.8818781177303.27422355850476.118121882352.34218720351826
81154211530.2526931791359.18858180153511.74730682092810.920043660299011
91153811604.6584682778236.747127652393-66.658468277833-2.01433451811386
101183711815.6822868926225.68580365421621.3177131074291-0.181964701118438
111206012049.7198196101229.27743902457410.28018038991350.0590835175226261
121242312391.7719120008277.77808663885931.22808799916540.797847831202871
131279112802.4347566347333.40431774105-11.43475663474291.0182222328493
141289112943.2312624623254.498123428254-52.2312624623293-1.21970181446696
151309813101.9885692694215.731152229803-3.98856926944557-0.643610112578598
161341813383.942655519243.42799201410934.05734448100740.457873754561834
171361413617.8511518545239.435723160518-3.85115185447749-0.065140366893704
181365313747.6680774390193.580505235018-94.668077439033-0.751501867438058
191398013940.3792362616193.21676459101739.6207637384379-0.00597939200671672
201408714044.9557571788156.1025472750942.0442428211844-0.610490613766667
211433214348.5105881860217.867215995426-16.51058818603651.01604471599163
221423214297.3195042576105.142820750440-65.319504257613-1.85440458507655
231422614268.609910528549.1019139696661-42.6099105285166-0.921850048890431
241418614207.84399279643.25978471960693-21.8439927964456-0.756502855574918
251431014242.020842642816.168526824347967.97915735719910.218397238532523
261415214196.3609551045-9.37915394003732-44.3609551045374-0.412626619824681
271412714156.5532715461-21.7715066267317-29.5532715461194-0.203793908346721
281416314127.5825656126-24.747002079052435.4174343874204-0.0493257421586975
291396413975.5052227228-77.6776467929766-11.5052227228487-0.867776581287822
301381113898.0667463759-77.5784066346216-87.0667463758570.00162616033679722
311444014264.5582527841106.584526260075175.4417472158853.0259345771543
321472414668.8617725076230.14040193718455.13822749242462.03219630061857
331479014793.2669073079186.232847218396-3.26690730789285-0.722291908257976
341496114990.6077211864190.845302206966-29.60772118641290.075875607105275
351511715147.5312625351176.778770566811-30.5312625351364-0.231450508482369
361545215446.6659404892227.4255614090095.334059510765220.836979558777251
371608015925.3483768262331.712867723907154.6516231738421.73282326886379
381628416314.3959474695355.372979925942-30.39594746949580.386059568765797
391652416570.7843181975314.913810732776-46.7843181974516-0.664351702594299
401678216734.5658830091252.73892915418347.4341169909307-1.02894724481577
411666316737.2689014171149.313078418830-74.2689014171212-1.70067336348240
421667816881.1309339626147.059879220053-203.130933962555-0.0369512761697523
431744817279.9468243233251.030098652220168.0531756766881.70776145768666
441774517639.5211453030295.873755238496105.4788546969610.73744008709896
451778917823.2997972484249.539611398962-34.2997972484466-0.76216746296519
461786417917.8199671701185.479043967609-53.819967170118-1.05379037834552
471807918131.6598161127197.18489594113-52.65981611268310.192706237903397
481848318502.7594778068268.942951931884-19.75947780682621.18523919452177
491903718878.5494346319313.115456239103158.4505653681010.729674662258837
501934419317.5193518114364.94962767941126.48064818863130.848644211941166
511959019612.0777526598336.135116962810-22.0777526597913-0.473193731154397
521986219784.0579077626268.74177311237977.9420922373997-1.11328493507764
532020720230.1217288908341.856011914412-23.12172889079421.20391581444042
542059320814.7527761654441.969431500659-221.7527761654331.64349683261922
552125321155.6571047633400.33189831272697.3428952366934-0.683867501769733
562150721403.3651845512337.453653047335103.634815448782-1.03379448313649
572152821558.7435182918262.42235669579-30.7435182917968-1.23410481749973
582181821859.0572268274278.032002385217-41.05722682735860.256800682792461
592220522268.2388418921332.02036228875-63.23884189205230.889103448178963
602262122659.7666454220356.526362045662-38.7666454220240.404409472118186
612300622908.8147847302312.21131306523097.1852152697695-0.73031651206288
622317823137.2946497613277.78156940526340.705350238717-0.564538662633011
632335823350.0137753084251.1375827509927.98622469161922-0.437690458610266
642351923521.8280880134218.608602319280-2.82808801337982-0.536673749048284
652372523800.6725805192243.390825046013-75.67258051916080.408283128732295
662378923998.4602877774224.618263759952-209.460287777367-0.308444981187799
672447224301.2340525172256.765218253769170.7659474827560.528045894338038
682477324606.4727019610276.696631818557166.5272980389520.327635917544852
692447724603.1372762029161.553761037450-126.137276202922-1.89368671991159
702466924747.0497842964154.302212659892-78.0497842963931-0.119314672324533
712482724907.7049872053156.912892804107-80.7049872053280.043001299764418

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 9782 & 9782 & 0 & 0 & 0 \tabularnewline
2 & 9938 & 9918.93605779396 & 23.5549301421804 & 19.0639422060417 & 0.857758874105988 \tabularnewline
3 & 10111 & 10077.9760546967 & 71.4188230684924 & 33.0239453032494 & 1.03391890128237 \tabularnewline
4 & 10259 & 10241.9844164491 & 110.157937722000 & 17.0155835509192 & 0.659212746247292 \tabularnewline
5 & 10419 & 10406.5785907746 & 133.353645316196 & 12.4214092253877 & 0.382204322318611 \tabularnewline
6 & 10622 & 10604.5079824549 & 161.004721374398 & 17.4920175451272 & 0.455522951897839 \tabularnewline
7 & 11173 & 11096.8818781177 & 303.274223558504 & 76.11812188235 & 2.34218720351826 \tabularnewline
8 & 11542 & 11530.2526931791 & 359.188581801535 & 11.7473068209281 & 0.920043660299011 \tabularnewline
9 & 11538 & 11604.6584682778 & 236.747127652393 & -66.658468277833 & -2.01433451811386 \tabularnewline
10 & 11837 & 11815.6822868926 & 225.685803654216 & 21.3177131074291 & -0.181964701118438 \tabularnewline
11 & 12060 & 12049.7198196101 & 229.277439024574 & 10.2801803899135 & 0.0590835175226261 \tabularnewline
12 & 12423 & 12391.7719120008 & 277.778086638859 & 31.2280879991654 & 0.797847831202871 \tabularnewline
13 & 12791 & 12802.4347566347 & 333.40431774105 & -11.4347566347429 & 1.0182222328493 \tabularnewline
14 & 12891 & 12943.2312624623 & 254.498123428254 & -52.2312624623293 & -1.21970181446696 \tabularnewline
15 & 13098 & 13101.9885692694 & 215.731152229803 & -3.98856926944557 & -0.643610112578598 \tabularnewline
16 & 13418 & 13383.942655519 & 243.427992014109 & 34.0573444810074 & 0.457873754561834 \tabularnewline
17 & 13614 & 13617.8511518545 & 239.435723160518 & -3.85115185447749 & -0.065140366893704 \tabularnewline
18 & 13653 & 13747.6680774390 & 193.580505235018 & -94.668077439033 & -0.751501867438058 \tabularnewline
19 & 13980 & 13940.3792362616 & 193.216764591017 & 39.6207637384379 & -0.00597939200671672 \tabularnewline
20 & 14087 & 14044.9557571788 & 156.10254727509 & 42.0442428211844 & -0.610490613766667 \tabularnewline
21 & 14332 & 14348.5105881860 & 217.867215995426 & -16.5105881860365 & 1.01604471599163 \tabularnewline
22 & 14232 & 14297.3195042576 & 105.142820750440 & -65.319504257613 & -1.85440458507655 \tabularnewline
23 & 14226 & 14268.6099105285 & 49.1019139696661 & -42.6099105285166 & -0.921850048890431 \tabularnewline
24 & 14186 & 14207.8439927964 & 3.25978471960693 & -21.8439927964456 & -0.756502855574918 \tabularnewline
25 & 14310 & 14242.0208426428 & 16.1685268243479 & 67.9791573571991 & 0.218397238532523 \tabularnewline
26 & 14152 & 14196.3609551045 & -9.37915394003732 & -44.3609551045374 & -0.412626619824681 \tabularnewline
27 & 14127 & 14156.5532715461 & -21.7715066267317 & -29.5532715461194 & -0.203793908346721 \tabularnewline
28 & 14163 & 14127.5825656126 & -24.7470020790524 & 35.4174343874204 & -0.0493257421586975 \tabularnewline
29 & 13964 & 13975.5052227228 & -77.6776467929766 & -11.5052227228487 & -0.867776581287822 \tabularnewline
30 & 13811 & 13898.0667463759 & -77.5784066346216 & -87.066746375857 & 0.00162616033679722 \tabularnewline
31 & 14440 & 14264.5582527841 & 106.584526260075 & 175.441747215885 & 3.0259345771543 \tabularnewline
32 & 14724 & 14668.8617725076 & 230.140401937184 & 55.1382274924246 & 2.03219630061857 \tabularnewline
33 & 14790 & 14793.2669073079 & 186.232847218396 & -3.26690730789285 & -0.722291908257976 \tabularnewline
34 & 14961 & 14990.6077211864 & 190.845302206966 & -29.6077211864129 & 0.075875607105275 \tabularnewline
35 & 15117 & 15147.5312625351 & 176.778770566811 & -30.5312625351364 & -0.231450508482369 \tabularnewline
36 & 15452 & 15446.6659404892 & 227.425561409009 & 5.33405951076522 & 0.836979558777251 \tabularnewline
37 & 16080 & 15925.3483768262 & 331.712867723907 & 154.651623173842 & 1.73282326886379 \tabularnewline
38 & 16284 & 16314.3959474695 & 355.372979925942 & -30.3959474694958 & 0.386059568765797 \tabularnewline
39 & 16524 & 16570.7843181975 & 314.913810732776 & -46.7843181974516 & -0.664351702594299 \tabularnewline
40 & 16782 & 16734.5658830091 & 252.738929154183 & 47.4341169909307 & -1.02894724481577 \tabularnewline
41 & 16663 & 16737.2689014171 & 149.313078418830 & -74.2689014171212 & -1.70067336348240 \tabularnewline
42 & 16678 & 16881.1309339626 & 147.059879220053 & -203.130933962555 & -0.0369512761697523 \tabularnewline
43 & 17448 & 17279.9468243233 & 251.030098652220 & 168.053175676688 & 1.70776145768666 \tabularnewline
44 & 17745 & 17639.5211453030 & 295.873755238496 & 105.478854696961 & 0.73744008709896 \tabularnewline
45 & 17789 & 17823.2997972484 & 249.539611398962 & -34.2997972484466 & -0.76216746296519 \tabularnewline
46 & 17864 & 17917.8199671701 & 185.479043967609 & -53.819967170118 & -1.05379037834552 \tabularnewline
47 & 18079 & 18131.6598161127 & 197.18489594113 & -52.6598161126831 & 0.192706237903397 \tabularnewline
48 & 18483 & 18502.7594778068 & 268.942951931884 & -19.7594778068262 & 1.18523919452177 \tabularnewline
49 & 19037 & 18878.5494346319 & 313.115456239103 & 158.450565368101 & 0.729674662258837 \tabularnewline
50 & 19344 & 19317.5193518114 & 364.949627679411 & 26.4806481886313 & 0.848644211941166 \tabularnewline
51 & 19590 & 19612.0777526598 & 336.135116962810 & -22.0777526597913 & -0.473193731154397 \tabularnewline
52 & 19862 & 19784.0579077626 & 268.741773112379 & 77.9420922373997 & -1.11328493507764 \tabularnewline
53 & 20207 & 20230.1217288908 & 341.856011914412 & -23.1217288907942 & 1.20391581444042 \tabularnewline
54 & 20593 & 20814.7527761654 & 441.969431500659 & -221.752776165433 & 1.64349683261922 \tabularnewline
55 & 21253 & 21155.6571047633 & 400.331898312726 & 97.3428952366934 & -0.683867501769733 \tabularnewline
56 & 21507 & 21403.3651845512 & 337.453653047335 & 103.634815448782 & -1.03379448313649 \tabularnewline
57 & 21528 & 21558.7435182918 & 262.42235669579 & -30.7435182917968 & -1.23410481749973 \tabularnewline
58 & 21818 & 21859.0572268274 & 278.032002385217 & -41.0572268273586 & 0.256800682792461 \tabularnewline
59 & 22205 & 22268.2388418921 & 332.02036228875 & -63.2388418920523 & 0.889103448178963 \tabularnewline
60 & 22621 & 22659.7666454220 & 356.526362045662 & -38.766645422024 & 0.404409472118186 \tabularnewline
61 & 23006 & 22908.8147847302 & 312.211313065230 & 97.1852152697695 & -0.73031651206288 \tabularnewline
62 & 23178 & 23137.2946497613 & 277.781569405263 & 40.705350238717 & -0.564538662633011 \tabularnewline
63 & 23358 & 23350.0137753084 & 251.137582750992 & 7.98622469161922 & -0.437690458610266 \tabularnewline
64 & 23519 & 23521.8280880134 & 218.608602319280 & -2.82808801337982 & -0.536673749048284 \tabularnewline
65 & 23725 & 23800.6725805192 & 243.390825046013 & -75.6725805191608 & 0.408283128732295 \tabularnewline
66 & 23789 & 23998.4602877774 & 224.618263759952 & -209.460287777367 & -0.308444981187799 \tabularnewline
67 & 24472 & 24301.2340525172 & 256.765218253769 & 170.765947482756 & 0.528045894338038 \tabularnewline
68 & 24773 & 24606.4727019610 & 276.696631818557 & 166.527298038952 & 0.327635917544852 \tabularnewline
69 & 24477 & 24603.1372762029 & 161.553761037450 & -126.137276202922 & -1.89368671991159 \tabularnewline
70 & 24669 & 24747.0497842964 & 154.302212659892 & -78.0497842963931 & -0.119314672324533 \tabularnewline
71 & 24827 & 24907.7049872053 & 156.912892804107 & -80.704987205328 & 0.043001299764418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116485&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]9782[/C][C]9782[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]9938[/C][C]9918.93605779396[/C][C]23.5549301421804[/C][C]19.0639422060417[/C][C]0.857758874105988[/C][/ROW]
[ROW][C]3[/C][C]10111[/C][C]10077.9760546967[/C][C]71.4188230684924[/C][C]33.0239453032494[/C][C]1.03391890128237[/C][/ROW]
[ROW][C]4[/C][C]10259[/C][C]10241.9844164491[/C][C]110.157937722000[/C][C]17.0155835509192[/C][C]0.659212746247292[/C][/ROW]
[ROW][C]5[/C][C]10419[/C][C]10406.5785907746[/C][C]133.353645316196[/C][C]12.4214092253877[/C][C]0.382204322318611[/C][/ROW]
[ROW][C]6[/C][C]10622[/C][C]10604.5079824549[/C][C]161.004721374398[/C][C]17.4920175451272[/C][C]0.455522951897839[/C][/ROW]
[ROW][C]7[/C][C]11173[/C][C]11096.8818781177[/C][C]303.274223558504[/C][C]76.11812188235[/C][C]2.34218720351826[/C][/ROW]
[ROW][C]8[/C][C]11542[/C][C]11530.2526931791[/C][C]359.188581801535[/C][C]11.7473068209281[/C][C]0.920043660299011[/C][/ROW]
[ROW][C]9[/C][C]11538[/C][C]11604.6584682778[/C][C]236.747127652393[/C][C]-66.658468277833[/C][C]-2.01433451811386[/C][/ROW]
[ROW][C]10[/C][C]11837[/C][C]11815.6822868926[/C][C]225.685803654216[/C][C]21.3177131074291[/C][C]-0.181964701118438[/C][/ROW]
[ROW][C]11[/C][C]12060[/C][C]12049.7198196101[/C][C]229.277439024574[/C][C]10.2801803899135[/C][C]0.0590835175226261[/C][/ROW]
[ROW][C]12[/C][C]12423[/C][C]12391.7719120008[/C][C]277.778086638859[/C][C]31.2280879991654[/C][C]0.797847831202871[/C][/ROW]
[ROW][C]13[/C][C]12791[/C][C]12802.4347566347[/C][C]333.40431774105[/C][C]-11.4347566347429[/C][C]1.0182222328493[/C][/ROW]
[ROW][C]14[/C][C]12891[/C][C]12943.2312624623[/C][C]254.498123428254[/C][C]-52.2312624623293[/C][C]-1.21970181446696[/C][/ROW]
[ROW][C]15[/C][C]13098[/C][C]13101.9885692694[/C][C]215.731152229803[/C][C]-3.98856926944557[/C][C]-0.643610112578598[/C][/ROW]
[ROW][C]16[/C][C]13418[/C][C]13383.942655519[/C][C]243.427992014109[/C][C]34.0573444810074[/C][C]0.457873754561834[/C][/ROW]
[ROW][C]17[/C][C]13614[/C][C]13617.8511518545[/C][C]239.435723160518[/C][C]-3.85115185447749[/C][C]-0.065140366893704[/C][/ROW]
[ROW][C]18[/C][C]13653[/C][C]13747.6680774390[/C][C]193.580505235018[/C][C]-94.668077439033[/C][C]-0.751501867438058[/C][/ROW]
[ROW][C]19[/C][C]13980[/C][C]13940.3792362616[/C][C]193.216764591017[/C][C]39.6207637384379[/C][C]-0.00597939200671672[/C][/ROW]
[ROW][C]20[/C][C]14087[/C][C]14044.9557571788[/C][C]156.10254727509[/C][C]42.0442428211844[/C][C]-0.610490613766667[/C][/ROW]
[ROW][C]21[/C][C]14332[/C][C]14348.5105881860[/C][C]217.867215995426[/C][C]-16.5105881860365[/C][C]1.01604471599163[/C][/ROW]
[ROW][C]22[/C][C]14232[/C][C]14297.3195042576[/C][C]105.142820750440[/C][C]-65.319504257613[/C][C]-1.85440458507655[/C][/ROW]
[ROW][C]23[/C][C]14226[/C][C]14268.6099105285[/C][C]49.1019139696661[/C][C]-42.6099105285166[/C][C]-0.921850048890431[/C][/ROW]
[ROW][C]24[/C][C]14186[/C][C]14207.8439927964[/C][C]3.25978471960693[/C][C]-21.8439927964456[/C][C]-0.756502855574918[/C][/ROW]
[ROW][C]25[/C][C]14310[/C][C]14242.0208426428[/C][C]16.1685268243479[/C][C]67.9791573571991[/C][C]0.218397238532523[/C][/ROW]
[ROW][C]26[/C][C]14152[/C][C]14196.3609551045[/C][C]-9.37915394003732[/C][C]-44.3609551045374[/C][C]-0.412626619824681[/C][/ROW]
[ROW][C]27[/C][C]14127[/C][C]14156.5532715461[/C][C]-21.7715066267317[/C][C]-29.5532715461194[/C][C]-0.203793908346721[/C][/ROW]
[ROW][C]28[/C][C]14163[/C][C]14127.5825656126[/C][C]-24.7470020790524[/C][C]35.4174343874204[/C][C]-0.0493257421586975[/C][/ROW]
[ROW][C]29[/C][C]13964[/C][C]13975.5052227228[/C][C]-77.6776467929766[/C][C]-11.5052227228487[/C][C]-0.867776581287822[/C][/ROW]
[ROW][C]30[/C][C]13811[/C][C]13898.0667463759[/C][C]-77.5784066346216[/C][C]-87.066746375857[/C][C]0.00162616033679722[/C][/ROW]
[ROW][C]31[/C][C]14440[/C][C]14264.5582527841[/C][C]106.584526260075[/C][C]175.441747215885[/C][C]3.0259345771543[/C][/ROW]
[ROW][C]32[/C][C]14724[/C][C]14668.8617725076[/C][C]230.140401937184[/C][C]55.1382274924246[/C][C]2.03219630061857[/C][/ROW]
[ROW][C]33[/C][C]14790[/C][C]14793.2669073079[/C][C]186.232847218396[/C][C]-3.26690730789285[/C][C]-0.722291908257976[/C][/ROW]
[ROW][C]34[/C][C]14961[/C][C]14990.6077211864[/C][C]190.845302206966[/C][C]-29.6077211864129[/C][C]0.075875607105275[/C][/ROW]
[ROW][C]35[/C][C]15117[/C][C]15147.5312625351[/C][C]176.778770566811[/C][C]-30.5312625351364[/C][C]-0.231450508482369[/C][/ROW]
[ROW][C]36[/C][C]15452[/C][C]15446.6659404892[/C][C]227.425561409009[/C][C]5.33405951076522[/C][C]0.836979558777251[/C][/ROW]
[ROW][C]37[/C][C]16080[/C][C]15925.3483768262[/C][C]331.712867723907[/C][C]154.651623173842[/C][C]1.73282326886379[/C][/ROW]
[ROW][C]38[/C][C]16284[/C][C]16314.3959474695[/C][C]355.372979925942[/C][C]-30.3959474694958[/C][C]0.386059568765797[/C][/ROW]
[ROW][C]39[/C][C]16524[/C][C]16570.7843181975[/C][C]314.913810732776[/C][C]-46.7843181974516[/C][C]-0.664351702594299[/C][/ROW]
[ROW][C]40[/C][C]16782[/C][C]16734.5658830091[/C][C]252.738929154183[/C][C]47.4341169909307[/C][C]-1.02894724481577[/C][/ROW]
[ROW][C]41[/C][C]16663[/C][C]16737.2689014171[/C][C]149.313078418830[/C][C]-74.2689014171212[/C][C]-1.70067336348240[/C][/ROW]
[ROW][C]42[/C][C]16678[/C][C]16881.1309339626[/C][C]147.059879220053[/C][C]-203.130933962555[/C][C]-0.0369512761697523[/C][/ROW]
[ROW][C]43[/C][C]17448[/C][C]17279.9468243233[/C][C]251.030098652220[/C][C]168.053175676688[/C][C]1.70776145768666[/C][/ROW]
[ROW][C]44[/C][C]17745[/C][C]17639.5211453030[/C][C]295.873755238496[/C][C]105.478854696961[/C][C]0.73744008709896[/C][/ROW]
[ROW][C]45[/C][C]17789[/C][C]17823.2997972484[/C][C]249.539611398962[/C][C]-34.2997972484466[/C][C]-0.76216746296519[/C][/ROW]
[ROW][C]46[/C][C]17864[/C][C]17917.8199671701[/C][C]185.479043967609[/C][C]-53.819967170118[/C][C]-1.05379037834552[/C][/ROW]
[ROW][C]47[/C][C]18079[/C][C]18131.6598161127[/C][C]197.18489594113[/C][C]-52.6598161126831[/C][C]0.192706237903397[/C][/ROW]
[ROW][C]48[/C][C]18483[/C][C]18502.7594778068[/C][C]268.942951931884[/C][C]-19.7594778068262[/C][C]1.18523919452177[/C][/ROW]
[ROW][C]49[/C][C]19037[/C][C]18878.5494346319[/C][C]313.115456239103[/C][C]158.450565368101[/C][C]0.729674662258837[/C][/ROW]
[ROW][C]50[/C][C]19344[/C][C]19317.5193518114[/C][C]364.949627679411[/C][C]26.4806481886313[/C][C]0.848644211941166[/C][/ROW]
[ROW][C]51[/C][C]19590[/C][C]19612.0777526598[/C][C]336.135116962810[/C][C]-22.0777526597913[/C][C]-0.473193731154397[/C][/ROW]
[ROW][C]52[/C][C]19862[/C][C]19784.0579077626[/C][C]268.741773112379[/C][C]77.9420922373997[/C][C]-1.11328493507764[/C][/ROW]
[ROW][C]53[/C][C]20207[/C][C]20230.1217288908[/C][C]341.856011914412[/C][C]-23.1217288907942[/C][C]1.20391581444042[/C][/ROW]
[ROW][C]54[/C][C]20593[/C][C]20814.7527761654[/C][C]441.969431500659[/C][C]-221.752776165433[/C][C]1.64349683261922[/C][/ROW]
[ROW][C]55[/C][C]21253[/C][C]21155.6571047633[/C][C]400.331898312726[/C][C]97.3428952366934[/C][C]-0.683867501769733[/C][/ROW]
[ROW][C]56[/C][C]21507[/C][C]21403.3651845512[/C][C]337.453653047335[/C][C]103.634815448782[/C][C]-1.03379448313649[/C][/ROW]
[ROW][C]57[/C][C]21528[/C][C]21558.7435182918[/C][C]262.42235669579[/C][C]-30.7435182917968[/C][C]-1.23410481749973[/C][/ROW]
[ROW][C]58[/C][C]21818[/C][C]21859.0572268274[/C][C]278.032002385217[/C][C]-41.0572268273586[/C][C]0.256800682792461[/C][/ROW]
[ROW][C]59[/C][C]22205[/C][C]22268.2388418921[/C][C]332.02036228875[/C][C]-63.2388418920523[/C][C]0.889103448178963[/C][/ROW]
[ROW][C]60[/C][C]22621[/C][C]22659.7666454220[/C][C]356.526362045662[/C][C]-38.766645422024[/C][C]0.404409472118186[/C][/ROW]
[ROW][C]61[/C][C]23006[/C][C]22908.8147847302[/C][C]312.211313065230[/C][C]97.1852152697695[/C][C]-0.73031651206288[/C][/ROW]
[ROW][C]62[/C][C]23178[/C][C]23137.2946497613[/C][C]277.781569405263[/C][C]40.705350238717[/C][C]-0.564538662633011[/C][/ROW]
[ROW][C]63[/C][C]23358[/C][C]23350.0137753084[/C][C]251.137582750992[/C][C]7.98622469161922[/C][C]-0.437690458610266[/C][/ROW]
[ROW][C]64[/C][C]23519[/C][C]23521.8280880134[/C][C]218.608602319280[/C][C]-2.82808801337982[/C][C]-0.536673749048284[/C][/ROW]
[ROW][C]65[/C][C]23725[/C][C]23800.6725805192[/C][C]243.390825046013[/C][C]-75.6725805191608[/C][C]0.408283128732295[/C][/ROW]
[ROW][C]66[/C][C]23789[/C][C]23998.4602877774[/C][C]224.618263759952[/C][C]-209.460287777367[/C][C]-0.308444981187799[/C][/ROW]
[ROW][C]67[/C][C]24472[/C][C]24301.2340525172[/C][C]256.765218253769[/C][C]170.765947482756[/C][C]0.528045894338038[/C][/ROW]
[ROW][C]68[/C][C]24773[/C][C]24606.4727019610[/C][C]276.696631818557[/C][C]166.527298038952[/C][C]0.327635917544852[/C][/ROW]
[ROW][C]69[/C][C]24477[/C][C]24603.1372762029[/C][C]161.553761037450[/C][C]-126.137276202922[/C][C]-1.89368671991159[/C][/ROW]
[ROW][C]70[/C][C]24669[/C][C]24747.0497842964[/C][C]154.302212659892[/C][C]-78.0497842963931[/C][C]-0.119314672324533[/C][/ROW]
[ROW][C]71[/C][C]24827[/C][C]24907.7049872053[/C][C]156.912892804107[/C][C]-80.704987205328[/C][C]0.043001299764418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116485&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
197829782000
299389918.9360577939623.554930142180419.06394220604170.857758874105988
31011110077.976054696771.418823068492433.02394530324941.03391890128237
41025910241.9844164491110.15793772200017.01558355091920.659212746247292
51041910406.5785907746133.35364531619612.42140922538770.382204322318611
61062210604.5079824549161.00472137439817.49201754512720.455522951897839
71117311096.8818781177303.27422355850476.118121882352.34218720351826
81154211530.2526931791359.18858180153511.74730682092810.920043660299011
91153811604.6584682778236.747127652393-66.658468277833-2.01433451811386
101183711815.6822868926225.68580365421621.3177131074291-0.181964701118438
111206012049.7198196101229.27743902457410.28018038991350.0590835175226261
121242312391.7719120008277.77808663885931.22808799916540.797847831202871
131279112802.4347566347333.40431774105-11.43475663474291.0182222328493
141289112943.2312624623254.498123428254-52.2312624623293-1.21970181446696
151309813101.9885692694215.731152229803-3.98856926944557-0.643610112578598
161341813383.942655519243.42799201410934.05734448100740.457873754561834
171361413617.8511518545239.435723160518-3.85115185447749-0.065140366893704
181365313747.6680774390193.580505235018-94.668077439033-0.751501867438058
191398013940.3792362616193.21676459101739.6207637384379-0.00597939200671672
201408714044.9557571788156.1025472750942.0442428211844-0.610490613766667
211433214348.5105881860217.867215995426-16.51058818603651.01604471599163
221423214297.3195042576105.142820750440-65.319504257613-1.85440458507655
231422614268.609910528549.1019139696661-42.6099105285166-0.921850048890431
241418614207.84399279643.25978471960693-21.8439927964456-0.756502855574918
251431014242.020842642816.168526824347967.97915735719910.218397238532523
261415214196.3609551045-9.37915394003732-44.3609551045374-0.412626619824681
271412714156.5532715461-21.7715066267317-29.5532715461194-0.203793908346721
281416314127.5825656126-24.747002079052435.4174343874204-0.0493257421586975
291396413975.5052227228-77.6776467929766-11.5052227228487-0.867776581287822
301381113898.0667463759-77.5784066346216-87.0667463758570.00162616033679722
311444014264.5582527841106.584526260075175.4417472158853.0259345771543
321472414668.8617725076230.14040193718455.13822749242462.03219630061857
331479014793.2669073079186.232847218396-3.26690730789285-0.722291908257976
341496114990.6077211864190.845302206966-29.60772118641290.075875607105275
351511715147.5312625351176.778770566811-30.5312625351364-0.231450508482369
361545215446.6659404892227.4255614090095.334059510765220.836979558777251
371608015925.3483768262331.712867723907154.6516231738421.73282326886379
381628416314.3959474695355.372979925942-30.39594746949580.386059568765797
391652416570.7843181975314.913810732776-46.7843181974516-0.664351702594299
401678216734.5658830091252.73892915418347.4341169909307-1.02894724481577
411666316737.2689014171149.313078418830-74.2689014171212-1.70067336348240
421667816881.1309339626147.059879220053-203.130933962555-0.0369512761697523
431744817279.9468243233251.030098652220168.0531756766881.70776145768666
441774517639.5211453030295.873755238496105.4788546969610.73744008709896
451778917823.2997972484249.539611398962-34.2997972484466-0.76216746296519
461786417917.8199671701185.479043967609-53.819967170118-1.05379037834552
471807918131.6598161127197.18489594113-52.65981611268310.192706237903397
481848318502.7594778068268.942951931884-19.75947780682621.18523919452177
491903718878.5494346319313.115456239103158.4505653681010.729674662258837
501934419317.5193518114364.94962767941126.48064818863130.848644211941166
511959019612.0777526598336.135116962810-22.0777526597913-0.473193731154397
521986219784.0579077626268.74177311237977.9420922373997-1.11328493507764
532020720230.1217288908341.856011914412-23.12172889079421.20391581444042
542059320814.7527761654441.969431500659-221.7527761654331.64349683261922
552125321155.6571047633400.33189831272697.3428952366934-0.683867501769733
562150721403.3651845512337.453653047335103.634815448782-1.03379448313649
572152821558.7435182918262.42235669579-30.7435182917968-1.23410481749973
582181821859.0572268274278.032002385217-41.05722682735860.256800682792461
592220522268.2388418921332.02036228875-63.23884189205230.889103448178963
602262122659.7666454220356.526362045662-38.7666454220240.404409472118186
612300622908.8147847302312.21131306523097.1852152697695-0.73031651206288
622317823137.2946497613277.78156940526340.705350238717-0.564538662633011
632335823350.0137753084251.1375827509927.98622469161922-0.437690458610266
642351923521.8280880134218.608602319280-2.82808801337982-0.536673749048284
652372523800.6725805192243.390825046013-75.67258051916080.408283128732295
662378923998.4602877774224.618263759952-209.460287777367-0.308444981187799
672447224301.2340525172256.765218253769170.7659474827560.528045894338038
682477324606.4727019610276.696631818557166.5272980389520.327635917544852
692447724603.1372762029161.553761037450-126.137276202922-1.89368671991159
702466924747.0497842964154.302212659892-78.0497842963931-0.119314672324533
712482724907.7049872053156.912892804107-80.7049872053280.043001299764418



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')