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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 computationThu, 09 Dec 2010 16:27:14 +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/09/t1291911933em4k9x61f80n0qa.htm/, Retrieved Sun, 28 Apr 2024 19:13:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107252, Retrieved Sun, 28 Apr 2024 19:13:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157
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   [Decomposition by Loess] [] [2010-12-07 11:51:00] [9315c5fa5df29386545a575306c6a452]
- RMPD      [Structural Time Series Models] [STSM] [2010-12-09 16:27:14] [be9b1effb945c5b0652fb49bcca5faef] [Current]
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Dataseries X:
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730
14538




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107252&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107252&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
13151431514000
22707128488.2212273871-1092.63511967583-1417.22122738713-1.46598300534814
32946228256.6349716561-703.1433937271161205.365028343950.311490301374225
42610526681.1863445095-1151.42398132673-576.186344509478-0.309348729200586
52239723266.1456560182-2311.8923233458-869.145656018176-0.773902918482607
62384322753.2425014063-1398.551163185871089.757498593730.621016281464426
72170521809.5519609645-1167.00062176535-104.5519609645240.158797925588194
81808918952.9154866462-2029.74342518538-863.915486646162-0.591919734718616
92076419423.4582449803-752.0092155006411340.541755019720.876493082066904
102531623548.09752792281739.877411081581767.902472077221.7094055674526
111770420588.7166309384-660.821193441494-2884.71663093844-1.64686183446903
121554816432.9158986701-2446.0898610964-884.915898670094-1.22467857740565
132802921943.65809112471543.873818280016085.341908875312.88637957046384
142938329386.94310556034496.42366564184-3.943105560292831.99736580372881
153643835122.86360573565090.311003827091315.136394264350.403221519417058
163203434834.21237721792469.73346978688-2800.21237721788-1.83277717885368
172267928115.1589124382-2084.13305485642-5436.15891243816-3.12236828533848
182431923375.7949989356-3394.70451896832943.20500106442-0.89166031005516
191800418142.4003279398-4299.60362375608-138.400327939775-0.619028939551949
201753717756.7072176541-2369.74896154116-219.7072176540751.3238400442228
212036619234.9677852415-468.6072820969171131.032214758521.30421222697792
222278218961.2397152154-372.2904438506083820.760284784560.0660722955655084
231916920082.6207999373364.866350614665-913.6207999372980.505788839182921
241380719011.6124477755-342.283221651173-5204.61244777549-0.486851166435701
252974323961.36080303422270.027516975785781.639196965791.81086866717164
262559126781.71249926142540.7681319951-1190.712499261410.185062379425685
272909626651.43502085361247.054845364752444.5649791464-0.882823073454282
282648226083.6978991895367.493641551635398.302100810479-0.608103734693225
292240526319.7769794379303.19324958791-3914.77697943795-0.0443024160915607
302704425817.5742423243-91.2278373383341226.4257576757-0.269655334946142
311797021602.5780615616-2104.92347908123-3632.57806156159-1.37682344777417
321873019759.9225270495-1976.89122823787-1029.922527049460.0877484655676938
331968418318.0297126147-1715.422088199391365.97028738530.179359381648078
341978516370.9629013692-1828.661416189833414.03709863076-0.077695110328347
351847917692.5620884627-289.879399954303786.4379115373461.05670711850978
361069818138.715016282969.696047029169-7440.71501628290.247479031943035
373195623764.08412808322788.248872532828191.915871916761.8706676840445
382950629092.14932134894027.60057321021413.8506786510810.848002732211462
393450632248.88091694393605.674050172062257.11908305605-0.288666585293711
402716529681.1770239054617.433506084196-2516.17702390538-2.05735468034303
412673629778.3258637963364.350265418488-3042.32586379626-0.17430263086117
422369123811.5921987584-2721.31134715396-120.592198758363-2.11544564455643
431815721100.1115898896-2716.52816758589-2943.111589889590.00327304663945432
441732818284.8278370536-2764.51200622069-956.827837053579-0.0328679746865906
451820516196.0630878301-2436.200722422962008.936912169860.225156364196841
462099517041.4817046502-841.6371436502513953.51829534981.09444070399215
471738217150.3468270701-379.713517185379231.6531729298650.317369819034716
48936718676.3965326998547.316984630072-9309.39653269980.637433920144565
493112422814.11167537292295.147377930788309.888324627071.20007575058211
502655125761.01029744312611.71108081836789.9897025569440.216709054194197
513065126900.78120262311899.695480103543750.21879737695-0.487645385788549
522585927990.58798227021508.24231731052-2131.58798227022-0.2690959440572
532510026773.807452881187.378996447071-1673.80745288103-0.908922851010369
542577825929.1190478969-313.810950606371-151.119047896935-0.343984937948234
552041823857.1357457246-1166.84705259402-3439.13574572458-0.584207483168731
561868820657.7921073125-2151.35322136518-1969.79210731248-0.674280897650774
572042419060.1900979504-1883.351313485621363.809902049640.183761235129989
582477619961.1418024234-535.8183690737874814.858197576640.925086773851587
591981420438.026705414-45.3659375627472-624.0267054140130.337018949556687
601273822675.83545353341061.62281234123-9937.835453533440.760683058345722
613156623795.62301694921089.832809416637770.376983050790.0193537559141595
623011127632.20462985522419.553050982622478.795370144810.910600280274049
633001927424.71081957391151.240439066132594.2891804261-0.869069542329468
643193431443.63133725992534.91514941043490.3686627401430.950530719347023
652582629391.1525439304317.335125140292-3565.1525439304-1.52496652118284
662683526809.4430710926-1086.2806477594825.5569289073651-0.963697357874404
672020523458.147856514-2182.4166615121-3253.14785651397-0.751122983402322
681778920273.8898930891-2666.48518493185-2484.8898930891-0.331567149409735
692052019320.7733431684-1839.583157818021199.226656831550.566935581227682
702251818071.6119185777-1554.66204510874446.388081422260.195608479914645
711557216923.6835349286-1358.21542188005-1351.68353492860.134982435235803
721150919836.2460455606706.787143468736-8327.246045560571.41842718367463
732544719628.2687863865264.4291086841585818.73121361346-0.303393890663685
742409020637.0681093318623.8374307246923452.931890668240.246192740508689
752778624742.26070453722301.420891695113043.739295462781.14982269207412
762619525022.4835432411327.878504605971172.51645675902-0.668539730547871
772051623679.832459702639.8456708709375-3163.83245970261-0.885312009111272
782275922113.0981708124-736.030694326834645.901829187568-0.532730011919173
791902821634.7581063078-611.612160398208-2606.75810630780.0852871052821534
801697120354.3949683974-934.051594808297-3383.39496839739-0.220897776081142
812003619036.5520929539-1118.87350012147999.447907046087-0.126715897967117
822248518251.6346566049-958.0747871181924233.36534339510.110388168502649
831873020300.4474713421490.970715153167-1570.447471342150.995514662440418
841453822239.33186750641189.43281575743-7701.33186750640.479639832666078

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 31514 & 31514 & 0 & 0 & 0 \tabularnewline
2 & 27071 & 28488.2212273871 & -1092.63511967583 & -1417.22122738713 & -1.46598300534814 \tabularnewline
3 & 29462 & 28256.6349716561 & -703.143393727116 & 1205.36502834395 & 0.311490301374225 \tabularnewline
4 & 26105 & 26681.1863445095 & -1151.42398132673 & -576.186344509478 & -0.309348729200586 \tabularnewline
5 & 22397 & 23266.1456560182 & -2311.8923233458 & -869.145656018176 & -0.773902918482607 \tabularnewline
6 & 23843 & 22753.2425014063 & -1398.55116318587 & 1089.75749859373 & 0.621016281464426 \tabularnewline
7 & 21705 & 21809.5519609645 & -1167.00062176535 & -104.551960964524 & 0.158797925588194 \tabularnewline
8 & 18089 & 18952.9154866462 & -2029.74342518538 & -863.915486646162 & -0.591919734718616 \tabularnewline
9 & 20764 & 19423.4582449803 & -752.009215500641 & 1340.54175501972 & 0.876493082066904 \tabularnewline
10 & 25316 & 23548.0975279228 & 1739.87741108158 & 1767.90247207722 & 1.7094055674526 \tabularnewline
11 & 17704 & 20588.7166309384 & -660.821193441494 & -2884.71663093844 & -1.64686183446903 \tabularnewline
12 & 15548 & 16432.9158986701 & -2446.0898610964 & -884.915898670094 & -1.22467857740565 \tabularnewline
13 & 28029 & 21943.6580911247 & 1543.87381828001 & 6085.34190887531 & 2.88637957046384 \tabularnewline
14 & 29383 & 29386.9431055603 & 4496.42366564184 & -3.94310556029283 & 1.99736580372881 \tabularnewline
15 & 36438 & 35122.8636057356 & 5090.31100382709 & 1315.13639426435 & 0.403221519417058 \tabularnewline
16 & 32034 & 34834.2123772179 & 2469.73346978688 & -2800.21237721788 & -1.83277717885368 \tabularnewline
17 & 22679 & 28115.1589124382 & -2084.13305485642 & -5436.15891243816 & -3.12236828533848 \tabularnewline
18 & 24319 & 23375.7949989356 & -3394.70451896832 & 943.20500106442 & -0.89166031005516 \tabularnewline
19 & 18004 & 18142.4003279398 & -4299.60362375608 & -138.400327939775 & -0.619028939551949 \tabularnewline
20 & 17537 & 17756.7072176541 & -2369.74896154116 & -219.707217654075 & 1.3238400442228 \tabularnewline
21 & 20366 & 19234.9677852415 & -468.607282096917 & 1131.03221475852 & 1.30421222697792 \tabularnewline
22 & 22782 & 18961.2397152154 & -372.290443850608 & 3820.76028478456 & 0.0660722955655084 \tabularnewline
23 & 19169 & 20082.6207999373 & 364.866350614665 & -913.620799937298 & 0.505788839182921 \tabularnewline
24 & 13807 & 19011.6124477755 & -342.283221651173 & -5204.61244777549 & -0.486851166435701 \tabularnewline
25 & 29743 & 23961.3608030342 & 2270.02751697578 & 5781.63919696579 & 1.81086866717164 \tabularnewline
26 & 25591 & 26781.7124992614 & 2540.7681319951 & -1190.71249926141 & 0.185062379425685 \tabularnewline
27 & 29096 & 26651.4350208536 & 1247.05484536475 & 2444.5649791464 & -0.882823073454282 \tabularnewline
28 & 26482 & 26083.6978991895 & 367.493641551635 & 398.302100810479 & -0.608103734693225 \tabularnewline
29 & 22405 & 26319.7769794379 & 303.19324958791 & -3914.77697943795 & -0.0443024160915607 \tabularnewline
30 & 27044 & 25817.5742423243 & -91.227837338334 & 1226.4257576757 & -0.269655334946142 \tabularnewline
31 & 17970 & 21602.5780615616 & -2104.92347908123 & -3632.57806156159 & -1.37682344777417 \tabularnewline
32 & 18730 & 19759.9225270495 & -1976.89122823787 & -1029.92252704946 & 0.0877484655676938 \tabularnewline
33 & 19684 & 18318.0297126147 & -1715.42208819939 & 1365.9702873853 & 0.179359381648078 \tabularnewline
34 & 19785 & 16370.9629013692 & -1828.66141618983 & 3414.03709863076 & -0.077695110328347 \tabularnewline
35 & 18479 & 17692.5620884627 & -289.879399954303 & 786.437911537346 & 1.05670711850978 \tabularnewline
36 & 10698 & 18138.7150162829 & 69.696047029169 & -7440.7150162829 & 0.247479031943035 \tabularnewline
37 & 31956 & 23764.0841280832 & 2788.24887253282 & 8191.91587191676 & 1.8706676840445 \tabularnewline
38 & 29506 & 29092.1493213489 & 4027.60057321021 & 413.850678651081 & 0.848002732211462 \tabularnewline
39 & 34506 & 32248.8809169439 & 3605.67405017206 & 2257.11908305605 & -0.288666585293711 \tabularnewline
40 & 27165 & 29681.1770239054 & 617.433506084196 & -2516.17702390538 & -2.05735468034303 \tabularnewline
41 & 26736 & 29778.3258637963 & 364.350265418488 & -3042.32586379626 & -0.17430263086117 \tabularnewline
42 & 23691 & 23811.5921987584 & -2721.31134715396 & -120.592198758363 & -2.11544564455643 \tabularnewline
43 & 18157 & 21100.1115898896 & -2716.52816758589 & -2943.11158988959 & 0.00327304663945432 \tabularnewline
44 & 17328 & 18284.8278370536 & -2764.51200622069 & -956.827837053579 & -0.0328679746865906 \tabularnewline
45 & 18205 & 16196.0630878301 & -2436.20072242296 & 2008.93691216986 & 0.225156364196841 \tabularnewline
46 & 20995 & 17041.4817046502 & -841.637143650251 & 3953.5182953498 & 1.09444070399215 \tabularnewline
47 & 17382 & 17150.3468270701 & -379.713517185379 & 231.653172929865 & 0.317369819034716 \tabularnewline
48 & 9367 & 18676.3965326998 & 547.316984630072 & -9309.3965326998 & 0.637433920144565 \tabularnewline
49 & 31124 & 22814.1116753729 & 2295.14737793078 & 8309.88832462707 & 1.20007575058211 \tabularnewline
50 & 26551 & 25761.0102974431 & 2611.71108081836 & 789.989702556944 & 0.216709054194197 \tabularnewline
51 & 30651 & 26900.7812026231 & 1899.69548010354 & 3750.21879737695 & -0.487645385788549 \tabularnewline
52 & 25859 & 27990.5879822702 & 1508.24231731052 & -2131.58798227022 & -0.2690959440572 \tabularnewline
53 & 25100 & 26773.807452881 & 187.378996447071 & -1673.80745288103 & -0.908922851010369 \tabularnewline
54 & 25778 & 25929.1190478969 & -313.810950606371 & -151.119047896935 & -0.343984937948234 \tabularnewline
55 & 20418 & 23857.1357457246 & -1166.84705259402 & -3439.13574572458 & -0.584207483168731 \tabularnewline
56 & 18688 & 20657.7921073125 & -2151.35322136518 & -1969.79210731248 & -0.674280897650774 \tabularnewline
57 & 20424 & 19060.1900979504 & -1883.35131348562 & 1363.80990204964 & 0.183761235129989 \tabularnewline
58 & 24776 & 19961.1418024234 & -535.818369073787 & 4814.85819757664 & 0.925086773851587 \tabularnewline
59 & 19814 & 20438.026705414 & -45.3659375627472 & -624.026705414013 & 0.337018949556687 \tabularnewline
60 & 12738 & 22675.8354535334 & 1061.62281234123 & -9937.83545353344 & 0.760683058345722 \tabularnewline
61 & 31566 & 23795.6230169492 & 1089.83280941663 & 7770.37698305079 & 0.0193537559141595 \tabularnewline
62 & 30111 & 27632.2046298552 & 2419.55305098262 & 2478.79537014481 & 0.910600280274049 \tabularnewline
63 & 30019 & 27424.7108195739 & 1151.24043906613 & 2594.2891804261 & -0.869069542329468 \tabularnewline
64 & 31934 & 31443.6313372599 & 2534.91514941043 & 490.368662740143 & 0.950530719347023 \tabularnewline
65 & 25826 & 29391.1525439304 & 317.335125140292 & -3565.1525439304 & -1.52496652118284 \tabularnewline
66 & 26835 & 26809.4430710926 & -1086.28064775948 & 25.5569289073651 & -0.963697357874404 \tabularnewline
67 & 20205 & 23458.147856514 & -2182.4166615121 & -3253.14785651397 & -0.751122983402322 \tabularnewline
68 & 17789 & 20273.8898930891 & -2666.48518493185 & -2484.8898930891 & -0.331567149409735 \tabularnewline
69 & 20520 & 19320.7733431684 & -1839.58315781802 & 1199.22665683155 & 0.566935581227682 \tabularnewline
70 & 22518 & 18071.6119185777 & -1554.6620451087 & 4446.38808142226 & 0.195608479914645 \tabularnewline
71 & 15572 & 16923.6835349286 & -1358.21542188005 & -1351.6835349286 & 0.134982435235803 \tabularnewline
72 & 11509 & 19836.2460455606 & 706.787143468736 & -8327.24604556057 & 1.41842718367463 \tabularnewline
73 & 25447 & 19628.2687863865 & 264.429108684158 & 5818.73121361346 & -0.303393890663685 \tabularnewline
74 & 24090 & 20637.0681093318 & 623.837430724692 & 3452.93189066824 & 0.246192740508689 \tabularnewline
75 & 27786 & 24742.2607045372 & 2301.42089169511 & 3043.73929546278 & 1.14982269207412 \tabularnewline
76 & 26195 & 25022.483543241 & 1327.87850460597 & 1172.51645675902 & -0.668539730547871 \tabularnewline
77 & 20516 & 23679.8324597026 & 39.8456708709375 & -3163.83245970261 & -0.885312009111272 \tabularnewline
78 & 22759 & 22113.0981708124 & -736.030694326834 & 645.901829187568 & -0.532730011919173 \tabularnewline
79 & 19028 & 21634.7581063078 & -611.612160398208 & -2606.7581063078 & 0.0852871052821534 \tabularnewline
80 & 16971 & 20354.3949683974 & -934.051594808297 & -3383.39496839739 & -0.220897776081142 \tabularnewline
81 & 20036 & 19036.5520929539 & -1118.87350012147 & 999.447907046087 & -0.126715897967117 \tabularnewline
82 & 22485 & 18251.6346566049 & -958.074787118192 & 4233.3653433951 & 0.110388168502649 \tabularnewline
83 & 18730 & 20300.4474713421 & 490.970715153167 & -1570.44747134215 & 0.995514662440418 \tabularnewline
84 & 14538 & 22239.3318675064 & 1189.43281575743 & -7701.3318675064 & 0.479639832666078 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107252&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]31514[/C][C]31514[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]27071[/C][C]28488.2212273871[/C][C]-1092.63511967583[/C][C]-1417.22122738713[/C][C]-1.46598300534814[/C][/ROW]
[ROW][C]3[/C][C]29462[/C][C]28256.6349716561[/C][C]-703.143393727116[/C][C]1205.36502834395[/C][C]0.311490301374225[/C][/ROW]
[ROW][C]4[/C][C]26105[/C][C]26681.1863445095[/C][C]-1151.42398132673[/C][C]-576.186344509478[/C][C]-0.309348729200586[/C][/ROW]
[ROW][C]5[/C][C]22397[/C][C]23266.1456560182[/C][C]-2311.8923233458[/C][C]-869.145656018176[/C][C]-0.773902918482607[/C][/ROW]
[ROW][C]6[/C][C]23843[/C][C]22753.2425014063[/C][C]-1398.55116318587[/C][C]1089.75749859373[/C][C]0.621016281464426[/C][/ROW]
[ROW][C]7[/C][C]21705[/C][C]21809.5519609645[/C][C]-1167.00062176535[/C][C]-104.551960964524[/C][C]0.158797925588194[/C][/ROW]
[ROW][C]8[/C][C]18089[/C][C]18952.9154866462[/C][C]-2029.74342518538[/C][C]-863.915486646162[/C][C]-0.591919734718616[/C][/ROW]
[ROW][C]9[/C][C]20764[/C][C]19423.4582449803[/C][C]-752.009215500641[/C][C]1340.54175501972[/C][C]0.876493082066904[/C][/ROW]
[ROW][C]10[/C][C]25316[/C][C]23548.0975279228[/C][C]1739.87741108158[/C][C]1767.90247207722[/C][C]1.7094055674526[/C][/ROW]
[ROW][C]11[/C][C]17704[/C][C]20588.7166309384[/C][C]-660.821193441494[/C][C]-2884.71663093844[/C][C]-1.64686183446903[/C][/ROW]
[ROW][C]12[/C][C]15548[/C][C]16432.9158986701[/C][C]-2446.0898610964[/C][C]-884.915898670094[/C][C]-1.22467857740565[/C][/ROW]
[ROW][C]13[/C][C]28029[/C][C]21943.6580911247[/C][C]1543.87381828001[/C][C]6085.34190887531[/C][C]2.88637957046384[/C][/ROW]
[ROW][C]14[/C][C]29383[/C][C]29386.9431055603[/C][C]4496.42366564184[/C][C]-3.94310556029283[/C][C]1.99736580372881[/C][/ROW]
[ROW][C]15[/C][C]36438[/C][C]35122.8636057356[/C][C]5090.31100382709[/C][C]1315.13639426435[/C][C]0.403221519417058[/C][/ROW]
[ROW][C]16[/C][C]32034[/C][C]34834.2123772179[/C][C]2469.73346978688[/C][C]-2800.21237721788[/C][C]-1.83277717885368[/C][/ROW]
[ROW][C]17[/C][C]22679[/C][C]28115.1589124382[/C][C]-2084.13305485642[/C][C]-5436.15891243816[/C][C]-3.12236828533848[/C][/ROW]
[ROW][C]18[/C][C]24319[/C][C]23375.7949989356[/C][C]-3394.70451896832[/C][C]943.20500106442[/C][C]-0.89166031005516[/C][/ROW]
[ROW][C]19[/C][C]18004[/C][C]18142.4003279398[/C][C]-4299.60362375608[/C][C]-138.400327939775[/C][C]-0.619028939551949[/C][/ROW]
[ROW][C]20[/C][C]17537[/C][C]17756.7072176541[/C][C]-2369.74896154116[/C][C]-219.707217654075[/C][C]1.3238400442228[/C][/ROW]
[ROW][C]21[/C][C]20366[/C][C]19234.9677852415[/C][C]-468.607282096917[/C][C]1131.03221475852[/C][C]1.30421222697792[/C][/ROW]
[ROW][C]22[/C][C]22782[/C][C]18961.2397152154[/C][C]-372.290443850608[/C][C]3820.76028478456[/C][C]0.0660722955655084[/C][/ROW]
[ROW][C]23[/C][C]19169[/C][C]20082.6207999373[/C][C]364.866350614665[/C][C]-913.620799937298[/C][C]0.505788839182921[/C][/ROW]
[ROW][C]24[/C][C]13807[/C][C]19011.6124477755[/C][C]-342.283221651173[/C][C]-5204.61244777549[/C][C]-0.486851166435701[/C][/ROW]
[ROW][C]25[/C][C]29743[/C][C]23961.3608030342[/C][C]2270.02751697578[/C][C]5781.63919696579[/C][C]1.81086866717164[/C][/ROW]
[ROW][C]26[/C][C]25591[/C][C]26781.7124992614[/C][C]2540.7681319951[/C][C]-1190.71249926141[/C][C]0.185062379425685[/C][/ROW]
[ROW][C]27[/C][C]29096[/C][C]26651.4350208536[/C][C]1247.05484536475[/C][C]2444.5649791464[/C][C]-0.882823073454282[/C][/ROW]
[ROW][C]28[/C][C]26482[/C][C]26083.6978991895[/C][C]367.493641551635[/C][C]398.302100810479[/C][C]-0.608103734693225[/C][/ROW]
[ROW][C]29[/C][C]22405[/C][C]26319.7769794379[/C][C]303.19324958791[/C][C]-3914.77697943795[/C][C]-0.0443024160915607[/C][/ROW]
[ROW][C]30[/C][C]27044[/C][C]25817.5742423243[/C][C]-91.227837338334[/C][C]1226.4257576757[/C][C]-0.269655334946142[/C][/ROW]
[ROW][C]31[/C][C]17970[/C][C]21602.5780615616[/C][C]-2104.92347908123[/C][C]-3632.57806156159[/C][C]-1.37682344777417[/C][/ROW]
[ROW][C]32[/C][C]18730[/C][C]19759.9225270495[/C][C]-1976.89122823787[/C][C]-1029.92252704946[/C][C]0.0877484655676938[/C][/ROW]
[ROW][C]33[/C][C]19684[/C][C]18318.0297126147[/C][C]-1715.42208819939[/C][C]1365.9702873853[/C][C]0.179359381648078[/C][/ROW]
[ROW][C]34[/C][C]19785[/C][C]16370.9629013692[/C][C]-1828.66141618983[/C][C]3414.03709863076[/C][C]-0.077695110328347[/C][/ROW]
[ROW][C]35[/C][C]18479[/C][C]17692.5620884627[/C][C]-289.879399954303[/C][C]786.437911537346[/C][C]1.05670711850978[/C][/ROW]
[ROW][C]36[/C][C]10698[/C][C]18138.7150162829[/C][C]69.696047029169[/C][C]-7440.7150162829[/C][C]0.247479031943035[/C][/ROW]
[ROW][C]37[/C][C]31956[/C][C]23764.0841280832[/C][C]2788.24887253282[/C][C]8191.91587191676[/C][C]1.8706676840445[/C][/ROW]
[ROW][C]38[/C][C]29506[/C][C]29092.1493213489[/C][C]4027.60057321021[/C][C]413.850678651081[/C][C]0.848002732211462[/C][/ROW]
[ROW][C]39[/C][C]34506[/C][C]32248.8809169439[/C][C]3605.67405017206[/C][C]2257.11908305605[/C][C]-0.288666585293711[/C][/ROW]
[ROW][C]40[/C][C]27165[/C][C]29681.1770239054[/C][C]617.433506084196[/C][C]-2516.17702390538[/C][C]-2.05735468034303[/C][/ROW]
[ROW][C]41[/C][C]26736[/C][C]29778.3258637963[/C][C]364.350265418488[/C][C]-3042.32586379626[/C][C]-0.17430263086117[/C][/ROW]
[ROW][C]42[/C][C]23691[/C][C]23811.5921987584[/C][C]-2721.31134715396[/C][C]-120.592198758363[/C][C]-2.11544564455643[/C][/ROW]
[ROW][C]43[/C][C]18157[/C][C]21100.1115898896[/C][C]-2716.52816758589[/C][C]-2943.11158988959[/C][C]0.00327304663945432[/C][/ROW]
[ROW][C]44[/C][C]17328[/C][C]18284.8278370536[/C][C]-2764.51200622069[/C][C]-956.827837053579[/C][C]-0.0328679746865906[/C][/ROW]
[ROW][C]45[/C][C]18205[/C][C]16196.0630878301[/C][C]-2436.20072242296[/C][C]2008.93691216986[/C][C]0.225156364196841[/C][/ROW]
[ROW][C]46[/C][C]20995[/C][C]17041.4817046502[/C][C]-841.637143650251[/C][C]3953.5182953498[/C][C]1.09444070399215[/C][/ROW]
[ROW][C]47[/C][C]17382[/C][C]17150.3468270701[/C][C]-379.713517185379[/C][C]231.653172929865[/C][C]0.317369819034716[/C][/ROW]
[ROW][C]48[/C][C]9367[/C][C]18676.3965326998[/C][C]547.316984630072[/C][C]-9309.3965326998[/C][C]0.637433920144565[/C][/ROW]
[ROW][C]49[/C][C]31124[/C][C]22814.1116753729[/C][C]2295.14737793078[/C][C]8309.88832462707[/C][C]1.20007575058211[/C][/ROW]
[ROW][C]50[/C][C]26551[/C][C]25761.0102974431[/C][C]2611.71108081836[/C][C]789.989702556944[/C][C]0.216709054194197[/C][/ROW]
[ROW][C]51[/C][C]30651[/C][C]26900.7812026231[/C][C]1899.69548010354[/C][C]3750.21879737695[/C][C]-0.487645385788549[/C][/ROW]
[ROW][C]52[/C][C]25859[/C][C]27990.5879822702[/C][C]1508.24231731052[/C][C]-2131.58798227022[/C][C]-0.2690959440572[/C][/ROW]
[ROW][C]53[/C][C]25100[/C][C]26773.807452881[/C][C]187.378996447071[/C][C]-1673.80745288103[/C][C]-0.908922851010369[/C][/ROW]
[ROW][C]54[/C][C]25778[/C][C]25929.1190478969[/C][C]-313.810950606371[/C][C]-151.119047896935[/C][C]-0.343984937948234[/C][/ROW]
[ROW][C]55[/C][C]20418[/C][C]23857.1357457246[/C][C]-1166.84705259402[/C][C]-3439.13574572458[/C][C]-0.584207483168731[/C][/ROW]
[ROW][C]56[/C][C]18688[/C][C]20657.7921073125[/C][C]-2151.35322136518[/C][C]-1969.79210731248[/C][C]-0.674280897650774[/C][/ROW]
[ROW][C]57[/C][C]20424[/C][C]19060.1900979504[/C][C]-1883.35131348562[/C][C]1363.80990204964[/C][C]0.183761235129989[/C][/ROW]
[ROW][C]58[/C][C]24776[/C][C]19961.1418024234[/C][C]-535.818369073787[/C][C]4814.85819757664[/C][C]0.925086773851587[/C][/ROW]
[ROW][C]59[/C][C]19814[/C][C]20438.026705414[/C][C]-45.3659375627472[/C][C]-624.026705414013[/C][C]0.337018949556687[/C][/ROW]
[ROW][C]60[/C][C]12738[/C][C]22675.8354535334[/C][C]1061.62281234123[/C][C]-9937.83545353344[/C][C]0.760683058345722[/C][/ROW]
[ROW][C]61[/C][C]31566[/C][C]23795.6230169492[/C][C]1089.83280941663[/C][C]7770.37698305079[/C][C]0.0193537559141595[/C][/ROW]
[ROW][C]62[/C][C]30111[/C][C]27632.2046298552[/C][C]2419.55305098262[/C][C]2478.79537014481[/C][C]0.910600280274049[/C][/ROW]
[ROW][C]63[/C][C]30019[/C][C]27424.7108195739[/C][C]1151.24043906613[/C][C]2594.2891804261[/C][C]-0.869069542329468[/C][/ROW]
[ROW][C]64[/C][C]31934[/C][C]31443.6313372599[/C][C]2534.91514941043[/C][C]490.368662740143[/C][C]0.950530719347023[/C][/ROW]
[ROW][C]65[/C][C]25826[/C][C]29391.1525439304[/C][C]317.335125140292[/C][C]-3565.1525439304[/C][C]-1.52496652118284[/C][/ROW]
[ROW][C]66[/C][C]26835[/C][C]26809.4430710926[/C][C]-1086.28064775948[/C][C]25.5569289073651[/C][C]-0.963697357874404[/C][/ROW]
[ROW][C]67[/C][C]20205[/C][C]23458.147856514[/C][C]-2182.4166615121[/C][C]-3253.14785651397[/C][C]-0.751122983402322[/C][/ROW]
[ROW][C]68[/C][C]17789[/C][C]20273.8898930891[/C][C]-2666.48518493185[/C][C]-2484.8898930891[/C][C]-0.331567149409735[/C][/ROW]
[ROW][C]69[/C][C]20520[/C][C]19320.7733431684[/C][C]-1839.58315781802[/C][C]1199.22665683155[/C][C]0.566935581227682[/C][/ROW]
[ROW][C]70[/C][C]22518[/C][C]18071.6119185777[/C][C]-1554.6620451087[/C][C]4446.38808142226[/C][C]0.195608479914645[/C][/ROW]
[ROW][C]71[/C][C]15572[/C][C]16923.6835349286[/C][C]-1358.21542188005[/C][C]-1351.6835349286[/C][C]0.134982435235803[/C][/ROW]
[ROW][C]72[/C][C]11509[/C][C]19836.2460455606[/C][C]706.787143468736[/C][C]-8327.24604556057[/C][C]1.41842718367463[/C][/ROW]
[ROW][C]73[/C][C]25447[/C][C]19628.2687863865[/C][C]264.429108684158[/C][C]5818.73121361346[/C][C]-0.303393890663685[/C][/ROW]
[ROW][C]74[/C][C]24090[/C][C]20637.0681093318[/C][C]623.837430724692[/C][C]3452.93189066824[/C][C]0.246192740508689[/C][/ROW]
[ROW][C]75[/C][C]27786[/C][C]24742.2607045372[/C][C]2301.42089169511[/C][C]3043.73929546278[/C][C]1.14982269207412[/C][/ROW]
[ROW][C]76[/C][C]26195[/C][C]25022.483543241[/C][C]1327.87850460597[/C][C]1172.51645675902[/C][C]-0.668539730547871[/C][/ROW]
[ROW][C]77[/C][C]20516[/C][C]23679.8324597026[/C][C]39.8456708709375[/C][C]-3163.83245970261[/C][C]-0.885312009111272[/C][/ROW]
[ROW][C]78[/C][C]22759[/C][C]22113.0981708124[/C][C]-736.030694326834[/C][C]645.901829187568[/C][C]-0.532730011919173[/C][/ROW]
[ROW][C]79[/C][C]19028[/C][C]21634.7581063078[/C][C]-611.612160398208[/C][C]-2606.7581063078[/C][C]0.0852871052821534[/C][/ROW]
[ROW][C]80[/C][C]16971[/C][C]20354.3949683974[/C][C]-934.051594808297[/C][C]-3383.39496839739[/C][C]-0.220897776081142[/C][/ROW]
[ROW][C]81[/C][C]20036[/C][C]19036.5520929539[/C][C]-1118.87350012147[/C][C]999.447907046087[/C][C]-0.126715897967117[/C][/ROW]
[ROW][C]82[/C][C]22485[/C][C]18251.6346566049[/C][C]-958.074787118192[/C][C]4233.3653433951[/C][C]0.110388168502649[/C][/ROW]
[ROW][C]83[/C][C]18730[/C][C]20300.4474713421[/C][C]490.970715153167[/C][C]-1570.44747134215[/C][C]0.995514662440418[/C][/ROW]
[ROW][C]84[/C][C]14538[/C][C]22239.3318675064[/C][C]1189.43281575743[/C][C]-7701.3318675064[/C][C]0.479639832666078[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107252&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
13151431514000
22707128488.2212273871-1092.63511967583-1417.22122738713-1.46598300534814
32946228256.6349716561-703.1433937271161205.365028343950.311490301374225
42610526681.1863445095-1151.42398132673-576.186344509478-0.309348729200586
52239723266.1456560182-2311.8923233458-869.145656018176-0.773902918482607
62384322753.2425014063-1398.551163185871089.757498593730.621016281464426
72170521809.5519609645-1167.00062176535-104.5519609645240.158797925588194
81808918952.9154866462-2029.74342518538-863.915486646162-0.591919734718616
92076419423.4582449803-752.0092155006411340.541755019720.876493082066904
102531623548.09752792281739.877411081581767.902472077221.7094055674526
111770420588.7166309384-660.821193441494-2884.71663093844-1.64686183446903
121554816432.9158986701-2446.0898610964-884.915898670094-1.22467857740565
132802921943.65809112471543.873818280016085.341908875312.88637957046384
142938329386.94310556034496.42366564184-3.943105560292831.99736580372881
153643835122.86360573565090.311003827091315.136394264350.403221519417058
163203434834.21237721792469.73346978688-2800.21237721788-1.83277717885368
172267928115.1589124382-2084.13305485642-5436.15891243816-3.12236828533848
182431923375.7949989356-3394.70451896832943.20500106442-0.89166031005516
191800418142.4003279398-4299.60362375608-138.400327939775-0.619028939551949
201753717756.7072176541-2369.74896154116-219.7072176540751.3238400442228
212036619234.9677852415-468.6072820969171131.032214758521.30421222697792
222278218961.2397152154-372.2904438506083820.760284784560.0660722955655084
231916920082.6207999373364.866350614665-913.6207999372980.505788839182921
241380719011.6124477755-342.283221651173-5204.61244777549-0.486851166435701
252974323961.36080303422270.027516975785781.639196965791.81086866717164
262559126781.71249926142540.7681319951-1190.712499261410.185062379425685
272909626651.43502085361247.054845364752444.5649791464-0.882823073454282
282648226083.6978991895367.493641551635398.302100810479-0.608103734693225
292240526319.7769794379303.19324958791-3914.77697943795-0.0443024160915607
302704425817.5742423243-91.2278373383341226.4257576757-0.269655334946142
311797021602.5780615616-2104.92347908123-3632.57806156159-1.37682344777417
321873019759.9225270495-1976.89122823787-1029.922527049460.0877484655676938
331968418318.0297126147-1715.422088199391365.97028738530.179359381648078
341978516370.9629013692-1828.661416189833414.03709863076-0.077695110328347
351847917692.5620884627-289.879399954303786.4379115373461.05670711850978
361069818138.715016282969.696047029169-7440.71501628290.247479031943035
373195623764.08412808322788.248872532828191.915871916761.8706676840445
382950629092.14932134894027.60057321021413.8506786510810.848002732211462
393450632248.88091694393605.674050172062257.11908305605-0.288666585293711
402716529681.1770239054617.433506084196-2516.17702390538-2.05735468034303
412673629778.3258637963364.350265418488-3042.32586379626-0.17430263086117
422369123811.5921987584-2721.31134715396-120.592198758363-2.11544564455643
431815721100.1115898896-2716.52816758589-2943.111589889590.00327304663945432
441732818284.8278370536-2764.51200622069-956.827837053579-0.0328679746865906
451820516196.0630878301-2436.200722422962008.936912169860.225156364196841
462099517041.4817046502-841.6371436502513953.51829534981.09444070399215
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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')