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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 computationTue, 29 Nov 2011 10:08:10 -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/2011/Nov/29/t13225793152q3l2fzaw8z79ms.htm/, Retrieved Fri, 26 Apr 2024 21:54:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148488, Retrieved Fri, 26 Apr 2024 21:54:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Exponential Smoothing] [WS 8 - Exponentia...] [2011-11-26 14:02:40] [ae1339cb5a7cf28362d01e7220b4a16c]
- RMP     [Structural Time Series Models] [WS 8 - Structural...] [2011-11-29 15:08:10] [e598b5cd83fcb010b35e92a01f5e81e9] [Current]
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Dataseries X:
6827
6178
7084
8162
8462
9644
10466
10748
9963
8194
6848
7027
7269
6775
7819
8371
9069
10248
11030
10882
10333
9109
7685
7602
8350
7829
8829
9948
10638
11253
11424
11391
10665
9396
7775
7933
8186
7444
8484
9864
10252
12282
11637
11577
12417
9637
8094
9280
8334
7899
9994
10078
10801
12950
12222
12246
13281
10366
8730
9614
8639
8772
10894
10455
11179
10588
10794
12770
13812
10857
9290
10925
9491
8919
11607
8852
12537
14759
13667
13731
15110
12185
10645
12161
10840
10436
13589
13402
13103
14933
14147
14057
16234
12389
11595
12772




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148488&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148488&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 time4 seconds
R Server'George Udny Yule' @ yule.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
168276827000
261786235.72999270304-192.914148908771-57.7299927030367-0.574778092098935
370846955.50691953209334.606296533422128.4930804679130.9538944681889
481628120.63402639137826.26739519132741.36597360863310.823301541277965
584628573.66793402803606.739517911771-111.667934028034-0.376797232327223
696449598.81968469442853.33639563675345.1803153055820.425320804035137
71046610503.9755014856883.903917138369-37.97550148563860.052732264577415
81074810852.2204843756567.889994483986-104.220484375591-0.545153212126783
9996310145.319519337-184.186556616909-182.31951933696-1.29739964949048
1081948387.24798659343-1112.73487158904-193.247986593436-1.60182984821943
1168486867.33507380275-1352.96202904091-19.3350738027491-0.414413629970516
1270276852.67849009587-563.383141181918174.3215099041321.36209519806918
1372696784.04251618974-277.873452943877484.9574838102570.542688179580451
1467756897.39771992526-65.4262019615746-122.3977199252570.344507876996103
1578197688.12542307039412.435112818936130.8745769296150.841018598885998
1683718255.31470298329501.252960143033115.6852970167150.151923149837434
1790699181.87973408127744.146118788751-112.8797340812710.41642292054081
181024810220.8450518377912.5611185381827.15494816225310.290349657686622
191103011093.7282858134889.86682994477-63.7282858134036-0.039149949425144
201088211038.4993853859349.139747826682-156.499385385912-0.932800726657837
211033310409.4326964557-210.544409122109-76.4326964556916-0.96550732115794
2291099296.553310914-726.87349256115-187.553310913991-0.890734970516916
2376857947.81169549259-1082.59953669638-262.811695492587-0.6136517214444
2476027366.71647630799-796.580466493244235.2835236920110.494508075257402
2583507702.49561818632-149.710127787967647.504381813681.14589954339696
2678298046.4646283109125.092140363575-217.4646283108950.464231627684668
2788298642.0418033827386.404227511379186.9581966173060.455121301756072
2899489792.20445302027819.166096856033155.795546979730.746459162968399
291063810832.5143319813944.295975242479-194.5143319812680.214681101112405
301125311374.4995848404716.934734517116-121.499584840365-0.391714297428987
311142411481.5397378824371.86315877725-57.5397378824455-0.595275894478062
321139111464.5845864368151.722906867989-73.584586436779-0.379759343895379
331066510719.4914553813-356.136473170424-54.4914553812788-0.876112289432719
3493969536.19361396675-824.512272252149-140.193613966747-0.808019869562062
3577758154.81760783177-1139.49111701944-379.817607831766-0.543386837795194
3679337726.71773643306-737.89676746733206.2822635669360.69535544626191
3781867518.40456721236-437.948572242858667.5954327876380.522227987867013
3874447649.99974257391-119.630473014432-205.9997425739130.54388137147883
3984848335.6184067746327.981860105382148.3815932254060.775645333606321
4098649625.77465183575869.502747637474238.2253481642540.936528835896411
411025210436.6615840814836.482923623066-184.661584081443-0.0567459665672158
421228212171.62309404581341.74841778163110.3769059542330.870137073292612
431163711982.5343575657480.288166082358-345.534357565677-1.48593000090446
441157711622.52624051427.00504257298383-45.5262405141669-0.816457437310893
451241712164.0706528641308.168244824137252.9293471358930.519541857456758
46963710069.1894102792-1045.30889673125-432.189410279201-2.33487215087513
4780948594.35064617398-1286.92486647949-500.350646173982-0.41694328082703
4892808831.65222902209-430.054602642194448.3477709779071.48341156420906
4983347865.6264998204-732.023820870034468.373500179595-0.522778199148365
5078998069.0628060525-209.17389717089-170.0628060524960.897111139040052
5199949722.77828621286827.291026457948271.2217137871351.7920509846485
521007810005.0217870332521.71075265214772.978212966824-0.528686619674509
531080111109.9716738589849.32193239081-308.9716738589240.563864053811946
541295012477.30015178341139.8358493214472.6998482165770.500265113333087
551222212657.3485216335601.458939363645-435.348521633458-0.928488890433205
561224612553.8293004073205.678347481354-307.829300407298-0.68275734858204
571328112515.587828082768.6935788160723765.412171917334-0.236313171214965
581036610964.4377065568-840.614988979107-598.437706556776-1.56863612058181
5987309565.77647272977-1153.54148960164-835.776472729768-0.540152347530339
6096148888.03648756044-886.687745158945725.9635124395590.461662698314086
6186398306.69097774468-715.229886097319332.3090222553210.296184992372512
6287729064.77622567783107.659102020865-292.776225677831.41464504595703
631089410315.1180733201743.712778570766578.881926679871.09861881294545
641045510636.6469828813507.56229035795-181.646982881307-0.408443907660823
651117911563.6989309542742.703207826479-384.6989309542010.405145219549018
661058810333.1973317282-362.048224938464254.802668271792-1.90266618033131
671079410934.7550628115177.353239211776-140.7550628115480.93010641655596
681277012772.69444033971107.52767922141-2.694440339649831.60458917420967
691381212882.6239912593548.552834795247929.376008740682-0.964282326734982
701085711596.4557278404-479.027397924592-739.455727840367-1.7727526210467
71929010281.9989678473-946.58665763173-991.998967847328-0.807208833157217
721092510077.6234113837-530.981463486219847.376588616280.718515435366873
7394919508.84514698945-552.157863010545-17.8451469894512-0.0365463777996079
7489199392.1390125585-309.128009657809-473.1390125585030.418228980365114
751160710680.2984699094580.099475460884926.7015300906371.53513980462796
7688529446.29732329504-433.122713724884-594.29732329504-1.75172504389035
771253711898.71043005211181.78528971975638.2895699478682.78440659676266
781475914556.48275505452007.17020187189202.5172449454521.42187859993131
791366714626.1060407251924.119556382343-959.106040725063-1.86731902150251
801373113840.9570360208-31.7421395023314-109.957036020751-1.64881360198429
811511013765.2139182815-56.35441683662331344.78608171852-0.0424583215289912
821218512882.0810928955-518.647147586901-697.081092895548-0.797597968857966
831064511838.5683251325-812.006832985063-1193.56832513248-0.506501872990439
841216111209.6174664803-709.627728812156951.3825335196750.176899126314597
851084010860.0449003649-508.222056494953-20.044900364910.347430180389698
861043611042.1974075085-123.175698081157-606.1974075084680.663032155516951
871358912040.5488640944501.1606790154281548.451135905561.07755125086267
881340214376.82353535751525.06359377105-974.8235353575061.76952408971205
891310313355.2993731159101.610022826094-252.299373115925-2.45536278085661
901493314172.9510583809501.657289987117760.0489416190620.689338579794586
911414714779.8046642828560.398875480505-632.8046642828260.101271198989018
921405714355.880927425210.6449918016082-298.880927425212-0.948236869005214
931623414626.3368021679155.7747678264061607.663197832090.25036269421458
941238913220.2354483861-716.452101621121-831.235448386101-1.50499023884941
951159512705.962709745-603.560446666479-1110.9627097450.194914981901618
961277211890.367218367-722.030503926116881.632781632989-0.20461625961283

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 6827 & 6827 & 0 & 0 & 0 \tabularnewline
2 & 6178 & 6235.72999270304 & -192.914148908771 & -57.7299927030367 & -0.574778092098935 \tabularnewline
3 & 7084 & 6955.50691953209 & 334.606296533422 & 128.493080467913 & 0.9538944681889 \tabularnewline
4 & 8162 & 8120.63402639137 & 826.267395191327 & 41.3659736086331 & 0.823301541277965 \tabularnewline
5 & 8462 & 8573.66793402803 & 606.739517911771 & -111.667934028034 & -0.376797232327223 \tabularnewline
6 & 9644 & 9598.81968469442 & 853.336395636753 & 45.180315305582 & 0.425320804035137 \tabularnewline
7 & 10466 & 10503.9755014856 & 883.903917138369 & -37.9755014856386 & 0.052732264577415 \tabularnewline
8 & 10748 & 10852.2204843756 & 567.889994483986 & -104.220484375591 & -0.545153212126783 \tabularnewline
9 & 9963 & 10145.319519337 & -184.186556616909 & -182.31951933696 & -1.29739964949048 \tabularnewline
10 & 8194 & 8387.24798659343 & -1112.73487158904 & -193.247986593436 & -1.60182984821943 \tabularnewline
11 & 6848 & 6867.33507380275 & -1352.96202904091 & -19.3350738027491 & -0.414413629970516 \tabularnewline
12 & 7027 & 6852.67849009587 & -563.383141181918 & 174.321509904132 & 1.36209519806918 \tabularnewline
13 & 7269 & 6784.04251618974 & -277.873452943877 & 484.957483810257 & 0.542688179580451 \tabularnewline
14 & 6775 & 6897.39771992526 & -65.4262019615746 & -122.397719925257 & 0.344507876996103 \tabularnewline
15 & 7819 & 7688.12542307039 & 412.435112818936 & 130.874576929615 & 0.841018598885998 \tabularnewline
16 & 8371 & 8255.31470298329 & 501.252960143033 & 115.685297016715 & 0.151923149837434 \tabularnewline
17 & 9069 & 9181.87973408127 & 744.146118788751 & -112.879734081271 & 0.41642292054081 \tabularnewline
18 & 10248 & 10220.8450518377 & 912.56111853818 & 27.1549481622531 & 0.290349657686622 \tabularnewline
19 & 11030 & 11093.7282858134 & 889.86682994477 & -63.7282858134036 & -0.039149949425144 \tabularnewline
20 & 10882 & 11038.4993853859 & 349.139747826682 & -156.499385385912 & -0.932800726657837 \tabularnewline
21 & 10333 & 10409.4326964557 & -210.544409122109 & -76.4326964556916 & -0.96550732115794 \tabularnewline
22 & 9109 & 9296.553310914 & -726.87349256115 & -187.553310913991 & -0.890734970516916 \tabularnewline
23 & 7685 & 7947.81169549259 & -1082.59953669638 & -262.811695492587 & -0.6136517214444 \tabularnewline
24 & 7602 & 7366.71647630799 & -796.580466493244 & 235.283523692011 & 0.494508075257402 \tabularnewline
25 & 8350 & 7702.49561818632 & -149.710127787967 & 647.50438181368 & 1.14589954339696 \tabularnewline
26 & 7829 & 8046.4646283109 & 125.092140363575 & -217.464628310895 & 0.464231627684668 \tabularnewline
27 & 8829 & 8642.0418033827 & 386.404227511379 & 186.958196617306 & 0.455121301756072 \tabularnewline
28 & 9948 & 9792.20445302027 & 819.166096856033 & 155.79554697973 & 0.746459162968399 \tabularnewline
29 & 10638 & 10832.5143319813 & 944.295975242479 & -194.514331981268 & 0.214681101112405 \tabularnewline
30 & 11253 & 11374.4995848404 & 716.934734517116 & -121.499584840365 & -0.391714297428987 \tabularnewline
31 & 11424 & 11481.5397378824 & 371.86315877725 & -57.5397378824455 & -0.595275894478062 \tabularnewline
32 & 11391 & 11464.5845864368 & 151.722906867989 & -73.584586436779 & -0.379759343895379 \tabularnewline
33 & 10665 & 10719.4914553813 & -356.136473170424 & -54.4914553812788 & -0.876112289432719 \tabularnewline
34 & 9396 & 9536.19361396675 & -824.512272252149 & -140.193613966747 & -0.808019869562062 \tabularnewline
35 & 7775 & 8154.81760783177 & -1139.49111701944 & -379.817607831766 & -0.543386837795194 \tabularnewline
36 & 7933 & 7726.71773643306 & -737.89676746733 & 206.282263566936 & 0.69535544626191 \tabularnewline
37 & 8186 & 7518.40456721236 & -437.948572242858 & 667.595432787638 & 0.522227987867013 \tabularnewline
38 & 7444 & 7649.99974257391 & -119.630473014432 & -205.999742573913 & 0.54388137147883 \tabularnewline
39 & 8484 & 8335.6184067746 & 327.981860105382 & 148.381593225406 & 0.775645333606321 \tabularnewline
40 & 9864 & 9625.77465183575 & 869.502747637474 & 238.225348164254 & 0.936528835896411 \tabularnewline
41 & 10252 & 10436.6615840814 & 836.482923623066 & -184.661584081443 & -0.0567459665672158 \tabularnewline
42 & 12282 & 12171.6230940458 & 1341.74841778163 & 110.376905954233 & 0.870137073292612 \tabularnewline
43 & 11637 & 11982.5343575657 & 480.288166082358 & -345.534357565677 & -1.48593000090446 \tabularnewline
44 & 11577 & 11622.5262405142 & 7.00504257298383 & -45.5262405141669 & -0.816457437310893 \tabularnewline
45 & 12417 & 12164.0706528641 & 308.168244824137 & 252.929347135893 & 0.519541857456758 \tabularnewline
46 & 9637 & 10069.1894102792 & -1045.30889673125 & -432.189410279201 & -2.33487215087513 \tabularnewline
47 & 8094 & 8594.35064617398 & -1286.92486647949 & -500.350646173982 & -0.41694328082703 \tabularnewline
48 & 9280 & 8831.65222902209 & -430.054602642194 & 448.347770977907 & 1.48341156420906 \tabularnewline
49 & 8334 & 7865.6264998204 & -732.023820870034 & 468.373500179595 & -0.522778199148365 \tabularnewline
50 & 7899 & 8069.0628060525 & -209.17389717089 & -170.062806052496 & 0.897111139040052 \tabularnewline
51 & 9994 & 9722.77828621286 & 827.291026457948 & 271.221713787135 & 1.7920509846485 \tabularnewline
52 & 10078 & 10005.0217870332 & 521.710752652147 & 72.978212966824 & -0.528686619674509 \tabularnewline
53 & 10801 & 11109.9716738589 & 849.32193239081 & -308.971673858924 & 0.563864053811946 \tabularnewline
54 & 12950 & 12477.3001517834 & 1139.8358493214 & 472.699848216577 & 0.500265113333087 \tabularnewline
55 & 12222 & 12657.3485216335 & 601.458939363645 & -435.348521633458 & -0.928488890433205 \tabularnewline
56 & 12246 & 12553.8293004073 & 205.678347481354 & -307.829300407298 & -0.68275734858204 \tabularnewline
57 & 13281 & 12515.5878280827 & 68.6935788160723 & 765.412171917334 & -0.236313171214965 \tabularnewline
58 & 10366 & 10964.4377065568 & -840.614988979107 & -598.437706556776 & -1.56863612058181 \tabularnewline
59 & 8730 & 9565.77647272977 & -1153.54148960164 & -835.776472729768 & -0.540152347530339 \tabularnewline
60 & 9614 & 8888.03648756044 & -886.687745158945 & 725.963512439559 & 0.461662698314086 \tabularnewline
61 & 8639 & 8306.69097774468 & -715.229886097319 & 332.309022255321 & 0.296184992372512 \tabularnewline
62 & 8772 & 9064.77622567783 & 107.659102020865 & -292.77622567783 & 1.41464504595703 \tabularnewline
63 & 10894 & 10315.1180733201 & 743.712778570766 & 578.88192667987 & 1.09861881294545 \tabularnewline
64 & 10455 & 10636.6469828813 & 507.56229035795 & -181.646982881307 & -0.408443907660823 \tabularnewline
65 & 11179 & 11563.6989309542 & 742.703207826479 & -384.698930954201 & 0.405145219549018 \tabularnewline
66 & 10588 & 10333.1973317282 & -362.048224938464 & 254.802668271792 & -1.90266618033131 \tabularnewline
67 & 10794 & 10934.7550628115 & 177.353239211776 & -140.755062811548 & 0.93010641655596 \tabularnewline
68 & 12770 & 12772.6944403397 & 1107.52767922141 & -2.69444033964983 & 1.60458917420967 \tabularnewline
69 & 13812 & 12882.6239912593 & 548.552834795247 & 929.376008740682 & -0.964282326734982 \tabularnewline
70 & 10857 & 11596.4557278404 & -479.027397924592 & -739.455727840367 & -1.7727526210467 \tabularnewline
71 & 9290 & 10281.9989678473 & -946.58665763173 & -991.998967847328 & -0.807208833157217 \tabularnewline
72 & 10925 & 10077.6234113837 & -530.981463486219 & 847.37658861628 & 0.718515435366873 \tabularnewline
73 & 9491 & 9508.84514698945 & -552.157863010545 & -17.8451469894512 & -0.0365463777996079 \tabularnewline
74 & 8919 & 9392.1390125585 & -309.128009657809 & -473.139012558503 & 0.418228980365114 \tabularnewline
75 & 11607 & 10680.2984699094 & 580.099475460884 & 926.701530090637 & 1.53513980462796 \tabularnewline
76 & 8852 & 9446.29732329504 & -433.122713724884 & -594.29732329504 & -1.75172504389035 \tabularnewline
77 & 12537 & 11898.7104300521 & 1181.78528971975 & 638.289569947868 & 2.78440659676266 \tabularnewline
78 & 14759 & 14556.4827550545 & 2007.17020187189 & 202.517244945452 & 1.42187859993131 \tabularnewline
79 & 13667 & 14626.1060407251 & 924.119556382343 & -959.106040725063 & -1.86731902150251 \tabularnewline
80 & 13731 & 13840.9570360208 & -31.7421395023314 & -109.957036020751 & -1.64881360198429 \tabularnewline
81 & 15110 & 13765.2139182815 & -56.3544168366233 & 1344.78608171852 & -0.0424583215289912 \tabularnewline
82 & 12185 & 12882.0810928955 & -518.647147586901 & -697.081092895548 & -0.797597968857966 \tabularnewline
83 & 10645 & 11838.5683251325 & -812.006832985063 & -1193.56832513248 & -0.506501872990439 \tabularnewline
84 & 12161 & 11209.6174664803 & -709.627728812156 & 951.382533519675 & 0.176899126314597 \tabularnewline
85 & 10840 & 10860.0449003649 & -508.222056494953 & -20.04490036491 & 0.347430180389698 \tabularnewline
86 & 10436 & 11042.1974075085 & -123.175698081157 & -606.197407508468 & 0.663032155516951 \tabularnewline
87 & 13589 & 12040.5488640944 & 501.160679015428 & 1548.45113590556 & 1.07755125086267 \tabularnewline
88 & 13402 & 14376.8235353575 & 1525.06359377105 & -974.823535357506 & 1.76952408971205 \tabularnewline
89 & 13103 & 13355.2993731159 & 101.610022826094 & -252.299373115925 & -2.45536278085661 \tabularnewline
90 & 14933 & 14172.9510583809 & 501.657289987117 & 760.048941619062 & 0.689338579794586 \tabularnewline
91 & 14147 & 14779.8046642828 & 560.398875480505 & -632.804664282826 & 0.101271198989018 \tabularnewline
92 & 14057 & 14355.8809274252 & 10.6449918016082 & -298.880927425212 & -0.948236869005214 \tabularnewline
93 & 16234 & 14626.3368021679 & 155.774767826406 & 1607.66319783209 & 0.25036269421458 \tabularnewline
94 & 12389 & 13220.2354483861 & -716.452101621121 & -831.235448386101 & -1.50499023884941 \tabularnewline
95 & 11595 & 12705.962709745 & -603.560446666479 & -1110.962709745 & 0.194914981901618 \tabularnewline
96 & 12772 & 11890.367218367 & -722.030503926116 & 881.632781632989 & -0.20461625961283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148488&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]6827[/C][C]6827[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]6178[/C][C]6235.72999270304[/C][C]-192.914148908771[/C][C]-57.7299927030367[/C][C]-0.574778092098935[/C][/ROW]
[ROW][C]3[/C][C]7084[/C][C]6955.50691953209[/C][C]334.606296533422[/C][C]128.493080467913[/C][C]0.9538944681889[/C][/ROW]
[ROW][C]4[/C][C]8162[/C][C]8120.63402639137[/C][C]826.267395191327[/C][C]41.3659736086331[/C][C]0.823301541277965[/C][/ROW]
[ROW][C]5[/C][C]8462[/C][C]8573.66793402803[/C][C]606.739517911771[/C][C]-111.667934028034[/C][C]-0.376797232327223[/C][/ROW]
[ROW][C]6[/C][C]9644[/C][C]9598.81968469442[/C][C]853.336395636753[/C][C]45.180315305582[/C][C]0.425320804035137[/C][/ROW]
[ROW][C]7[/C][C]10466[/C][C]10503.9755014856[/C][C]883.903917138369[/C][C]-37.9755014856386[/C][C]0.052732264577415[/C][/ROW]
[ROW][C]8[/C][C]10748[/C][C]10852.2204843756[/C][C]567.889994483986[/C][C]-104.220484375591[/C][C]-0.545153212126783[/C][/ROW]
[ROW][C]9[/C][C]9963[/C][C]10145.319519337[/C][C]-184.186556616909[/C][C]-182.31951933696[/C][C]-1.29739964949048[/C][/ROW]
[ROW][C]10[/C][C]8194[/C][C]8387.24798659343[/C][C]-1112.73487158904[/C][C]-193.247986593436[/C][C]-1.60182984821943[/C][/ROW]
[ROW][C]11[/C][C]6848[/C][C]6867.33507380275[/C][C]-1352.96202904091[/C][C]-19.3350738027491[/C][C]-0.414413629970516[/C][/ROW]
[ROW][C]12[/C][C]7027[/C][C]6852.67849009587[/C][C]-563.383141181918[/C][C]174.321509904132[/C][C]1.36209519806918[/C][/ROW]
[ROW][C]13[/C][C]7269[/C][C]6784.04251618974[/C][C]-277.873452943877[/C][C]484.957483810257[/C][C]0.542688179580451[/C][/ROW]
[ROW][C]14[/C][C]6775[/C][C]6897.39771992526[/C][C]-65.4262019615746[/C][C]-122.397719925257[/C][C]0.344507876996103[/C][/ROW]
[ROW][C]15[/C][C]7819[/C][C]7688.12542307039[/C][C]412.435112818936[/C][C]130.874576929615[/C][C]0.841018598885998[/C][/ROW]
[ROW][C]16[/C][C]8371[/C][C]8255.31470298329[/C][C]501.252960143033[/C][C]115.685297016715[/C][C]0.151923149837434[/C][/ROW]
[ROW][C]17[/C][C]9069[/C][C]9181.87973408127[/C][C]744.146118788751[/C][C]-112.879734081271[/C][C]0.41642292054081[/C][/ROW]
[ROW][C]18[/C][C]10248[/C][C]10220.8450518377[/C][C]912.56111853818[/C][C]27.1549481622531[/C][C]0.290349657686622[/C][/ROW]
[ROW][C]19[/C][C]11030[/C][C]11093.7282858134[/C][C]889.86682994477[/C][C]-63.7282858134036[/C][C]-0.039149949425144[/C][/ROW]
[ROW][C]20[/C][C]10882[/C][C]11038.4993853859[/C][C]349.139747826682[/C][C]-156.499385385912[/C][C]-0.932800726657837[/C][/ROW]
[ROW][C]21[/C][C]10333[/C][C]10409.4326964557[/C][C]-210.544409122109[/C][C]-76.4326964556916[/C][C]-0.96550732115794[/C][/ROW]
[ROW][C]22[/C][C]9109[/C][C]9296.553310914[/C][C]-726.87349256115[/C][C]-187.553310913991[/C][C]-0.890734970516916[/C][/ROW]
[ROW][C]23[/C][C]7685[/C][C]7947.81169549259[/C][C]-1082.59953669638[/C][C]-262.811695492587[/C][C]-0.6136517214444[/C][/ROW]
[ROW][C]24[/C][C]7602[/C][C]7366.71647630799[/C][C]-796.580466493244[/C][C]235.283523692011[/C][C]0.494508075257402[/C][/ROW]
[ROW][C]25[/C][C]8350[/C][C]7702.49561818632[/C][C]-149.710127787967[/C][C]647.50438181368[/C][C]1.14589954339696[/C][/ROW]
[ROW][C]26[/C][C]7829[/C][C]8046.4646283109[/C][C]125.092140363575[/C][C]-217.464628310895[/C][C]0.464231627684668[/C][/ROW]
[ROW][C]27[/C][C]8829[/C][C]8642.0418033827[/C][C]386.404227511379[/C][C]186.958196617306[/C][C]0.455121301756072[/C][/ROW]
[ROW][C]28[/C][C]9948[/C][C]9792.20445302027[/C][C]819.166096856033[/C][C]155.79554697973[/C][C]0.746459162968399[/C][/ROW]
[ROW][C]29[/C][C]10638[/C][C]10832.5143319813[/C][C]944.295975242479[/C][C]-194.514331981268[/C][C]0.214681101112405[/C][/ROW]
[ROW][C]30[/C][C]11253[/C][C]11374.4995848404[/C][C]716.934734517116[/C][C]-121.499584840365[/C][C]-0.391714297428987[/C][/ROW]
[ROW][C]31[/C][C]11424[/C][C]11481.5397378824[/C][C]371.86315877725[/C][C]-57.5397378824455[/C][C]-0.595275894478062[/C][/ROW]
[ROW][C]32[/C][C]11391[/C][C]11464.5845864368[/C][C]151.722906867989[/C][C]-73.584586436779[/C][C]-0.379759343895379[/C][/ROW]
[ROW][C]33[/C][C]10665[/C][C]10719.4914553813[/C][C]-356.136473170424[/C][C]-54.4914553812788[/C][C]-0.876112289432719[/C][/ROW]
[ROW][C]34[/C][C]9396[/C][C]9536.19361396675[/C][C]-824.512272252149[/C][C]-140.193613966747[/C][C]-0.808019869562062[/C][/ROW]
[ROW][C]35[/C][C]7775[/C][C]8154.81760783177[/C][C]-1139.49111701944[/C][C]-379.817607831766[/C][C]-0.543386837795194[/C][/ROW]
[ROW][C]36[/C][C]7933[/C][C]7726.71773643306[/C][C]-737.89676746733[/C][C]206.282263566936[/C][C]0.69535544626191[/C][/ROW]
[ROW][C]37[/C][C]8186[/C][C]7518.40456721236[/C][C]-437.948572242858[/C][C]667.595432787638[/C][C]0.522227987867013[/C][/ROW]
[ROW][C]38[/C][C]7444[/C][C]7649.99974257391[/C][C]-119.630473014432[/C][C]-205.999742573913[/C][C]0.54388137147883[/C][/ROW]
[ROW][C]39[/C][C]8484[/C][C]8335.6184067746[/C][C]327.981860105382[/C][C]148.381593225406[/C][C]0.775645333606321[/C][/ROW]
[ROW][C]40[/C][C]9864[/C][C]9625.77465183575[/C][C]869.502747637474[/C][C]238.225348164254[/C][C]0.936528835896411[/C][/ROW]
[ROW][C]41[/C][C]10252[/C][C]10436.6615840814[/C][C]836.482923623066[/C][C]-184.661584081443[/C][C]-0.0567459665672158[/C][/ROW]
[ROW][C]42[/C][C]12282[/C][C]12171.6230940458[/C][C]1341.74841778163[/C][C]110.376905954233[/C][C]0.870137073292612[/C][/ROW]
[ROW][C]43[/C][C]11637[/C][C]11982.5343575657[/C][C]480.288166082358[/C][C]-345.534357565677[/C][C]-1.48593000090446[/C][/ROW]
[ROW][C]44[/C][C]11577[/C][C]11622.5262405142[/C][C]7.00504257298383[/C][C]-45.5262405141669[/C][C]-0.816457437310893[/C][/ROW]
[ROW][C]45[/C][C]12417[/C][C]12164.0706528641[/C][C]308.168244824137[/C][C]252.929347135893[/C][C]0.519541857456758[/C][/ROW]
[ROW][C]46[/C][C]9637[/C][C]10069.1894102792[/C][C]-1045.30889673125[/C][C]-432.189410279201[/C][C]-2.33487215087513[/C][/ROW]
[ROW][C]47[/C][C]8094[/C][C]8594.35064617398[/C][C]-1286.92486647949[/C][C]-500.350646173982[/C][C]-0.41694328082703[/C][/ROW]
[ROW][C]48[/C][C]9280[/C][C]8831.65222902209[/C][C]-430.054602642194[/C][C]448.347770977907[/C][C]1.48341156420906[/C][/ROW]
[ROW][C]49[/C][C]8334[/C][C]7865.6264998204[/C][C]-732.023820870034[/C][C]468.373500179595[/C][C]-0.522778199148365[/C][/ROW]
[ROW][C]50[/C][C]7899[/C][C]8069.0628060525[/C][C]-209.17389717089[/C][C]-170.062806052496[/C][C]0.897111139040052[/C][/ROW]
[ROW][C]51[/C][C]9994[/C][C]9722.77828621286[/C][C]827.291026457948[/C][C]271.221713787135[/C][C]1.7920509846485[/C][/ROW]
[ROW][C]52[/C][C]10078[/C][C]10005.0217870332[/C][C]521.710752652147[/C][C]72.978212966824[/C][C]-0.528686619674509[/C][/ROW]
[ROW][C]53[/C][C]10801[/C][C]11109.9716738589[/C][C]849.32193239081[/C][C]-308.971673858924[/C][C]0.563864053811946[/C][/ROW]
[ROW][C]54[/C][C]12950[/C][C]12477.3001517834[/C][C]1139.8358493214[/C][C]472.699848216577[/C][C]0.500265113333087[/C][/ROW]
[ROW][C]55[/C][C]12222[/C][C]12657.3485216335[/C][C]601.458939363645[/C][C]-435.348521633458[/C][C]-0.928488890433205[/C][/ROW]
[ROW][C]56[/C][C]12246[/C][C]12553.8293004073[/C][C]205.678347481354[/C][C]-307.829300407298[/C][C]-0.68275734858204[/C][/ROW]
[ROW][C]57[/C][C]13281[/C][C]12515.5878280827[/C][C]68.6935788160723[/C][C]765.412171917334[/C][C]-0.236313171214965[/C][/ROW]
[ROW][C]58[/C][C]10366[/C][C]10964.4377065568[/C][C]-840.614988979107[/C][C]-598.437706556776[/C][C]-1.56863612058181[/C][/ROW]
[ROW][C]59[/C][C]8730[/C][C]9565.77647272977[/C][C]-1153.54148960164[/C][C]-835.776472729768[/C][C]-0.540152347530339[/C][/ROW]
[ROW][C]60[/C][C]9614[/C][C]8888.03648756044[/C][C]-886.687745158945[/C][C]725.963512439559[/C][C]0.461662698314086[/C][/ROW]
[ROW][C]61[/C][C]8639[/C][C]8306.69097774468[/C][C]-715.229886097319[/C][C]332.309022255321[/C][C]0.296184992372512[/C][/ROW]
[ROW][C]62[/C][C]8772[/C][C]9064.77622567783[/C][C]107.659102020865[/C][C]-292.77622567783[/C][C]1.41464504595703[/C][/ROW]
[ROW][C]63[/C][C]10894[/C][C]10315.1180733201[/C][C]743.712778570766[/C][C]578.88192667987[/C][C]1.09861881294545[/C][/ROW]
[ROW][C]64[/C][C]10455[/C][C]10636.6469828813[/C][C]507.56229035795[/C][C]-181.646982881307[/C][C]-0.408443907660823[/C][/ROW]
[ROW][C]65[/C][C]11179[/C][C]11563.6989309542[/C][C]742.703207826479[/C][C]-384.698930954201[/C][C]0.405145219549018[/C][/ROW]
[ROW][C]66[/C][C]10588[/C][C]10333.1973317282[/C][C]-362.048224938464[/C][C]254.802668271792[/C][C]-1.90266618033131[/C][/ROW]
[ROW][C]67[/C][C]10794[/C][C]10934.7550628115[/C][C]177.353239211776[/C][C]-140.755062811548[/C][C]0.93010641655596[/C][/ROW]
[ROW][C]68[/C][C]12770[/C][C]12772.6944403397[/C][C]1107.52767922141[/C][C]-2.69444033964983[/C][C]1.60458917420967[/C][/ROW]
[ROW][C]69[/C][C]13812[/C][C]12882.6239912593[/C][C]548.552834795247[/C][C]929.376008740682[/C][C]-0.964282326734982[/C][/ROW]
[ROW][C]70[/C][C]10857[/C][C]11596.4557278404[/C][C]-479.027397924592[/C][C]-739.455727840367[/C][C]-1.7727526210467[/C][/ROW]
[ROW][C]71[/C][C]9290[/C][C]10281.9989678473[/C][C]-946.58665763173[/C][C]-991.998967847328[/C][C]-0.807208833157217[/C][/ROW]
[ROW][C]72[/C][C]10925[/C][C]10077.6234113837[/C][C]-530.981463486219[/C][C]847.37658861628[/C][C]0.718515435366873[/C][/ROW]
[ROW][C]73[/C][C]9491[/C][C]9508.84514698945[/C][C]-552.157863010545[/C][C]-17.8451469894512[/C][C]-0.0365463777996079[/C][/ROW]
[ROW][C]74[/C][C]8919[/C][C]9392.1390125585[/C][C]-309.128009657809[/C][C]-473.139012558503[/C][C]0.418228980365114[/C][/ROW]
[ROW][C]75[/C][C]11607[/C][C]10680.2984699094[/C][C]580.099475460884[/C][C]926.701530090637[/C][C]1.53513980462796[/C][/ROW]
[ROW][C]76[/C][C]8852[/C][C]9446.29732329504[/C][C]-433.122713724884[/C][C]-594.29732329504[/C][C]-1.75172504389035[/C][/ROW]
[ROW][C]77[/C][C]12537[/C][C]11898.7104300521[/C][C]1181.78528971975[/C][C]638.289569947868[/C][C]2.78440659676266[/C][/ROW]
[ROW][C]78[/C][C]14759[/C][C]14556.4827550545[/C][C]2007.17020187189[/C][C]202.517244945452[/C][C]1.42187859993131[/C][/ROW]
[ROW][C]79[/C][C]13667[/C][C]14626.1060407251[/C][C]924.119556382343[/C][C]-959.106040725063[/C][C]-1.86731902150251[/C][/ROW]
[ROW][C]80[/C][C]13731[/C][C]13840.9570360208[/C][C]-31.7421395023314[/C][C]-109.957036020751[/C][C]-1.64881360198429[/C][/ROW]
[ROW][C]81[/C][C]15110[/C][C]13765.2139182815[/C][C]-56.3544168366233[/C][C]1344.78608171852[/C][C]-0.0424583215289912[/C][/ROW]
[ROW][C]82[/C][C]12185[/C][C]12882.0810928955[/C][C]-518.647147586901[/C][C]-697.081092895548[/C][C]-0.797597968857966[/C][/ROW]
[ROW][C]83[/C][C]10645[/C][C]11838.5683251325[/C][C]-812.006832985063[/C][C]-1193.56832513248[/C][C]-0.506501872990439[/C][/ROW]
[ROW][C]84[/C][C]12161[/C][C]11209.6174664803[/C][C]-709.627728812156[/C][C]951.382533519675[/C][C]0.176899126314597[/C][/ROW]
[ROW][C]85[/C][C]10840[/C][C]10860.0449003649[/C][C]-508.222056494953[/C][C]-20.04490036491[/C][C]0.347430180389698[/C][/ROW]
[ROW][C]86[/C][C]10436[/C][C]11042.1974075085[/C][C]-123.175698081157[/C][C]-606.197407508468[/C][C]0.663032155516951[/C][/ROW]
[ROW][C]87[/C][C]13589[/C][C]12040.5488640944[/C][C]501.160679015428[/C][C]1548.45113590556[/C][C]1.07755125086267[/C][/ROW]
[ROW][C]88[/C][C]13402[/C][C]14376.8235353575[/C][C]1525.06359377105[/C][C]-974.823535357506[/C][C]1.76952408971205[/C][/ROW]
[ROW][C]89[/C][C]13103[/C][C]13355.2993731159[/C][C]101.610022826094[/C][C]-252.299373115925[/C][C]-2.45536278085661[/C][/ROW]
[ROW][C]90[/C][C]14933[/C][C]14172.9510583809[/C][C]501.657289987117[/C][C]760.048941619062[/C][C]0.689338579794586[/C][/ROW]
[ROW][C]91[/C][C]14147[/C][C]14779.8046642828[/C][C]560.398875480505[/C][C]-632.804664282826[/C][C]0.101271198989018[/C][/ROW]
[ROW][C]92[/C][C]14057[/C][C]14355.8809274252[/C][C]10.6449918016082[/C][C]-298.880927425212[/C][C]-0.948236869005214[/C][/ROW]
[ROW][C]93[/C][C]16234[/C][C]14626.3368021679[/C][C]155.774767826406[/C][C]1607.66319783209[/C][C]0.25036269421458[/C][/ROW]
[ROW][C]94[/C][C]12389[/C][C]13220.2354483861[/C][C]-716.452101621121[/C][C]-831.235448386101[/C][C]-1.50499023884941[/C][/ROW]
[ROW][C]95[/C][C]11595[/C][C]12705.962709745[/C][C]-603.560446666479[/C][C]-1110.962709745[/C][C]0.194914981901618[/C][/ROW]
[ROW][C]96[/C][C]12772[/C][C]11890.367218367[/C][C]-722.030503926116[/C][C]881.632781632989[/C][C]-0.20461625961283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148488&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
168276827000
261786235.72999270304-192.914148908771-57.7299927030367-0.574778092098935
370846955.50691953209334.606296533422128.4930804679130.9538944681889
481628120.63402639137826.26739519132741.36597360863310.823301541277965
584628573.66793402803606.739517911771-111.667934028034-0.376797232327223
696449598.81968469442853.33639563675345.1803153055820.425320804035137
71046610503.9755014856883.903917138369-37.97550148563860.052732264577415
81074810852.2204843756567.889994483986-104.220484375591-0.545153212126783
9996310145.319519337-184.186556616909-182.31951933696-1.29739964949048
1081948387.24798659343-1112.73487158904-193.247986593436-1.60182984821943
1168486867.33507380275-1352.96202904091-19.3350738027491-0.414413629970516
1270276852.67849009587-563.383141181918174.3215099041321.36209519806918
1372696784.04251618974-277.873452943877484.9574838102570.542688179580451
1467756897.39771992526-65.4262019615746-122.3977199252570.344507876996103
1578197688.12542307039412.435112818936130.8745769296150.841018598885998
1683718255.31470298329501.252960143033115.6852970167150.151923149837434
1790699181.87973408127744.146118788751-112.8797340812710.41642292054081
181024810220.8450518377912.5611185381827.15494816225310.290349657686622
191103011093.7282858134889.86682994477-63.7282858134036-0.039149949425144
201088211038.4993853859349.139747826682-156.499385385912-0.932800726657837
211033310409.4326964557-210.544409122109-76.4326964556916-0.96550732115794
2291099296.553310914-726.87349256115-187.553310913991-0.890734970516916
2376857947.81169549259-1082.59953669638-262.811695492587-0.6136517214444
2476027366.71647630799-796.580466493244235.2835236920110.494508075257402
2583507702.49561818632-149.710127787967647.504381813681.14589954339696
2678298046.4646283109125.092140363575-217.4646283108950.464231627684668
2788298642.0418033827386.404227511379186.9581966173060.455121301756072
2899489792.20445302027819.166096856033155.795546979730.746459162968399
291063810832.5143319813944.295975242479-194.5143319812680.214681101112405
301125311374.4995848404716.934734517116-121.499584840365-0.391714297428987
311142411481.5397378824371.86315877725-57.5397378824455-0.595275894478062
321139111464.5845864368151.722906867989-73.584586436779-0.379759343895379
331066510719.4914553813-356.136473170424-54.4914553812788-0.876112289432719
3493969536.19361396675-824.512272252149-140.193613966747-0.808019869562062
3577758154.81760783177-1139.49111701944-379.817607831766-0.543386837795194
3679337726.71773643306-737.89676746733206.2822635669360.69535544626191
3781867518.40456721236-437.948572242858667.5954327876380.522227987867013
3874447649.99974257391-119.630473014432-205.9997425739130.54388137147883
3984848335.6184067746327.981860105382148.3815932254060.775645333606321
4098649625.77465183575869.502747637474238.2253481642540.936528835896411
411025210436.6615840814836.482923623066-184.661584081443-0.0567459665672158
421228212171.62309404581341.74841778163110.3769059542330.870137073292612
431163711982.5343575657480.288166082358-345.534357565677-1.48593000090446
441157711622.52624051427.00504257298383-45.5262405141669-0.816457437310893
451241712164.0706528641308.168244824137252.9293471358930.519541857456758
46963710069.1894102792-1045.30889673125-432.189410279201-2.33487215087513
4780948594.35064617398-1286.92486647949-500.350646173982-0.41694328082703
4892808831.65222902209-430.054602642194448.3477709779071.48341156420906
4983347865.6264998204-732.023820870034468.373500179595-0.522778199148365
5078998069.0628060525-209.17389717089-170.0628060524960.897111139040052
5199949722.77828621286827.291026457948271.2217137871351.7920509846485
521007810005.0217870332521.71075265214772.978212966824-0.528686619674509
531080111109.9716738589849.32193239081-308.9716738589240.563864053811946
541295012477.30015178341139.8358493214472.6998482165770.500265113333087
551222212657.3485216335601.458939363645-435.348521633458-0.928488890433205
561224612553.8293004073205.678347481354-307.829300407298-0.68275734858204
571328112515.587828082768.6935788160723765.412171917334-0.236313171214965
581036610964.4377065568-840.614988979107-598.437706556776-1.56863612058181
5987309565.77647272977-1153.54148960164-835.776472729768-0.540152347530339
6096148888.03648756044-886.687745158945725.9635124395590.461662698314086
6186398306.69097774468-715.229886097319332.3090222553210.296184992372512
6287729064.77622567783107.659102020865-292.776225677831.41464504595703
631089410315.1180733201743.712778570766578.881926679871.09861881294545
641045510636.6469828813507.56229035795-181.646982881307-0.408443907660823
651117911563.6989309542742.703207826479-384.6989309542010.405145219549018
661058810333.1973317282-362.048224938464254.802668271792-1.90266618033131
671079410934.7550628115177.353239211776-140.7550628115480.93010641655596
681277012772.69444033971107.52767922141-2.694440339649831.60458917420967
691381212882.6239912593548.552834795247929.376008740682-0.964282326734982
701085711596.4557278404-479.027397924592-739.455727840367-1.7727526210467
71929010281.9989678473-946.58665763173-991.998967847328-0.807208833157217
721092510077.6234113837-530.981463486219847.376588616280.718515435366873
7394919508.84514698945-552.157863010545-17.8451469894512-0.0365463777996079
7489199392.1390125585-309.128009657809-473.1390125585030.418228980365114
751160710680.2984699094580.099475460884926.7015300906371.53513980462796
7688529446.29732329504-433.122713724884-594.29732329504-1.75172504389035
771253711898.71043005211181.78528971975638.2895699478682.78440659676266
781475914556.48275505452007.17020187189202.5172449454521.42187859993131
791366714626.1060407251924.119556382343-959.106040725063-1.86731902150251
801373113840.9570360208-31.7421395023314-109.957036020751-1.64881360198429
811511013765.2139182815-56.35441683662331344.78608171852-0.0424583215289912
821218512882.0810928955-518.647147586901-697.081092895548-0.797597968857966
831064511838.5683251325-812.006832985063-1193.56832513248-0.506501872990439
841216111209.6174664803-709.627728812156951.3825335196750.176899126314597
851084010860.0449003649-508.222056494953-20.044900364910.347430180389698
861043611042.1974075085-123.175698081157-606.1974075084680.663032155516951
871358912040.5488640944501.1606790154281548.451135905561.07755125086267
881340214376.82353535751525.06359377105-974.8235353575061.76952408971205
891310313355.2993731159101.610022826094-252.299373115925-2.45536278085661
901493314172.9510583809501.657289987117760.0489416190620.689338579794586
911414714779.8046642828560.398875480505-632.8046642828260.101271198989018
921405714355.880927425210.6449918016082-298.880927425212-0.948236869005214
931623414626.3368021679155.7747678264061607.663197832090.25036269421458
941238913220.2354483861-716.452101621121-831.235448386101-1.50499023884941
951159512705.962709745-603.560446666479-1110.9627097450.194914981901618
961277211890.367218367-722.030503926116881.632781632989-0.20461625961283



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')