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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 16 Dec 2009 07:18:57 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/16/t1260973190zmhjwsrg6x6sogq.htm/, Retrieved Tue, 30 Apr 2024 13:02:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68368, Retrieved Tue, 30 Apr 2024 13:02:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Structural Time Series Models] [] [2009-11-27 15:02:30] [b98453cac15ba1066b407e146608df68]
- R  D      [Structural Time Series Models] [] [2009-12-16 14:18:57] [c88a5f1b97e332c6387d668c465455af] [Current]
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Dataseries X:
19915
19843
19761
20858
21968
23061
22661
22269
21857
21568
21274
20987
19683
19381
19071
20772
22485
24181
23479
22782
22067
21489
20903
20330
19736
19483
19242
20334
21423
22523
21986
21462
20908
20575
20237
19904
19610
19251
18941
20450
21946
23409
22741
22069
21539
21189
20960
20704
19697
19598
19456
20316
21083
22158
21469
20892
20578
20233
19947
20049




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68368&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68368&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'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11991519915000
21984319843.9943178957-71.0878571363803-0.994317895669007-0.118782435020626
31976119760.7309832625-82.79602668467610.26901673746091-0.0197979137823644
42085820822.07852034641008.5146906316035.92147965359161.80930311820643
52196821973.6653171121145.05557553730-5.665317111981930.226651828859217
62306123064.75001113971093.53921294631-3.75001113973822-0.0855081607236897
72266122707.9502449778-290.808999241377-46.9502449778206-2.29777874350131
82226922262.8157970249-438.111539458916.18420297505747-0.244496714917772
92185721855.5771135006-408.6435652994051.422886499428030.0489117356031883
102156821565.2986171617-295.6647061171762.701382838319890.187525347244533
112127421275.6281967602-289.943191324189-1.628196760194850.00949672404276561
122098720987.8237163819-287.901802787922-0.8237163818640510.00338835156325109
131968319713.5671243585-1229.09328510059-30.5671243585169-1.56288797494588
141938119310.5884745786-440.18826518659770.41152542137851.31544285068647
151907119115.7896343943-211.956638228701-44.78963439425920.382814742405743
162077220656.37726587781417.39023402376115.6227341222092.70100817048867
172248522522.43573348421834.19199958307-37.43573348418310.691915353464615
182418124141.50930331621634.2847814599939.4906966838404-0.331810701648741
192347923624.4298294729-364.968905476902-145.429829472927-3.31841868158201
202278222775.8528421517-814.373498158816.14715784833346-0.74593380816506
212206722056.2694797685-726.28766210580110.73052023154120.146207240116577
222148921478.6668899565-588.11838222658910.33311004346000.2293370881841
232090320933.5700212574-548.139154619983-30.57002125740860.0663586319469552
242033020275.3975838953-650.38812623818154.6024161047364-0.169715975389280
251973619789.5287823-497.55170229978-53.5287823000060.253817091961421
261948319358.6951226839-435.517830545865124.3048773160610.103160025034256
271924219360.8158324495-34.3595406185888-118.8158324495190.669222744032911
282033420212.0385840219779.028274343585121.9614159780931.34931367886376
292142321503.31693496861248.84227704478-80.31693496862570.779813140841009
302252322377.3750178998904.978549369957145.624982100197-0.570766242281175
312198622155.8645338846-128.625359802679-169.864533884586-1.71560132897775
322146221477.5015573102-633.022576485718-15.5015573102070-0.837212478640571
332090820895.7119109632-586.01572558229812.28808903684170.0780232366798802
342057520556.1559478777-359.88405017702918.84405212232270.375339451984497
352023720254.9294447219-306.063858675002-17.92944472189360.0893324737880168
361990419868.3104800743-379.96973858059835.6895199256944-0.122671609575035
371961019643.4889262014-237.656303722162-33.48892620142130.236367687042846
381925119137.8444870749-483.583490040556113.155512925058-0.408410334452181
391894119081.9069836659-94.1583856891801-140.9069836659200.648006001669356
402045020312.19681775111114.45402029051137.8031822489112.00602414980104
412194622015.4320284251651.00213349906-69.43202842501290.890443159575436
422340923226.22704624251249.74236237062182.772953757488-0.666052638284688
432274122952.3107253375-139.244469042447-211.310725337477-2.30546715178198
442206922111.0188322956-779.231719801418-42.0188322955578-1.06226889600168
452153921523.7632597185-604.2288316279615.23674028150330.290474498005167
462118921158.6678057946-386.23592165702130.33219420542570.361830646819602
472096020961.7651676648-213.639583325585-1.765167664814490.286481276815693
482070420701.5272083712-256.1133256693082.47279162876521-0.0705004529366505
491969719728.6285921275-909.418221897572-31.6285921275245-1.08506379752044
501959819424.1086607690-358.094964831915173.8913392309550.915106239945355
511945619651.4821299626173.136185246543-195.4821299625650.882959553042894
522031620235.6739290013546.74631062888580.32607099870730.620273994884358
532108321160.3438615304889.878027274081-77.34386153039650.569405803683436
542215821880.0884890089735.391152201141277.911510991058-0.256435028722037
552146921665.6914020749-127.163385140742-196.691402074868-1.43168603319950
562089220968.7377564075-644.621381960067-76.7377564074897-0.858890526294234
572057820556.6979809134-433.40393198805321.30201908655550.350584443613076
582023320221.433729847-344.27838873054411.56627015301510.147933217242533
591994719964.3764038498-265.069359148595-17.37640384977800.131473536489530
602004919945.1468305703-41.8454646103689103.85316942970.370530374304483

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 19915 & 19915 & 0 & 0 & 0 \tabularnewline
2 & 19843 & 19843.9943178957 & -71.0878571363803 & -0.994317895669007 & -0.118782435020626 \tabularnewline
3 & 19761 & 19760.7309832625 & -82.7960266846761 & 0.26901673746091 & -0.0197979137823644 \tabularnewline
4 & 20858 & 20822.0785203464 & 1008.51469063160 & 35.9214796535916 & 1.80930311820643 \tabularnewline
5 & 21968 & 21973.665317112 & 1145.05557553730 & -5.66531711198193 & 0.226651828859217 \tabularnewline
6 & 23061 & 23064.7500111397 & 1093.53921294631 & -3.75001113973822 & -0.0855081607236897 \tabularnewline
7 & 22661 & 22707.9502449778 & -290.808999241377 & -46.9502449778206 & -2.29777874350131 \tabularnewline
8 & 22269 & 22262.8157970249 & -438.11153945891 & 6.18420297505747 & -0.244496714917772 \tabularnewline
9 & 21857 & 21855.5771135006 & -408.643565299405 & 1.42288649942803 & 0.0489117356031883 \tabularnewline
10 & 21568 & 21565.2986171617 & -295.664706117176 & 2.70138283831989 & 0.187525347244533 \tabularnewline
11 & 21274 & 21275.6281967602 & -289.943191324189 & -1.62819676019485 & 0.00949672404276561 \tabularnewline
12 & 20987 & 20987.8237163819 & -287.901802787922 & -0.823716381864051 & 0.00338835156325109 \tabularnewline
13 & 19683 & 19713.5671243585 & -1229.09328510059 & -30.5671243585169 & -1.56288797494588 \tabularnewline
14 & 19381 & 19310.5884745786 & -440.188265186597 & 70.4115254213785 & 1.31544285068647 \tabularnewline
15 & 19071 & 19115.7896343943 & -211.956638228701 & -44.7896343942592 & 0.382814742405743 \tabularnewline
16 & 20772 & 20656.3772658778 & 1417.39023402376 & 115.622734122209 & 2.70100817048867 \tabularnewline
17 & 22485 & 22522.4357334842 & 1834.19199958307 & -37.4357334841831 & 0.691915353464615 \tabularnewline
18 & 24181 & 24141.5093033162 & 1634.28478145999 & 39.4906966838404 & -0.331810701648741 \tabularnewline
19 & 23479 & 23624.4298294729 & -364.968905476902 & -145.429829472927 & -3.31841868158201 \tabularnewline
20 & 22782 & 22775.8528421517 & -814.37349815881 & 6.14715784833346 & -0.74593380816506 \tabularnewline
21 & 22067 & 22056.2694797685 & -726.287662105801 & 10.7305202315412 & 0.146207240116577 \tabularnewline
22 & 21489 & 21478.6668899565 & -588.118382226589 & 10.3331100434600 & 0.2293370881841 \tabularnewline
23 & 20903 & 20933.5700212574 & -548.139154619983 & -30.5700212574086 & 0.0663586319469552 \tabularnewline
24 & 20330 & 20275.3975838953 & -650.388126238181 & 54.6024161047364 & -0.169715975389280 \tabularnewline
25 & 19736 & 19789.5287823 & -497.55170229978 & -53.528782300006 & 0.253817091961421 \tabularnewline
26 & 19483 & 19358.6951226839 & -435.517830545865 & 124.304877316061 & 0.103160025034256 \tabularnewline
27 & 19242 & 19360.8158324495 & -34.3595406185888 & -118.815832449519 & 0.669222744032911 \tabularnewline
28 & 20334 & 20212.0385840219 & 779.028274343585 & 121.961415978093 & 1.34931367886376 \tabularnewline
29 & 21423 & 21503.3169349686 & 1248.84227704478 & -80.3169349686257 & 0.779813140841009 \tabularnewline
30 & 22523 & 22377.3750178998 & 904.978549369957 & 145.624982100197 & -0.570766242281175 \tabularnewline
31 & 21986 & 22155.8645338846 & -128.625359802679 & -169.864533884586 & -1.71560132897775 \tabularnewline
32 & 21462 & 21477.5015573102 & -633.022576485718 & -15.5015573102070 & -0.837212478640571 \tabularnewline
33 & 20908 & 20895.7119109632 & -586.015725582298 & 12.2880890368417 & 0.0780232366798802 \tabularnewline
34 & 20575 & 20556.1559478777 & -359.884050177029 & 18.8440521223227 & 0.375339451984497 \tabularnewline
35 & 20237 & 20254.9294447219 & -306.063858675002 & -17.9294447218936 & 0.0893324737880168 \tabularnewline
36 & 19904 & 19868.3104800743 & -379.969738580598 & 35.6895199256944 & -0.122671609575035 \tabularnewline
37 & 19610 & 19643.4889262014 & -237.656303722162 & -33.4889262014213 & 0.236367687042846 \tabularnewline
38 & 19251 & 19137.8444870749 & -483.583490040556 & 113.155512925058 & -0.408410334452181 \tabularnewline
39 & 18941 & 19081.9069836659 & -94.1583856891801 & -140.906983665920 & 0.648006001669356 \tabularnewline
40 & 20450 & 20312.1968177511 & 1114.45402029051 & 137.803182248911 & 2.00602414980104 \tabularnewline
41 & 21946 & 22015.432028425 & 1651.00213349906 & -69.4320284250129 & 0.890443159575436 \tabularnewline
42 & 23409 & 23226.2270462425 & 1249.74236237062 & 182.772953757488 & -0.666052638284688 \tabularnewline
43 & 22741 & 22952.3107253375 & -139.244469042447 & -211.310725337477 & -2.30546715178198 \tabularnewline
44 & 22069 & 22111.0188322956 & -779.231719801418 & -42.0188322955578 & -1.06226889600168 \tabularnewline
45 & 21539 & 21523.7632597185 & -604.22883162796 & 15.2367402815033 & 0.290474498005167 \tabularnewline
46 & 21189 & 21158.6678057946 & -386.235921657021 & 30.3321942054257 & 0.361830646819602 \tabularnewline
47 & 20960 & 20961.7651676648 & -213.639583325585 & -1.76516766481449 & 0.286481276815693 \tabularnewline
48 & 20704 & 20701.5272083712 & -256.113325669308 & 2.47279162876521 & -0.0705004529366505 \tabularnewline
49 & 19697 & 19728.6285921275 & -909.418221897572 & -31.6285921275245 & -1.08506379752044 \tabularnewline
50 & 19598 & 19424.1086607690 & -358.094964831915 & 173.891339230955 & 0.915106239945355 \tabularnewline
51 & 19456 & 19651.4821299626 & 173.136185246543 & -195.482129962565 & 0.882959553042894 \tabularnewline
52 & 20316 & 20235.6739290013 & 546.746310628885 & 80.3260709987073 & 0.620273994884358 \tabularnewline
53 & 21083 & 21160.3438615304 & 889.878027274081 & -77.3438615303965 & 0.569405803683436 \tabularnewline
54 & 22158 & 21880.0884890089 & 735.391152201141 & 277.911510991058 & -0.256435028722037 \tabularnewline
55 & 21469 & 21665.6914020749 & -127.163385140742 & -196.691402074868 & -1.43168603319950 \tabularnewline
56 & 20892 & 20968.7377564075 & -644.621381960067 & -76.7377564074897 & -0.858890526294234 \tabularnewline
57 & 20578 & 20556.6979809134 & -433.403931988053 & 21.3020190865555 & 0.350584443613076 \tabularnewline
58 & 20233 & 20221.433729847 & -344.278388730544 & 11.5662701530151 & 0.147933217242533 \tabularnewline
59 & 19947 & 19964.3764038498 & -265.069359148595 & -17.3764038497780 & 0.131473536489530 \tabularnewline
60 & 20049 & 19945.1468305703 & -41.8454646103689 & 103.8531694297 & 0.370530374304483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68368&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]19915[/C][C]19915[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]19843[/C][C]19843.9943178957[/C][C]-71.0878571363803[/C][C]-0.994317895669007[/C][C]-0.118782435020626[/C][/ROW]
[ROW][C]3[/C][C]19761[/C][C]19760.7309832625[/C][C]-82.7960266846761[/C][C]0.26901673746091[/C][C]-0.0197979137823644[/C][/ROW]
[ROW][C]4[/C][C]20858[/C][C]20822.0785203464[/C][C]1008.51469063160[/C][C]35.9214796535916[/C][C]1.80930311820643[/C][/ROW]
[ROW][C]5[/C][C]21968[/C][C]21973.665317112[/C][C]1145.05557553730[/C][C]-5.66531711198193[/C][C]0.226651828859217[/C][/ROW]
[ROW][C]6[/C][C]23061[/C][C]23064.7500111397[/C][C]1093.53921294631[/C][C]-3.75001113973822[/C][C]-0.0855081607236897[/C][/ROW]
[ROW][C]7[/C][C]22661[/C][C]22707.9502449778[/C][C]-290.808999241377[/C][C]-46.9502449778206[/C][C]-2.29777874350131[/C][/ROW]
[ROW][C]8[/C][C]22269[/C][C]22262.8157970249[/C][C]-438.11153945891[/C][C]6.18420297505747[/C][C]-0.244496714917772[/C][/ROW]
[ROW][C]9[/C][C]21857[/C][C]21855.5771135006[/C][C]-408.643565299405[/C][C]1.42288649942803[/C][C]0.0489117356031883[/C][/ROW]
[ROW][C]10[/C][C]21568[/C][C]21565.2986171617[/C][C]-295.664706117176[/C][C]2.70138283831989[/C][C]0.187525347244533[/C][/ROW]
[ROW][C]11[/C][C]21274[/C][C]21275.6281967602[/C][C]-289.943191324189[/C][C]-1.62819676019485[/C][C]0.00949672404276561[/C][/ROW]
[ROW][C]12[/C][C]20987[/C][C]20987.8237163819[/C][C]-287.901802787922[/C][C]-0.823716381864051[/C][C]0.00338835156325109[/C][/ROW]
[ROW][C]13[/C][C]19683[/C][C]19713.5671243585[/C][C]-1229.09328510059[/C][C]-30.5671243585169[/C][C]-1.56288797494588[/C][/ROW]
[ROW][C]14[/C][C]19381[/C][C]19310.5884745786[/C][C]-440.188265186597[/C][C]70.4115254213785[/C][C]1.31544285068647[/C][/ROW]
[ROW][C]15[/C][C]19071[/C][C]19115.7896343943[/C][C]-211.956638228701[/C][C]-44.7896343942592[/C][C]0.382814742405743[/C][/ROW]
[ROW][C]16[/C][C]20772[/C][C]20656.3772658778[/C][C]1417.39023402376[/C][C]115.622734122209[/C][C]2.70100817048867[/C][/ROW]
[ROW][C]17[/C][C]22485[/C][C]22522.4357334842[/C][C]1834.19199958307[/C][C]-37.4357334841831[/C][C]0.691915353464615[/C][/ROW]
[ROW][C]18[/C][C]24181[/C][C]24141.5093033162[/C][C]1634.28478145999[/C][C]39.4906966838404[/C][C]-0.331810701648741[/C][/ROW]
[ROW][C]19[/C][C]23479[/C][C]23624.4298294729[/C][C]-364.968905476902[/C][C]-145.429829472927[/C][C]-3.31841868158201[/C][/ROW]
[ROW][C]20[/C][C]22782[/C][C]22775.8528421517[/C][C]-814.37349815881[/C][C]6.14715784833346[/C][C]-0.74593380816506[/C][/ROW]
[ROW][C]21[/C][C]22067[/C][C]22056.2694797685[/C][C]-726.287662105801[/C][C]10.7305202315412[/C][C]0.146207240116577[/C][/ROW]
[ROW][C]22[/C][C]21489[/C][C]21478.6668899565[/C][C]-588.118382226589[/C][C]10.3331100434600[/C][C]0.2293370881841[/C][/ROW]
[ROW][C]23[/C][C]20903[/C][C]20933.5700212574[/C][C]-548.139154619983[/C][C]-30.5700212574086[/C][C]0.0663586319469552[/C][/ROW]
[ROW][C]24[/C][C]20330[/C][C]20275.3975838953[/C][C]-650.388126238181[/C][C]54.6024161047364[/C][C]-0.169715975389280[/C][/ROW]
[ROW][C]25[/C][C]19736[/C][C]19789.5287823[/C][C]-497.55170229978[/C][C]-53.528782300006[/C][C]0.253817091961421[/C][/ROW]
[ROW][C]26[/C][C]19483[/C][C]19358.6951226839[/C][C]-435.517830545865[/C][C]124.304877316061[/C][C]0.103160025034256[/C][/ROW]
[ROW][C]27[/C][C]19242[/C][C]19360.8158324495[/C][C]-34.3595406185888[/C][C]-118.815832449519[/C][C]0.669222744032911[/C][/ROW]
[ROW][C]28[/C][C]20334[/C][C]20212.0385840219[/C][C]779.028274343585[/C][C]121.961415978093[/C][C]1.34931367886376[/C][/ROW]
[ROW][C]29[/C][C]21423[/C][C]21503.3169349686[/C][C]1248.84227704478[/C][C]-80.3169349686257[/C][C]0.779813140841009[/C][/ROW]
[ROW][C]30[/C][C]22523[/C][C]22377.3750178998[/C][C]904.978549369957[/C][C]145.624982100197[/C][C]-0.570766242281175[/C][/ROW]
[ROW][C]31[/C][C]21986[/C][C]22155.8645338846[/C][C]-128.625359802679[/C][C]-169.864533884586[/C][C]-1.71560132897775[/C][/ROW]
[ROW][C]32[/C][C]21462[/C][C]21477.5015573102[/C][C]-633.022576485718[/C][C]-15.5015573102070[/C][C]-0.837212478640571[/C][/ROW]
[ROW][C]33[/C][C]20908[/C][C]20895.7119109632[/C][C]-586.015725582298[/C][C]12.2880890368417[/C][C]0.0780232366798802[/C][/ROW]
[ROW][C]34[/C][C]20575[/C][C]20556.1559478777[/C][C]-359.884050177029[/C][C]18.8440521223227[/C][C]0.375339451984497[/C][/ROW]
[ROW][C]35[/C][C]20237[/C][C]20254.9294447219[/C][C]-306.063858675002[/C][C]-17.9294447218936[/C][C]0.0893324737880168[/C][/ROW]
[ROW][C]36[/C][C]19904[/C][C]19868.3104800743[/C][C]-379.969738580598[/C][C]35.6895199256944[/C][C]-0.122671609575035[/C][/ROW]
[ROW][C]37[/C][C]19610[/C][C]19643.4889262014[/C][C]-237.656303722162[/C][C]-33.4889262014213[/C][C]0.236367687042846[/C][/ROW]
[ROW][C]38[/C][C]19251[/C][C]19137.8444870749[/C][C]-483.583490040556[/C][C]113.155512925058[/C][C]-0.408410334452181[/C][/ROW]
[ROW][C]39[/C][C]18941[/C][C]19081.9069836659[/C][C]-94.1583856891801[/C][C]-140.906983665920[/C][C]0.648006001669356[/C][/ROW]
[ROW][C]40[/C][C]20450[/C][C]20312.1968177511[/C][C]1114.45402029051[/C][C]137.803182248911[/C][C]2.00602414980104[/C][/ROW]
[ROW][C]41[/C][C]21946[/C][C]22015.432028425[/C][C]1651.00213349906[/C][C]-69.4320284250129[/C][C]0.890443159575436[/C][/ROW]
[ROW][C]42[/C][C]23409[/C][C]23226.2270462425[/C][C]1249.74236237062[/C][C]182.772953757488[/C][C]-0.666052638284688[/C][/ROW]
[ROW][C]43[/C][C]22741[/C][C]22952.3107253375[/C][C]-139.244469042447[/C][C]-211.310725337477[/C][C]-2.30546715178198[/C][/ROW]
[ROW][C]44[/C][C]22069[/C][C]22111.0188322956[/C][C]-779.231719801418[/C][C]-42.0188322955578[/C][C]-1.06226889600168[/C][/ROW]
[ROW][C]45[/C][C]21539[/C][C]21523.7632597185[/C][C]-604.22883162796[/C][C]15.2367402815033[/C][C]0.290474498005167[/C][/ROW]
[ROW][C]46[/C][C]21189[/C][C]21158.6678057946[/C][C]-386.235921657021[/C][C]30.3321942054257[/C][C]0.361830646819602[/C][/ROW]
[ROW][C]47[/C][C]20960[/C][C]20961.7651676648[/C][C]-213.639583325585[/C][C]-1.76516766481449[/C][C]0.286481276815693[/C][/ROW]
[ROW][C]48[/C][C]20704[/C][C]20701.5272083712[/C][C]-256.113325669308[/C][C]2.47279162876521[/C][C]-0.0705004529366505[/C][/ROW]
[ROW][C]49[/C][C]19697[/C][C]19728.6285921275[/C][C]-909.418221897572[/C][C]-31.6285921275245[/C][C]-1.08506379752044[/C][/ROW]
[ROW][C]50[/C][C]19598[/C][C]19424.1086607690[/C][C]-358.094964831915[/C][C]173.891339230955[/C][C]0.915106239945355[/C][/ROW]
[ROW][C]51[/C][C]19456[/C][C]19651.4821299626[/C][C]173.136185246543[/C][C]-195.482129962565[/C][C]0.882959553042894[/C][/ROW]
[ROW][C]52[/C][C]20316[/C][C]20235.6739290013[/C][C]546.746310628885[/C][C]80.3260709987073[/C][C]0.620273994884358[/C][/ROW]
[ROW][C]53[/C][C]21083[/C][C]21160.3438615304[/C][C]889.878027274081[/C][C]-77.3438615303965[/C][C]0.569405803683436[/C][/ROW]
[ROW][C]54[/C][C]22158[/C][C]21880.0884890089[/C][C]735.391152201141[/C][C]277.911510991058[/C][C]-0.256435028722037[/C][/ROW]
[ROW][C]55[/C][C]21469[/C][C]21665.6914020749[/C][C]-127.163385140742[/C][C]-196.691402074868[/C][C]-1.43168603319950[/C][/ROW]
[ROW][C]56[/C][C]20892[/C][C]20968.7377564075[/C][C]-644.621381960067[/C][C]-76.7377564074897[/C][C]-0.858890526294234[/C][/ROW]
[ROW][C]57[/C][C]20578[/C][C]20556.6979809134[/C][C]-433.403931988053[/C][C]21.3020190865555[/C][C]0.350584443613076[/C][/ROW]
[ROW][C]58[/C][C]20233[/C][C]20221.433729847[/C][C]-344.278388730544[/C][C]11.5662701530151[/C][C]0.147933217242533[/C][/ROW]
[ROW][C]59[/C][C]19947[/C][C]19964.3764038498[/C][C]-265.069359148595[/C][C]-17.3764038497780[/C][C]0.131473536489530[/C][/ROW]
[ROW][C]60[/C][C]20049[/C][C]19945.1468305703[/C][C]-41.8454646103689[/C][C]103.8531694297[/C][C]0.370530374304483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68368&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
11991519915000
21984319843.9943178957-71.0878571363803-0.994317895669007-0.118782435020626
31976119760.7309832625-82.79602668467610.26901673746091-0.0197979137823644
42085820822.07852034641008.5146906316035.92147965359161.80930311820643
52196821973.6653171121145.05557553730-5.665317111981930.226651828859217
62306123064.75001113971093.53921294631-3.75001113973822-0.0855081607236897
72266122707.9502449778-290.808999241377-46.9502449778206-2.29777874350131
82226922262.8157970249-438.111539458916.18420297505747-0.244496714917772
92185721855.5771135006-408.6435652994051.422886499428030.0489117356031883
102156821565.2986171617-295.6647061171762.701382838319890.187525347244533
112127421275.6281967602-289.943191324189-1.628196760194850.00949672404276561
122098720987.8237163819-287.901802787922-0.8237163818640510.00338835156325109
131968319713.5671243585-1229.09328510059-30.5671243585169-1.56288797494588
141938119310.5884745786-440.18826518659770.41152542137851.31544285068647
151907119115.7896343943-211.956638228701-44.78963439425920.382814742405743
162077220656.37726587781417.39023402376115.6227341222092.70100817048867
172248522522.43573348421834.19199958307-37.43573348418310.691915353464615
182418124141.50930331621634.2847814599939.4906966838404-0.331810701648741
192347923624.4298294729-364.968905476902-145.429829472927-3.31841868158201
202278222775.8528421517-814.373498158816.14715784833346-0.74593380816506
212206722056.2694797685-726.28766210580110.73052023154120.146207240116577
222148921478.6668899565-588.11838222658910.33311004346000.2293370881841
232090320933.5700212574-548.139154619983-30.57002125740860.0663586319469552
242033020275.3975838953-650.38812623818154.6024161047364-0.169715975389280
251973619789.5287823-497.55170229978-53.5287823000060.253817091961421
261948319358.6951226839-435.517830545865124.3048773160610.103160025034256
271924219360.8158324495-34.3595406185888-118.8158324495190.669222744032911
282033420212.0385840219779.028274343585121.9614159780931.34931367886376
292142321503.31693496861248.84227704478-80.31693496862570.779813140841009
302252322377.3750178998904.978549369957145.624982100197-0.570766242281175
312198622155.8645338846-128.625359802679-169.864533884586-1.71560132897775
322146221477.5015573102-633.022576485718-15.5015573102070-0.837212478640571
332090820895.7119109632-586.01572558229812.28808903684170.0780232366798802
342057520556.1559478777-359.88405017702918.84405212232270.375339451984497
352023720254.9294447219-306.063858675002-17.92944472189360.0893324737880168
361990419868.3104800743-379.96973858059835.6895199256944-0.122671609575035
371961019643.4889262014-237.656303722162-33.48892620142130.236367687042846
381925119137.8444870749-483.583490040556113.155512925058-0.408410334452181
391894119081.9069836659-94.1583856891801-140.9069836659200.648006001669356
402045020312.19681775111114.45402029051137.8031822489112.00602414980104
412194622015.4320284251651.00213349906-69.43202842501290.890443159575436
422340923226.22704624251249.74236237062182.772953757488-0.666052638284688
432274122952.3107253375-139.244469042447-211.310725337477-2.30546715178198
442206922111.0188322956-779.231719801418-42.0188322955578-1.06226889600168
452153921523.7632597185-604.2288316279615.23674028150330.290474498005167
462118921158.6678057946-386.23592165702130.33219420542570.361830646819602
472096020961.7651676648-213.639583325585-1.765167664814490.286481276815693
482070420701.5272083712-256.1133256693082.47279162876521-0.0705004529366505
491969719728.6285921275-909.418221897572-31.6285921275245-1.08506379752044
501959819424.1086607690-358.094964831915173.8913392309550.915106239945355
511945619651.4821299626173.136185246543-195.4821299625650.882959553042894
522031620235.6739290013546.74631062888580.32607099870730.620273994884358
532108321160.3438615304889.878027274081-77.34386153039650.569405803683436
542215821880.0884890089735.391152201141277.911510991058-0.256435028722037
552146921665.6914020749-127.163385140742-196.691402074868-1.43168603319950
562089220968.7377564075-644.621381960067-76.7377564074897-0.858890526294234
572057820556.6979809134-433.40393198805321.30201908655550.350584443613076
582023320221.433729847-344.27838873054411.56627015301510.147933217242533
591994719964.3764038498-265.069359148595-17.37640384977800.131473536489530
602004919945.1468305703-41.8454646103689103.85316942970.370530374304483



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')