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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 computationThu, 22 Dec 2011 19:21:12 -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/Dec/22/t1324599709ypqjorsfhx7iw5a.htm/, Retrieved Fri, 03 May 2024 10:49:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160110, Retrieved Fri, 03 May 2024 10:49:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [classical decompo...] [2011-12-21 22:41:03] [d67ce207bd02ca41b9162077ae11c874]
- RMP     [Structural Time Series Models] [STSM] [2011-12-23 00:21:12] [3bdb54d050744f47368418ea7c7e8e96] [Current]
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Dataseries X:
2582
2624
2566
2645
3167
3051
2503
2574
2988
3086
2632
2604
2377
2258
2266
2601
2843
3018
2493
2647
3015
3101
2496
2342
2271
1969
2196
2294
2706
3001
2691
2554
2961
3226
2960
2749
2379
2254
2592
2780
2833
2911
2494
2643
2902
2880
2657
2609
2394
2492
2414
2621
3055
2940
2582
2430
2781
2904
2474
2254
2244
1972
2408
2523
2634
2798
2418
2551
2741
3011
2558
2167
1944
1836
2292
2576
2653
2900
2438
2439
2717
2872
2157
1541




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160110&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160110&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160110&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'Gertrude Mary Cox' @ cox.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
125822582000
226242614.410524169351.522696929959049.589475830649570.160269563137961
325662587.124459683390.117976400581123-21.1244596833941-0.179350673579334
426452617.816025070150.96422109614995927.18397492985030.220311898332086
531672949.279693790066.16236921574309217.7203062099392.41892809662827
630513063.222093231737.57836354059217-12.22209323173080.787702663115203
725032744.992350443632.96776560462239-241.992350443631-2.37667003943239
825742589.115936618050.477803224365024-15.1159366180478-1.15697736035089
929882801.567838906684.05803446526963186.4321610933221.54223121154947
1030863005.778928549487.6271357884349580.22107145051821.45487008177488
1126322813.815725604663.90422585520229-181.81572560466-1.44950165072094
1226042655.162501590430.745646962227746-51.162501590426-1.1795283145584
1323772496.809103516833.26734061272396-119.809103516833-1.25748632209929
1422582322.454382129380.328761594554832-64.454382129381-1.26770328259335
1522662293.17899622118-0.645697304755458-27.178996221184-0.198235229848187
1626012528.451089359366.9941195522703272.548910640641.65215132352867
1728432623.139539181679.36365819297114219.8604608183320.630367492004792
1830182783.1550215733312.8963718390364234.8449784266741.08706906597031
1924932751.4317505145211.8938996991984-258.431750514521-0.321648614778335
2026472758.8328274465911.7907959747948-111.832827446587-0.0323505881675425
2130152843.5108187486313.5313908501366171.4891812513750.524405687280478
2231012909.8802620419414.8256227101281191.1197379580620.379895094785758
2324962746.8565494527910.5942421181399-250.856549452793-1.27666557380104
2423422479.18302479634.83356270746921-137.183024796297-1.99840965883359
2522712356.319444910012.69793780564996-85.3194449100051-0.933610798322451
2619692165.96280216253-1.84740907468203-196.962802162525-1.38020870521291
2721962233.998303463710.30593177618821-37.99830346371480.484225471714184
2822942259.045261090641.1209166161117934.95473890935490.172919799029094
2927062419.696210205986.1647480278835286.3037897940241.13370112806004
3030012625.4229944623612.0933971994904375.5770055376371.42691603784816
3126912846.7194440532718.0803942764874-155.7194440532681.49633101307577
3225542807.4453783728916.4527299162163-253.445378372886-0.409936423505884
3329612806.4623245969715.9561397976186154.537675403029-0.124527004283324
3432262883.0977629073617.6758045727624342.9022370926450.432862967650784
3529603006.3624049913520.5859444454873-46.36240499134940.752260771979041
3627492917.0948535180317.6870559365805-168.094853518029-0.784180224850846
3723792616.374247231799.33828424869511-237.374247231786-2.28368605514637
3822542508.945748015965.99100731356788-254.945748015961-0.829929535675148
3925922581.253949579658.091311720643810.74605042034740.464638327969284
4027802734.659467015612.911857928457745.3405329843981.01870514130292
4128332708.0199274865911.6033514603341124.980072513413-0.27976000933769
4229112656.186257502799.55445657389368254.813742497205-0.451213768508789
4324942635.847353726248.61057897493169-141.847353726244-0.212851456217219
4426432787.3925843850113.0626581537164-144.3925843850051.01703845924638
4529022811.6999362106513.409939943175590.30006378934950.0799205961431886
4628802680.667287125188.99549429470459199.332712874819-1.02532840984056
4726572630.677247953887.2195525640653926.3227520461203-0.418549088481872
4826092623.743414329886.79823739751982-14.7434143298775-0.100624007501164
4923942606.819099710396.08559569036701-212.819099710391-0.168936554622472
5024922712.208155810999.17872575852475-220.2081558109930.703803196391088
5124142583.877328146574.71234056380248-169.877328146575-0.967371557225079
5226212550.430142836483.4410675697036970.5698571635154-0.268212186825478
5330552747.277415062079.91273119981923307.7225849379331.3659788200318
5429402742.084841126829.41173874418643197.915158873182-0.107139323802369
5525822769.227074057829.99245139390912-187.2270740578160.125913731205973
5624302658.527775027886.08320392194802-228.527775027881-0.85646912236077
5727812626.104316329484.84742545325216154.895683670523-0.272887754493231
5829042652.607213885825.53640552864215251.3927861141820.153304314899873
5924742536.926715178411.70900997589017-62.9267151784101-0.858286422672329
6022542371.06140650912-3.56851234769335-117.061406509118-1.18849778996116
6122442412.59326501812-2.13760316971491-168.5932650181220.320127646579047
6219722257.52734227505-7.07397869424747-285.527342275054-1.08244452245715
6324082423.47900261527-1.37895628718334-15.4790026152651.21945635732472
6425232506.854438774711.4481624882793616.14556122529350.596757306040393
6526342411.20393444834-1.80398172146202222.796065551658-0.685548871845885
6627982503.005040037591.32100926280474294.9949599624070.662903065023543
6724182541.229357687752.54467394019774-123.2293576877480.261632173434029
6825512671.960630076056.76353559507381-120.9606300760510.90817321841083
6927412635.140319966935.33899232790485105.859680033071-0.308373192927284
7030112660.607813548335.99301871467959350.3921864516730.142298385855091
7125582602.751538196843.92665420593426-44.751538196835-0.451570682978001
7221672420.00210474284-2.1126785730872-253.002104742845-1.32205695123142
7319442201.29221014921-9.15270199273982-257.292210149211-1.53476161085326
7418362176.29654998717-9.6721973381415-340.296549987171-0.112062606697729
7522922258.85157146559-6.6186047117844333.14842853441360.650619419616348
7625762418.23176391741-1.08361831593716157.7682360825881.17011471337854
7726532469.471135486220.665765190291909183.5288645137820.369423115115806
7829002570.058846536964.00254817605861329.9411534630450.707002794871922
7924382607.962160684855.13049832495376-169.962160684850.240075726240204
8024392577.666084295533.95719125158448-138.666084295535-0.25073384858089
8127172592.376322254114.31172050374977124.6236777458940.0760180539082059
8228722522.191890537571.86469596727874349.808109462431-0.526310568436662
8321572270.1504622104-6.45730606027176-113.150462210401-1.79462949470414
8415411917.13359661959-17.8174244858644-376.133596619586-2.45215742243941

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 2582 & 2582 & 0 & 0 & 0 \tabularnewline
2 & 2624 & 2614.41052416935 & 1.52269692995904 & 9.58947583064957 & 0.160269563137961 \tabularnewline
3 & 2566 & 2587.12445968339 & 0.117976400581123 & -21.1244596833941 & -0.179350673579334 \tabularnewline
4 & 2645 & 2617.81602507015 & 0.964221096149959 & 27.1839749298503 & 0.220311898332086 \tabularnewline
5 & 3167 & 2949.27969379006 & 6.16236921574309 & 217.720306209939 & 2.41892809662827 \tabularnewline
6 & 3051 & 3063.22209323173 & 7.57836354059217 & -12.2220932317308 & 0.787702663115203 \tabularnewline
7 & 2503 & 2744.99235044363 & 2.96776560462239 & -241.992350443631 & -2.37667003943239 \tabularnewline
8 & 2574 & 2589.11593661805 & 0.477803224365024 & -15.1159366180478 & -1.15697736035089 \tabularnewline
9 & 2988 & 2801.56783890668 & 4.05803446526963 & 186.432161093322 & 1.54223121154947 \tabularnewline
10 & 3086 & 3005.77892854948 & 7.62713578843495 & 80.2210714505182 & 1.45487008177488 \tabularnewline
11 & 2632 & 2813.81572560466 & 3.90422585520229 & -181.81572560466 & -1.44950165072094 \tabularnewline
12 & 2604 & 2655.16250159043 & 0.745646962227746 & -51.162501590426 & -1.1795283145584 \tabularnewline
13 & 2377 & 2496.80910351683 & 3.26734061272396 & -119.809103516833 & -1.25748632209929 \tabularnewline
14 & 2258 & 2322.45438212938 & 0.328761594554832 & -64.454382129381 & -1.26770328259335 \tabularnewline
15 & 2266 & 2293.17899622118 & -0.645697304755458 & -27.178996221184 & -0.198235229848187 \tabularnewline
16 & 2601 & 2528.45108935936 & 6.99411955227032 & 72.54891064064 & 1.65215132352867 \tabularnewline
17 & 2843 & 2623.13953918167 & 9.36365819297114 & 219.860460818332 & 0.630367492004792 \tabularnewline
18 & 3018 & 2783.15502157333 & 12.8963718390364 & 234.844978426674 & 1.08706906597031 \tabularnewline
19 & 2493 & 2751.43175051452 & 11.8938996991984 & -258.431750514521 & -0.321648614778335 \tabularnewline
20 & 2647 & 2758.83282744659 & 11.7907959747948 & -111.832827446587 & -0.0323505881675425 \tabularnewline
21 & 3015 & 2843.51081874863 & 13.5313908501366 & 171.489181251375 & 0.524405687280478 \tabularnewline
22 & 3101 & 2909.88026204194 & 14.8256227101281 & 191.119737958062 & 0.379895094785758 \tabularnewline
23 & 2496 & 2746.85654945279 & 10.5942421181399 & -250.856549452793 & -1.27666557380104 \tabularnewline
24 & 2342 & 2479.1830247963 & 4.83356270746921 & -137.183024796297 & -1.99840965883359 \tabularnewline
25 & 2271 & 2356.31944491001 & 2.69793780564996 & -85.3194449100051 & -0.933610798322451 \tabularnewline
26 & 1969 & 2165.96280216253 & -1.84740907468203 & -196.962802162525 & -1.38020870521291 \tabularnewline
27 & 2196 & 2233.99830346371 & 0.30593177618821 & -37.9983034637148 & 0.484225471714184 \tabularnewline
28 & 2294 & 2259.04526109064 & 1.12091661611179 & 34.9547389093549 & 0.172919799029094 \tabularnewline
29 & 2706 & 2419.69621020598 & 6.1647480278835 & 286.303789794024 & 1.13370112806004 \tabularnewline
30 & 3001 & 2625.42299446236 & 12.0933971994904 & 375.577005537637 & 1.42691603784816 \tabularnewline
31 & 2691 & 2846.71944405327 & 18.0803942764874 & -155.719444053268 & 1.49633101307577 \tabularnewline
32 & 2554 & 2807.44537837289 & 16.4527299162163 & -253.445378372886 & -0.409936423505884 \tabularnewline
33 & 2961 & 2806.46232459697 & 15.9561397976186 & 154.537675403029 & -0.124527004283324 \tabularnewline
34 & 3226 & 2883.09776290736 & 17.6758045727624 & 342.902237092645 & 0.432862967650784 \tabularnewline
35 & 2960 & 3006.36240499135 & 20.5859444454873 & -46.3624049913494 & 0.752260771979041 \tabularnewline
36 & 2749 & 2917.09485351803 & 17.6870559365805 & -168.094853518029 & -0.784180224850846 \tabularnewline
37 & 2379 & 2616.37424723179 & 9.33828424869511 & -237.374247231786 & -2.28368605514637 \tabularnewline
38 & 2254 & 2508.94574801596 & 5.99100731356788 & -254.945748015961 & -0.829929535675148 \tabularnewline
39 & 2592 & 2581.25394957965 & 8.0913117206438 & 10.7460504203474 & 0.464638327969284 \tabularnewline
40 & 2780 & 2734.6594670156 & 12.9118579284577 & 45.340532984398 & 1.01870514130292 \tabularnewline
41 & 2833 & 2708.01992748659 & 11.6033514603341 & 124.980072513413 & -0.27976000933769 \tabularnewline
42 & 2911 & 2656.18625750279 & 9.55445657389368 & 254.813742497205 & -0.451213768508789 \tabularnewline
43 & 2494 & 2635.84735372624 & 8.61057897493169 & -141.847353726244 & -0.212851456217219 \tabularnewline
44 & 2643 & 2787.39258438501 & 13.0626581537164 & -144.392584385005 & 1.01703845924638 \tabularnewline
45 & 2902 & 2811.69993621065 & 13.4099399431755 & 90.3000637893495 & 0.0799205961431886 \tabularnewline
46 & 2880 & 2680.66728712518 & 8.99549429470459 & 199.332712874819 & -1.02532840984056 \tabularnewline
47 & 2657 & 2630.67724795388 & 7.21955256406539 & 26.3227520461203 & -0.418549088481872 \tabularnewline
48 & 2609 & 2623.74341432988 & 6.79823739751982 & -14.7434143298775 & -0.100624007501164 \tabularnewline
49 & 2394 & 2606.81909971039 & 6.08559569036701 & -212.819099710391 & -0.168936554622472 \tabularnewline
50 & 2492 & 2712.20815581099 & 9.17872575852475 & -220.208155810993 & 0.703803196391088 \tabularnewline
51 & 2414 & 2583.87732814657 & 4.71234056380248 & -169.877328146575 & -0.967371557225079 \tabularnewline
52 & 2621 & 2550.43014283648 & 3.44106756970369 & 70.5698571635154 & -0.268212186825478 \tabularnewline
53 & 3055 & 2747.27741506207 & 9.91273119981923 & 307.722584937933 & 1.3659788200318 \tabularnewline
54 & 2940 & 2742.08484112682 & 9.41173874418643 & 197.915158873182 & -0.107139323802369 \tabularnewline
55 & 2582 & 2769.22707405782 & 9.99245139390912 & -187.227074057816 & 0.125913731205973 \tabularnewline
56 & 2430 & 2658.52777502788 & 6.08320392194802 & -228.527775027881 & -0.85646912236077 \tabularnewline
57 & 2781 & 2626.10431632948 & 4.84742545325216 & 154.895683670523 & -0.272887754493231 \tabularnewline
58 & 2904 & 2652.60721388582 & 5.53640552864215 & 251.392786114182 & 0.153304314899873 \tabularnewline
59 & 2474 & 2536.92671517841 & 1.70900997589017 & -62.9267151784101 & -0.858286422672329 \tabularnewline
60 & 2254 & 2371.06140650912 & -3.56851234769335 & -117.061406509118 & -1.18849778996116 \tabularnewline
61 & 2244 & 2412.59326501812 & -2.13760316971491 & -168.593265018122 & 0.320127646579047 \tabularnewline
62 & 1972 & 2257.52734227505 & -7.07397869424747 & -285.527342275054 & -1.08244452245715 \tabularnewline
63 & 2408 & 2423.47900261527 & -1.37895628718334 & -15.479002615265 & 1.21945635732472 \tabularnewline
64 & 2523 & 2506.85443877471 & 1.44816248827936 & 16.1455612252935 & 0.596757306040393 \tabularnewline
65 & 2634 & 2411.20393444834 & -1.80398172146202 & 222.796065551658 & -0.685548871845885 \tabularnewline
66 & 2798 & 2503.00504003759 & 1.32100926280474 & 294.994959962407 & 0.662903065023543 \tabularnewline
67 & 2418 & 2541.22935768775 & 2.54467394019774 & -123.229357687748 & 0.261632173434029 \tabularnewline
68 & 2551 & 2671.96063007605 & 6.76353559507381 & -120.960630076051 & 0.90817321841083 \tabularnewline
69 & 2741 & 2635.14031996693 & 5.33899232790485 & 105.859680033071 & -0.308373192927284 \tabularnewline
70 & 3011 & 2660.60781354833 & 5.99301871467959 & 350.392186451673 & 0.142298385855091 \tabularnewline
71 & 2558 & 2602.75153819684 & 3.92665420593426 & -44.751538196835 & -0.451570682978001 \tabularnewline
72 & 2167 & 2420.00210474284 & -2.1126785730872 & -253.002104742845 & -1.32205695123142 \tabularnewline
73 & 1944 & 2201.29221014921 & -9.15270199273982 & -257.292210149211 & -1.53476161085326 \tabularnewline
74 & 1836 & 2176.29654998717 & -9.6721973381415 & -340.296549987171 & -0.112062606697729 \tabularnewline
75 & 2292 & 2258.85157146559 & -6.61860471178443 & 33.1484285344136 & 0.650619419616348 \tabularnewline
76 & 2576 & 2418.23176391741 & -1.08361831593716 & 157.768236082588 & 1.17011471337854 \tabularnewline
77 & 2653 & 2469.47113548622 & 0.665765190291909 & 183.528864513782 & 0.369423115115806 \tabularnewline
78 & 2900 & 2570.05884653696 & 4.00254817605861 & 329.941153463045 & 0.707002794871922 \tabularnewline
79 & 2438 & 2607.96216068485 & 5.13049832495376 & -169.96216068485 & 0.240075726240204 \tabularnewline
80 & 2439 & 2577.66608429553 & 3.95719125158448 & -138.666084295535 & -0.25073384858089 \tabularnewline
81 & 2717 & 2592.37632225411 & 4.31172050374977 & 124.623677745894 & 0.0760180539082059 \tabularnewline
82 & 2872 & 2522.19189053757 & 1.86469596727874 & 349.808109462431 & -0.526310568436662 \tabularnewline
83 & 2157 & 2270.1504622104 & -6.45730606027176 & -113.150462210401 & -1.79462949470414 \tabularnewline
84 & 1541 & 1917.13359661959 & -17.8174244858644 & -376.133596619586 & -2.45215742243941 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160110&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]2582[/C][C]2582[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]2624[/C][C]2614.41052416935[/C][C]1.52269692995904[/C][C]9.58947583064957[/C][C]0.160269563137961[/C][/ROW]
[ROW][C]3[/C][C]2566[/C][C]2587.12445968339[/C][C]0.117976400581123[/C][C]-21.1244596833941[/C][C]-0.179350673579334[/C][/ROW]
[ROW][C]4[/C][C]2645[/C][C]2617.81602507015[/C][C]0.964221096149959[/C][C]27.1839749298503[/C][C]0.220311898332086[/C][/ROW]
[ROW][C]5[/C][C]3167[/C][C]2949.27969379006[/C][C]6.16236921574309[/C][C]217.720306209939[/C][C]2.41892809662827[/C][/ROW]
[ROW][C]6[/C][C]3051[/C][C]3063.22209323173[/C][C]7.57836354059217[/C][C]-12.2220932317308[/C][C]0.787702663115203[/C][/ROW]
[ROW][C]7[/C][C]2503[/C][C]2744.99235044363[/C][C]2.96776560462239[/C][C]-241.992350443631[/C][C]-2.37667003943239[/C][/ROW]
[ROW][C]8[/C][C]2574[/C][C]2589.11593661805[/C][C]0.477803224365024[/C][C]-15.1159366180478[/C][C]-1.15697736035089[/C][/ROW]
[ROW][C]9[/C][C]2988[/C][C]2801.56783890668[/C][C]4.05803446526963[/C][C]186.432161093322[/C][C]1.54223121154947[/C][/ROW]
[ROW][C]10[/C][C]3086[/C][C]3005.77892854948[/C][C]7.62713578843495[/C][C]80.2210714505182[/C][C]1.45487008177488[/C][/ROW]
[ROW][C]11[/C][C]2632[/C][C]2813.81572560466[/C][C]3.90422585520229[/C][C]-181.81572560466[/C][C]-1.44950165072094[/C][/ROW]
[ROW][C]12[/C][C]2604[/C][C]2655.16250159043[/C][C]0.745646962227746[/C][C]-51.162501590426[/C][C]-1.1795283145584[/C][/ROW]
[ROW][C]13[/C][C]2377[/C][C]2496.80910351683[/C][C]3.26734061272396[/C][C]-119.809103516833[/C][C]-1.25748632209929[/C][/ROW]
[ROW][C]14[/C][C]2258[/C][C]2322.45438212938[/C][C]0.328761594554832[/C][C]-64.454382129381[/C][C]-1.26770328259335[/C][/ROW]
[ROW][C]15[/C][C]2266[/C][C]2293.17899622118[/C][C]-0.645697304755458[/C][C]-27.178996221184[/C][C]-0.198235229848187[/C][/ROW]
[ROW][C]16[/C][C]2601[/C][C]2528.45108935936[/C][C]6.99411955227032[/C][C]72.54891064064[/C][C]1.65215132352867[/C][/ROW]
[ROW][C]17[/C][C]2843[/C][C]2623.13953918167[/C][C]9.36365819297114[/C][C]219.860460818332[/C][C]0.630367492004792[/C][/ROW]
[ROW][C]18[/C][C]3018[/C][C]2783.15502157333[/C][C]12.8963718390364[/C][C]234.844978426674[/C][C]1.08706906597031[/C][/ROW]
[ROW][C]19[/C][C]2493[/C][C]2751.43175051452[/C][C]11.8938996991984[/C][C]-258.431750514521[/C][C]-0.321648614778335[/C][/ROW]
[ROW][C]20[/C][C]2647[/C][C]2758.83282744659[/C][C]11.7907959747948[/C][C]-111.832827446587[/C][C]-0.0323505881675425[/C][/ROW]
[ROW][C]21[/C][C]3015[/C][C]2843.51081874863[/C][C]13.5313908501366[/C][C]171.489181251375[/C][C]0.524405687280478[/C][/ROW]
[ROW][C]22[/C][C]3101[/C][C]2909.88026204194[/C][C]14.8256227101281[/C][C]191.119737958062[/C][C]0.379895094785758[/C][/ROW]
[ROW][C]23[/C][C]2496[/C][C]2746.85654945279[/C][C]10.5942421181399[/C][C]-250.856549452793[/C][C]-1.27666557380104[/C][/ROW]
[ROW][C]24[/C][C]2342[/C][C]2479.1830247963[/C][C]4.83356270746921[/C][C]-137.183024796297[/C][C]-1.99840965883359[/C][/ROW]
[ROW][C]25[/C][C]2271[/C][C]2356.31944491001[/C][C]2.69793780564996[/C][C]-85.3194449100051[/C][C]-0.933610798322451[/C][/ROW]
[ROW][C]26[/C][C]1969[/C][C]2165.96280216253[/C][C]-1.84740907468203[/C][C]-196.962802162525[/C][C]-1.38020870521291[/C][/ROW]
[ROW][C]27[/C][C]2196[/C][C]2233.99830346371[/C][C]0.30593177618821[/C][C]-37.9983034637148[/C][C]0.484225471714184[/C][/ROW]
[ROW][C]28[/C][C]2294[/C][C]2259.04526109064[/C][C]1.12091661611179[/C][C]34.9547389093549[/C][C]0.172919799029094[/C][/ROW]
[ROW][C]29[/C][C]2706[/C][C]2419.69621020598[/C][C]6.1647480278835[/C][C]286.303789794024[/C][C]1.13370112806004[/C][/ROW]
[ROW][C]30[/C][C]3001[/C][C]2625.42299446236[/C][C]12.0933971994904[/C][C]375.577005537637[/C][C]1.42691603784816[/C][/ROW]
[ROW][C]31[/C][C]2691[/C][C]2846.71944405327[/C][C]18.0803942764874[/C][C]-155.719444053268[/C][C]1.49633101307577[/C][/ROW]
[ROW][C]32[/C][C]2554[/C][C]2807.44537837289[/C][C]16.4527299162163[/C][C]-253.445378372886[/C][C]-0.409936423505884[/C][/ROW]
[ROW][C]33[/C][C]2961[/C][C]2806.46232459697[/C][C]15.9561397976186[/C][C]154.537675403029[/C][C]-0.124527004283324[/C][/ROW]
[ROW][C]34[/C][C]3226[/C][C]2883.09776290736[/C][C]17.6758045727624[/C][C]342.902237092645[/C][C]0.432862967650784[/C][/ROW]
[ROW][C]35[/C][C]2960[/C][C]3006.36240499135[/C][C]20.5859444454873[/C][C]-46.3624049913494[/C][C]0.752260771979041[/C][/ROW]
[ROW][C]36[/C][C]2749[/C][C]2917.09485351803[/C][C]17.6870559365805[/C][C]-168.094853518029[/C][C]-0.784180224850846[/C][/ROW]
[ROW][C]37[/C][C]2379[/C][C]2616.37424723179[/C][C]9.33828424869511[/C][C]-237.374247231786[/C][C]-2.28368605514637[/C][/ROW]
[ROW][C]38[/C][C]2254[/C][C]2508.94574801596[/C][C]5.99100731356788[/C][C]-254.945748015961[/C][C]-0.829929535675148[/C][/ROW]
[ROW][C]39[/C][C]2592[/C][C]2581.25394957965[/C][C]8.0913117206438[/C][C]10.7460504203474[/C][C]0.464638327969284[/C][/ROW]
[ROW][C]40[/C][C]2780[/C][C]2734.6594670156[/C][C]12.9118579284577[/C][C]45.340532984398[/C][C]1.01870514130292[/C][/ROW]
[ROW][C]41[/C][C]2833[/C][C]2708.01992748659[/C][C]11.6033514603341[/C][C]124.980072513413[/C][C]-0.27976000933769[/C][/ROW]
[ROW][C]42[/C][C]2911[/C][C]2656.18625750279[/C][C]9.55445657389368[/C][C]254.813742497205[/C][C]-0.451213768508789[/C][/ROW]
[ROW][C]43[/C][C]2494[/C][C]2635.84735372624[/C][C]8.61057897493169[/C][C]-141.847353726244[/C][C]-0.212851456217219[/C][/ROW]
[ROW][C]44[/C][C]2643[/C][C]2787.39258438501[/C][C]13.0626581537164[/C][C]-144.392584385005[/C][C]1.01703845924638[/C][/ROW]
[ROW][C]45[/C][C]2902[/C][C]2811.69993621065[/C][C]13.4099399431755[/C][C]90.3000637893495[/C][C]0.0799205961431886[/C][/ROW]
[ROW][C]46[/C][C]2880[/C][C]2680.66728712518[/C][C]8.99549429470459[/C][C]199.332712874819[/C][C]-1.02532840984056[/C][/ROW]
[ROW][C]47[/C][C]2657[/C][C]2630.67724795388[/C][C]7.21955256406539[/C][C]26.3227520461203[/C][C]-0.418549088481872[/C][/ROW]
[ROW][C]48[/C][C]2609[/C][C]2623.74341432988[/C][C]6.79823739751982[/C][C]-14.7434143298775[/C][C]-0.100624007501164[/C][/ROW]
[ROW][C]49[/C][C]2394[/C][C]2606.81909971039[/C][C]6.08559569036701[/C][C]-212.819099710391[/C][C]-0.168936554622472[/C][/ROW]
[ROW][C]50[/C][C]2492[/C][C]2712.20815581099[/C][C]9.17872575852475[/C][C]-220.208155810993[/C][C]0.703803196391088[/C][/ROW]
[ROW][C]51[/C][C]2414[/C][C]2583.87732814657[/C][C]4.71234056380248[/C][C]-169.877328146575[/C][C]-0.967371557225079[/C][/ROW]
[ROW][C]52[/C][C]2621[/C][C]2550.43014283648[/C][C]3.44106756970369[/C][C]70.5698571635154[/C][C]-0.268212186825478[/C][/ROW]
[ROW][C]53[/C][C]3055[/C][C]2747.27741506207[/C][C]9.91273119981923[/C][C]307.722584937933[/C][C]1.3659788200318[/C][/ROW]
[ROW][C]54[/C][C]2940[/C][C]2742.08484112682[/C][C]9.41173874418643[/C][C]197.915158873182[/C][C]-0.107139323802369[/C][/ROW]
[ROW][C]55[/C][C]2582[/C][C]2769.22707405782[/C][C]9.99245139390912[/C][C]-187.227074057816[/C][C]0.125913731205973[/C][/ROW]
[ROW][C]56[/C][C]2430[/C][C]2658.52777502788[/C][C]6.08320392194802[/C][C]-228.527775027881[/C][C]-0.85646912236077[/C][/ROW]
[ROW][C]57[/C][C]2781[/C][C]2626.10431632948[/C][C]4.84742545325216[/C][C]154.895683670523[/C][C]-0.272887754493231[/C][/ROW]
[ROW][C]58[/C][C]2904[/C][C]2652.60721388582[/C][C]5.53640552864215[/C][C]251.392786114182[/C][C]0.153304314899873[/C][/ROW]
[ROW][C]59[/C][C]2474[/C][C]2536.92671517841[/C][C]1.70900997589017[/C][C]-62.9267151784101[/C][C]-0.858286422672329[/C][/ROW]
[ROW][C]60[/C][C]2254[/C][C]2371.06140650912[/C][C]-3.56851234769335[/C][C]-117.061406509118[/C][C]-1.18849778996116[/C][/ROW]
[ROW][C]61[/C][C]2244[/C][C]2412.59326501812[/C][C]-2.13760316971491[/C][C]-168.593265018122[/C][C]0.320127646579047[/C][/ROW]
[ROW][C]62[/C][C]1972[/C][C]2257.52734227505[/C][C]-7.07397869424747[/C][C]-285.527342275054[/C][C]-1.08244452245715[/C][/ROW]
[ROW][C]63[/C][C]2408[/C][C]2423.47900261527[/C][C]-1.37895628718334[/C][C]-15.479002615265[/C][C]1.21945635732472[/C][/ROW]
[ROW][C]64[/C][C]2523[/C][C]2506.85443877471[/C][C]1.44816248827936[/C][C]16.1455612252935[/C][C]0.596757306040393[/C][/ROW]
[ROW][C]65[/C][C]2634[/C][C]2411.20393444834[/C][C]-1.80398172146202[/C][C]222.796065551658[/C][C]-0.685548871845885[/C][/ROW]
[ROW][C]66[/C][C]2798[/C][C]2503.00504003759[/C][C]1.32100926280474[/C][C]294.994959962407[/C][C]0.662903065023543[/C][/ROW]
[ROW][C]67[/C][C]2418[/C][C]2541.22935768775[/C][C]2.54467394019774[/C][C]-123.229357687748[/C][C]0.261632173434029[/C][/ROW]
[ROW][C]68[/C][C]2551[/C][C]2671.96063007605[/C][C]6.76353559507381[/C][C]-120.960630076051[/C][C]0.90817321841083[/C][/ROW]
[ROW][C]69[/C][C]2741[/C][C]2635.14031996693[/C][C]5.33899232790485[/C][C]105.859680033071[/C][C]-0.308373192927284[/C][/ROW]
[ROW][C]70[/C][C]3011[/C][C]2660.60781354833[/C][C]5.99301871467959[/C][C]350.392186451673[/C][C]0.142298385855091[/C][/ROW]
[ROW][C]71[/C][C]2558[/C][C]2602.75153819684[/C][C]3.92665420593426[/C][C]-44.751538196835[/C][C]-0.451570682978001[/C][/ROW]
[ROW][C]72[/C][C]2167[/C][C]2420.00210474284[/C][C]-2.1126785730872[/C][C]-253.002104742845[/C][C]-1.32205695123142[/C][/ROW]
[ROW][C]73[/C][C]1944[/C][C]2201.29221014921[/C][C]-9.15270199273982[/C][C]-257.292210149211[/C][C]-1.53476161085326[/C][/ROW]
[ROW][C]74[/C][C]1836[/C][C]2176.29654998717[/C][C]-9.6721973381415[/C][C]-340.296549987171[/C][C]-0.112062606697729[/C][/ROW]
[ROW][C]75[/C][C]2292[/C][C]2258.85157146559[/C][C]-6.61860471178443[/C][C]33.1484285344136[/C][C]0.650619419616348[/C][/ROW]
[ROW][C]76[/C][C]2576[/C][C]2418.23176391741[/C][C]-1.08361831593716[/C][C]157.768236082588[/C][C]1.17011471337854[/C][/ROW]
[ROW][C]77[/C][C]2653[/C][C]2469.47113548622[/C][C]0.665765190291909[/C][C]183.528864513782[/C][C]0.369423115115806[/C][/ROW]
[ROW][C]78[/C][C]2900[/C][C]2570.05884653696[/C][C]4.00254817605861[/C][C]329.941153463045[/C][C]0.707002794871922[/C][/ROW]
[ROW][C]79[/C][C]2438[/C][C]2607.96216068485[/C][C]5.13049832495376[/C][C]-169.96216068485[/C][C]0.240075726240204[/C][/ROW]
[ROW][C]80[/C][C]2439[/C][C]2577.66608429553[/C][C]3.95719125158448[/C][C]-138.666084295535[/C][C]-0.25073384858089[/C][/ROW]
[ROW][C]81[/C][C]2717[/C][C]2592.37632225411[/C][C]4.31172050374977[/C][C]124.623677745894[/C][C]0.0760180539082059[/C][/ROW]
[ROW][C]82[/C][C]2872[/C][C]2522.19189053757[/C][C]1.86469596727874[/C][C]349.808109462431[/C][C]-0.526310568436662[/C][/ROW]
[ROW][C]83[/C][C]2157[/C][C]2270.1504622104[/C][C]-6.45730606027176[/C][C]-113.150462210401[/C][C]-1.79462949470414[/C][/ROW]
[ROW][C]84[/C][C]1541[/C][C]1917.13359661959[/C][C]-17.8174244858644[/C][C]-376.133596619586[/C][C]-2.45215742243941[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160110&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160110&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
125822582000
226242614.410524169351.522696929959049.589475830649570.160269563137961
325662587.124459683390.117976400581123-21.1244596833941-0.179350673579334
426452617.816025070150.96422109614995927.18397492985030.220311898332086
531672949.279693790066.16236921574309217.7203062099392.41892809662827
630513063.222093231737.57836354059217-12.22209323173080.787702663115203
725032744.992350443632.96776560462239-241.992350443631-2.37667003943239
825742589.115936618050.477803224365024-15.1159366180478-1.15697736035089
929882801.567838906684.05803446526963186.4321610933221.54223121154947
1030863005.778928549487.6271357884349580.22107145051821.45487008177488
1126322813.815725604663.90422585520229-181.81572560466-1.44950165072094
1226042655.162501590430.745646962227746-51.162501590426-1.1795283145584
1323772496.809103516833.26734061272396-119.809103516833-1.25748632209929
1422582322.454382129380.328761594554832-64.454382129381-1.26770328259335
1522662293.17899622118-0.645697304755458-27.178996221184-0.198235229848187
1626012528.451089359366.9941195522703272.548910640641.65215132352867
1728432623.139539181679.36365819297114219.8604608183320.630367492004792
1830182783.1550215733312.8963718390364234.8449784266741.08706906597031
1924932751.4317505145211.8938996991984-258.431750514521-0.321648614778335
2026472758.8328274465911.7907959747948-111.832827446587-0.0323505881675425
2130152843.5108187486313.5313908501366171.4891812513750.524405687280478
2231012909.8802620419414.8256227101281191.1197379580620.379895094785758
2324962746.8565494527910.5942421181399-250.856549452793-1.27666557380104
2423422479.18302479634.83356270746921-137.183024796297-1.99840965883359
2522712356.319444910012.69793780564996-85.3194449100051-0.933610798322451
2619692165.96280216253-1.84740907468203-196.962802162525-1.38020870521291
2721962233.998303463710.30593177618821-37.99830346371480.484225471714184
2822942259.045261090641.1209166161117934.95473890935490.172919799029094
2927062419.696210205986.1647480278835286.3037897940241.13370112806004
3030012625.4229944623612.0933971994904375.5770055376371.42691603784816
3126912846.7194440532718.0803942764874-155.7194440532681.49633101307577
3225542807.4453783728916.4527299162163-253.445378372886-0.409936423505884
3329612806.4623245969715.9561397976186154.537675403029-0.124527004283324
3432262883.0977629073617.6758045727624342.9022370926450.432862967650784
3529603006.3624049913520.5859444454873-46.36240499134940.752260771979041
3627492917.0948535180317.6870559365805-168.094853518029-0.784180224850846
3723792616.374247231799.33828424869511-237.374247231786-2.28368605514637
3822542508.945748015965.99100731356788-254.945748015961-0.829929535675148
3925922581.253949579658.091311720643810.74605042034740.464638327969284
4027802734.659467015612.911857928457745.3405329843981.01870514130292
4128332708.0199274865911.6033514603341124.980072513413-0.27976000933769
4229112656.186257502799.55445657389368254.813742497205-0.451213768508789
4324942635.847353726248.61057897493169-141.847353726244-0.212851456217219
4426432787.3925843850113.0626581537164-144.3925843850051.01703845924638
4529022811.6999362106513.409939943175590.30006378934950.0799205961431886
4628802680.667287125188.99549429470459199.332712874819-1.02532840984056
4726572630.677247953887.2195525640653926.3227520461203-0.418549088481872
4826092623.743414329886.79823739751982-14.7434143298775-0.100624007501164
4923942606.819099710396.08559569036701-212.819099710391-0.168936554622472
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5226212550.430142836483.4410675697036970.5698571635154-0.268212186825478
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5429402742.084841126829.41173874418643197.915158873182-0.107139323802369
5525822769.227074057829.99245139390912-187.2270740578160.125913731205973
5624302658.527775027886.08320392194802-228.527775027881-0.85646912236077
5727812626.104316329484.84742545325216154.895683670523-0.272887754493231
5829042652.607213885825.53640552864215251.3927861141820.153304314899873
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7625762418.23176391741-1.08361831593716157.7682360825881.17011471337854
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8024392577.666084295533.95719125158448-138.666084295535-0.25073384858089
8127172592.376322254114.31172050374977124.6236777458940.0760180539082059
8228722522.191890537571.86469596727874349.808109462431-0.526310568436662
8321572270.1504622104-6.45730606027176-113.150462210401-1.79462949470414
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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')