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Author's title

Author*Unverified author*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationFri, 04 Dec 2009 09:43:02 -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/04/t1259945017agocbz9b0nw57gu.htm/, Retrieved Sun, 28 Apr 2024 09:45:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63884, Retrieved Sun, 28 Apr 2024 09:45:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [] [2009-12-04 16:43:02] [d39d4e1021a28f94dc953cf77db656ab] [Current]
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Dataseries X:
12008
9169
8788
8417
8247
8197
8236
8253
7733
8366
8626
8863
10102
8463
9114
8563
8872
8301
8301
8278
7736
7973
8268
9476
11100
8962
9173
8738
8459
8078
8411
8291
7810
8616
8312
9692
9911
8915
9452
9112
8472
8230
8384
8625
8221
8649
8625
10443
10357
8586
8892
8329
8101
7922
8120
7838
7735
8406
8209
9451
10041
9411
10405
8467
8464
8102
7627
7513
7510
8291
8064
9383




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63884&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63884&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63884&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11200812008000
291699388.89187389219-142.267203920301-219.891873892190-3.66385078260992
387888928.99339069425-148.056579919683-140.993390694249-0.722911170744540
484178577.3297007661-149.799458812119-160.329700766098-0.467289399940227
582478389.36906915085-150.171333053023-142.369069150852-0.0874665006930955
681978329.19439861759-149.137135318066-132.1943986175910.206089528795015
782368360.96198754883-146.813586532851-124.9619875488300.41392900734709
882538383.2965189313-144.432430028789-130.2965189313040.386718887093018
977337930.66895588783-149.140299301582-197.668955887832-0.704062661676525
1083668407.3791195413-138.851646211607-41.3791195412961.42863347237353
1186268733.47106523327-130.685260314494-107.4710652332711.06053131835543
1288638974.04803516124-123.761885758681-111.0480351612430.846224807480347
13101028665.55589346594-120.1118244512231436.44410653406-0.490615788453608
1484638627.57214717709-117.349491576919-164.5721471770900.165819693271633
1591149088.71900432842-100.67370792988525.28099567157641.28998246343461
1685638771.40038656781-105.519165425684-208.400386567813-0.492000874706544
1788728931.3674104351-99.7601543957376-59.36741043510580.602130349631512
1883018514.20870383302-106.98177739346-213.208703833020-0.719305695704975
1983018407.99035886114-106.963617146731-106.9903588611390.00172906624957253
2082788324.27033547651-106.390963267445-46.27033547650820.0526131346914988
2177368018.04378824652-111.471055638895-282.043788246520-0.452096222166425
2279738011.0079475362-108.728664000288-38.0079475361930.236179881216291
2382688322.92037226898-97.385584640251-54.92037226897910.95095469916207
2494769346.9105825418-69.1206623408951129.0894174581952.53041039435348
25111009661.95994966065-62.85466826305111438.040050339350.9170713418778
2689629318.00853468992-72.2196725848506-356.008534689924-0.605346919005672
2791739137.04228679038-75.94555763604535.9577132096195-0.240653722603108
2887389012.53935390992-77.4561619906584-274.539353909923-0.109458120248236
2984598558.46490641278-88.7465262007022-99.4649064127828-0.848507729440133
3080788317.6489566293-93.3469080741954-239.648956629305-0.342359596871604
3184118463.13926176181-85.9884829484922-52.13926176180710.537526130308832
3282918322.96406482126-87.6849064919641-31.9640648212641-0.121919195057910
3378108119.73792109858-91.3551816504363-309.737921098577-0.259917963357657
3486168581.59882854004-73.541095817279934.40117145995721.24442028134611
3583128583.75365550529-71.1028740098202-271.7536555052870.170138674147751
3696929426.61851386154-43.0361381812555265.3814861384632.05459010125163
3799118653.41820958264-63.92058599903191257.58179041736-1.68417676388808
3889159118.26991304246-45.4556964029372-203.2699130424611.16317317278305
3994529358.7359633396-35.071406685783193.26403666040130.632355164329172
4091129320.67113704642-35.1762182128944-208.671137046421-0.0067183005476785
4184728684.02278423839-55.7079706096739-212.022784238391-1.35048000077100
4282308505.36939312431-59.893582432723-275.369393124314-0.275819163036141
4383848401.97636331256-61.3841490454277-17.9763633125611-0.0975693135988474
4486258557.48336768916-53.89472912080167.5166323108380.48647364380057
4582218600.15875750428-50.536598758424-379.1587575042780.216610905850307
4686498616.97990627379-48.184377110333932.02009372621410.151071277538892
4786258967.66725386497-34.3435875179660-342.6672538649750.893628842527756
48104439844.35587197534-3.50141250389114598.6441280246572.04492958615987
49103579384.05146324699-18.7906917118122972.94853675301-1.03874933142919
5085868948.49316683246-33.7969884700164-362.493166832463-0.924423479886598
5188928805.33235151454-37.837752538506386.6676484854634-0.242260994363088
5283298479.93846257643-48.3220563267916-150.938462576429-0.643842691458393
5381018301.40150270439-52.9996655068539-200.401502704386-0.291901610103104
5479228191.26148582335-55.0425831732391-269.26148582335-0.127977612445619
5581208162.71302475495-54.0938132245838-42.71302475494920.0593262704475487
5678387842.72929752526-63.6488662587655-4.7292975252641-0.59543939044256
5777358046.13160930995-54.0221437774254-311.1316093099500.598105136908483
5884068385.11286867014-39.848748545601920.88713132986330.879948595988164
5982098678.07922050442-27.9161924609225-469.079220504420.744474207562555
6094518757.61648712134-24.108323809053693.383512878660.241013864461902
61100418938.58564728828-16.83784552473161102.414352711720.463214322977008
6294119597.382694421657.85222950915386-186.3826944216541.50404381469909
631040510160.206688993828.4300790146273244.7933110062161.23166513306803
6484678935.01565940254-17.8451539640008-468.015659402537-2.80328752306328
6584648675.48643981995-26.6952648094470-211.486439819950-0.541349303893581
6681028408.07059718626-35.4757937121427-306.070597186256-0.538760069718842
6776277744.84866308833-58.3701885985506-117.848663088333-1.40452386271733
6875137563.58552269625-62.858406708887-50.5855226962466-0.274983567620467
6975107805.0947013321-51.729569658535-295.0947013321040.681087404233371
7082918218.66335305533-34.728578927477172.33664694467041.04076132430908
7180648492.0031661567-23.5174066830719-428.0031661566960.688663990943668
7293838702.99372492693-15.0284324160277680.0062750730660.525732422054486

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 12008 & 12008 & 0 & 0 & 0 \tabularnewline
2 & 9169 & 9388.89187389219 & -142.267203920301 & -219.891873892190 & -3.66385078260992 \tabularnewline
3 & 8788 & 8928.99339069425 & -148.056579919683 & -140.993390694249 & -0.722911170744540 \tabularnewline
4 & 8417 & 8577.3297007661 & -149.799458812119 & -160.329700766098 & -0.467289399940227 \tabularnewline
5 & 8247 & 8389.36906915085 & -150.171333053023 & -142.369069150852 & -0.0874665006930955 \tabularnewline
6 & 8197 & 8329.19439861759 & -149.137135318066 & -132.194398617591 & 0.206089528795015 \tabularnewline
7 & 8236 & 8360.96198754883 & -146.813586532851 & -124.961987548830 & 0.41392900734709 \tabularnewline
8 & 8253 & 8383.2965189313 & -144.432430028789 & -130.296518931304 & 0.386718887093018 \tabularnewline
9 & 7733 & 7930.66895588783 & -149.140299301582 & -197.668955887832 & -0.704062661676525 \tabularnewline
10 & 8366 & 8407.3791195413 & -138.851646211607 & -41.379119541296 & 1.42863347237353 \tabularnewline
11 & 8626 & 8733.47106523327 & -130.685260314494 & -107.471065233271 & 1.06053131835543 \tabularnewline
12 & 8863 & 8974.04803516124 & -123.761885758681 & -111.048035161243 & 0.846224807480347 \tabularnewline
13 & 10102 & 8665.55589346594 & -120.111824451223 & 1436.44410653406 & -0.490615788453608 \tabularnewline
14 & 8463 & 8627.57214717709 & -117.349491576919 & -164.572147177090 & 0.165819693271633 \tabularnewline
15 & 9114 & 9088.71900432842 & -100.673707929885 & 25.2809956715764 & 1.28998246343461 \tabularnewline
16 & 8563 & 8771.40038656781 & -105.519165425684 & -208.400386567813 & -0.492000874706544 \tabularnewline
17 & 8872 & 8931.3674104351 & -99.7601543957376 & -59.3674104351058 & 0.602130349631512 \tabularnewline
18 & 8301 & 8514.20870383302 & -106.98177739346 & -213.208703833020 & -0.719305695704975 \tabularnewline
19 & 8301 & 8407.99035886114 & -106.963617146731 & -106.990358861139 & 0.00172906624957253 \tabularnewline
20 & 8278 & 8324.27033547651 & -106.390963267445 & -46.2703354765082 & 0.0526131346914988 \tabularnewline
21 & 7736 & 8018.04378824652 & -111.471055638895 & -282.043788246520 & -0.452096222166425 \tabularnewline
22 & 7973 & 8011.0079475362 & -108.728664000288 & -38.007947536193 & 0.236179881216291 \tabularnewline
23 & 8268 & 8322.92037226898 & -97.385584640251 & -54.9203722689791 & 0.95095469916207 \tabularnewline
24 & 9476 & 9346.9105825418 & -69.1206623408951 & 129.089417458195 & 2.53041039435348 \tabularnewline
25 & 11100 & 9661.95994966065 & -62.8546682630511 & 1438.04005033935 & 0.9170713418778 \tabularnewline
26 & 8962 & 9318.00853468992 & -72.2196725848506 & -356.008534689924 & -0.605346919005672 \tabularnewline
27 & 9173 & 9137.04228679038 & -75.945557636045 & 35.9577132096195 & -0.240653722603108 \tabularnewline
28 & 8738 & 9012.53935390992 & -77.4561619906584 & -274.539353909923 & -0.109458120248236 \tabularnewline
29 & 8459 & 8558.46490641278 & -88.7465262007022 & -99.4649064127828 & -0.848507729440133 \tabularnewline
30 & 8078 & 8317.6489566293 & -93.3469080741954 & -239.648956629305 & -0.342359596871604 \tabularnewline
31 & 8411 & 8463.13926176181 & -85.9884829484922 & -52.1392617618071 & 0.537526130308832 \tabularnewline
32 & 8291 & 8322.96406482126 & -87.6849064919641 & -31.9640648212641 & -0.121919195057910 \tabularnewline
33 & 7810 & 8119.73792109858 & -91.3551816504363 & -309.737921098577 & -0.259917963357657 \tabularnewline
34 & 8616 & 8581.59882854004 & -73.5410958172799 & 34.4011714599572 & 1.24442028134611 \tabularnewline
35 & 8312 & 8583.75365550529 & -71.1028740098202 & -271.753655505287 & 0.170138674147751 \tabularnewline
36 & 9692 & 9426.61851386154 & -43.0361381812555 & 265.381486138463 & 2.05459010125163 \tabularnewline
37 & 9911 & 8653.41820958264 & -63.9205859990319 & 1257.58179041736 & -1.68417676388808 \tabularnewline
38 & 8915 & 9118.26991304246 & -45.4556964029372 & -203.269913042461 & 1.16317317278305 \tabularnewline
39 & 9452 & 9358.7359633396 & -35.0714066857831 & 93.2640366604013 & 0.632355164329172 \tabularnewline
40 & 9112 & 9320.67113704642 & -35.1762182128944 & -208.671137046421 & -0.0067183005476785 \tabularnewline
41 & 8472 & 8684.02278423839 & -55.7079706096739 & -212.022784238391 & -1.35048000077100 \tabularnewline
42 & 8230 & 8505.36939312431 & -59.893582432723 & -275.369393124314 & -0.275819163036141 \tabularnewline
43 & 8384 & 8401.97636331256 & -61.3841490454277 & -17.9763633125611 & -0.0975693135988474 \tabularnewline
44 & 8625 & 8557.48336768916 & -53.894729120801 & 67.516632310838 & 0.48647364380057 \tabularnewline
45 & 8221 & 8600.15875750428 & -50.536598758424 & -379.158757504278 & 0.216610905850307 \tabularnewline
46 & 8649 & 8616.97990627379 & -48.1843771103339 & 32.0200937262141 & 0.151071277538892 \tabularnewline
47 & 8625 & 8967.66725386497 & -34.3435875179660 & -342.667253864975 & 0.893628842527756 \tabularnewline
48 & 10443 & 9844.35587197534 & -3.50141250389114 & 598.644128024657 & 2.04492958615987 \tabularnewline
49 & 10357 & 9384.05146324699 & -18.7906917118122 & 972.94853675301 & -1.03874933142919 \tabularnewline
50 & 8586 & 8948.49316683246 & -33.7969884700164 & -362.493166832463 & -0.924423479886598 \tabularnewline
51 & 8892 & 8805.33235151454 & -37.8377525385063 & 86.6676484854634 & -0.242260994363088 \tabularnewline
52 & 8329 & 8479.93846257643 & -48.3220563267916 & -150.938462576429 & -0.643842691458393 \tabularnewline
53 & 8101 & 8301.40150270439 & -52.9996655068539 & -200.401502704386 & -0.291901610103104 \tabularnewline
54 & 7922 & 8191.26148582335 & -55.0425831732391 & -269.26148582335 & -0.127977612445619 \tabularnewline
55 & 8120 & 8162.71302475495 & -54.0938132245838 & -42.7130247549492 & 0.0593262704475487 \tabularnewline
56 & 7838 & 7842.72929752526 & -63.6488662587655 & -4.7292975252641 & -0.59543939044256 \tabularnewline
57 & 7735 & 8046.13160930995 & -54.0221437774254 & -311.131609309950 & 0.598105136908483 \tabularnewline
58 & 8406 & 8385.11286867014 & -39.8487485456019 & 20.8871313298633 & 0.879948595988164 \tabularnewline
59 & 8209 & 8678.07922050442 & -27.9161924609225 & -469.07922050442 & 0.744474207562555 \tabularnewline
60 & 9451 & 8757.61648712134 & -24.108323809053 & 693.38351287866 & 0.241013864461902 \tabularnewline
61 & 10041 & 8938.58564728828 & -16.8378455247316 & 1102.41435271172 & 0.463214322977008 \tabularnewline
62 & 9411 & 9597.38269442165 & 7.85222950915386 & -186.382694421654 & 1.50404381469909 \tabularnewline
63 & 10405 & 10160.2066889938 & 28.4300790146273 & 244.793311006216 & 1.23166513306803 \tabularnewline
64 & 8467 & 8935.01565940254 & -17.8451539640008 & -468.015659402537 & -2.80328752306328 \tabularnewline
65 & 8464 & 8675.48643981995 & -26.6952648094470 & -211.486439819950 & -0.541349303893581 \tabularnewline
66 & 8102 & 8408.07059718626 & -35.4757937121427 & -306.070597186256 & -0.538760069718842 \tabularnewline
67 & 7627 & 7744.84866308833 & -58.3701885985506 & -117.848663088333 & -1.40452386271733 \tabularnewline
68 & 7513 & 7563.58552269625 & -62.858406708887 & -50.5855226962466 & -0.274983567620467 \tabularnewline
69 & 7510 & 7805.0947013321 & -51.729569658535 & -295.094701332104 & 0.681087404233371 \tabularnewline
70 & 8291 & 8218.66335305533 & -34.7285789274771 & 72.3366469446704 & 1.04076132430908 \tabularnewline
71 & 8064 & 8492.0031661567 & -23.5174066830719 & -428.003166156696 & 0.688663990943668 \tabularnewline
72 & 9383 & 8702.99372492693 & -15.0284324160277 & 680.006275073066 & 0.525732422054486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63884&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]12008[/C][C]12008[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]9169[/C][C]9388.89187389219[/C][C]-142.267203920301[/C][C]-219.891873892190[/C][C]-3.66385078260992[/C][/ROW]
[ROW][C]3[/C][C]8788[/C][C]8928.99339069425[/C][C]-148.056579919683[/C][C]-140.993390694249[/C][C]-0.722911170744540[/C][/ROW]
[ROW][C]4[/C][C]8417[/C][C]8577.3297007661[/C][C]-149.799458812119[/C][C]-160.329700766098[/C][C]-0.467289399940227[/C][/ROW]
[ROW][C]5[/C][C]8247[/C][C]8389.36906915085[/C][C]-150.171333053023[/C][C]-142.369069150852[/C][C]-0.0874665006930955[/C][/ROW]
[ROW][C]6[/C][C]8197[/C][C]8329.19439861759[/C][C]-149.137135318066[/C][C]-132.194398617591[/C][C]0.206089528795015[/C][/ROW]
[ROW][C]7[/C][C]8236[/C][C]8360.96198754883[/C][C]-146.813586532851[/C][C]-124.961987548830[/C][C]0.41392900734709[/C][/ROW]
[ROW][C]8[/C][C]8253[/C][C]8383.2965189313[/C][C]-144.432430028789[/C][C]-130.296518931304[/C][C]0.386718887093018[/C][/ROW]
[ROW][C]9[/C][C]7733[/C][C]7930.66895588783[/C][C]-149.140299301582[/C][C]-197.668955887832[/C][C]-0.704062661676525[/C][/ROW]
[ROW][C]10[/C][C]8366[/C][C]8407.3791195413[/C][C]-138.851646211607[/C][C]-41.379119541296[/C][C]1.42863347237353[/C][/ROW]
[ROW][C]11[/C][C]8626[/C][C]8733.47106523327[/C][C]-130.685260314494[/C][C]-107.471065233271[/C][C]1.06053131835543[/C][/ROW]
[ROW][C]12[/C][C]8863[/C][C]8974.04803516124[/C][C]-123.761885758681[/C][C]-111.048035161243[/C][C]0.846224807480347[/C][/ROW]
[ROW][C]13[/C][C]10102[/C][C]8665.55589346594[/C][C]-120.111824451223[/C][C]1436.44410653406[/C][C]-0.490615788453608[/C][/ROW]
[ROW][C]14[/C][C]8463[/C][C]8627.57214717709[/C][C]-117.349491576919[/C][C]-164.572147177090[/C][C]0.165819693271633[/C][/ROW]
[ROW][C]15[/C][C]9114[/C][C]9088.71900432842[/C][C]-100.673707929885[/C][C]25.2809956715764[/C][C]1.28998246343461[/C][/ROW]
[ROW][C]16[/C][C]8563[/C][C]8771.40038656781[/C][C]-105.519165425684[/C][C]-208.400386567813[/C][C]-0.492000874706544[/C][/ROW]
[ROW][C]17[/C][C]8872[/C][C]8931.3674104351[/C][C]-99.7601543957376[/C][C]-59.3674104351058[/C][C]0.602130349631512[/C][/ROW]
[ROW][C]18[/C][C]8301[/C][C]8514.20870383302[/C][C]-106.98177739346[/C][C]-213.208703833020[/C][C]-0.719305695704975[/C][/ROW]
[ROW][C]19[/C][C]8301[/C][C]8407.99035886114[/C][C]-106.963617146731[/C][C]-106.990358861139[/C][C]0.00172906624957253[/C][/ROW]
[ROW][C]20[/C][C]8278[/C][C]8324.27033547651[/C][C]-106.390963267445[/C][C]-46.2703354765082[/C][C]0.0526131346914988[/C][/ROW]
[ROW][C]21[/C][C]7736[/C][C]8018.04378824652[/C][C]-111.471055638895[/C][C]-282.043788246520[/C][C]-0.452096222166425[/C][/ROW]
[ROW][C]22[/C][C]7973[/C][C]8011.0079475362[/C][C]-108.728664000288[/C][C]-38.007947536193[/C][C]0.236179881216291[/C][/ROW]
[ROW][C]23[/C][C]8268[/C][C]8322.92037226898[/C][C]-97.385584640251[/C][C]-54.9203722689791[/C][C]0.95095469916207[/C][/ROW]
[ROW][C]24[/C][C]9476[/C][C]9346.9105825418[/C][C]-69.1206623408951[/C][C]129.089417458195[/C][C]2.53041039435348[/C][/ROW]
[ROW][C]25[/C][C]11100[/C][C]9661.95994966065[/C][C]-62.8546682630511[/C][C]1438.04005033935[/C][C]0.9170713418778[/C][/ROW]
[ROW][C]26[/C][C]8962[/C][C]9318.00853468992[/C][C]-72.2196725848506[/C][C]-356.008534689924[/C][C]-0.605346919005672[/C][/ROW]
[ROW][C]27[/C][C]9173[/C][C]9137.04228679038[/C][C]-75.945557636045[/C][C]35.9577132096195[/C][C]-0.240653722603108[/C][/ROW]
[ROW][C]28[/C][C]8738[/C][C]9012.53935390992[/C][C]-77.4561619906584[/C][C]-274.539353909923[/C][C]-0.109458120248236[/C][/ROW]
[ROW][C]29[/C][C]8459[/C][C]8558.46490641278[/C][C]-88.7465262007022[/C][C]-99.4649064127828[/C][C]-0.848507729440133[/C][/ROW]
[ROW][C]30[/C][C]8078[/C][C]8317.6489566293[/C][C]-93.3469080741954[/C][C]-239.648956629305[/C][C]-0.342359596871604[/C][/ROW]
[ROW][C]31[/C][C]8411[/C][C]8463.13926176181[/C][C]-85.9884829484922[/C][C]-52.1392617618071[/C][C]0.537526130308832[/C][/ROW]
[ROW][C]32[/C][C]8291[/C][C]8322.96406482126[/C][C]-87.6849064919641[/C][C]-31.9640648212641[/C][C]-0.121919195057910[/C][/ROW]
[ROW][C]33[/C][C]7810[/C][C]8119.73792109858[/C][C]-91.3551816504363[/C][C]-309.737921098577[/C][C]-0.259917963357657[/C][/ROW]
[ROW][C]34[/C][C]8616[/C][C]8581.59882854004[/C][C]-73.5410958172799[/C][C]34.4011714599572[/C][C]1.24442028134611[/C][/ROW]
[ROW][C]35[/C][C]8312[/C][C]8583.75365550529[/C][C]-71.1028740098202[/C][C]-271.753655505287[/C][C]0.170138674147751[/C][/ROW]
[ROW][C]36[/C][C]9692[/C][C]9426.61851386154[/C][C]-43.0361381812555[/C][C]265.381486138463[/C][C]2.05459010125163[/C][/ROW]
[ROW][C]37[/C][C]9911[/C][C]8653.41820958264[/C][C]-63.9205859990319[/C][C]1257.58179041736[/C][C]-1.68417676388808[/C][/ROW]
[ROW][C]38[/C][C]8915[/C][C]9118.26991304246[/C][C]-45.4556964029372[/C][C]-203.269913042461[/C][C]1.16317317278305[/C][/ROW]
[ROW][C]39[/C][C]9452[/C][C]9358.7359633396[/C][C]-35.0714066857831[/C][C]93.2640366604013[/C][C]0.632355164329172[/C][/ROW]
[ROW][C]40[/C][C]9112[/C][C]9320.67113704642[/C][C]-35.1762182128944[/C][C]-208.671137046421[/C][C]-0.0067183005476785[/C][/ROW]
[ROW][C]41[/C][C]8472[/C][C]8684.02278423839[/C][C]-55.7079706096739[/C][C]-212.022784238391[/C][C]-1.35048000077100[/C][/ROW]
[ROW][C]42[/C][C]8230[/C][C]8505.36939312431[/C][C]-59.893582432723[/C][C]-275.369393124314[/C][C]-0.275819163036141[/C][/ROW]
[ROW][C]43[/C][C]8384[/C][C]8401.97636331256[/C][C]-61.3841490454277[/C][C]-17.9763633125611[/C][C]-0.0975693135988474[/C][/ROW]
[ROW][C]44[/C][C]8625[/C][C]8557.48336768916[/C][C]-53.894729120801[/C][C]67.516632310838[/C][C]0.48647364380057[/C][/ROW]
[ROW][C]45[/C][C]8221[/C][C]8600.15875750428[/C][C]-50.536598758424[/C][C]-379.158757504278[/C][C]0.216610905850307[/C][/ROW]
[ROW][C]46[/C][C]8649[/C][C]8616.97990627379[/C][C]-48.1843771103339[/C][C]32.0200937262141[/C][C]0.151071277538892[/C][/ROW]
[ROW][C]47[/C][C]8625[/C][C]8967.66725386497[/C][C]-34.3435875179660[/C][C]-342.667253864975[/C][C]0.893628842527756[/C][/ROW]
[ROW][C]48[/C][C]10443[/C][C]9844.35587197534[/C][C]-3.50141250389114[/C][C]598.644128024657[/C][C]2.04492958615987[/C][/ROW]
[ROW][C]49[/C][C]10357[/C][C]9384.05146324699[/C][C]-18.7906917118122[/C][C]972.94853675301[/C][C]-1.03874933142919[/C][/ROW]
[ROW][C]50[/C][C]8586[/C][C]8948.49316683246[/C][C]-33.7969884700164[/C][C]-362.493166832463[/C][C]-0.924423479886598[/C][/ROW]
[ROW][C]51[/C][C]8892[/C][C]8805.33235151454[/C][C]-37.8377525385063[/C][C]86.6676484854634[/C][C]-0.242260994363088[/C][/ROW]
[ROW][C]52[/C][C]8329[/C][C]8479.93846257643[/C][C]-48.3220563267916[/C][C]-150.938462576429[/C][C]-0.643842691458393[/C][/ROW]
[ROW][C]53[/C][C]8101[/C][C]8301.40150270439[/C][C]-52.9996655068539[/C][C]-200.401502704386[/C][C]-0.291901610103104[/C][/ROW]
[ROW][C]54[/C][C]7922[/C][C]8191.26148582335[/C][C]-55.0425831732391[/C][C]-269.26148582335[/C][C]-0.127977612445619[/C][/ROW]
[ROW][C]55[/C][C]8120[/C][C]8162.71302475495[/C][C]-54.0938132245838[/C][C]-42.7130247549492[/C][C]0.0593262704475487[/C][/ROW]
[ROW][C]56[/C][C]7838[/C][C]7842.72929752526[/C][C]-63.6488662587655[/C][C]-4.7292975252641[/C][C]-0.59543939044256[/C][/ROW]
[ROW][C]57[/C][C]7735[/C][C]8046.13160930995[/C][C]-54.0221437774254[/C][C]-311.131609309950[/C][C]0.598105136908483[/C][/ROW]
[ROW][C]58[/C][C]8406[/C][C]8385.11286867014[/C][C]-39.8487485456019[/C][C]20.8871313298633[/C][C]0.879948595988164[/C][/ROW]
[ROW][C]59[/C][C]8209[/C][C]8678.07922050442[/C][C]-27.9161924609225[/C][C]-469.07922050442[/C][C]0.744474207562555[/C][/ROW]
[ROW][C]60[/C][C]9451[/C][C]8757.61648712134[/C][C]-24.108323809053[/C][C]693.38351287866[/C][C]0.241013864461902[/C][/ROW]
[ROW][C]61[/C][C]10041[/C][C]8938.58564728828[/C][C]-16.8378455247316[/C][C]1102.41435271172[/C][C]0.463214322977008[/C][/ROW]
[ROW][C]62[/C][C]9411[/C][C]9597.38269442165[/C][C]7.85222950915386[/C][C]-186.382694421654[/C][C]1.50404381469909[/C][/ROW]
[ROW][C]63[/C][C]10405[/C][C]10160.2066889938[/C][C]28.4300790146273[/C][C]244.793311006216[/C][C]1.23166513306803[/C][/ROW]
[ROW][C]64[/C][C]8467[/C][C]8935.01565940254[/C][C]-17.8451539640008[/C][C]-468.015659402537[/C][C]-2.80328752306328[/C][/ROW]
[ROW][C]65[/C][C]8464[/C][C]8675.48643981995[/C][C]-26.6952648094470[/C][C]-211.486439819950[/C][C]-0.541349303893581[/C][/ROW]
[ROW][C]66[/C][C]8102[/C][C]8408.07059718626[/C][C]-35.4757937121427[/C][C]-306.070597186256[/C][C]-0.538760069718842[/C][/ROW]
[ROW][C]67[/C][C]7627[/C][C]7744.84866308833[/C][C]-58.3701885985506[/C][C]-117.848663088333[/C][C]-1.40452386271733[/C][/ROW]
[ROW][C]68[/C][C]7513[/C][C]7563.58552269625[/C][C]-62.858406708887[/C][C]-50.5855226962466[/C][C]-0.274983567620467[/C][/ROW]
[ROW][C]69[/C][C]7510[/C][C]7805.0947013321[/C][C]-51.729569658535[/C][C]-295.094701332104[/C][C]0.681087404233371[/C][/ROW]
[ROW][C]70[/C][C]8291[/C][C]8218.66335305533[/C][C]-34.7285789274771[/C][C]72.3366469446704[/C][C]1.04076132430908[/C][/ROW]
[ROW][C]71[/C][C]8064[/C][C]8492.0031661567[/C][C]-23.5174066830719[/C][C]-428.003166156696[/C][C]0.688663990943668[/C][/ROW]
[ROW][C]72[/C][C]9383[/C][C]8702.99372492693[/C][C]-15.0284324160277[/C][C]680.006275073066[/C][C]0.525732422054486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63884&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63884&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
11200812008000
291699388.89187389219-142.267203920301-219.891873892190-3.66385078260992
387888928.99339069425-148.056579919683-140.993390694249-0.722911170744540
484178577.3297007661-149.799458812119-160.329700766098-0.467289399940227
582478389.36906915085-150.171333053023-142.369069150852-0.0874665006930955
681978329.19439861759-149.137135318066-132.1943986175910.206089528795015
782368360.96198754883-146.813586532851-124.9619875488300.41392900734709
882538383.2965189313-144.432430028789-130.2965189313040.386718887093018
977337930.66895588783-149.140299301582-197.668955887832-0.704062661676525
1083668407.3791195413-138.851646211607-41.3791195412961.42863347237353
1186268733.47106523327-130.685260314494-107.4710652332711.06053131835543
1288638974.04803516124-123.761885758681-111.0480351612430.846224807480347
13101028665.55589346594-120.1118244512231436.44410653406-0.490615788453608
1484638627.57214717709-117.349491576919-164.5721471770900.165819693271633
1591149088.71900432842-100.67370792988525.28099567157641.28998246343461
1685638771.40038656781-105.519165425684-208.400386567813-0.492000874706544
1788728931.3674104351-99.7601543957376-59.36741043510580.602130349631512
1883018514.20870383302-106.98177739346-213.208703833020-0.719305695704975
1983018407.99035886114-106.963617146731-106.9903588611390.00172906624957253
2082788324.27033547651-106.390963267445-46.27033547650820.0526131346914988
2177368018.04378824652-111.471055638895-282.043788246520-0.452096222166425
2279738011.0079475362-108.728664000288-38.0079475361930.236179881216291
2382688322.92037226898-97.385584640251-54.92037226897910.95095469916207
2494769346.9105825418-69.1206623408951129.0894174581952.53041039435348
25111009661.95994966065-62.85466826305111438.040050339350.9170713418778
2689629318.00853468992-72.2196725848506-356.008534689924-0.605346919005672
2791739137.04228679038-75.94555763604535.9577132096195-0.240653722603108
2887389012.53935390992-77.4561619906584-274.539353909923-0.109458120248236
2984598558.46490641278-88.7465262007022-99.4649064127828-0.848507729440133
3080788317.6489566293-93.3469080741954-239.648956629305-0.342359596871604
3184118463.13926176181-85.9884829484922-52.13926176180710.537526130308832
3282918322.96406482126-87.6849064919641-31.9640648212641-0.121919195057910
3378108119.73792109858-91.3551816504363-309.737921098577-0.259917963357657
3486168581.59882854004-73.541095817279934.40117145995721.24442028134611
3583128583.75365550529-71.1028740098202-271.7536555052870.170138674147751
3696929426.61851386154-43.0361381812555265.3814861384632.05459010125163
3799118653.41820958264-63.92058599903191257.58179041736-1.68417676388808
3889159118.26991304246-45.4556964029372-203.2699130424611.16317317278305
3994529358.7359633396-35.071406685783193.26403666040130.632355164329172
4091129320.67113704642-35.1762182128944-208.671137046421-0.0067183005476785
4184728684.02278423839-55.7079706096739-212.022784238391-1.35048000077100
4282308505.36939312431-59.893582432723-275.369393124314-0.275819163036141
4383848401.97636331256-61.3841490454277-17.9763633125611-0.0975693135988474
4486258557.48336768916-53.89472912080167.5166323108380.48647364380057
4582218600.15875750428-50.536598758424-379.1587575042780.216610905850307
4686498616.97990627379-48.184377110333932.02009372621410.151071277538892
4786258967.66725386497-34.3435875179660-342.6672538649750.893628842527756
48104439844.35587197534-3.50141250389114598.6441280246572.04492958615987
49103579384.05146324699-18.7906917118122972.94853675301-1.03874933142919
5085868948.49316683246-33.7969884700164-362.493166832463-0.924423479886598
5188928805.33235151454-37.837752538506386.6676484854634-0.242260994363088
5283298479.93846257643-48.3220563267916-150.938462576429-0.643842691458393
5381018301.40150270439-52.9996655068539-200.401502704386-0.291901610103104
5479228191.26148582335-55.0425831732391-269.26148582335-0.127977612445619
5581208162.71302475495-54.0938132245838-42.71302475494920.0593262704475487
5678387842.72929752526-63.6488662587655-4.7292975252641-0.59543939044256
5777358046.13160930995-54.0221437774254-311.1316093099500.598105136908483
5884068385.11286867014-39.848748545601920.88713132986330.879948595988164
5982098678.07922050442-27.9161924609225-469.079220504420.744474207562555
6094518757.61648712134-24.108323809053693.383512878660.241013864461902
61100418938.58564728828-16.83784552473161102.414352711720.463214322977008
6294119597.382694421657.85222950915386-186.3826944216541.50404381469909
631040510160.206688993828.4300790146273244.7933110062161.23166513306803
6484678935.01565940254-17.8451539640008-468.015659402537-2.80328752306328
6584648675.48643981995-26.6952648094470-211.486439819950-0.541349303893581
6681028408.07059718626-35.4757937121427-306.070597186256-0.538760069718842
6776277744.84866308833-58.3701885985506-117.848663088333-1.40452386271733
6875137563.58552269625-62.858406708887-50.5855226962466-0.274983567620467
6975107805.0947013321-51.729569658535-295.0947013321040.681087404233371
7082918218.66335305533-34.728578927477172.33664694467041.04076132430908
7180648492.0031661567-23.5174066830719-428.0031661566960.688663990943668
7293838702.99372492693-15.0284324160277680.0062750730660.525732422054486



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')