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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 computationFri, 18 Dec 2009 02:46:34 -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/18/t126112961723uzdn33cugcm81.htm/, Retrieved Sat, 27 Apr 2024 20:13:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69198, Retrieved Sat, 27 Apr 2024 20:13:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
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]
-   PD      [Structural Time Series Models] [] [2009-12-18 09:46:34] [409dc0d28e18f9691548de68770dd903] [Current]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971




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=69198&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=69198&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69198&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
12036620366000
22278221192.8451924941958.1802919585921589.154807505870.988967204645153
31916920924.5075597769237.625787910858-1755.50755977685-0.433375364748934
41380716728.1081653659-2217.32226812177-2921.1081653659-1.7247754410732
52974323289.72347753582906.129688943336453.276522464223.30016680842751
62559127163.60339297353456.1972338822-1572.603392973480.340923758438181
72909629875.25946326043038.61256038465-779.259463260393-0.262471663803087
82648228864.1054217508757.880330871136-2382.10542175076-1.43811313382639
92240524645.2781362471-2053.83036759147-2240.27813624709-1.76855917728509
102704424815.4945042030-796.7060781286162228.505495796950.79036270804015
111797020595.2929229606-2731.40230129571-2625.29292296061-1.21659674231775
121873018041.7774424149-2630.90634946330688.2225575851480.0631944230686166
131968417940.7657967778-1209.66563505441743.234203222190.898094254258725
141978516975.8805688021-1071.412983905652809.119431197940.088424326657573
151847917684.1298134932-79.2062242131777794.870186506840.618855614954735
161069817854.516197236256.30386771606-7156.516197236210.085437351820229
173195623169.61100413152934.103629115878786.388995868541.84118317930649
182950629556.17996801294836.07240260554-50.17996801292341.19792108688685
193450634022.20560168014633.8536221962483.794398319929-0.126525407088543
202716531726.9232165526863.18658177475-4561.92321655261-2.36958844976569
212673629995.5918444113-551.226994155067-3259.59184441131-0.890169520138849
222369123177.6396485601-3973.12433948536513.360351439931-2.15211394615063
231815719625.1733051999-3743.46334955044-1468.173305199930.144432763473818
241732816921.7516658738-3176.10878602574406.2483341262260.357106617504284
251820515389.4376130231-2278.778281655362815.562386976940.565959870835344
262099516663.2333219120-336.7066855525474331.766678088031.22336394634789
271738217277.2672774953180.429617990396104.7327225046810.324164237801773
28936719048.07432408181038.98436277583-9681.074324081750.539795864984487
293112423112.42784555292674.047322612118011.572154447081.03437660202425
302655126436.67035758283027.02458887888114.329642417190.222722004728340
313065127994.97396954982230.624765963332656.0260304502-0.499948109818415
322585928999.38234319911568.08966123052-3140.38234319911-0.415776007046794
332510027138.7314052673-282.324749683393-2038.73140526729-1.16318783698822
342577825488.7724371708-1020.78188437583289.227562829242-0.464583200189152
352041822910.08623837-1862.35774838318-2492.08623837002-0.529670212222713
361868819653.3180983905-2616.00549608923-965.318098390518-0.47458871454281
372042418146.3097939701-2016.046421087202277.690206029940.377787345280847
382477619263.4623917253-321.4053710292875512.537608274671.06524751903637
391981420470.3820088242502.626193894056-656.3820088242070.517191853013738
401273823113.53524350851652.88333387154-10375.53524350850.72330051130369
413156624521.74894402241521.348242396967044.25105597757-0.0829657380246594
423011128219.11299170462694.195820320181891.887008295420.739481438473368
433001928457.00396066621369.862273482651561.99603933382-0.832589600462527
443193431873.74459101482471.0145754431360.25540898516080.691281070924243
452582629872.056093133869.7103544923293-4046.05609313384-1.50860829147536
462683526574.9018829367-1736.9555322795260.098117063315-1.13655258581735
472020522654.2773848609-2909.39880887272-2449.27738486092-0.738252364671326
481778919331.4099970327-3131.6273352766-1542.40999703273-0.139956573977509
492052018392.7960406685-1952.095478092412127.203959331480.742239425622086
502251817551.7016378320-1354.973748080544966.298362168040.375189097242518
511557216924.7903523204-964.574603769477-1352.790352320430.24515725933423
521150919977.3744569321185.26905455739-8468.374456932021.35197119230072
532544720501.2522577965831.2003181623054945.74774220348-0.223095983629654
542409021503.6858491850923.0259879830842586.314150814970.057859544180473
552778625315.72630846332473.138749238272470.273691536670.974953278542742
562619525492.24651066881242.65898510451702.75348933124-0.772802277934032
572051623839.2608111191-305.713893246069-3323.26081111909-0.972674190162594
582275921787.9361281382-1238.29266853464971.063871861812-0.586591924232752
591902820894.1820914719-1054.13716245344-1866.182091471880.115960509178643
601697119616.5935575569-1173.70450066586-2645.59355755693-0.075295778914886

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 20366 & 20366 & 0 & 0 & 0 \tabularnewline
2 & 22782 & 21192.8451924941 & 958.180291958592 & 1589.15480750587 & 0.988967204645153 \tabularnewline
3 & 19169 & 20924.5075597769 & 237.625787910858 & -1755.50755977685 & -0.433375364748934 \tabularnewline
4 & 13807 & 16728.1081653659 & -2217.32226812177 & -2921.1081653659 & -1.7247754410732 \tabularnewline
5 & 29743 & 23289.7234775358 & 2906.12968894333 & 6453.27652246422 & 3.30016680842751 \tabularnewline
6 & 25591 & 27163.6033929735 & 3456.1972338822 & -1572.60339297348 & 0.340923758438181 \tabularnewline
7 & 29096 & 29875.2594632604 & 3038.61256038465 & -779.259463260393 & -0.262471663803087 \tabularnewline
8 & 26482 & 28864.1054217508 & 757.880330871136 & -2382.10542175076 & -1.43811313382639 \tabularnewline
9 & 22405 & 24645.2781362471 & -2053.83036759147 & -2240.27813624709 & -1.76855917728509 \tabularnewline
10 & 27044 & 24815.4945042030 & -796.706078128616 & 2228.50549579695 & 0.79036270804015 \tabularnewline
11 & 17970 & 20595.2929229606 & -2731.40230129571 & -2625.29292296061 & -1.21659674231775 \tabularnewline
12 & 18730 & 18041.7774424149 & -2630.90634946330 & 688.222557585148 & 0.0631944230686166 \tabularnewline
13 & 19684 & 17940.7657967778 & -1209.6656350544 & 1743.23420322219 & 0.898094254258725 \tabularnewline
14 & 19785 & 16975.8805688021 & -1071.41298390565 & 2809.11943119794 & 0.088424326657573 \tabularnewline
15 & 18479 & 17684.1298134932 & -79.2062242131777 & 794.87018650684 & 0.618855614954735 \tabularnewline
16 & 10698 & 17854.5161972362 & 56.30386771606 & -7156.51619723621 & 0.085437351820229 \tabularnewline
17 & 31956 & 23169.6110041315 & 2934.10362911587 & 8786.38899586854 & 1.84118317930649 \tabularnewline
18 & 29506 & 29556.1799680129 & 4836.07240260554 & -50.1799680129234 & 1.19792108688685 \tabularnewline
19 & 34506 & 34022.2056016801 & 4633.8536221962 & 483.794398319929 & -0.126525407088543 \tabularnewline
20 & 27165 & 31726.9232165526 & 863.18658177475 & -4561.92321655261 & -2.36958844976569 \tabularnewline
21 & 26736 & 29995.5918444113 & -551.226994155067 & -3259.59184441131 & -0.890169520138849 \tabularnewline
22 & 23691 & 23177.6396485601 & -3973.12433948536 & 513.360351439931 & -2.15211394615063 \tabularnewline
23 & 18157 & 19625.1733051999 & -3743.46334955044 & -1468.17330519993 & 0.144432763473818 \tabularnewline
24 & 17328 & 16921.7516658738 & -3176.10878602574 & 406.248334126226 & 0.357106617504284 \tabularnewline
25 & 18205 & 15389.4376130231 & -2278.77828165536 & 2815.56238697694 & 0.565959870835344 \tabularnewline
26 & 20995 & 16663.2333219120 & -336.706685552547 & 4331.76667808803 & 1.22336394634789 \tabularnewline
27 & 17382 & 17277.2672774953 & 180.429617990396 & 104.732722504681 & 0.324164237801773 \tabularnewline
28 & 9367 & 19048.0743240818 & 1038.98436277583 & -9681.07432408175 & 0.539795864984487 \tabularnewline
29 & 31124 & 23112.4278455529 & 2674.04732261211 & 8011.57215444708 & 1.03437660202425 \tabularnewline
30 & 26551 & 26436.6703575828 & 3027.02458887888 & 114.32964241719 & 0.222722004728340 \tabularnewline
31 & 30651 & 27994.9739695498 & 2230.62476596333 & 2656.0260304502 & -0.499948109818415 \tabularnewline
32 & 25859 & 28999.3823431991 & 1568.08966123052 & -3140.38234319911 & -0.415776007046794 \tabularnewline
33 & 25100 & 27138.7314052673 & -282.324749683393 & -2038.73140526729 & -1.16318783698822 \tabularnewline
34 & 25778 & 25488.7724371708 & -1020.78188437583 & 289.227562829242 & -0.464583200189152 \tabularnewline
35 & 20418 & 22910.08623837 & -1862.35774838318 & -2492.08623837002 & -0.529670212222713 \tabularnewline
36 & 18688 & 19653.3180983905 & -2616.00549608923 & -965.318098390518 & -0.47458871454281 \tabularnewline
37 & 20424 & 18146.3097939701 & -2016.04642108720 & 2277.69020602994 & 0.377787345280847 \tabularnewline
38 & 24776 & 19263.4623917253 & -321.405371029287 & 5512.53760827467 & 1.06524751903637 \tabularnewline
39 & 19814 & 20470.3820088242 & 502.626193894056 & -656.382008824207 & 0.517191853013738 \tabularnewline
40 & 12738 & 23113.5352435085 & 1652.88333387154 & -10375.5352435085 & 0.72330051130369 \tabularnewline
41 & 31566 & 24521.7489440224 & 1521.34824239696 & 7044.25105597757 & -0.0829657380246594 \tabularnewline
42 & 30111 & 28219.1129917046 & 2694.19582032018 & 1891.88700829542 & 0.739481438473368 \tabularnewline
43 & 30019 & 28457.0039606662 & 1369.86227348265 & 1561.99603933382 & -0.832589600462527 \tabularnewline
44 & 31934 & 31873.7445910148 & 2471.01457544313 & 60.2554089851608 & 0.691281070924243 \tabularnewline
45 & 25826 & 29872.0560931338 & 69.7103544923293 & -4046.05609313384 & -1.50860829147536 \tabularnewline
46 & 26835 & 26574.9018829367 & -1736.9555322795 & 260.098117063315 & -1.13655258581735 \tabularnewline
47 & 20205 & 22654.2773848609 & -2909.39880887272 & -2449.27738486092 & -0.738252364671326 \tabularnewline
48 & 17789 & 19331.4099970327 & -3131.6273352766 & -1542.40999703273 & -0.139956573977509 \tabularnewline
49 & 20520 & 18392.7960406685 & -1952.09547809241 & 2127.20395933148 & 0.742239425622086 \tabularnewline
50 & 22518 & 17551.7016378320 & -1354.97374808054 & 4966.29836216804 & 0.375189097242518 \tabularnewline
51 & 15572 & 16924.7903523204 & -964.574603769477 & -1352.79035232043 & 0.24515725933423 \tabularnewline
52 & 11509 & 19977.374456932 & 1185.26905455739 & -8468.37445693202 & 1.35197119230072 \tabularnewline
53 & 25447 & 20501.2522577965 & 831.200318162305 & 4945.74774220348 & -0.223095983629654 \tabularnewline
54 & 24090 & 21503.6858491850 & 923.025987983084 & 2586.31415081497 & 0.057859544180473 \tabularnewline
55 & 27786 & 25315.7263084633 & 2473.13874923827 & 2470.27369153667 & 0.974953278542742 \tabularnewline
56 & 26195 & 25492.2465106688 & 1242.65898510451 & 702.75348933124 & -0.772802277934032 \tabularnewline
57 & 20516 & 23839.2608111191 & -305.713893246069 & -3323.26081111909 & -0.972674190162594 \tabularnewline
58 & 22759 & 21787.9361281382 & -1238.29266853464 & 971.063871861812 & -0.586591924232752 \tabularnewline
59 & 19028 & 20894.1820914719 & -1054.13716245344 & -1866.18209147188 & 0.115960509178643 \tabularnewline
60 & 16971 & 19616.5935575569 & -1173.70450066586 & -2645.59355755693 & -0.075295778914886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69198&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]20366[/C][C]20366[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]22782[/C][C]21192.8451924941[/C][C]958.180291958592[/C][C]1589.15480750587[/C][C]0.988967204645153[/C][/ROW]
[ROW][C]3[/C][C]19169[/C][C]20924.5075597769[/C][C]237.625787910858[/C][C]-1755.50755977685[/C][C]-0.433375364748934[/C][/ROW]
[ROW][C]4[/C][C]13807[/C][C]16728.1081653659[/C][C]-2217.32226812177[/C][C]-2921.1081653659[/C][C]-1.7247754410732[/C][/ROW]
[ROW][C]5[/C][C]29743[/C][C]23289.7234775358[/C][C]2906.12968894333[/C][C]6453.27652246422[/C][C]3.30016680842751[/C][/ROW]
[ROW][C]6[/C][C]25591[/C][C]27163.6033929735[/C][C]3456.1972338822[/C][C]-1572.60339297348[/C][C]0.340923758438181[/C][/ROW]
[ROW][C]7[/C][C]29096[/C][C]29875.2594632604[/C][C]3038.61256038465[/C][C]-779.259463260393[/C][C]-0.262471663803087[/C][/ROW]
[ROW][C]8[/C][C]26482[/C][C]28864.1054217508[/C][C]757.880330871136[/C][C]-2382.10542175076[/C][C]-1.43811313382639[/C][/ROW]
[ROW][C]9[/C][C]22405[/C][C]24645.2781362471[/C][C]-2053.83036759147[/C][C]-2240.27813624709[/C][C]-1.76855917728509[/C][/ROW]
[ROW][C]10[/C][C]27044[/C][C]24815.4945042030[/C][C]-796.706078128616[/C][C]2228.50549579695[/C][C]0.79036270804015[/C][/ROW]
[ROW][C]11[/C][C]17970[/C][C]20595.2929229606[/C][C]-2731.40230129571[/C][C]-2625.29292296061[/C][C]-1.21659674231775[/C][/ROW]
[ROW][C]12[/C][C]18730[/C][C]18041.7774424149[/C][C]-2630.90634946330[/C][C]688.222557585148[/C][C]0.0631944230686166[/C][/ROW]
[ROW][C]13[/C][C]19684[/C][C]17940.7657967778[/C][C]-1209.6656350544[/C][C]1743.23420322219[/C][C]0.898094254258725[/C][/ROW]
[ROW][C]14[/C][C]19785[/C][C]16975.8805688021[/C][C]-1071.41298390565[/C][C]2809.11943119794[/C][C]0.088424326657573[/C][/ROW]
[ROW][C]15[/C][C]18479[/C][C]17684.1298134932[/C][C]-79.2062242131777[/C][C]794.87018650684[/C][C]0.618855614954735[/C][/ROW]
[ROW][C]16[/C][C]10698[/C][C]17854.5161972362[/C][C]56.30386771606[/C][C]-7156.51619723621[/C][C]0.085437351820229[/C][/ROW]
[ROW][C]17[/C][C]31956[/C][C]23169.6110041315[/C][C]2934.10362911587[/C][C]8786.38899586854[/C][C]1.84118317930649[/C][/ROW]
[ROW][C]18[/C][C]29506[/C][C]29556.1799680129[/C][C]4836.07240260554[/C][C]-50.1799680129234[/C][C]1.19792108688685[/C][/ROW]
[ROW][C]19[/C][C]34506[/C][C]34022.2056016801[/C][C]4633.8536221962[/C][C]483.794398319929[/C][C]-0.126525407088543[/C][/ROW]
[ROW][C]20[/C][C]27165[/C][C]31726.9232165526[/C][C]863.18658177475[/C][C]-4561.92321655261[/C][C]-2.36958844976569[/C][/ROW]
[ROW][C]21[/C][C]26736[/C][C]29995.5918444113[/C][C]-551.226994155067[/C][C]-3259.59184441131[/C][C]-0.890169520138849[/C][/ROW]
[ROW][C]22[/C][C]23691[/C][C]23177.6396485601[/C][C]-3973.12433948536[/C][C]513.360351439931[/C][C]-2.15211394615063[/C][/ROW]
[ROW][C]23[/C][C]18157[/C][C]19625.1733051999[/C][C]-3743.46334955044[/C][C]-1468.17330519993[/C][C]0.144432763473818[/C][/ROW]
[ROW][C]24[/C][C]17328[/C][C]16921.7516658738[/C][C]-3176.10878602574[/C][C]406.248334126226[/C][C]0.357106617504284[/C][/ROW]
[ROW][C]25[/C][C]18205[/C][C]15389.4376130231[/C][C]-2278.77828165536[/C][C]2815.56238697694[/C][C]0.565959870835344[/C][/ROW]
[ROW][C]26[/C][C]20995[/C][C]16663.2333219120[/C][C]-336.706685552547[/C][C]4331.76667808803[/C][C]1.22336394634789[/C][/ROW]
[ROW][C]27[/C][C]17382[/C][C]17277.2672774953[/C][C]180.429617990396[/C][C]104.732722504681[/C][C]0.324164237801773[/C][/ROW]
[ROW][C]28[/C][C]9367[/C][C]19048.0743240818[/C][C]1038.98436277583[/C][C]-9681.07432408175[/C][C]0.539795864984487[/C][/ROW]
[ROW][C]29[/C][C]31124[/C][C]23112.4278455529[/C][C]2674.04732261211[/C][C]8011.57215444708[/C][C]1.03437660202425[/C][/ROW]
[ROW][C]30[/C][C]26551[/C][C]26436.6703575828[/C][C]3027.02458887888[/C][C]114.32964241719[/C][C]0.222722004728340[/C][/ROW]
[ROW][C]31[/C][C]30651[/C][C]27994.9739695498[/C][C]2230.62476596333[/C][C]2656.0260304502[/C][C]-0.499948109818415[/C][/ROW]
[ROW][C]32[/C][C]25859[/C][C]28999.3823431991[/C][C]1568.08966123052[/C][C]-3140.38234319911[/C][C]-0.415776007046794[/C][/ROW]
[ROW][C]33[/C][C]25100[/C][C]27138.7314052673[/C][C]-282.324749683393[/C][C]-2038.73140526729[/C][C]-1.16318783698822[/C][/ROW]
[ROW][C]34[/C][C]25778[/C][C]25488.7724371708[/C][C]-1020.78188437583[/C][C]289.227562829242[/C][C]-0.464583200189152[/C][/ROW]
[ROW][C]35[/C][C]20418[/C][C]22910.08623837[/C][C]-1862.35774838318[/C][C]-2492.08623837002[/C][C]-0.529670212222713[/C][/ROW]
[ROW][C]36[/C][C]18688[/C][C]19653.3180983905[/C][C]-2616.00549608923[/C][C]-965.318098390518[/C][C]-0.47458871454281[/C][/ROW]
[ROW][C]37[/C][C]20424[/C][C]18146.3097939701[/C][C]-2016.04642108720[/C][C]2277.69020602994[/C][C]0.377787345280847[/C][/ROW]
[ROW][C]38[/C][C]24776[/C][C]19263.4623917253[/C][C]-321.405371029287[/C][C]5512.53760827467[/C][C]1.06524751903637[/C][/ROW]
[ROW][C]39[/C][C]19814[/C][C]20470.3820088242[/C][C]502.626193894056[/C][C]-656.382008824207[/C][C]0.517191853013738[/C][/ROW]
[ROW][C]40[/C][C]12738[/C][C]23113.5352435085[/C][C]1652.88333387154[/C][C]-10375.5352435085[/C][C]0.72330051130369[/C][/ROW]
[ROW][C]41[/C][C]31566[/C][C]24521.7489440224[/C][C]1521.34824239696[/C][C]7044.25105597757[/C][C]-0.0829657380246594[/C][/ROW]
[ROW][C]42[/C][C]30111[/C][C]28219.1129917046[/C][C]2694.19582032018[/C][C]1891.88700829542[/C][C]0.739481438473368[/C][/ROW]
[ROW][C]43[/C][C]30019[/C][C]28457.0039606662[/C][C]1369.86227348265[/C][C]1561.99603933382[/C][C]-0.832589600462527[/C][/ROW]
[ROW][C]44[/C][C]31934[/C][C]31873.7445910148[/C][C]2471.01457544313[/C][C]60.2554089851608[/C][C]0.691281070924243[/C][/ROW]
[ROW][C]45[/C][C]25826[/C][C]29872.0560931338[/C][C]69.7103544923293[/C][C]-4046.05609313384[/C][C]-1.50860829147536[/C][/ROW]
[ROW][C]46[/C][C]26835[/C][C]26574.9018829367[/C][C]-1736.9555322795[/C][C]260.098117063315[/C][C]-1.13655258581735[/C][/ROW]
[ROW][C]47[/C][C]20205[/C][C]22654.2773848609[/C][C]-2909.39880887272[/C][C]-2449.27738486092[/C][C]-0.738252364671326[/C][/ROW]
[ROW][C]48[/C][C]17789[/C][C]19331.4099970327[/C][C]-3131.6273352766[/C][C]-1542.40999703273[/C][C]-0.139956573977509[/C][/ROW]
[ROW][C]49[/C][C]20520[/C][C]18392.7960406685[/C][C]-1952.09547809241[/C][C]2127.20395933148[/C][C]0.742239425622086[/C][/ROW]
[ROW][C]50[/C][C]22518[/C][C]17551.7016378320[/C][C]-1354.97374808054[/C][C]4966.29836216804[/C][C]0.375189097242518[/C][/ROW]
[ROW][C]51[/C][C]15572[/C][C]16924.7903523204[/C][C]-964.574603769477[/C][C]-1352.79035232043[/C][C]0.24515725933423[/C][/ROW]
[ROW][C]52[/C][C]11509[/C][C]19977.374456932[/C][C]1185.26905455739[/C][C]-8468.37445693202[/C][C]1.35197119230072[/C][/ROW]
[ROW][C]53[/C][C]25447[/C][C]20501.2522577965[/C][C]831.200318162305[/C][C]4945.74774220348[/C][C]-0.223095983629654[/C][/ROW]
[ROW][C]54[/C][C]24090[/C][C]21503.6858491850[/C][C]923.025987983084[/C][C]2586.31415081497[/C][C]0.057859544180473[/C][/ROW]
[ROW][C]55[/C][C]27786[/C][C]25315.7263084633[/C][C]2473.13874923827[/C][C]2470.27369153667[/C][C]0.974953278542742[/C][/ROW]
[ROW][C]56[/C][C]26195[/C][C]25492.2465106688[/C][C]1242.65898510451[/C][C]702.75348933124[/C][C]-0.772802277934032[/C][/ROW]
[ROW][C]57[/C][C]20516[/C][C]23839.2608111191[/C][C]-305.713893246069[/C][C]-3323.26081111909[/C][C]-0.972674190162594[/C][/ROW]
[ROW][C]58[/C][C]22759[/C][C]21787.9361281382[/C][C]-1238.29266853464[/C][C]971.063871861812[/C][C]-0.586591924232752[/C][/ROW]
[ROW][C]59[/C][C]19028[/C][C]20894.1820914719[/C][C]-1054.13716245344[/C][C]-1866.18209147188[/C][C]0.115960509178643[/C][/ROW]
[ROW][C]60[/C][C]16971[/C][C]19616.5935575569[/C][C]-1173.70450066586[/C][C]-2645.59355755693[/C][C]-0.075295778914886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69198&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69198&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
12036620366000
22278221192.8451924941958.1802919585921589.154807505870.988967204645153
31916920924.5075597769237.625787910858-1755.50755977685-0.433375364748934
41380716728.1081653659-2217.32226812177-2921.1081653659-1.7247754410732
52974323289.72347753582906.129688943336453.276522464223.30016680842751
62559127163.60339297353456.1972338822-1572.603392973480.340923758438181
72909629875.25946326043038.61256038465-779.259463260393-0.262471663803087
82648228864.1054217508757.880330871136-2382.10542175076-1.43811313382639
92240524645.2781362471-2053.83036759147-2240.27813624709-1.76855917728509
102704424815.4945042030-796.7060781286162228.505495796950.79036270804015
111797020595.2929229606-2731.40230129571-2625.29292296061-1.21659674231775
121873018041.7774424149-2630.90634946330688.2225575851480.0631944230686166
131968417940.7657967778-1209.66563505441743.234203222190.898094254258725
141978516975.8805688021-1071.412983905652809.119431197940.088424326657573
151847917684.1298134932-79.2062242131777794.870186506840.618855614954735
161069817854.516197236256.30386771606-7156.516197236210.085437351820229
173195623169.61100413152934.103629115878786.388995868541.84118317930649
182950629556.17996801294836.07240260554-50.17996801292341.19792108688685
193450634022.20560168014633.8536221962483.794398319929-0.126525407088543
202716531726.9232165526863.18658177475-4561.92321655261-2.36958844976569
212673629995.5918444113-551.226994155067-3259.59184441131-0.890169520138849
222369123177.6396485601-3973.12433948536513.360351439931-2.15211394615063
231815719625.1733051999-3743.46334955044-1468.173305199930.144432763473818
241732816921.7516658738-3176.10878602574406.2483341262260.357106617504284
251820515389.4376130231-2278.778281655362815.562386976940.565959870835344
262099516663.2333219120-336.7066855525474331.766678088031.22336394634789
271738217277.2672774953180.429617990396104.7327225046810.324164237801773
28936719048.07432408181038.98436277583-9681.074324081750.539795864984487
293112423112.42784555292674.047322612118011.572154447081.03437660202425
302655126436.67035758283027.02458887888114.329642417190.222722004728340
313065127994.97396954982230.624765963332656.0260304502-0.499948109818415
322585928999.38234319911568.08966123052-3140.38234319911-0.415776007046794
332510027138.7314052673-282.324749683393-2038.73140526729-1.16318783698822
342577825488.7724371708-1020.78188437583289.227562829242-0.464583200189152
352041822910.08623837-1862.35774838318-2492.08623837002-0.529670212222713
361868819653.3180983905-2616.00549608923-965.318098390518-0.47458871454281
372042418146.3097939701-2016.046421087202277.690206029940.377787345280847
382477619263.4623917253-321.4053710292875512.537608274671.06524751903637
391981420470.3820088242502.626193894056-656.3820088242070.517191853013738
401273823113.53524350851652.88333387154-10375.53524350850.72330051130369
413156624521.74894402241521.348242396967044.25105597757-0.0829657380246594
423011128219.11299170462694.195820320181891.887008295420.739481438473368
433001928457.00396066621369.862273482651561.99603933382-0.832589600462527
443193431873.74459101482471.0145754431360.25540898516080.691281070924243
452582629872.056093133869.7103544923293-4046.05609313384-1.50860829147536
462683526574.9018829367-1736.9555322795260.098117063315-1.13655258581735
472020522654.2773848609-2909.39880887272-2449.27738486092-0.738252364671326
481778919331.4099970327-3131.6273352766-1542.40999703273-0.139956573977509
492052018392.7960406685-1952.095478092412127.203959331480.742239425622086
502251817551.7016378320-1354.973748080544966.298362168040.375189097242518
511557216924.7903523204-964.574603769477-1352.790352320430.24515725933423
521150919977.3744569321185.26905455739-8468.374456932021.35197119230072
532544720501.2522577965831.2003181623054945.74774220348-0.223095983629654
542409021503.6858491850923.0259879830842586.314150814970.057859544180473
552778625315.72630846332473.138749238272470.273691536670.974953278542742
562619525492.24651066881242.65898510451702.75348933124-0.772802277934032
572051623839.2608111191-305.713893246069-3323.26081111909-0.972674190162594
582275921787.9361281382-1238.29266853464971.063871861812-0.586591924232752
591902820894.1820914719-1054.13716245344-1866.182091471880.115960509178643
601697119616.5935575569-1173.70450066586-2645.59355755693-0.075295778914886



Parameters (Session):
par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
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')