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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationFri, 04 Dec 2009 12:26:25 -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/t125995488925cjzhv214d9lm0.htm/, Retrieved Sat, 27 Apr 2024 22:50:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64066, Retrieved Sat, 27 Apr 2024 22:50:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
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]
-    D      [Structural Time Series Models] [Structural Time S...] [2009-12-04 19:26:25] [d1081bd6cdf1fed9ed45c42dbd523bf1] [Current]
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Dataseries X:
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8
7.5
6.8
6.5
6.6
7.6
8
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5




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=64066&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=64066&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64066&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
17.37.3000
27.67.596395402372010.234285422268640.00360459762799170.872311949205638
37.57.49357827748373-0.07506796121311550.00642172251626942-0.970173911050916
47.67.593699243402270.08564596170000330.006300756597729150.532724146801564
57.97.893711394606580.2824141659922230.006288605393423680.652468147237377
67.97.893710081175750.02316965422484480.00628991882425245-0.859636822184238
78.18.093710148645730.1854925900532740.006289851354267680.538251606697165
88.28.193710145969550.1070139321738190.00628985403044805-0.260229791212702
987.9937101451811-0.1748121457620420.00628985481890516-0.93451574480604
107.57.49371014511258-0.4733211316681790.00628985488742043-0.989835111564299
116.86.79371014510866-0.6814029472410580.00628985489133873-0.689984881047587
126.56.4937101451092-0.3312908335234640.006289854890797841.16094750745841
136.66.622494024819470.0871420213598957-0.02249402481946801.46296838828869
147.67.587536106825190.7972277513562760.01246389317480742.31033551408993
1587.985590558685020.4309751284679690.0144094413149839-1.17879502927377
168.18.085457608955550.1271446157910270.0145423910444483-1.00728304615704
177.77.6854402367889-0.3567524122774740.0145597632110952-1.60456689144521
187.57.48544066059922-0.2128601878889700.01455933940077750.477136640564384
197.67.585440729996220.07433251073392630.01455927000377980.95231108705789
207.87.785440732283120.1896900626637040.01455926771688390.382517648296371
217.87.785440731999910.01556243918617110.0145592680000890-0.57739513297434
227.87.785440731998000.001276764370375380.0145592680019952-0.0473703077384437
237.57.48544073199498-0.2752828310672620.0145592680050227-0.917052453792022
247.57.4854407319952-0.02258459013257050.01455926800479580.837929855774401
257.17.27226335877404-0.196530167346724-0.172263358774043-0.596561262010691
267.57.480906152310510.1438345235508800.01909384768949291.11702491797441
277.57.480394253591650.01137572427170720.0196057464083517-0.429865863048256
287.67.580420124225080.0927309007112590.01957987577491710.269729622804666
297.77.680420298312480.09940363385599330.01957970168751530.0221262994531427
307.77.680420103003560.0081552136578660.0195798969964388-0.302573436202211
317.97.880420133928080.1842607842578130.01957986607192260.58395386854156
328.18.080420134136220.1987087326326630.01957986586377620.0479083956152225
338.28.180420134029130.1080982030748930.0195798659708724-0.300458236998992
348.28.18042013401950.008868528418748380.0195798659804946-0.329038724866522
358.28.180420134019440.0007275865285167670.0195798659805593-0.0269947991672508
367.97.88042013401926-0.2753278863888010.0195798659807396-0.91538081844869
377.37.5193445893845-0.353709715765585-0.219344589384493-0.266412201014775
386.96.88192914455305-0.5969513646596310.0180708554469515-0.801098916764735
396.66.5827591201618-0.3236737728358340.01724087983820200.891022041950161
406.76.682856251489060.06524781942366350.01714374851093731.28949248454303
416.96.882858786011130.1889447559802440.01714121398887400.410170160360221
4276.98285864876070.1072971526526330.0171413512393016-0.270737793346502
437.17.08285864783690.1005986686534210.0171413521631056-0.0222117087575052
447.27.182858647830680.1000491156172380.0171413521693236-0.00182227978574612
457.17.08285864766021-0.08358768955883620.0171413523397862-0.608926920531383
466.96.88285864765208-0.1904493705346370.0171413523479243-0.354345928949323
4776.982858647653740.07617112566607930.01714135234625850.884095089469596
486.86.78285864765361-0.1773425329308140.0171413523463885-0.840633724236474
496.46.58914992692075-0.192316358738675-0.189149926920748-0.0506304848348785
506.76.68127114218430.05468772026955990.01872885781570560.814982755297965
516.66.58091521163117-0.08760447543058670.0190847883688329-0.465341983043639
526.46.38089399715998-0.1907803571708810.0191060028400165-0.342092499914615
536.36.28089540290874-0.1074477401660720.0191045970912580.276325011665894
546.26.18089541237053-0.1006110230602440.01910458762946540.0226700800659161
556.56.480895454125190.2671333089575690.01910454587481141.21941472145232
566.86.780895454406230.2973035705011860.01910454559376960.100042496577755
576.86.780895454197660.02439120252682360.0191045458023379-0.904958500264783
586.46.38089545417324-0.3651823496300970.0191045458267636-1.29179890277406
596.16.08089545417354-0.3053476515210430.01910454582645580.198407712579930
605.85.78089545417355-0.3004387288422830.01910454582645380.0162776474304136
616.16.286022512032990.437023850462163-0.1860225120329872.48511089966492
627.27.18100002249470.8382020033515150.01899997750529931.32513066817445
637.37.279556538150450.1593656406191950.0204434618495487-2.22467789645746
646.96.87946681357677-0.3541149639107080.0205331864232308-1.70253256245747
656.16.07946094583202-0.7634189980982260.0205390541679799-1.35722309747112
665.85.77946144616051-0.3380195453091720.02053855383948871.41059510164002
676.26.179461511531090.3394518398574430.02053848846890672.24644816659836
687.17.079461515604530.854011841576530.02053848439547441.70624530836807
697.77.679461515453090.6208394882767810.0205384845469122-0.773183365457345
707.97.87946151543250.2345262627439690.0205384845674963-1.28098788561853
717.77.67946151543076-0.1643508550538260.0205384845692399-1.3226488817324
727.47.37946151543072-0.2888711536111220.0205384845692847-0.412900681164878
737.57.710147141511730.278539781442523-0.2101471415117251.90750876607253

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 7.3 & 7.3 & 0 & 0 & 0 \tabularnewline
2 & 7.6 & 7.59639540237201 & 0.23428542226864 & 0.0036045976279917 & 0.872311949205638 \tabularnewline
3 & 7.5 & 7.49357827748373 & -0.0750679612131155 & 0.00642172251626942 & -0.970173911050916 \tabularnewline
4 & 7.6 & 7.59369924340227 & 0.0856459617000033 & 0.00630075659772915 & 0.532724146801564 \tabularnewline
5 & 7.9 & 7.89371139460658 & 0.282414165992223 & 0.00628860539342368 & 0.652468147237377 \tabularnewline
6 & 7.9 & 7.89371008117575 & 0.0231696542248448 & 0.00628991882425245 & -0.859636822184238 \tabularnewline
7 & 8.1 & 8.09371014864573 & 0.185492590053274 & 0.00628985135426768 & 0.538251606697165 \tabularnewline
8 & 8.2 & 8.19371014596955 & 0.107013932173819 & 0.00628985403044805 & -0.260229791212702 \tabularnewline
9 & 8 & 7.9937101451811 & -0.174812145762042 & 0.00628985481890516 & -0.93451574480604 \tabularnewline
10 & 7.5 & 7.49371014511258 & -0.473321131668179 & 0.00628985488742043 & -0.989835111564299 \tabularnewline
11 & 6.8 & 6.79371014510866 & -0.681402947241058 & 0.00628985489133873 & -0.689984881047587 \tabularnewline
12 & 6.5 & 6.4937101451092 & -0.331290833523464 & 0.00628985489079784 & 1.16094750745841 \tabularnewline
13 & 6.6 & 6.62249402481947 & 0.0871420213598957 & -0.0224940248194680 & 1.46296838828869 \tabularnewline
14 & 7.6 & 7.58753610682519 & 0.797227751356276 & 0.0124638931748074 & 2.31033551408993 \tabularnewline
15 & 8 & 7.98559055868502 & 0.430975128467969 & 0.0144094413149839 & -1.17879502927377 \tabularnewline
16 & 8.1 & 8.08545760895555 & 0.127144615791027 & 0.0145423910444483 & -1.00728304615704 \tabularnewline
17 & 7.7 & 7.6854402367889 & -0.356752412277474 & 0.0145597632110952 & -1.60456689144521 \tabularnewline
18 & 7.5 & 7.48544066059922 & -0.212860187888970 & 0.0145593394007775 & 0.477136640564384 \tabularnewline
19 & 7.6 & 7.58544072999622 & 0.0743325107339263 & 0.0145592700037798 & 0.95231108705789 \tabularnewline
20 & 7.8 & 7.78544073228312 & 0.189690062663704 & 0.0145592677168839 & 0.382517648296371 \tabularnewline
21 & 7.8 & 7.78544073199991 & 0.0155624391861711 & 0.0145592680000890 & -0.57739513297434 \tabularnewline
22 & 7.8 & 7.78544073199800 & 0.00127676437037538 & 0.0145592680019952 & -0.0473703077384437 \tabularnewline
23 & 7.5 & 7.48544073199498 & -0.275282831067262 & 0.0145592680050227 & -0.917052453792022 \tabularnewline
24 & 7.5 & 7.4854407319952 & -0.0225845901325705 & 0.0145592680047958 & 0.837929855774401 \tabularnewline
25 & 7.1 & 7.27226335877404 & -0.196530167346724 & -0.172263358774043 & -0.596561262010691 \tabularnewline
26 & 7.5 & 7.48090615231051 & 0.143834523550880 & 0.0190938476894929 & 1.11702491797441 \tabularnewline
27 & 7.5 & 7.48039425359165 & 0.0113757242717072 & 0.0196057464083517 & -0.429865863048256 \tabularnewline
28 & 7.6 & 7.58042012422508 & 0.092730900711259 & 0.0195798757749171 & 0.269729622804666 \tabularnewline
29 & 7.7 & 7.68042029831248 & 0.0994036338559933 & 0.0195797016875153 & 0.0221262994531427 \tabularnewline
30 & 7.7 & 7.68042010300356 & 0.008155213657866 & 0.0195798969964388 & -0.302573436202211 \tabularnewline
31 & 7.9 & 7.88042013392808 & 0.184260784257813 & 0.0195798660719226 & 0.58395386854156 \tabularnewline
32 & 8.1 & 8.08042013413622 & 0.198708732632663 & 0.0195798658637762 & 0.0479083956152225 \tabularnewline
33 & 8.2 & 8.18042013402913 & 0.108098203074893 & 0.0195798659708724 & -0.300458236998992 \tabularnewline
34 & 8.2 & 8.1804201340195 & 0.00886852841874838 & 0.0195798659804946 & -0.329038724866522 \tabularnewline
35 & 8.2 & 8.18042013401944 & 0.000727586528516767 & 0.0195798659805593 & -0.0269947991672508 \tabularnewline
36 & 7.9 & 7.88042013401926 & -0.275327886388801 & 0.0195798659807396 & -0.91538081844869 \tabularnewline
37 & 7.3 & 7.5193445893845 & -0.353709715765585 & -0.219344589384493 & -0.266412201014775 \tabularnewline
38 & 6.9 & 6.88192914455305 & -0.596951364659631 & 0.0180708554469515 & -0.801098916764735 \tabularnewline
39 & 6.6 & 6.5827591201618 & -0.323673772835834 & 0.0172408798382020 & 0.891022041950161 \tabularnewline
40 & 6.7 & 6.68285625148906 & 0.0652478194236635 & 0.0171437485109373 & 1.28949248454303 \tabularnewline
41 & 6.9 & 6.88285878601113 & 0.188944755980244 & 0.0171412139888740 & 0.410170160360221 \tabularnewline
42 & 7 & 6.9828586487607 & 0.107297152652633 & 0.0171413512393016 & -0.270737793346502 \tabularnewline
43 & 7.1 & 7.0828586478369 & 0.100598668653421 & 0.0171413521631056 & -0.0222117087575052 \tabularnewline
44 & 7.2 & 7.18285864783068 & 0.100049115617238 & 0.0171413521693236 & -0.00182227978574612 \tabularnewline
45 & 7.1 & 7.08285864766021 & -0.0835876895588362 & 0.0171413523397862 & -0.608926920531383 \tabularnewline
46 & 6.9 & 6.88285864765208 & -0.190449370534637 & 0.0171413523479243 & -0.354345928949323 \tabularnewline
47 & 7 & 6.98285864765374 & 0.0761711256660793 & 0.0171413523462585 & 0.884095089469596 \tabularnewline
48 & 6.8 & 6.78285864765361 & -0.177342532930814 & 0.0171413523463885 & -0.840633724236474 \tabularnewline
49 & 6.4 & 6.58914992692075 & -0.192316358738675 & -0.189149926920748 & -0.0506304848348785 \tabularnewline
50 & 6.7 & 6.6812711421843 & 0.0546877202695599 & 0.0187288578157056 & 0.814982755297965 \tabularnewline
51 & 6.6 & 6.58091521163117 & -0.0876044754305867 & 0.0190847883688329 & -0.465341983043639 \tabularnewline
52 & 6.4 & 6.38089399715998 & -0.190780357170881 & 0.0191060028400165 & -0.342092499914615 \tabularnewline
53 & 6.3 & 6.28089540290874 & -0.107447740166072 & 0.019104597091258 & 0.276325011665894 \tabularnewline
54 & 6.2 & 6.18089541237053 & -0.100611023060244 & 0.0191045876294654 & 0.0226700800659161 \tabularnewline
55 & 6.5 & 6.48089545412519 & 0.267133308957569 & 0.0191045458748114 & 1.21941472145232 \tabularnewline
56 & 6.8 & 6.78089545440623 & 0.297303570501186 & 0.0191045455937696 & 0.100042496577755 \tabularnewline
57 & 6.8 & 6.78089545419766 & 0.0243912025268236 & 0.0191045458023379 & -0.904958500264783 \tabularnewline
58 & 6.4 & 6.38089545417324 & -0.365182349630097 & 0.0191045458267636 & -1.29179890277406 \tabularnewline
59 & 6.1 & 6.08089545417354 & -0.305347651521043 & 0.0191045458264558 & 0.198407712579930 \tabularnewline
60 & 5.8 & 5.78089545417355 & -0.300438728842283 & 0.0191045458264538 & 0.0162776474304136 \tabularnewline
61 & 6.1 & 6.28602251203299 & 0.437023850462163 & -0.186022512032987 & 2.48511089966492 \tabularnewline
62 & 7.2 & 7.1810000224947 & 0.838202003351515 & 0.0189999775052993 & 1.32513066817445 \tabularnewline
63 & 7.3 & 7.27955653815045 & 0.159365640619195 & 0.0204434618495487 & -2.22467789645746 \tabularnewline
64 & 6.9 & 6.87946681357677 & -0.354114963910708 & 0.0205331864232308 & -1.70253256245747 \tabularnewline
65 & 6.1 & 6.07946094583202 & -0.763418998098226 & 0.0205390541679799 & -1.35722309747112 \tabularnewline
66 & 5.8 & 5.77946144616051 & -0.338019545309172 & 0.0205385538394887 & 1.41059510164002 \tabularnewline
67 & 6.2 & 6.17946151153109 & 0.339451839857443 & 0.0205384884689067 & 2.24644816659836 \tabularnewline
68 & 7.1 & 7.07946151560453 & 0.85401184157653 & 0.0205384843954744 & 1.70624530836807 \tabularnewline
69 & 7.7 & 7.67946151545309 & 0.620839488276781 & 0.0205384845469122 & -0.773183365457345 \tabularnewline
70 & 7.9 & 7.8794615154325 & 0.234526262743969 & 0.0205384845674963 & -1.28098788561853 \tabularnewline
71 & 7.7 & 7.67946151543076 & -0.164350855053826 & 0.0205384845692399 & -1.3226488817324 \tabularnewline
72 & 7.4 & 7.37946151543072 & -0.288871153611122 & 0.0205384845692847 & -0.412900681164878 \tabularnewline
73 & 7.5 & 7.71014714151173 & 0.278539781442523 & -0.210147141511725 & 1.90750876607253 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64066&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]7.3[/C][C]7.3[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]7.6[/C][C]7.59639540237201[/C][C]0.23428542226864[/C][C]0.0036045976279917[/C][C]0.872311949205638[/C][/ROW]
[ROW][C]3[/C][C]7.5[/C][C]7.49357827748373[/C][C]-0.0750679612131155[/C][C]0.00642172251626942[/C][C]-0.970173911050916[/C][/ROW]
[ROW][C]4[/C][C]7.6[/C][C]7.59369924340227[/C][C]0.0856459617000033[/C][C]0.00630075659772915[/C][C]0.532724146801564[/C][/ROW]
[ROW][C]5[/C][C]7.9[/C][C]7.89371139460658[/C][C]0.282414165992223[/C][C]0.00628860539342368[/C][C]0.652468147237377[/C][/ROW]
[ROW][C]6[/C][C]7.9[/C][C]7.89371008117575[/C][C]0.0231696542248448[/C][C]0.00628991882425245[/C][C]-0.859636822184238[/C][/ROW]
[ROW][C]7[/C][C]8.1[/C][C]8.09371014864573[/C][C]0.185492590053274[/C][C]0.00628985135426768[/C][C]0.538251606697165[/C][/ROW]
[ROW][C]8[/C][C]8.2[/C][C]8.19371014596955[/C][C]0.107013932173819[/C][C]0.00628985403044805[/C][C]-0.260229791212702[/C][/ROW]
[ROW][C]9[/C][C]8[/C][C]7.9937101451811[/C][C]-0.174812145762042[/C][C]0.00628985481890516[/C][C]-0.93451574480604[/C][/ROW]
[ROW][C]10[/C][C]7.5[/C][C]7.49371014511258[/C][C]-0.473321131668179[/C][C]0.00628985488742043[/C][C]-0.989835111564299[/C][/ROW]
[ROW][C]11[/C][C]6.8[/C][C]6.79371014510866[/C][C]-0.681402947241058[/C][C]0.00628985489133873[/C][C]-0.689984881047587[/C][/ROW]
[ROW][C]12[/C][C]6.5[/C][C]6.4937101451092[/C][C]-0.331290833523464[/C][C]0.00628985489079784[/C][C]1.16094750745841[/C][/ROW]
[ROW][C]13[/C][C]6.6[/C][C]6.62249402481947[/C][C]0.0871420213598957[/C][C]-0.0224940248194680[/C][C]1.46296838828869[/C][/ROW]
[ROW][C]14[/C][C]7.6[/C][C]7.58753610682519[/C][C]0.797227751356276[/C][C]0.0124638931748074[/C][C]2.31033551408993[/C][/ROW]
[ROW][C]15[/C][C]8[/C][C]7.98559055868502[/C][C]0.430975128467969[/C][C]0.0144094413149839[/C][C]-1.17879502927377[/C][/ROW]
[ROW][C]16[/C][C]8.1[/C][C]8.08545760895555[/C][C]0.127144615791027[/C][C]0.0145423910444483[/C][C]-1.00728304615704[/C][/ROW]
[ROW][C]17[/C][C]7.7[/C][C]7.6854402367889[/C][C]-0.356752412277474[/C][C]0.0145597632110952[/C][C]-1.60456689144521[/C][/ROW]
[ROW][C]18[/C][C]7.5[/C][C]7.48544066059922[/C][C]-0.212860187888970[/C][C]0.0145593394007775[/C][C]0.477136640564384[/C][/ROW]
[ROW][C]19[/C][C]7.6[/C][C]7.58544072999622[/C][C]0.0743325107339263[/C][C]0.0145592700037798[/C][C]0.95231108705789[/C][/ROW]
[ROW][C]20[/C][C]7.8[/C][C]7.78544073228312[/C][C]0.189690062663704[/C][C]0.0145592677168839[/C][C]0.382517648296371[/C][/ROW]
[ROW][C]21[/C][C]7.8[/C][C]7.78544073199991[/C][C]0.0155624391861711[/C][C]0.0145592680000890[/C][C]-0.57739513297434[/C][/ROW]
[ROW][C]22[/C][C]7.8[/C][C]7.78544073199800[/C][C]0.00127676437037538[/C][C]0.0145592680019952[/C][C]-0.0473703077384437[/C][/ROW]
[ROW][C]23[/C][C]7.5[/C][C]7.48544073199498[/C][C]-0.275282831067262[/C][C]0.0145592680050227[/C][C]-0.917052453792022[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]7.4854407319952[/C][C]-0.0225845901325705[/C][C]0.0145592680047958[/C][C]0.837929855774401[/C][/ROW]
[ROW][C]25[/C][C]7.1[/C][C]7.27226335877404[/C][C]-0.196530167346724[/C][C]-0.172263358774043[/C][C]-0.596561262010691[/C][/ROW]
[ROW][C]26[/C][C]7.5[/C][C]7.48090615231051[/C][C]0.143834523550880[/C][C]0.0190938476894929[/C][C]1.11702491797441[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]7.48039425359165[/C][C]0.0113757242717072[/C][C]0.0196057464083517[/C][C]-0.429865863048256[/C][/ROW]
[ROW][C]28[/C][C]7.6[/C][C]7.58042012422508[/C][C]0.092730900711259[/C][C]0.0195798757749171[/C][C]0.269729622804666[/C][/ROW]
[ROW][C]29[/C][C]7.7[/C][C]7.68042029831248[/C][C]0.0994036338559933[/C][C]0.0195797016875153[/C][C]0.0221262994531427[/C][/ROW]
[ROW][C]30[/C][C]7.7[/C][C]7.68042010300356[/C][C]0.008155213657866[/C][C]0.0195798969964388[/C][C]-0.302573436202211[/C][/ROW]
[ROW][C]31[/C][C]7.9[/C][C]7.88042013392808[/C][C]0.184260784257813[/C][C]0.0195798660719226[/C][C]0.58395386854156[/C][/ROW]
[ROW][C]32[/C][C]8.1[/C][C]8.08042013413622[/C][C]0.198708732632663[/C][C]0.0195798658637762[/C][C]0.0479083956152225[/C][/ROW]
[ROW][C]33[/C][C]8.2[/C][C]8.18042013402913[/C][C]0.108098203074893[/C][C]0.0195798659708724[/C][C]-0.300458236998992[/C][/ROW]
[ROW][C]34[/C][C]8.2[/C][C]8.1804201340195[/C][C]0.00886852841874838[/C][C]0.0195798659804946[/C][C]-0.329038724866522[/C][/ROW]
[ROW][C]35[/C][C]8.2[/C][C]8.18042013401944[/C][C]0.000727586528516767[/C][C]0.0195798659805593[/C][C]-0.0269947991672508[/C][/ROW]
[ROW][C]36[/C][C]7.9[/C][C]7.88042013401926[/C][C]-0.275327886388801[/C][C]0.0195798659807396[/C][C]-0.91538081844869[/C][/ROW]
[ROW][C]37[/C][C]7.3[/C][C]7.5193445893845[/C][C]-0.353709715765585[/C][C]-0.219344589384493[/C][C]-0.266412201014775[/C][/ROW]
[ROW][C]38[/C][C]6.9[/C][C]6.88192914455305[/C][C]-0.596951364659631[/C][C]0.0180708554469515[/C][C]-0.801098916764735[/C][/ROW]
[ROW][C]39[/C][C]6.6[/C][C]6.5827591201618[/C][C]-0.323673772835834[/C][C]0.0172408798382020[/C][C]0.891022041950161[/C][/ROW]
[ROW][C]40[/C][C]6.7[/C][C]6.68285625148906[/C][C]0.0652478194236635[/C][C]0.0171437485109373[/C][C]1.28949248454303[/C][/ROW]
[ROW][C]41[/C][C]6.9[/C][C]6.88285878601113[/C][C]0.188944755980244[/C][C]0.0171412139888740[/C][C]0.410170160360221[/C][/ROW]
[ROW][C]42[/C][C]7[/C][C]6.9828586487607[/C][C]0.107297152652633[/C][C]0.0171413512393016[/C][C]-0.270737793346502[/C][/ROW]
[ROW][C]43[/C][C]7.1[/C][C]7.0828586478369[/C][C]0.100598668653421[/C][C]0.0171413521631056[/C][C]-0.0222117087575052[/C][/ROW]
[ROW][C]44[/C][C]7.2[/C][C]7.18285864783068[/C][C]0.100049115617238[/C][C]0.0171413521693236[/C][C]-0.00182227978574612[/C][/ROW]
[ROW][C]45[/C][C]7.1[/C][C]7.08285864766021[/C][C]-0.0835876895588362[/C][C]0.0171413523397862[/C][C]-0.608926920531383[/C][/ROW]
[ROW][C]46[/C][C]6.9[/C][C]6.88285864765208[/C][C]-0.190449370534637[/C][C]0.0171413523479243[/C][C]-0.354345928949323[/C][/ROW]
[ROW][C]47[/C][C]7[/C][C]6.98285864765374[/C][C]0.0761711256660793[/C][C]0.0171413523462585[/C][C]0.884095089469596[/C][/ROW]
[ROW][C]48[/C][C]6.8[/C][C]6.78285864765361[/C][C]-0.177342532930814[/C][C]0.0171413523463885[/C][C]-0.840633724236474[/C][/ROW]
[ROW][C]49[/C][C]6.4[/C][C]6.58914992692075[/C][C]-0.192316358738675[/C][C]-0.189149926920748[/C][C]-0.0506304848348785[/C][/ROW]
[ROW][C]50[/C][C]6.7[/C][C]6.6812711421843[/C][C]0.0546877202695599[/C][C]0.0187288578157056[/C][C]0.814982755297965[/C][/ROW]
[ROW][C]51[/C][C]6.6[/C][C]6.58091521163117[/C][C]-0.0876044754305867[/C][C]0.0190847883688329[/C][C]-0.465341983043639[/C][/ROW]
[ROW][C]52[/C][C]6.4[/C][C]6.38089399715998[/C][C]-0.190780357170881[/C][C]0.0191060028400165[/C][C]-0.342092499914615[/C][/ROW]
[ROW][C]53[/C][C]6.3[/C][C]6.28089540290874[/C][C]-0.107447740166072[/C][C]0.019104597091258[/C][C]0.276325011665894[/C][/ROW]
[ROW][C]54[/C][C]6.2[/C][C]6.18089541237053[/C][C]-0.100611023060244[/C][C]0.0191045876294654[/C][C]0.0226700800659161[/C][/ROW]
[ROW][C]55[/C][C]6.5[/C][C]6.48089545412519[/C][C]0.267133308957569[/C][C]0.0191045458748114[/C][C]1.21941472145232[/C][/ROW]
[ROW][C]56[/C][C]6.8[/C][C]6.78089545440623[/C][C]0.297303570501186[/C][C]0.0191045455937696[/C][C]0.100042496577755[/C][/ROW]
[ROW][C]57[/C][C]6.8[/C][C]6.78089545419766[/C][C]0.0243912025268236[/C][C]0.0191045458023379[/C][C]-0.904958500264783[/C][/ROW]
[ROW][C]58[/C][C]6.4[/C][C]6.38089545417324[/C][C]-0.365182349630097[/C][C]0.0191045458267636[/C][C]-1.29179890277406[/C][/ROW]
[ROW][C]59[/C][C]6.1[/C][C]6.08089545417354[/C][C]-0.305347651521043[/C][C]0.0191045458264558[/C][C]0.198407712579930[/C][/ROW]
[ROW][C]60[/C][C]5.8[/C][C]5.78089545417355[/C][C]-0.300438728842283[/C][C]0.0191045458264538[/C][C]0.0162776474304136[/C][/ROW]
[ROW][C]61[/C][C]6.1[/C][C]6.28602251203299[/C][C]0.437023850462163[/C][C]-0.186022512032987[/C][C]2.48511089966492[/C][/ROW]
[ROW][C]62[/C][C]7.2[/C][C]7.1810000224947[/C][C]0.838202003351515[/C][C]0.0189999775052993[/C][C]1.32513066817445[/C][/ROW]
[ROW][C]63[/C][C]7.3[/C][C]7.27955653815045[/C][C]0.159365640619195[/C][C]0.0204434618495487[/C][C]-2.22467789645746[/C][/ROW]
[ROW][C]64[/C][C]6.9[/C][C]6.87946681357677[/C][C]-0.354114963910708[/C][C]0.0205331864232308[/C][C]-1.70253256245747[/C][/ROW]
[ROW][C]65[/C][C]6.1[/C][C]6.07946094583202[/C][C]-0.763418998098226[/C][C]0.0205390541679799[/C][C]-1.35722309747112[/C][/ROW]
[ROW][C]66[/C][C]5.8[/C][C]5.77946144616051[/C][C]-0.338019545309172[/C][C]0.0205385538394887[/C][C]1.41059510164002[/C][/ROW]
[ROW][C]67[/C][C]6.2[/C][C]6.17946151153109[/C][C]0.339451839857443[/C][C]0.0205384884689067[/C][C]2.24644816659836[/C][/ROW]
[ROW][C]68[/C][C]7.1[/C][C]7.07946151560453[/C][C]0.85401184157653[/C][C]0.0205384843954744[/C][C]1.70624530836807[/C][/ROW]
[ROW][C]69[/C][C]7.7[/C][C]7.67946151545309[/C][C]0.620839488276781[/C][C]0.0205384845469122[/C][C]-0.773183365457345[/C][/ROW]
[ROW][C]70[/C][C]7.9[/C][C]7.8794615154325[/C][C]0.234526262743969[/C][C]0.0205384845674963[/C][C]-1.28098788561853[/C][/ROW]
[ROW][C]71[/C][C]7.7[/C][C]7.67946151543076[/C][C]-0.164350855053826[/C][C]0.0205384845692399[/C][C]-1.3226488817324[/C][/ROW]
[ROW][C]72[/C][C]7.4[/C][C]7.37946151543072[/C][C]-0.288871153611122[/C][C]0.0205384845692847[/C][C]-0.412900681164878[/C][/ROW]
[ROW][C]73[/C][C]7.5[/C][C]7.71014714151173[/C][C]0.278539781442523[/C][C]-0.210147141511725[/C][C]1.90750876607253[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64066&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64066&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
17.37.3000
27.67.596395402372010.234285422268640.00360459762799170.872311949205638
37.57.49357827748373-0.07506796121311550.00642172251626942-0.970173911050916
47.67.593699243402270.08564596170000330.006300756597729150.532724146801564
57.97.893711394606580.2824141659922230.006288605393423680.652468147237377
67.97.893710081175750.02316965422484480.00628991882425245-0.859636822184238
78.18.093710148645730.1854925900532740.006289851354267680.538251606697165
88.28.193710145969550.1070139321738190.00628985403044805-0.260229791212702
987.9937101451811-0.1748121457620420.00628985481890516-0.93451574480604
107.57.49371014511258-0.4733211316681790.00628985488742043-0.989835111564299
116.86.79371014510866-0.6814029472410580.00628985489133873-0.689984881047587
126.56.4937101451092-0.3312908335234640.006289854890797841.16094750745841
136.66.622494024819470.0871420213598957-0.02249402481946801.46296838828869
147.67.587536106825190.7972277513562760.01246389317480742.31033551408993
1587.985590558685020.4309751284679690.0144094413149839-1.17879502927377
168.18.085457608955550.1271446157910270.0145423910444483-1.00728304615704
177.77.6854402367889-0.3567524122774740.0145597632110952-1.60456689144521
187.57.48544066059922-0.2128601878889700.01455933940077750.477136640564384
197.67.585440729996220.07433251073392630.01455927000377980.95231108705789
207.87.785440732283120.1896900626637040.01455926771688390.382517648296371
217.87.785440731999910.01556243918617110.0145592680000890-0.57739513297434
227.87.785440731998000.001276764370375380.0145592680019952-0.0473703077384437
237.57.48544073199498-0.2752828310672620.0145592680050227-0.917052453792022
247.57.4854407319952-0.02258459013257050.01455926800479580.837929855774401
257.17.27226335877404-0.196530167346724-0.172263358774043-0.596561262010691
267.57.480906152310510.1438345235508800.01909384768949291.11702491797441
277.57.480394253591650.01137572427170720.0196057464083517-0.429865863048256
287.67.580420124225080.0927309007112590.01957987577491710.269729622804666
297.77.680420298312480.09940363385599330.01957970168751530.0221262994531427
307.77.680420103003560.0081552136578660.0195798969964388-0.302573436202211
317.97.880420133928080.1842607842578130.01957986607192260.58395386854156
328.18.080420134136220.1987087326326630.01957986586377620.0479083956152225
338.28.180420134029130.1080982030748930.0195798659708724-0.300458236998992
348.28.18042013401950.008868528418748380.0195798659804946-0.329038724866522
358.28.180420134019440.0007275865285167670.0195798659805593-0.0269947991672508
367.97.88042013401926-0.2753278863888010.0195798659807396-0.91538081844869
377.37.5193445893845-0.353709715765585-0.219344589384493-0.266412201014775
386.96.88192914455305-0.5969513646596310.0180708554469515-0.801098916764735
396.66.5827591201618-0.3236737728358340.01724087983820200.891022041950161
406.76.682856251489060.06524781942366350.01714374851093731.28949248454303
416.96.882858786011130.1889447559802440.01714121398887400.410170160360221
4276.98285864876070.1072971526526330.0171413512393016-0.270737793346502
437.17.08285864783690.1005986686534210.0171413521631056-0.0222117087575052
447.27.182858647830680.1000491156172380.0171413521693236-0.00182227978574612
457.17.08285864766021-0.08358768955883620.0171413523397862-0.608926920531383
466.96.88285864765208-0.1904493705346370.0171413523479243-0.354345928949323
4776.982858647653740.07617112566607930.01714135234625850.884095089469596
486.86.78285864765361-0.1773425329308140.0171413523463885-0.840633724236474
496.46.58914992692075-0.192316358738675-0.189149926920748-0.0506304848348785
506.76.68127114218430.05468772026955990.01872885781570560.814982755297965
516.66.58091521163117-0.08760447543058670.0190847883688329-0.465341983043639
526.46.38089399715998-0.1907803571708810.0191060028400165-0.342092499914615
536.36.28089540290874-0.1074477401660720.0191045970912580.276325011665894
546.26.18089541237053-0.1006110230602440.01910458762946540.0226700800659161
556.56.480895454125190.2671333089575690.01910454587481141.21941472145232
566.86.780895454406230.2973035705011860.01910454559376960.100042496577755
576.86.780895454197660.02439120252682360.0191045458023379-0.904958500264783
586.46.38089545417324-0.3651823496300970.0191045458267636-1.29179890277406
596.16.08089545417354-0.3053476515210430.01910454582645580.198407712579930
605.85.78089545417355-0.3004387288422830.01910454582645380.0162776474304136
616.16.286022512032990.437023850462163-0.1860225120329872.48511089966492
627.27.18100002249470.8382020033515150.01899997750529931.32513066817445
637.37.279556538150450.1593656406191950.0204434618495487-2.22467789645746
646.96.87946681357677-0.3541149639107080.0205331864232308-1.70253256245747
656.16.07946094583202-0.7634189980982260.0205390541679799-1.35722309747112
665.85.77946144616051-0.3380195453091720.02053855383948871.41059510164002
676.26.179461511531090.3394518398574430.02053848846890672.24644816659836
687.17.079461515604530.854011841576530.02053848439547441.70624530836807
697.77.679461515453090.6208394882767810.0205384845469122-0.773183365457345
707.97.87946151543250.2345262627439690.0205384845674963-1.28098788561853
717.77.67946151543076-0.1643508550538260.0205384845692399-1.3226488817324
727.47.37946151543072-0.2888711536111220.0205384845692847-0.412900681164878
737.57.710147141511730.278539781442523-0.2101471415117251.90750876607253



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')