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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 17 Dec 2014 13:13:53 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t1418822049780eeuil9zmo0jc.htm/, Retrieved Thu, 16 May 2024 04:46:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270178, Retrieved Thu, 16 May 2024 04:46:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [smp] [2014-12-17 13:13:53] [ec1b40d1a9751af99658fe8fca4f9eca] [Current]
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Dataseries X:
12.9
12.2
12.8
7.4
6.7
12.6
14.8
13.3
11.1
8.2
11.4
6.4
10.6
12
6.3
11.3
11.9
9.3
9.6
10
6.4
13.8
10.8
13.8
11.7
10.9
16.1
13.4
9.9
11.5
8.3
11.7
9
9.7
10.8
10.3
10.4
12.7
9.3
11.8
5.9
11.4
13
10.8
12.3
11.3
11.8
7.9
12.7
12.3
11.6
6.7
10.9
12.1
13.3
10.1
5.7
14.3
8
13.3
9.3
12.5
7.6
15.9
9.2
9.1
11.1
13
14.5
12.2
12.3
11.4
8.8
14.6
12.6
13
12.6
13.2
9.9
7.7
10.5
13.4
10.9
4.3
10.3
11.8
11.2
11.4
8.6
13.2
12.6
5.6
9.9
8.8
7.7
9
7.3
11.4
13.6
7.9
10.7
10.3
8.3
9.6
14.2
8.5
13.5
4.9
6.4
9.6
11.6
11.1




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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270178&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270178&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270178&T=0

As an alternative you can also use a QR Code:  

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

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







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
112.912.9000
212.212.7950547726714-0.0288653964419677-0.0322255568462371-0.260924337265043
312.812.7777282477269-0.0264416213358672-0.02388659076727470.0219703598292483
47.411.6168970962675-0.219542243069028-0.254210100020812-1.90949444118779
56.710.3973085774644-0.362790859070087-0.376674157187682-1.60567267449679
612.610.6875304546927-0.282027402010838-0.250328367119691.04386392302204
714.811.4398384452571-0.169476252087052-0.1471330451554221.68503941291266
813.311.7466582383443-0.123213544240117-0.1221036211529550.800371054357302
911.111.5412311557692-0.130423739019729-0.139464692210973-0.143301616760206
108.210.7882083436791-0.180189709684576-0.19958888495326-1.12780695824222
1111.410.7962729022414-0.166367229960666-0.1507387376806510.354332526778134
126.49.86120443038813-0.218558682086048-0.248838957312222-1.50136789192377
1310.69.54567695413906-0.2131516390873752.33396155708044-0.566410617189011
14129.92221959319768-0.177395350276972-0.1298277753535541.04563063897179
156.39.10703906345096-0.213706776265969-0.251150791773106-1.20239297993238
1611.39.37797449432441-0.187865795162119-0.1511488801158090.968576380057697
1711.99.71076514069306-0.161767009699956-0.1629540973245421.09287541436607
189.39.53478220186788-0.162439330819942-0.167517557222397-0.0311123438813633
199.69.43443398802346-0.159659712427648-0.1401191644561720.140864963239703
20109.41693688962559-0.153617454074607-0.1413092127210190.33276001119813
216.48.83893967359543-0.170789567245586-0.210613434232501-1.02091923115586
2213.89.48246931426677-0.13933971295873-0.07286930749991642.00688306703175
2310.89.58362302239299-0.130454083568909-0.110987323622620.605542440266221
2413.810.1202392968475-0.10689887040082-0.08501464613273251.71410271436371
2511.710.0671771061742-0.1074896650700341.151135856843750.214234539345543
2610.910.1126850191279-0.102179659142593-0.02684726979541810.373387829140399
2716.110.9580391790805-0.070224141641129-0.0109076841591972.36055837109004
2813.411.2760039893278-0.0577009017640777-0.04760155098804260.992529531821147
299.911.0393417343882-0.0632341955306524-0.113314334603132-0.46802251570846
3011.511.0591297930354-0.0607687873771807-0.04537761958430170.221429142578853
318.310.6278414536728-0.0713573392395134-0.116903734510953-1.00536648284907
3211.710.7164184917649-0.06695076578148770.01343060207183920.440596221682623
33910.4458142429291-0.0723699149851694-0.192370460603626-0.568627908808404
349.710.2830988999503-0.074695423670684-0.0197947352377259-0.255296512307511
3510.810.298424505837-0.0724508868803094-0.06626585510728510.257130339547357
3610.310.2444127184262-0.0720095309692304-0.06227132318252790.0533058594688557
3710.410.1177281800993-0.07169858495313710.746288863729522-0.207041923045386
3812.710.4169748881118-0.06270268529953390.01155133333179781.03312159853847
399.310.2201171858643-0.0659401720323703-0.09370721972601-0.375966379026405
4011.810.3784214882459-0.06071669026720670.01831932197736710.637673901298037
415.99.75208410552437-0.0734452041298003-0.262494021751217-1.6295293299473
4211.49.90078695501328-0.06860730485027860.07186079241094030.64738401789284
431310.2614463621093-0.0595455449222426-0.04988661335181011.26372734607542
4410.810.2792132540453-0.05796114385760670.01367986622297690.229663911458548
4512.310.5090630594921-0.0522270490508802-0.1133031847774780.861886107320745
4611.310.5677145322014-0.0500766968414451-0.00704642068394250.334449855021851
4711.810.6861596254854-0.0468926681767606-0.01784517749325910.511682251092272
487.910.304200794068-0.0529392421905196-0.130650755926065-1.02693719376822
4912.710.4490713211904-0.05359750504999610.6110754956348080.733863033792462
5012.310.6387617589616-0.04909168854078580.06430126633798030.724651924028415
5111.610.7350399261721-0.0463532675728771-0.08819942340373720.432859304223997
526.710.1741228118174-0.0557630212814118-0.0653941247974596-1.54695554160977
5310.910.2429072285893-0.0535529697425912-0.1758655371489410.377767186350765
5412.110.4241841745321-0.04950342583932890.09199994969259380.717884832876391
5513.310.7466858219786-0.04325985585698850.02545842567133851.14519848916872
5610.110.6350043485839-0.0443790591180168-0.066948883376441-0.211947860174073
575.710.004805731653-0.0537302101543772-0.27330749310015-1.8248307207582
5814.310.4763723828058-0.04553821058615440.1891021454993551.64454609486405
59810.1407451529855-0.0499583362037377-0.123510671075856-0.912437767506286
6013.310.4923105415239-0.0441733302566192-0.01109322793613791.27374902404545
619.310.2816428715598-0.04385444249700760.377991977208928-0.61015365397363
6212.510.5062271144059-0.03986053091908380.1584968066078610.832552175507498
637.610.1196565642441-0.0452209134784267-0.161089115485042-1.07105869516102
6415.910.790619762881-0.03442162384409080.2017957990783512.22761663693489
659.210.6018421873645-0.036686674606103-0.33658780187145-0.483305057227725
669.110.3789134377266-0.03934974768827140.0145620093694095-0.586602200530393
6711.110.422912937109-0.03818677519117180.09494491918093550.26390808393356
681310.6976413370874-0.03392071674737460.1058169646584120.995448935477054
6914.511.1656492208187-0.0272265233798723-0.2049299265633031.6034875324152
7012.211.2442526939778-0.02584433906524870.206453588298080.339379893669181
7112.311.3669522902084-0.0239464722631662-0.1228243289102840.478106784737902
7211.411.3496726453581-0.02386696262799390.002497288529848140.0216363745673305
738.811.0434221092033-0.02359597341067120.0374897832713844-1.02620184235474
7414.611.4163422681614-0.01869690494176740.3997331004636631.26350401886169
7512.611.5786424272956-0.0163239638468163-0.2400399832645630.573177459521521
761311.7085044174675-0.01444635336577410.2672505137261180.465280582856739
7712.611.8386969565933-0.0126345630838734-0.2578112002725140.462782431366099
7813.211.9885180465191-0.01064789148036040.06104319891767020.522246262373813
799.911.7277313089423-0.0136382674618019-0.0483813799827604-0.8075079203393
807.711.2322713696335-0.0192764131841414-0.0910693318858686-1.56128749755019
8110.511.1453749140401-0.0200518279739563-0.160685284085062-0.219854540201506
8213.411.3673765256853-0.01732940856313220.2919467077743280.78940104703768
8310.911.3155169918495-0.0177093373837894-0.166371469668125-0.112960699650557
844.310.4821069329003-0.0259679358048396-0.242002042981743-2.69049428399811
8510.310.4268318564738-0.02596009340457720.107901200125892-0.105851343549828
8611.810.5203838612588-0.02470432312578380.4248010396725780.388270990821929
8711.210.6134722655141-0.0233644050484184-0.2485112010282790.379769552831734
8811.410.6605670635024-0.02257556975937510.2379738198235590.228018837468152
898.610.4355064294648-0.0247904595057296-0.387775329990733-0.658109339148423
9013.210.720545048842-0.02147712659557020.2549583450555211.01094186162509
9112.610.9225408606782-0.01913771217207370.06698703257072790.731719126331941
925.610.3034845861365-0.0252930597524362-0.36571163288151-1.97045216816693
939.910.2466086278975-0.0256110215368873-0.117561686659919-0.104025762500801
948.810.0215156584603-0.02758283339671040.229130231299673-0.658720556929981
957.79.72942560193927-0.0301381236577126-0.100170904661667-0.875852097643133
9699.64109769122121-0.0306478548580725-0.212748674666484-0.19426775571233
977.39.35010884996512-0.03071399080547760.0210963808037365-0.935906779942724
9811.49.50658122702692-0.02901043689434590.5362211347727380.617008541658773
9913.69.99081014497248-0.0238583139799524-0.07563137661585931.67736654105607
1007.99.70744105903833-0.02643477771933470.0610561930825912-0.850477657197576
10110.79.84596288295908-0.0248319886940841-0.3382425270456880.542559053240077
10210.39.85450798612635-0.02451457042652480.2033883355066210.110147139535189
1038.39.63484998764656-0.02633314099526190.085147622851541-0.645910666288607
1049.69.64431916364994-0.0260057956682582-0.3055825674417910.118818954785363
10514.210.1508006433097-0.0212240715223460.1535056386450371.77142206478206
1068.59.92245913021306-0.0230513474982520.0963931614073223-0.690536180963171
10713.510.3141319581484-0.01948176105811940.1361230190426681.38623795874794
1084.99.71255967498626-0.023960398602465-0.492767173180611-1.9615638982851
1096.49.3356298631591-0.0241921460536016-0.142740614917191-1.26428352244856
1109.69.28524613223372-0.02440166047344780.506627362820208-0.0873063065971949
11111.69.53102943795267-0.02197677037307330.110027609321540.892513915395631
11211.19.69373863716841-0.02032903301891490.06455149608854390.611280613029477

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 12.9 & 12.9 & 0 & 0 & 0 \tabularnewline
2 & 12.2 & 12.7950547726714 & -0.0288653964419677 & -0.0322255568462371 & -0.260924337265043 \tabularnewline
3 & 12.8 & 12.7777282477269 & -0.0264416213358672 & -0.0238865907672747 & 0.0219703598292483 \tabularnewline
4 & 7.4 & 11.6168970962675 & -0.219542243069028 & -0.254210100020812 & -1.90949444118779 \tabularnewline
5 & 6.7 & 10.3973085774644 & -0.362790859070087 & -0.376674157187682 & -1.60567267449679 \tabularnewline
6 & 12.6 & 10.6875304546927 & -0.282027402010838 & -0.25032836711969 & 1.04386392302204 \tabularnewline
7 & 14.8 & 11.4398384452571 & -0.169476252087052 & -0.147133045155422 & 1.68503941291266 \tabularnewline
8 & 13.3 & 11.7466582383443 & -0.123213544240117 & -0.122103621152955 & 0.800371054357302 \tabularnewline
9 & 11.1 & 11.5412311557692 & -0.130423739019729 & -0.139464692210973 & -0.143301616760206 \tabularnewline
10 & 8.2 & 10.7882083436791 & -0.180189709684576 & -0.19958888495326 & -1.12780695824222 \tabularnewline
11 & 11.4 & 10.7962729022414 & -0.166367229960666 & -0.150738737680651 & 0.354332526778134 \tabularnewline
12 & 6.4 & 9.86120443038813 & -0.218558682086048 & -0.248838957312222 & -1.50136789192377 \tabularnewline
13 & 10.6 & 9.54567695413906 & -0.213151639087375 & 2.33396155708044 & -0.566410617189011 \tabularnewline
14 & 12 & 9.92221959319768 & -0.177395350276972 & -0.129827775353554 & 1.04563063897179 \tabularnewline
15 & 6.3 & 9.10703906345096 & -0.213706776265969 & -0.251150791773106 & -1.20239297993238 \tabularnewline
16 & 11.3 & 9.37797449432441 & -0.187865795162119 & -0.151148880115809 & 0.968576380057697 \tabularnewline
17 & 11.9 & 9.71076514069306 & -0.161767009699956 & -0.162954097324542 & 1.09287541436607 \tabularnewline
18 & 9.3 & 9.53478220186788 & -0.162439330819942 & -0.167517557222397 & -0.0311123438813633 \tabularnewline
19 & 9.6 & 9.43443398802346 & -0.159659712427648 & -0.140119164456172 & 0.140864963239703 \tabularnewline
20 & 10 & 9.41693688962559 & -0.153617454074607 & -0.141309212721019 & 0.33276001119813 \tabularnewline
21 & 6.4 & 8.83893967359543 & -0.170789567245586 & -0.210613434232501 & -1.02091923115586 \tabularnewline
22 & 13.8 & 9.48246931426677 & -0.13933971295873 & -0.0728693074999164 & 2.00688306703175 \tabularnewline
23 & 10.8 & 9.58362302239299 & -0.130454083568909 & -0.11098732362262 & 0.605542440266221 \tabularnewline
24 & 13.8 & 10.1202392968475 & -0.10689887040082 & -0.0850146461327325 & 1.71410271436371 \tabularnewline
25 & 11.7 & 10.0671771061742 & -0.107489665070034 & 1.15113585684375 & 0.214234539345543 \tabularnewline
26 & 10.9 & 10.1126850191279 & -0.102179659142593 & -0.0268472697954181 & 0.373387829140399 \tabularnewline
27 & 16.1 & 10.9580391790805 & -0.070224141641129 & -0.010907684159197 & 2.36055837109004 \tabularnewline
28 & 13.4 & 11.2760039893278 & -0.0577009017640777 & -0.0476015509880426 & 0.992529531821147 \tabularnewline
29 & 9.9 & 11.0393417343882 & -0.0632341955306524 & -0.113314334603132 & -0.46802251570846 \tabularnewline
30 & 11.5 & 11.0591297930354 & -0.0607687873771807 & -0.0453776195843017 & 0.221429142578853 \tabularnewline
31 & 8.3 & 10.6278414536728 & -0.0713573392395134 & -0.116903734510953 & -1.00536648284907 \tabularnewline
32 & 11.7 & 10.7164184917649 & -0.0669507657814877 & 0.0134306020718392 & 0.440596221682623 \tabularnewline
33 & 9 & 10.4458142429291 & -0.0723699149851694 & -0.192370460603626 & -0.568627908808404 \tabularnewline
34 & 9.7 & 10.2830988999503 & -0.074695423670684 & -0.0197947352377259 & -0.255296512307511 \tabularnewline
35 & 10.8 & 10.298424505837 & -0.0724508868803094 & -0.0662658551072851 & 0.257130339547357 \tabularnewline
36 & 10.3 & 10.2444127184262 & -0.0720095309692304 & -0.0622713231825279 & 0.0533058594688557 \tabularnewline
37 & 10.4 & 10.1177281800993 & -0.0716985849531371 & 0.746288863729522 & -0.207041923045386 \tabularnewline
38 & 12.7 & 10.4169748881118 & -0.0627026852995339 & 0.0115513333317978 & 1.03312159853847 \tabularnewline
39 & 9.3 & 10.2201171858643 & -0.0659401720323703 & -0.09370721972601 & -0.375966379026405 \tabularnewline
40 & 11.8 & 10.3784214882459 & -0.0607166902672067 & 0.0183193219773671 & 0.637673901298037 \tabularnewline
41 & 5.9 & 9.75208410552437 & -0.0734452041298003 & -0.262494021751217 & -1.6295293299473 \tabularnewline
42 & 11.4 & 9.90078695501328 & -0.0686073048502786 & 0.0718607924109403 & 0.64738401789284 \tabularnewline
43 & 13 & 10.2614463621093 & -0.0595455449222426 & -0.0498866133518101 & 1.26372734607542 \tabularnewline
44 & 10.8 & 10.2792132540453 & -0.0579611438576067 & 0.0136798662229769 & 0.229663911458548 \tabularnewline
45 & 12.3 & 10.5090630594921 & -0.0522270490508802 & -0.113303184777478 & 0.861886107320745 \tabularnewline
46 & 11.3 & 10.5677145322014 & -0.0500766968414451 & -0.0070464206839425 & 0.334449855021851 \tabularnewline
47 & 11.8 & 10.6861596254854 & -0.0468926681767606 & -0.0178451774932591 & 0.511682251092272 \tabularnewline
48 & 7.9 & 10.304200794068 & -0.0529392421905196 & -0.130650755926065 & -1.02693719376822 \tabularnewline
49 & 12.7 & 10.4490713211904 & -0.0535975050499961 & 0.611075495634808 & 0.733863033792462 \tabularnewline
50 & 12.3 & 10.6387617589616 & -0.0490916885407858 & 0.0643012663379803 & 0.724651924028415 \tabularnewline
51 & 11.6 & 10.7350399261721 & -0.0463532675728771 & -0.0881994234037372 & 0.432859304223997 \tabularnewline
52 & 6.7 & 10.1741228118174 & -0.0557630212814118 & -0.0653941247974596 & -1.54695554160977 \tabularnewline
53 & 10.9 & 10.2429072285893 & -0.0535529697425912 & -0.175865537148941 & 0.377767186350765 \tabularnewline
54 & 12.1 & 10.4241841745321 & -0.0495034258393289 & 0.0919999496925938 & 0.717884832876391 \tabularnewline
55 & 13.3 & 10.7466858219786 & -0.0432598558569885 & 0.0254584256713385 & 1.14519848916872 \tabularnewline
56 & 10.1 & 10.6350043485839 & -0.0443790591180168 & -0.066948883376441 & -0.211947860174073 \tabularnewline
57 & 5.7 & 10.004805731653 & -0.0537302101543772 & -0.27330749310015 & -1.8248307207582 \tabularnewline
58 & 14.3 & 10.4763723828058 & -0.0455382105861544 & 0.189102145499355 & 1.64454609486405 \tabularnewline
59 & 8 & 10.1407451529855 & -0.0499583362037377 & -0.123510671075856 & -0.912437767506286 \tabularnewline
60 & 13.3 & 10.4923105415239 & -0.0441733302566192 & -0.0110932279361379 & 1.27374902404545 \tabularnewline
61 & 9.3 & 10.2816428715598 & -0.0438544424970076 & 0.377991977208928 & -0.61015365397363 \tabularnewline
62 & 12.5 & 10.5062271144059 & -0.0398605309190838 & 0.158496806607861 & 0.832552175507498 \tabularnewline
63 & 7.6 & 10.1196565642441 & -0.0452209134784267 & -0.161089115485042 & -1.07105869516102 \tabularnewline
64 & 15.9 & 10.790619762881 & -0.0344216238440908 & 0.201795799078351 & 2.22761663693489 \tabularnewline
65 & 9.2 & 10.6018421873645 & -0.036686674606103 & -0.33658780187145 & -0.483305057227725 \tabularnewline
66 & 9.1 & 10.3789134377266 & -0.0393497476882714 & 0.0145620093694095 & -0.586602200530393 \tabularnewline
67 & 11.1 & 10.422912937109 & -0.0381867751911718 & 0.0949449191809355 & 0.26390808393356 \tabularnewline
68 & 13 & 10.6976413370874 & -0.0339207167473746 & 0.105816964658412 & 0.995448935477054 \tabularnewline
69 & 14.5 & 11.1656492208187 & -0.0272265233798723 & -0.204929926563303 & 1.6034875324152 \tabularnewline
70 & 12.2 & 11.2442526939778 & -0.0258443390652487 & 0.20645358829808 & 0.339379893669181 \tabularnewline
71 & 12.3 & 11.3669522902084 & -0.0239464722631662 & -0.122824328910284 & 0.478106784737902 \tabularnewline
72 & 11.4 & 11.3496726453581 & -0.0238669626279939 & 0.00249728852984814 & 0.0216363745673305 \tabularnewline
73 & 8.8 & 11.0434221092033 & -0.0235959734106712 & 0.0374897832713844 & -1.02620184235474 \tabularnewline
74 & 14.6 & 11.4163422681614 & -0.0186969049417674 & 0.399733100463663 & 1.26350401886169 \tabularnewline
75 & 12.6 & 11.5786424272956 & -0.0163239638468163 & -0.240039983264563 & 0.573177459521521 \tabularnewline
76 & 13 & 11.7085044174675 & -0.0144463533657741 & 0.267250513726118 & 0.465280582856739 \tabularnewline
77 & 12.6 & 11.8386969565933 & -0.0126345630838734 & -0.257811200272514 & 0.462782431366099 \tabularnewline
78 & 13.2 & 11.9885180465191 & -0.0106478914803604 & 0.0610431989176702 & 0.522246262373813 \tabularnewline
79 & 9.9 & 11.7277313089423 & -0.0136382674618019 & -0.0483813799827604 & -0.8075079203393 \tabularnewline
80 & 7.7 & 11.2322713696335 & -0.0192764131841414 & -0.0910693318858686 & -1.56128749755019 \tabularnewline
81 & 10.5 & 11.1453749140401 & -0.0200518279739563 & -0.160685284085062 & -0.219854540201506 \tabularnewline
82 & 13.4 & 11.3673765256853 & -0.0173294085631322 & 0.291946707774328 & 0.78940104703768 \tabularnewline
83 & 10.9 & 11.3155169918495 & -0.0177093373837894 & -0.166371469668125 & -0.112960699650557 \tabularnewline
84 & 4.3 & 10.4821069329003 & -0.0259679358048396 & -0.242002042981743 & -2.69049428399811 \tabularnewline
85 & 10.3 & 10.4268318564738 & -0.0259600934045772 & 0.107901200125892 & -0.105851343549828 \tabularnewline
86 & 11.8 & 10.5203838612588 & -0.0247043231257838 & 0.424801039672578 & 0.388270990821929 \tabularnewline
87 & 11.2 & 10.6134722655141 & -0.0233644050484184 & -0.248511201028279 & 0.379769552831734 \tabularnewline
88 & 11.4 & 10.6605670635024 & -0.0225755697593751 & 0.237973819823559 & 0.228018837468152 \tabularnewline
89 & 8.6 & 10.4355064294648 & -0.0247904595057296 & -0.387775329990733 & -0.658109339148423 \tabularnewline
90 & 13.2 & 10.720545048842 & -0.0214771265955702 & 0.254958345055521 & 1.01094186162509 \tabularnewline
91 & 12.6 & 10.9225408606782 & -0.0191377121720737 & 0.0669870325707279 & 0.731719126331941 \tabularnewline
92 & 5.6 & 10.3034845861365 & -0.0252930597524362 & -0.36571163288151 & -1.97045216816693 \tabularnewline
93 & 9.9 & 10.2466086278975 & -0.0256110215368873 & -0.117561686659919 & -0.104025762500801 \tabularnewline
94 & 8.8 & 10.0215156584603 & -0.0275828333967104 & 0.229130231299673 & -0.658720556929981 \tabularnewline
95 & 7.7 & 9.72942560193927 & -0.0301381236577126 & -0.100170904661667 & -0.875852097643133 \tabularnewline
96 & 9 & 9.64109769122121 & -0.0306478548580725 & -0.212748674666484 & -0.19426775571233 \tabularnewline
97 & 7.3 & 9.35010884996512 & -0.0307139908054776 & 0.0210963808037365 & -0.935906779942724 \tabularnewline
98 & 11.4 & 9.50658122702692 & -0.0290104368943459 & 0.536221134772738 & 0.617008541658773 \tabularnewline
99 & 13.6 & 9.99081014497248 & -0.0238583139799524 & -0.0756313766158593 & 1.67736654105607 \tabularnewline
100 & 7.9 & 9.70744105903833 & -0.0264347777193347 & 0.0610561930825912 & -0.850477657197576 \tabularnewline
101 & 10.7 & 9.84596288295908 & -0.0248319886940841 & -0.338242527045688 & 0.542559053240077 \tabularnewline
102 & 10.3 & 9.85450798612635 & -0.0245145704265248 & 0.203388335506621 & 0.110147139535189 \tabularnewline
103 & 8.3 & 9.63484998764656 & -0.0263331409952619 & 0.085147622851541 & -0.645910666288607 \tabularnewline
104 & 9.6 & 9.64431916364994 & -0.0260057956682582 & -0.305582567441791 & 0.118818954785363 \tabularnewline
105 & 14.2 & 10.1508006433097 & -0.021224071522346 & 0.153505638645037 & 1.77142206478206 \tabularnewline
106 & 8.5 & 9.92245913021306 & -0.023051347498252 & 0.0963931614073223 & -0.690536180963171 \tabularnewline
107 & 13.5 & 10.3141319581484 & -0.0194817610581194 & 0.136123019042668 & 1.38623795874794 \tabularnewline
108 & 4.9 & 9.71255967498626 & -0.023960398602465 & -0.492767173180611 & -1.9615638982851 \tabularnewline
109 & 6.4 & 9.3356298631591 & -0.0241921460536016 & -0.142740614917191 & -1.26428352244856 \tabularnewline
110 & 9.6 & 9.28524613223372 & -0.0244016604734478 & 0.506627362820208 & -0.0873063065971949 \tabularnewline
111 & 11.6 & 9.53102943795267 & -0.0219767703730733 & 0.11002760932154 & 0.892513915395631 \tabularnewline
112 & 11.1 & 9.69373863716841 & -0.0203290330189149 & 0.0645514960885439 & 0.611280613029477 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270178&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]12.9[/C][C]12.9[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.7950547726714[/C][C]-0.0288653964419677[/C][C]-0.0322255568462371[/C][C]-0.260924337265043[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.7777282477269[/C][C]-0.0264416213358672[/C][C]-0.0238865907672747[/C][C]0.0219703598292483[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.6168970962675[/C][C]-0.219542243069028[/C][C]-0.254210100020812[/C][C]-1.90949444118779[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.3973085774644[/C][C]-0.362790859070087[/C][C]-0.376674157187682[/C][C]-1.60567267449679[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]10.6875304546927[/C][C]-0.282027402010838[/C][C]-0.25032836711969[/C][C]1.04386392302204[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.4398384452571[/C][C]-0.169476252087052[/C][C]-0.147133045155422[/C][C]1.68503941291266[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.7466582383443[/C][C]-0.123213544240117[/C][C]-0.122103621152955[/C][C]0.800371054357302[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.5412311557692[/C][C]-0.130423739019729[/C][C]-0.139464692210973[/C][C]-0.143301616760206[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]10.7882083436791[/C][C]-0.180189709684576[/C][C]-0.19958888495326[/C][C]-1.12780695824222[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.7962729022414[/C][C]-0.166367229960666[/C][C]-0.150738737680651[/C][C]0.354332526778134[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]9.86120443038813[/C][C]-0.218558682086048[/C][C]-0.248838957312222[/C][C]-1.50136789192377[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.54567695413906[/C][C]-0.213151639087375[/C][C]2.33396155708044[/C][C]-0.566410617189011[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]9.92221959319768[/C][C]-0.177395350276972[/C][C]-0.129827775353554[/C][C]1.04563063897179[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.10703906345096[/C][C]-0.213706776265969[/C][C]-0.251150791773106[/C][C]-1.20239297993238[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.37797449432441[/C][C]-0.187865795162119[/C][C]-0.151148880115809[/C][C]0.968576380057697[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]9.71076514069306[/C][C]-0.161767009699956[/C][C]-0.162954097324542[/C][C]1.09287541436607[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]9.53478220186788[/C][C]-0.162439330819942[/C][C]-0.167517557222397[/C][C]-0.0311123438813633[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]9.43443398802346[/C][C]-0.159659712427648[/C][C]-0.140119164456172[/C][C]0.140864963239703[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.41693688962559[/C][C]-0.153617454074607[/C][C]-0.141309212721019[/C][C]0.33276001119813[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]8.83893967359543[/C][C]-0.170789567245586[/C][C]-0.210613434232501[/C][C]-1.02091923115586[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]9.48246931426677[/C][C]-0.13933971295873[/C][C]-0.0728693074999164[/C][C]2.00688306703175[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]9.58362302239299[/C][C]-0.130454083568909[/C][C]-0.11098732362262[/C][C]0.605542440266221[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]10.1202392968475[/C][C]-0.10689887040082[/C][C]-0.0850146461327325[/C][C]1.71410271436371[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.0671771061742[/C][C]-0.107489665070034[/C][C]1.15113585684375[/C][C]0.214234539345543[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]10.1126850191279[/C][C]-0.102179659142593[/C][C]-0.0268472697954181[/C][C]0.373387829140399[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]10.9580391790805[/C][C]-0.070224141641129[/C][C]-0.010907684159197[/C][C]2.36055837109004[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.2760039893278[/C][C]-0.0577009017640777[/C][C]-0.0476015509880426[/C][C]0.992529531821147[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.0393417343882[/C][C]-0.0632341955306524[/C][C]-0.113314334603132[/C][C]-0.46802251570846[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.0591297930354[/C][C]-0.0607687873771807[/C][C]-0.0453776195843017[/C][C]0.221429142578853[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]10.6278414536728[/C][C]-0.0713573392395134[/C][C]-0.116903734510953[/C][C]-1.00536648284907[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]10.7164184917649[/C][C]-0.0669507657814877[/C][C]0.0134306020718392[/C][C]0.440596221682623[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.4458142429291[/C][C]-0.0723699149851694[/C][C]-0.192370460603626[/C][C]-0.568627908808404[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]10.2830988999503[/C][C]-0.074695423670684[/C][C]-0.0197947352377259[/C][C]-0.255296512307511[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.298424505837[/C][C]-0.0724508868803094[/C][C]-0.0662658551072851[/C][C]0.257130339547357[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]10.2444127184262[/C][C]-0.0720095309692304[/C][C]-0.0622713231825279[/C][C]0.0533058594688557[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.1177281800993[/C][C]-0.0716985849531371[/C][C]0.746288863729522[/C][C]-0.207041923045386[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.4169748881118[/C][C]-0.0627026852995339[/C][C]0.0115513333317978[/C][C]1.03312159853847[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]10.2201171858643[/C][C]-0.0659401720323703[/C][C]-0.09370721972601[/C][C]-0.375966379026405[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]10.3784214882459[/C][C]-0.0607166902672067[/C][C]0.0183193219773671[/C][C]0.637673901298037[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.75208410552437[/C][C]-0.0734452041298003[/C][C]-0.262494021751217[/C][C]-1.6295293299473[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]9.90078695501328[/C][C]-0.0686073048502786[/C][C]0.0718607924109403[/C][C]0.64738401789284[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]10.2614463621093[/C][C]-0.0595455449222426[/C][C]-0.0498866133518101[/C][C]1.26372734607542[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.2792132540453[/C][C]-0.0579611438576067[/C][C]0.0136798662229769[/C][C]0.229663911458548[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.5090630594921[/C][C]-0.0522270490508802[/C][C]-0.113303184777478[/C][C]0.861886107320745[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]10.5677145322014[/C][C]-0.0500766968414451[/C][C]-0.0070464206839425[/C][C]0.334449855021851[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]10.6861596254854[/C][C]-0.0468926681767606[/C][C]-0.0178451774932591[/C][C]0.511682251092272[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.304200794068[/C][C]-0.0529392421905196[/C][C]-0.130650755926065[/C][C]-1.02693719376822[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.4490713211904[/C][C]-0.0535975050499961[/C][C]0.611075495634808[/C][C]0.733863033792462[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.6387617589616[/C][C]-0.0490916885407858[/C][C]0.0643012663379803[/C][C]0.724651924028415[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.7350399261721[/C][C]-0.0463532675728771[/C][C]-0.0881994234037372[/C][C]0.432859304223997[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.1741228118174[/C][C]-0.0557630212814118[/C][C]-0.0653941247974596[/C][C]-1.54695554160977[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.2429072285893[/C][C]-0.0535529697425912[/C][C]-0.175865537148941[/C][C]0.377767186350765[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.4241841745321[/C][C]-0.0495034258393289[/C][C]0.0919999496925938[/C][C]0.717884832876391[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.7466858219786[/C][C]-0.0432598558569885[/C][C]0.0254584256713385[/C][C]1.14519848916872[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.6350043485839[/C][C]-0.0443790591180168[/C][C]-0.066948883376441[/C][C]-0.211947860174073[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.004805731653[/C][C]-0.0537302101543772[/C][C]-0.27330749310015[/C][C]-1.8248307207582[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.4763723828058[/C][C]-0.0455382105861544[/C][C]0.189102145499355[/C][C]1.64454609486405[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]10.1407451529855[/C][C]-0.0499583362037377[/C][C]-0.123510671075856[/C][C]-0.912437767506286[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.4923105415239[/C][C]-0.0441733302566192[/C][C]-0.0110932279361379[/C][C]1.27374902404545[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]10.2816428715598[/C][C]-0.0438544424970076[/C][C]0.377991977208928[/C][C]-0.61015365397363[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.5062271144059[/C][C]-0.0398605309190838[/C][C]0.158496806607861[/C][C]0.832552175507498[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.1196565642441[/C][C]-0.0452209134784267[/C][C]-0.161089115485042[/C][C]-1.07105869516102[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]10.790619762881[/C][C]-0.0344216238440908[/C][C]0.201795799078351[/C][C]2.22761663693489[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]10.6018421873645[/C][C]-0.036686674606103[/C][C]-0.33658780187145[/C][C]-0.483305057227725[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.3789134377266[/C][C]-0.0393497476882714[/C][C]0.0145620093694095[/C][C]-0.586602200530393[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]10.422912937109[/C][C]-0.0381867751911718[/C][C]0.0949449191809355[/C][C]0.26390808393356[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]10.6976413370874[/C][C]-0.0339207167473746[/C][C]0.105816964658412[/C][C]0.995448935477054[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.1656492208187[/C][C]-0.0272265233798723[/C][C]-0.204929926563303[/C][C]1.6034875324152[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.2442526939778[/C][C]-0.0258443390652487[/C][C]0.20645358829808[/C][C]0.339379893669181[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]11.3669522902084[/C][C]-0.0239464722631662[/C][C]-0.122824328910284[/C][C]0.478106784737902[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.3496726453581[/C][C]-0.0238669626279939[/C][C]0.00249728852984814[/C][C]0.0216363745673305[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.0434221092033[/C][C]-0.0235959734106712[/C][C]0.0374897832713844[/C][C]-1.02620184235474[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.4163422681614[/C][C]-0.0186969049417674[/C][C]0.399733100463663[/C][C]1.26350401886169[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.5786424272956[/C][C]-0.0163239638468163[/C][C]-0.240039983264563[/C][C]0.573177459521521[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.7085044174675[/C][C]-0.0144463533657741[/C][C]0.267250513726118[/C][C]0.465280582856739[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.8386969565933[/C][C]-0.0126345630838734[/C][C]-0.257811200272514[/C][C]0.462782431366099[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]11.9885180465191[/C][C]-0.0106478914803604[/C][C]0.0610431989176702[/C][C]0.522246262373813[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]11.7277313089423[/C][C]-0.0136382674618019[/C][C]-0.0483813799827604[/C][C]-0.8075079203393[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.2322713696335[/C][C]-0.0192764131841414[/C][C]-0.0910693318858686[/C][C]-1.56128749755019[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]11.1453749140401[/C][C]-0.0200518279739563[/C][C]-0.160685284085062[/C][C]-0.219854540201506[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]11.3673765256853[/C][C]-0.0173294085631322[/C][C]0.291946707774328[/C][C]0.78940104703768[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.3155169918495[/C][C]-0.0177093373837894[/C][C]-0.166371469668125[/C][C]-0.112960699650557[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]10.4821069329003[/C][C]-0.0259679358048396[/C][C]-0.242002042981743[/C][C]-2.69049428399811[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]10.4268318564738[/C][C]-0.0259600934045772[/C][C]0.107901200125892[/C][C]-0.105851343549828[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]10.5203838612588[/C][C]-0.0247043231257838[/C][C]0.424801039672578[/C][C]0.388270990821929[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.6134722655141[/C][C]-0.0233644050484184[/C][C]-0.248511201028279[/C][C]0.379769552831734[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.6605670635024[/C][C]-0.0225755697593751[/C][C]0.237973819823559[/C][C]0.228018837468152[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.4355064294648[/C][C]-0.0247904595057296[/C][C]-0.387775329990733[/C][C]-0.658109339148423[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]10.720545048842[/C][C]-0.0214771265955702[/C][C]0.254958345055521[/C][C]1.01094186162509[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.9225408606782[/C][C]-0.0191377121720737[/C][C]0.0669870325707279[/C][C]0.731719126331941[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.3034845861365[/C][C]-0.0252930597524362[/C][C]-0.36571163288151[/C][C]-1.97045216816693[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]10.2466086278975[/C][C]-0.0256110215368873[/C][C]-0.117561686659919[/C][C]-0.104025762500801[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.0215156584603[/C][C]-0.0275828333967104[/C][C]0.229130231299673[/C][C]-0.658720556929981[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]9.72942560193927[/C][C]-0.0301381236577126[/C][C]-0.100170904661667[/C][C]-0.875852097643133[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]9.64109769122121[/C][C]-0.0306478548580725[/C][C]-0.212748674666484[/C][C]-0.19426775571233[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]9.35010884996512[/C][C]-0.0307139908054776[/C][C]0.0210963808037365[/C][C]-0.935906779942724[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]9.50658122702692[/C][C]-0.0290104368943459[/C][C]0.536221134772738[/C][C]0.617008541658773[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]9.99081014497248[/C][C]-0.0238583139799524[/C][C]-0.0756313766158593[/C][C]1.67736654105607[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]9.70744105903833[/C][C]-0.0264347777193347[/C][C]0.0610561930825912[/C][C]-0.850477657197576[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]9.84596288295908[/C][C]-0.0248319886940841[/C][C]-0.338242527045688[/C][C]0.542559053240077[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]9.85450798612635[/C][C]-0.0245145704265248[/C][C]0.203388335506621[/C][C]0.110147139535189[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.63484998764656[/C][C]-0.0263331409952619[/C][C]0.085147622851541[/C][C]-0.645910666288607[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]9.64431916364994[/C][C]-0.0260057956682582[/C][C]-0.305582567441791[/C][C]0.118818954785363[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]10.1508006433097[/C][C]-0.021224071522346[/C][C]0.153505638645037[/C][C]1.77142206478206[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]9.92245913021306[/C][C]-0.023051347498252[/C][C]0.0963931614073223[/C][C]-0.690536180963171[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.3141319581484[/C][C]-0.0194817610581194[/C][C]0.136123019042668[/C][C]1.38623795874794[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]9.71255967498626[/C][C]-0.023960398602465[/C][C]-0.492767173180611[/C][C]-1.9615638982851[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]9.3356298631591[/C][C]-0.0241921460536016[/C][C]-0.142740614917191[/C][C]-1.26428352244856[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]9.28524613223372[/C][C]-0.0244016604734478[/C][C]0.506627362820208[/C][C]-0.0873063065971949[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]9.53102943795267[/C][C]-0.0219767703730733[/C][C]0.11002760932154[/C][C]0.892513915395631[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]9.69373863716841[/C][C]-0.0203290330189149[/C][C]0.0645514960885439[/C][C]0.611280613029477[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270178&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270178&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
112.912.9000
212.212.7950547726714-0.0288653964419677-0.0322255568462371-0.260924337265043
312.812.7777282477269-0.0264416213358672-0.02388659076727470.0219703598292483
47.411.6168970962675-0.219542243069028-0.254210100020812-1.90949444118779
56.710.3973085774644-0.362790859070087-0.376674157187682-1.60567267449679
612.610.6875304546927-0.282027402010838-0.250328367119691.04386392302204
714.811.4398384452571-0.169476252087052-0.1471330451554221.68503941291266
813.311.7466582383443-0.123213544240117-0.1221036211529550.800371054357302
911.111.5412311557692-0.130423739019729-0.139464692210973-0.143301616760206
108.210.7882083436791-0.180189709684576-0.19958888495326-1.12780695824222
1111.410.7962729022414-0.166367229960666-0.1507387376806510.354332526778134
126.49.86120443038813-0.218558682086048-0.248838957312222-1.50136789192377
1310.69.54567695413906-0.2131516390873752.33396155708044-0.566410617189011
14129.92221959319768-0.177395350276972-0.1298277753535541.04563063897179
156.39.10703906345096-0.213706776265969-0.251150791773106-1.20239297993238
1611.39.37797449432441-0.187865795162119-0.1511488801158090.968576380057697
1711.99.71076514069306-0.161767009699956-0.1629540973245421.09287541436607
189.39.53478220186788-0.162439330819942-0.167517557222397-0.0311123438813633
199.69.43443398802346-0.159659712427648-0.1401191644561720.140864963239703
20109.41693688962559-0.153617454074607-0.1413092127210190.33276001119813
216.48.83893967359543-0.170789567245586-0.210613434232501-1.02091923115586
2213.89.48246931426677-0.13933971295873-0.07286930749991642.00688306703175
2310.89.58362302239299-0.130454083568909-0.110987323622620.605542440266221
2413.810.1202392968475-0.10689887040082-0.08501464613273251.71410271436371
2511.710.0671771061742-0.1074896650700341.151135856843750.214234539345543
2610.910.1126850191279-0.102179659142593-0.02684726979541810.373387829140399
2716.110.9580391790805-0.070224141641129-0.0109076841591972.36055837109004
2813.411.2760039893278-0.0577009017640777-0.04760155098804260.992529531821147
299.911.0393417343882-0.0632341955306524-0.113314334603132-0.46802251570846
3011.511.0591297930354-0.0607687873771807-0.04537761958430170.221429142578853
318.310.6278414536728-0.0713573392395134-0.116903734510953-1.00536648284907
3211.710.7164184917649-0.06695076578148770.01343060207183920.440596221682623
33910.4458142429291-0.0723699149851694-0.192370460603626-0.568627908808404
349.710.2830988999503-0.074695423670684-0.0197947352377259-0.255296512307511
3510.810.298424505837-0.0724508868803094-0.06626585510728510.257130339547357
3610.310.2444127184262-0.0720095309692304-0.06227132318252790.0533058594688557
3710.410.1177281800993-0.07169858495313710.746288863729522-0.207041923045386
3812.710.4169748881118-0.06270268529953390.01155133333179781.03312159853847
399.310.2201171858643-0.0659401720323703-0.09370721972601-0.375966379026405
4011.810.3784214882459-0.06071669026720670.01831932197736710.637673901298037
415.99.75208410552437-0.0734452041298003-0.262494021751217-1.6295293299473
4211.49.90078695501328-0.06860730485027860.07186079241094030.64738401789284
431310.2614463621093-0.0595455449222426-0.04988661335181011.26372734607542
4410.810.2792132540453-0.05796114385760670.01367986622297690.229663911458548
4512.310.5090630594921-0.0522270490508802-0.1133031847774780.861886107320745
4611.310.5677145322014-0.0500766968414451-0.00704642068394250.334449855021851
4711.810.6861596254854-0.0468926681767606-0.01784517749325910.511682251092272
487.910.304200794068-0.0529392421905196-0.130650755926065-1.02693719376822
4912.710.4490713211904-0.05359750504999610.6110754956348080.733863033792462
5012.310.6387617589616-0.04909168854078580.06430126633798030.724651924028415
5111.610.7350399261721-0.0463532675728771-0.08819942340373720.432859304223997
526.710.1741228118174-0.0557630212814118-0.0653941247974596-1.54695554160977
5310.910.2429072285893-0.0535529697425912-0.1758655371489410.377767186350765
5412.110.4241841745321-0.04950342583932890.09199994969259380.717884832876391
5513.310.7466858219786-0.04325985585698850.02545842567133851.14519848916872
5610.110.6350043485839-0.0443790591180168-0.066948883376441-0.211947860174073
575.710.004805731653-0.0537302101543772-0.27330749310015-1.8248307207582
5814.310.4763723828058-0.04553821058615440.1891021454993551.64454609486405
59810.1407451529855-0.0499583362037377-0.123510671075856-0.912437767506286
6013.310.4923105415239-0.0441733302566192-0.01109322793613791.27374902404545
619.310.2816428715598-0.04385444249700760.377991977208928-0.61015365397363
6212.510.5062271144059-0.03986053091908380.1584968066078610.832552175507498
637.610.1196565642441-0.0452209134784267-0.161089115485042-1.07105869516102
6415.910.790619762881-0.03442162384409080.2017957990783512.22761663693489
659.210.6018421873645-0.036686674606103-0.33658780187145-0.483305057227725
669.110.3789134377266-0.03934974768827140.0145620093694095-0.586602200530393
6711.110.422912937109-0.03818677519117180.09494491918093550.26390808393356
681310.6976413370874-0.03392071674737460.1058169646584120.995448935477054
6914.511.1656492208187-0.0272265233798723-0.2049299265633031.6034875324152
7012.211.2442526939778-0.02584433906524870.206453588298080.339379893669181
7112.311.3669522902084-0.0239464722631662-0.1228243289102840.478106784737902
7211.411.3496726453581-0.02386696262799390.002497288529848140.0216363745673305
738.811.0434221092033-0.02359597341067120.0374897832713844-1.02620184235474
7414.611.4163422681614-0.01869690494176740.3997331004636631.26350401886169
7512.611.5786424272956-0.0163239638468163-0.2400399832645630.573177459521521
761311.7085044174675-0.01444635336577410.2672505137261180.465280582856739
7712.611.8386969565933-0.0126345630838734-0.2578112002725140.462782431366099
7813.211.9885180465191-0.01064789148036040.06104319891767020.522246262373813
799.911.7277313089423-0.0136382674618019-0.0483813799827604-0.8075079203393
807.711.2322713696335-0.0192764131841414-0.0910693318858686-1.56128749755019
8110.511.1453749140401-0.0200518279739563-0.160685284085062-0.219854540201506
8213.411.3673765256853-0.01732940856313220.2919467077743280.78940104703768
8310.911.3155169918495-0.0177093373837894-0.166371469668125-0.112960699650557
844.310.4821069329003-0.0259679358048396-0.242002042981743-2.69049428399811
8510.310.4268318564738-0.02596009340457720.107901200125892-0.105851343549828
8611.810.5203838612588-0.02470432312578380.4248010396725780.388270990821929
8711.210.6134722655141-0.0233644050484184-0.2485112010282790.379769552831734
8811.410.6605670635024-0.02257556975937510.2379738198235590.228018837468152
898.610.4355064294648-0.0247904595057296-0.387775329990733-0.658109339148423
9013.210.720545048842-0.02147712659557020.2549583450555211.01094186162509
9112.610.9225408606782-0.01913771217207370.06698703257072790.731719126331941
925.610.3034845861365-0.0252930597524362-0.36571163288151-1.97045216816693
939.910.2466086278975-0.0256110215368873-0.117561686659919-0.104025762500801
948.810.0215156584603-0.02758283339671040.229130231299673-0.658720556929981
957.79.72942560193927-0.0301381236577126-0.100170904661667-0.875852097643133
9699.64109769122121-0.0306478548580725-0.212748674666484-0.19426775571233
977.39.35010884996512-0.03071399080547760.0210963808037365-0.935906779942724
9811.49.50658122702692-0.02901043689434590.5362211347727380.617008541658773
9913.69.99081014497248-0.0238583139799524-0.07563137661585931.67736654105607
1007.99.70744105903833-0.02643477771933470.0610561930825912-0.850477657197576
10110.79.84596288295908-0.0248319886940841-0.3382425270456880.542559053240077
10210.39.85450798612635-0.02451457042652480.2033883355066210.110147139535189
1038.39.63484998764656-0.02633314099526190.085147622851541-0.645910666288607
1049.69.64431916364994-0.0260057956682582-0.3055825674417910.118818954785363
10514.210.1508006433097-0.0212240715223460.1535056386450371.77142206478206
1068.59.92245913021306-0.0230513474982520.0963931614073223-0.690536180963171
10713.510.3141319581484-0.01948176105811940.1361230190426681.38623795874794
1084.99.71255967498626-0.023960398602465-0.492767173180611-1.9615638982851
1096.49.3356298631591-0.0241921460536016-0.142740614917191-1.26428352244856
1109.69.28524613223372-0.02440166047344780.506627362820208-0.0873063065971949
11111.69.53102943795267-0.02197677037307330.110027609321540.892513915395631
11211.19.69373863716841-0.02032903301891490.06455149608854390.611280613029477



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')