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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 05:08:38 -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/t12599285800ey7p4ktaym5bwt.htm/, Retrieved Sun, 28 Apr 2024 17:58:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63357, Retrieved Sun, 28 Apr 2024 17:58:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
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] [] [2009-12-04 12:08:38] [2f6049721194fa571920c3539d7b729e] [Current]
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Dataseries X:
17
14
15
16
16
15
13
12
13
13
12
10
14
14
15
16
16
15
15
13
15
15
15
13
16
16
14
16
15
14
15
15
14
13
12
13
12
9
10
8
11
8
8
8
4
6
8
10
5
6
5
9
8
6
9
11
11
8
11
11
13




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=63357&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=63357&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63357&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
11717000
21415.0330593463373-0.144548055205191-0.144548055091753-1.39601525305627
31515.0366808303117-0.138307627077558-0.1383076270775580.137928287429375
41615.5961311402861-0.119417418645176-0.1194174186451760.688758691943332
51615.8357560627452-0.112118441539720-0.1121184415397200.360365262724881
61515.3827831630744-0.118005192720895-0.118005192720895-0.344067796622985
71314.0691240284864-0.136918270649693-0.136918270649693-1.20961451838913
81212.9325956774681-0.15197898024712-0.15197898024712-1.01224113206571
91312.9873708409666-0.148955645344341-0.1489556453443410.209458126868009
101313.0113044090183-0.146480521280286-0.1464805212802860.175189117610645
111212.4648892919948-0.152108572521464-0.152108572521464-0.405306986957112
121011.1098001374771-0.168780627979749-0.168780627979750-1.21924732374979
131411.3756416220192-0.2052512394135272.257763633768310.567694259254424
141413.0383969104541-0.142189019082738-0.1421890199801941.56498830053981
151514.1774554729902-0.117448303603044-0.1174483036030451.24240554910863
161615.2141406993944-0.102989882207872-0.1029898822078721.15631406542678
171615.6652041148266-0.0977286659580146-0.09772866595801470.560046448290538
181515.3053892072666-0.0998613408926226-0.0998613408926226-0.265683953191292
191515.1465975156957-0.100304137481318-0.100304137481318-0.0598034462106509
201313.9611778528158-0.108131168628344-0.108131168628344-1.10167800158178
211514.5528627435966-0.103194633832754-0.1031946338327540.710635470163316
221514.8140578757829-0.100659380517216-0.1006593805172160.370057237879655
231514.9293247976099-0.0991719079499465-0.09917190794994640.219295115615948
241313.8649999670494-0.105766415333544-0.105766415333544-0.980238835697362
251614.2365783282754-0.1248994104210641.373893514188510.553914904181705
261615.3084776697695-0.0984727622146713-0.09847276233959941.07834052927469
271414.5807013950321-0.106359536487027-0.106359536487027-0.620875895544766
281615.3883504798348-0.0989144933689914-0.09891449336899090.920793180730677
291515.1830244920161-0.0995734487915743-0.0995734487915745-0.107816674866238
301414.5343662583743-0.102495413321234-0.102495413321234-0.557372502113621
311514.8060330623435-0.100652015435196-0.1006520154351960.380073973590501
321514.9258924724297-0.0996064964441538-0.0996064964441540.224059292236240
331414.4209063444220-0.101490727025675-0.101490727025675-0.411952916642729
341313.6400034895741-0.104612889819452-0.104612889819453-0.690468204408783
351212.7372428223082-0.108252973234636-0.108252973234636-0.811158944943769
361312.8963431083871-0.107040811397382-0.1070408113973820.271715847118304
371211.8514325660342-0.08234735403108370.905820894809686-1.04350229454497
38910.1980073566812-0.108122373080189-0.108122372716817-1.46319107171368
391010.1001729521356-0.108026935179564-0.1080269351795630.0102335043072029
4088.93777017747933-0.114389693068281-0.114389693068280-1.06500713937670
411110.1028784046752-0.108511302608257-0.1085113026082571.29787006018571
4288.9417652538594-0.112672742069584-0.112672742069583-1.06918731527649
4388.42929940350655-0.114137928063877-0.114137928063877-0.406301479613735
4488.2029902745396-0.114534033766936-0.114534033766936-0.114021241683403
4545.87107349387417-0.122219295461473-0.122219295461473-2.2541589831711
4665.95718333309146-0.121504590659857-0.1215045906598570.211793093529790
4787.11111232857776-0.117157057188541-0.1171570571885411.29666645327670
48108.73662323004881-0.111244918378391-0.1112449183783921.77169793326062
4956.22346939730925-0.06415994286130710.705759371332797-2.61528642839447
5066.10420289893826-0.0648791670129732-0.0648791668404713-0.0523032537481351
5155.49078970019951-0.068918363081794-0.0689183630817937-0.54823484984933
5297.4618682697087-0.0591414082220524-0.05914140822205092.06375593968118
5387.76930974647398-0.0578027201474461-0.0578027201474460.372095809486748
5466.78840994928271-0.0607058403524902-0.0607058403524898-0.938003378715683
5598.02977458718216-0.0569069382366746-0.05690693823667441.32363668466822
56119.69399359139506-0.0520649575285591-0.05206495752855971.74992448499083
571110.4288715210590-0.0498905100301642-0.04989051003016410.800167762386354
5889.07921757702635-0.0534478988365732-0.0534478988365732-1.32164912009629
591110.1573243834821-0.050368608791682-0.05036860879168231.15062567861942
601110.6334311280640-0.0489417030731311-0.04894170307313120.535352692433209
611311.5361672855467-0.06380146842179340.7018161514664031.02265693568257

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 17 & 17 & 0 & 0 & 0 \tabularnewline
2 & 14 & 15.0330593463373 & -0.144548055205191 & -0.144548055091753 & -1.39601525305627 \tabularnewline
3 & 15 & 15.0366808303117 & -0.138307627077558 & -0.138307627077558 & 0.137928287429375 \tabularnewline
4 & 16 & 15.5961311402861 & -0.119417418645176 & -0.119417418645176 & 0.688758691943332 \tabularnewline
5 & 16 & 15.8357560627452 & -0.112118441539720 & -0.112118441539720 & 0.360365262724881 \tabularnewline
6 & 15 & 15.3827831630744 & -0.118005192720895 & -0.118005192720895 & -0.344067796622985 \tabularnewline
7 & 13 & 14.0691240284864 & -0.136918270649693 & -0.136918270649693 & -1.20961451838913 \tabularnewline
8 & 12 & 12.9325956774681 & -0.15197898024712 & -0.15197898024712 & -1.01224113206571 \tabularnewline
9 & 13 & 12.9873708409666 & -0.148955645344341 & -0.148955645344341 & 0.209458126868009 \tabularnewline
10 & 13 & 13.0113044090183 & -0.146480521280286 & -0.146480521280286 & 0.175189117610645 \tabularnewline
11 & 12 & 12.4648892919948 & -0.152108572521464 & -0.152108572521464 & -0.405306986957112 \tabularnewline
12 & 10 & 11.1098001374771 & -0.168780627979749 & -0.168780627979750 & -1.21924732374979 \tabularnewline
13 & 14 & 11.3756416220192 & -0.205251239413527 & 2.25776363376831 & 0.567694259254424 \tabularnewline
14 & 14 & 13.0383969104541 & -0.142189019082738 & -0.142189019980194 & 1.56498830053981 \tabularnewline
15 & 15 & 14.1774554729902 & -0.117448303603044 & -0.117448303603045 & 1.24240554910863 \tabularnewline
16 & 16 & 15.2141406993944 & -0.102989882207872 & -0.102989882207872 & 1.15631406542678 \tabularnewline
17 & 16 & 15.6652041148266 & -0.0977286659580146 & -0.0977286659580147 & 0.560046448290538 \tabularnewline
18 & 15 & 15.3053892072666 & -0.0998613408926226 & -0.0998613408926226 & -0.265683953191292 \tabularnewline
19 & 15 & 15.1465975156957 & -0.100304137481318 & -0.100304137481318 & -0.0598034462106509 \tabularnewline
20 & 13 & 13.9611778528158 & -0.108131168628344 & -0.108131168628344 & -1.10167800158178 \tabularnewline
21 & 15 & 14.5528627435966 & -0.103194633832754 & -0.103194633832754 & 0.710635470163316 \tabularnewline
22 & 15 & 14.8140578757829 & -0.100659380517216 & -0.100659380517216 & 0.370057237879655 \tabularnewline
23 & 15 & 14.9293247976099 & -0.0991719079499465 & -0.0991719079499464 & 0.219295115615948 \tabularnewline
24 & 13 & 13.8649999670494 & -0.105766415333544 & -0.105766415333544 & -0.980238835697362 \tabularnewline
25 & 16 & 14.2365783282754 & -0.124899410421064 & 1.37389351418851 & 0.553914904181705 \tabularnewline
26 & 16 & 15.3084776697695 & -0.0984727622146713 & -0.0984727623395994 & 1.07834052927469 \tabularnewline
27 & 14 & 14.5807013950321 & -0.106359536487027 & -0.106359536487027 & -0.620875895544766 \tabularnewline
28 & 16 & 15.3883504798348 & -0.0989144933689914 & -0.0989144933689909 & 0.920793180730677 \tabularnewline
29 & 15 & 15.1830244920161 & -0.0995734487915743 & -0.0995734487915745 & -0.107816674866238 \tabularnewline
30 & 14 & 14.5343662583743 & -0.102495413321234 & -0.102495413321234 & -0.557372502113621 \tabularnewline
31 & 15 & 14.8060330623435 & -0.100652015435196 & -0.100652015435196 & 0.380073973590501 \tabularnewline
32 & 15 & 14.9258924724297 & -0.0996064964441538 & -0.099606496444154 & 0.224059292236240 \tabularnewline
33 & 14 & 14.4209063444220 & -0.101490727025675 & -0.101490727025675 & -0.411952916642729 \tabularnewline
34 & 13 & 13.6400034895741 & -0.104612889819452 & -0.104612889819453 & -0.690468204408783 \tabularnewline
35 & 12 & 12.7372428223082 & -0.108252973234636 & -0.108252973234636 & -0.811158944943769 \tabularnewline
36 & 13 & 12.8963431083871 & -0.107040811397382 & -0.107040811397382 & 0.271715847118304 \tabularnewline
37 & 12 & 11.8514325660342 & -0.0823473540310837 & 0.905820894809686 & -1.04350229454497 \tabularnewline
38 & 9 & 10.1980073566812 & -0.108122373080189 & -0.108122372716817 & -1.46319107171368 \tabularnewline
39 & 10 & 10.1001729521356 & -0.108026935179564 & -0.108026935179563 & 0.0102335043072029 \tabularnewline
40 & 8 & 8.93777017747933 & -0.114389693068281 & -0.114389693068280 & -1.06500713937670 \tabularnewline
41 & 11 & 10.1028784046752 & -0.108511302608257 & -0.108511302608257 & 1.29787006018571 \tabularnewline
42 & 8 & 8.9417652538594 & -0.112672742069584 & -0.112672742069583 & -1.06918731527649 \tabularnewline
43 & 8 & 8.42929940350655 & -0.114137928063877 & -0.114137928063877 & -0.406301479613735 \tabularnewline
44 & 8 & 8.2029902745396 & -0.114534033766936 & -0.114534033766936 & -0.114021241683403 \tabularnewline
45 & 4 & 5.87107349387417 & -0.122219295461473 & -0.122219295461473 & -2.2541589831711 \tabularnewline
46 & 6 & 5.95718333309146 & -0.121504590659857 & -0.121504590659857 & 0.211793093529790 \tabularnewline
47 & 8 & 7.11111232857776 & -0.117157057188541 & -0.117157057188541 & 1.29666645327670 \tabularnewline
48 & 10 & 8.73662323004881 & -0.111244918378391 & -0.111244918378392 & 1.77169793326062 \tabularnewline
49 & 5 & 6.22346939730925 & -0.0641599428613071 & 0.705759371332797 & -2.61528642839447 \tabularnewline
50 & 6 & 6.10420289893826 & -0.0648791670129732 & -0.0648791668404713 & -0.0523032537481351 \tabularnewline
51 & 5 & 5.49078970019951 & -0.068918363081794 & -0.0689183630817937 & -0.54823484984933 \tabularnewline
52 & 9 & 7.4618682697087 & -0.0591414082220524 & -0.0591414082220509 & 2.06375593968118 \tabularnewline
53 & 8 & 7.76930974647398 & -0.0578027201474461 & -0.057802720147446 & 0.372095809486748 \tabularnewline
54 & 6 & 6.78840994928271 & -0.0607058403524902 & -0.0607058403524898 & -0.938003378715683 \tabularnewline
55 & 9 & 8.02977458718216 & -0.0569069382366746 & -0.0569069382366744 & 1.32363668466822 \tabularnewline
56 & 11 & 9.69399359139506 & -0.0520649575285591 & -0.0520649575285597 & 1.74992448499083 \tabularnewline
57 & 11 & 10.4288715210590 & -0.0498905100301642 & -0.0498905100301641 & 0.800167762386354 \tabularnewline
58 & 8 & 9.07921757702635 & -0.0534478988365732 & -0.0534478988365732 & -1.32164912009629 \tabularnewline
59 & 11 & 10.1573243834821 & -0.050368608791682 & -0.0503686087916823 & 1.15062567861942 \tabularnewline
60 & 11 & 10.6334311280640 & -0.0489417030731311 & -0.0489417030731312 & 0.535352692433209 \tabularnewline
61 & 13 & 11.5361672855467 & -0.0638014684217934 & 0.701816151466403 & 1.02265693568257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63357&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]17[/C][C]17[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]14[/C][C]15.0330593463373[/C][C]-0.144548055205191[/C][C]-0.144548055091753[/C][C]-1.39601525305627[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]15.0366808303117[/C][C]-0.138307627077558[/C][C]-0.138307627077558[/C][C]0.137928287429375[/C][/ROW]
[ROW][C]4[/C][C]16[/C][C]15.5961311402861[/C][C]-0.119417418645176[/C][C]-0.119417418645176[/C][C]0.688758691943332[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]15.8357560627452[/C][C]-0.112118441539720[/C][C]-0.112118441539720[/C][C]0.360365262724881[/C][/ROW]
[ROW][C]6[/C][C]15[/C][C]15.3827831630744[/C][C]-0.118005192720895[/C][C]-0.118005192720895[/C][C]-0.344067796622985[/C][/ROW]
[ROW][C]7[/C][C]13[/C][C]14.0691240284864[/C][C]-0.136918270649693[/C][C]-0.136918270649693[/C][C]-1.20961451838913[/C][/ROW]
[ROW][C]8[/C][C]12[/C][C]12.9325956774681[/C][C]-0.15197898024712[/C][C]-0.15197898024712[/C][C]-1.01224113206571[/C][/ROW]
[ROW][C]9[/C][C]13[/C][C]12.9873708409666[/C][C]-0.148955645344341[/C][C]-0.148955645344341[/C][C]0.209458126868009[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]13.0113044090183[/C][C]-0.146480521280286[/C][C]-0.146480521280286[/C][C]0.175189117610645[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]12.4648892919948[/C][C]-0.152108572521464[/C][C]-0.152108572521464[/C][C]-0.405306986957112[/C][/ROW]
[ROW][C]12[/C][C]10[/C][C]11.1098001374771[/C][C]-0.168780627979749[/C][C]-0.168780627979750[/C][C]-1.21924732374979[/C][/ROW]
[ROW][C]13[/C][C]14[/C][C]11.3756416220192[/C][C]-0.205251239413527[/C][C]2.25776363376831[/C][C]0.567694259254424[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]13.0383969104541[/C][C]-0.142189019082738[/C][C]-0.142189019980194[/C][C]1.56498830053981[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]14.1774554729902[/C][C]-0.117448303603044[/C][C]-0.117448303603045[/C][C]1.24240554910863[/C][/ROW]
[ROW][C]16[/C][C]16[/C][C]15.2141406993944[/C][C]-0.102989882207872[/C][C]-0.102989882207872[/C][C]1.15631406542678[/C][/ROW]
[ROW][C]17[/C][C]16[/C][C]15.6652041148266[/C][C]-0.0977286659580146[/C][C]-0.0977286659580147[/C][C]0.560046448290538[/C][/ROW]
[ROW][C]18[/C][C]15[/C][C]15.3053892072666[/C][C]-0.0998613408926226[/C][C]-0.0998613408926226[/C][C]-0.265683953191292[/C][/ROW]
[ROW][C]19[/C][C]15[/C][C]15.1465975156957[/C][C]-0.100304137481318[/C][C]-0.100304137481318[/C][C]-0.0598034462106509[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]13.9611778528158[/C][C]-0.108131168628344[/C][C]-0.108131168628344[/C][C]-1.10167800158178[/C][/ROW]
[ROW][C]21[/C][C]15[/C][C]14.5528627435966[/C][C]-0.103194633832754[/C][C]-0.103194633832754[/C][C]0.710635470163316[/C][/ROW]
[ROW][C]22[/C][C]15[/C][C]14.8140578757829[/C][C]-0.100659380517216[/C][C]-0.100659380517216[/C][C]0.370057237879655[/C][/ROW]
[ROW][C]23[/C][C]15[/C][C]14.9293247976099[/C][C]-0.0991719079499465[/C][C]-0.0991719079499464[/C][C]0.219295115615948[/C][/ROW]
[ROW][C]24[/C][C]13[/C][C]13.8649999670494[/C][C]-0.105766415333544[/C][C]-0.105766415333544[/C][C]-0.980238835697362[/C][/ROW]
[ROW][C]25[/C][C]16[/C][C]14.2365783282754[/C][C]-0.124899410421064[/C][C]1.37389351418851[/C][C]0.553914904181705[/C][/ROW]
[ROW][C]26[/C][C]16[/C][C]15.3084776697695[/C][C]-0.0984727622146713[/C][C]-0.0984727623395994[/C][C]1.07834052927469[/C][/ROW]
[ROW][C]27[/C][C]14[/C][C]14.5807013950321[/C][C]-0.106359536487027[/C][C]-0.106359536487027[/C][C]-0.620875895544766[/C][/ROW]
[ROW][C]28[/C][C]16[/C][C]15.3883504798348[/C][C]-0.0989144933689914[/C][C]-0.0989144933689909[/C][C]0.920793180730677[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]15.1830244920161[/C][C]-0.0995734487915743[/C][C]-0.0995734487915745[/C][C]-0.107816674866238[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.5343662583743[/C][C]-0.102495413321234[/C][C]-0.102495413321234[/C][C]-0.557372502113621[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]14.8060330623435[/C][C]-0.100652015435196[/C][C]-0.100652015435196[/C][C]0.380073973590501[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.9258924724297[/C][C]-0.0996064964441538[/C][C]-0.099606496444154[/C][C]0.224059292236240[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4209063444220[/C][C]-0.101490727025675[/C][C]-0.101490727025675[/C][C]-0.411952916642729[/C][/ROW]
[ROW][C]34[/C][C]13[/C][C]13.6400034895741[/C][C]-0.104612889819452[/C][C]-0.104612889819453[/C][C]-0.690468204408783[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]12.7372428223082[/C][C]-0.108252973234636[/C][C]-0.108252973234636[/C][C]-0.811158944943769[/C][/ROW]
[ROW][C]36[/C][C]13[/C][C]12.8963431083871[/C][C]-0.107040811397382[/C][C]-0.107040811397382[/C][C]0.271715847118304[/C][/ROW]
[ROW][C]37[/C][C]12[/C][C]11.8514325660342[/C][C]-0.0823473540310837[/C][C]0.905820894809686[/C][C]-1.04350229454497[/C][/ROW]
[ROW][C]38[/C][C]9[/C][C]10.1980073566812[/C][C]-0.108122373080189[/C][C]-0.108122372716817[/C][C]-1.46319107171368[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.1001729521356[/C][C]-0.108026935179564[/C][C]-0.108026935179563[/C][C]0.0102335043072029[/C][/ROW]
[ROW][C]40[/C][C]8[/C][C]8.93777017747933[/C][C]-0.114389693068281[/C][C]-0.114389693068280[/C][C]-1.06500713937670[/C][/ROW]
[ROW][C]41[/C][C]11[/C][C]10.1028784046752[/C][C]-0.108511302608257[/C][C]-0.108511302608257[/C][C]1.29787006018571[/C][/ROW]
[ROW][C]42[/C][C]8[/C][C]8.9417652538594[/C][C]-0.112672742069584[/C][C]-0.112672742069583[/C][C]-1.06918731527649[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]8.42929940350655[/C][C]-0.114137928063877[/C][C]-0.114137928063877[/C][C]-0.406301479613735[/C][/ROW]
[ROW][C]44[/C][C]8[/C][C]8.2029902745396[/C][C]-0.114534033766936[/C][C]-0.114534033766936[/C][C]-0.114021241683403[/C][/ROW]
[ROW][C]45[/C][C]4[/C][C]5.87107349387417[/C][C]-0.122219295461473[/C][C]-0.122219295461473[/C][C]-2.2541589831711[/C][/ROW]
[ROW][C]46[/C][C]6[/C][C]5.95718333309146[/C][C]-0.121504590659857[/C][C]-0.121504590659857[/C][C]0.211793093529790[/C][/ROW]
[ROW][C]47[/C][C]8[/C][C]7.11111232857776[/C][C]-0.117157057188541[/C][C]-0.117157057188541[/C][C]1.29666645327670[/C][/ROW]
[ROW][C]48[/C][C]10[/C][C]8.73662323004881[/C][C]-0.111244918378391[/C][C]-0.111244918378392[/C][C]1.77169793326062[/C][/ROW]
[ROW][C]49[/C][C]5[/C][C]6.22346939730925[/C][C]-0.0641599428613071[/C][C]0.705759371332797[/C][C]-2.61528642839447[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]6.10420289893826[/C][C]-0.0648791670129732[/C][C]-0.0648791668404713[/C][C]-0.0523032537481351[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.49078970019951[/C][C]-0.068918363081794[/C][C]-0.0689183630817937[/C][C]-0.54823484984933[/C][/ROW]
[ROW][C]52[/C][C]9[/C][C]7.4618682697087[/C][C]-0.0591414082220524[/C][C]-0.0591414082220509[/C][C]2.06375593968118[/C][/ROW]
[ROW][C]53[/C][C]8[/C][C]7.76930974647398[/C][C]-0.0578027201474461[/C][C]-0.057802720147446[/C][C]0.372095809486748[/C][/ROW]
[ROW][C]54[/C][C]6[/C][C]6.78840994928271[/C][C]-0.0607058403524902[/C][C]-0.0607058403524898[/C][C]-0.938003378715683[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]8.02977458718216[/C][C]-0.0569069382366746[/C][C]-0.0569069382366744[/C][C]1.32363668466822[/C][/ROW]
[ROW][C]56[/C][C]11[/C][C]9.69399359139506[/C][C]-0.0520649575285591[/C][C]-0.0520649575285597[/C][C]1.74992448499083[/C][/ROW]
[ROW][C]57[/C][C]11[/C][C]10.4288715210590[/C][C]-0.0498905100301642[/C][C]-0.0498905100301641[/C][C]0.800167762386354[/C][/ROW]
[ROW][C]58[/C][C]8[/C][C]9.07921757702635[/C][C]-0.0534478988365732[/C][C]-0.0534478988365732[/C][C]-1.32164912009629[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]10.1573243834821[/C][C]-0.050368608791682[/C][C]-0.0503686087916823[/C][C]1.15062567861942[/C][/ROW]
[ROW][C]60[/C][C]11[/C][C]10.6334311280640[/C][C]-0.0489417030731311[/C][C]-0.0489417030731312[/C][C]0.535352692433209[/C][/ROW]
[ROW][C]61[/C][C]13[/C][C]11.5361672855467[/C][C]-0.0638014684217934[/C][C]0.701816151466403[/C][C]1.02265693568257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63357&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63357&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
11717000
21415.0330593463373-0.144548055205191-0.144548055091753-1.39601525305627
31515.0366808303117-0.138307627077558-0.1383076270775580.137928287429375
41615.5961311402861-0.119417418645176-0.1194174186451760.688758691943332
51615.8357560627452-0.112118441539720-0.1121184415397200.360365262724881
61515.3827831630744-0.118005192720895-0.118005192720895-0.344067796622985
71314.0691240284864-0.136918270649693-0.136918270649693-1.20961451838913
81212.9325956774681-0.15197898024712-0.15197898024712-1.01224113206571
91312.9873708409666-0.148955645344341-0.1489556453443410.209458126868009
101313.0113044090183-0.146480521280286-0.1464805212802860.175189117610645
111212.4648892919948-0.152108572521464-0.152108572521464-0.405306986957112
121011.1098001374771-0.168780627979749-0.168780627979750-1.21924732374979
131411.3756416220192-0.2052512394135272.257763633768310.567694259254424
141413.0383969104541-0.142189019082738-0.1421890199801941.56498830053981
151514.1774554729902-0.117448303603044-0.1174483036030451.24240554910863
161615.2141406993944-0.102989882207872-0.1029898822078721.15631406542678
171615.6652041148266-0.0977286659580146-0.09772866595801470.560046448290538
181515.3053892072666-0.0998613408926226-0.0998613408926226-0.265683953191292
191515.1465975156957-0.100304137481318-0.100304137481318-0.0598034462106509
201313.9611778528158-0.108131168628344-0.108131168628344-1.10167800158178
211514.5528627435966-0.103194633832754-0.1031946338327540.710635470163316
221514.8140578757829-0.100659380517216-0.1006593805172160.370057237879655
231514.9293247976099-0.0991719079499465-0.09917190794994640.219295115615948
241313.8649999670494-0.105766415333544-0.105766415333544-0.980238835697362
251614.2365783282754-0.1248994104210641.373893514188510.553914904181705
261615.3084776697695-0.0984727622146713-0.09847276233959941.07834052927469
271414.5807013950321-0.106359536487027-0.106359536487027-0.620875895544766
281615.3883504798348-0.0989144933689914-0.09891449336899090.920793180730677
291515.1830244920161-0.0995734487915743-0.0995734487915745-0.107816674866238
301414.5343662583743-0.102495413321234-0.102495413321234-0.557372502113621
311514.8060330623435-0.100652015435196-0.1006520154351960.380073973590501
321514.9258924724297-0.0996064964441538-0.0996064964441540.224059292236240
331414.4209063444220-0.101490727025675-0.101490727025675-0.411952916642729
341313.6400034895741-0.104612889819452-0.104612889819453-0.690468204408783
351212.7372428223082-0.108252973234636-0.108252973234636-0.811158944943769
361312.8963431083871-0.107040811397382-0.1070408113973820.271715847118304
371211.8514325660342-0.08234735403108370.905820894809686-1.04350229454497
38910.1980073566812-0.108122373080189-0.108122372716817-1.46319107171368
391010.1001729521356-0.108026935179564-0.1080269351795630.0102335043072029
4088.93777017747933-0.114389693068281-0.114389693068280-1.06500713937670
411110.1028784046752-0.108511302608257-0.1085113026082571.29787006018571
4288.9417652538594-0.112672742069584-0.112672742069583-1.06918731527649
4388.42929940350655-0.114137928063877-0.114137928063877-0.406301479613735
4488.2029902745396-0.114534033766936-0.114534033766936-0.114021241683403
4545.87107349387417-0.122219295461473-0.122219295461473-2.2541589831711
4665.95718333309146-0.121504590659857-0.1215045906598570.211793093529790
4787.11111232857776-0.117157057188541-0.1171570571885411.29666645327670
48108.73662323004881-0.111244918378391-0.1112449183783921.77169793326062
4956.22346939730925-0.06415994286130710.705759371332797-2.61528642839447
5066.10420289893826-0.0648791670129732-0.0648791668404713-0.0523032537481351
5155.49078970019951-0.068918363081794-0.0689183630817937-0.54823484984933
5297.4618682697087-0.0591414082220524-0.05914140822205092.06375593968118
5387.76930974647398-0.0578027201474461-0.0578027201474460.372095809486748
5466.78840994928271-0.0607058403524902-0.0607058403524898-0.938003378715683
5598.02977458718216-0.0569069382366746-0.05690693823667441.32363668466822
56119.69399359139506-0.0520649575285591-0.05206495752855971.74992448499083
571110.4288715210590-0.0498905100301642-0.04989051003016410.800167762386354
5889.07921757702635-0.0534478988365732-0.0534478988365732-1.32164912009629
591110.1573243834821-0.050368608791682-0.05036860879168231.15062567861942
601110.6334311280640-0.0489417030731311-0.04894170307313120.535352692433209
611311.5361672855467-0.06380146842179340.7018161514664031.02265693568257



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')