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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Thu, 03 Dec 2009 11:46:26 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259866238yjqnw1ht40f15mh.htm/, Retrieved Tue, 23 Apr 2024 08:02:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63060, Retrieved Tue, 23 Apr 2024 08:02:46 +0000

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No (this computation is public)

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Estimated Impact

151

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] [SHW WS9] [2009-12-03 18:46:26] [b7e46d23597387652ca7420fdeb9acca] [Current]
-   PD        [Structural Time Series Models] [Structural Time S...] [2009-12-04 15:49:46] [ba905ddf7cdf9ecb063c35348c4dab2e] 
-   PD          [Structural Time Series Models] [Structural Time S...] [2009-12-06 20:06:51] [ba905ddf7cdf9ecb063c35348c4dab2e] 
-   PD          [Structural Time Series Models] [] [2009-12-06 20:06:51] [ba905ddf7cdf9ecb063c35348c4dab2e] 

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Dataseries X:

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1.59
1.26
1.13
1.92
2.61
2.26
2.41
2.26
2.03
2.86
2.55
2.27
2.26
2.57
3.07
2.76
2.51
2.87
3.14
3.11
3.16
2.47
2.57
2.89
2.63
2.38
1.69
1.96
2.19
1.87
1.6
1.63
1.22
1.21
1.49
1.64
1.66
1.77
1.82
1.78
1.28
1.29
1.37
1.12
1.51
2.24
2.94
3.09
3.46
3.64
4.39
4.15
5.21
5.8
5.91
5.39
5.46
4.72
3.14
2.63

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=63060&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=63060&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63060&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	1.59	1.59	0	0	0
2	1.26	1.27664147880926	-0.0266130193168101	-0.0166414788092608	-0.468949884678013
3	1.13	1.14658931093672	-0.0426786025786395	-0.0165893109367155	-0.240877315287619
4	1.92	1.93692502223450	0.124687571458184	-0.016925022234496	1.88692291413097
5	2.61	2.62710072633706	0.254193854788040	-0.0171007263370595	1.25832718603289
6	2.26	2.27695902627387	0.105907435734632	-0.0169590262738673	-1.3305436525685
7	2.41	2.42696673419582	0.117134248415217	-0.016966734195819	0.0965066188707478
8	2.26	2.27693216297358	0.0477619711295369	-0.0169321629735759	-0.582691676530388
9	2.03	2.04690565090215	-0.0251393727433627	-0.0169056509021519	-0.60473942082146
10	2.86	2.87696572779066	0.200585771877503	-0.0169657277906597	1.85989902742832
11	2.55	2.56693935484482	0.0653946804138398	-0.0169393548448212	-1.10989283844115
12	2.27	2.28692624597294	-0.0262094864032349	-0.0169262459729372	-0.750582012439315
13	2.26	2.12697237175659	-0.0604611290668771	0.133027628243410	-0.337207095851677
14	2.57	2.57083166378842	0.0668687993113224	-0.000831663788421312	0.915813897078617
15	3.07	3.07136231291933	0.182262255291627	-0.0013623129193256	0.940473964105364
16	2.76	2.76091970240126	0.0512710137581165	-0.000919702401255461	-1.06909787240323
17	2.51	2.51072085498038	-0.0288460150357446	-0.000720854980381655	-0.654378010343151
18	2.87	2.87090927715949	0.0745241277695391	-0.00090927715949085	0.844648798105718
19	3.14	3.14097882258534	0.126479413233335	-0.000978822585340527	0.424625741548868
20	3.11	3.11093794648578	0.084893123708108	-0.000937946485777381	-0.339921207557084
21	3.16	3.16093125384634	0.0756203577080185	-0.000931253846337647	-0.0757992934482249
22	2.47	2.47082342847113	-0.127835522174789	-0.000823428471132048	-1.66318697082964
23	2.57	2.57084698879969	-0.0672914854001537	-0.000846988799694827	0.49493740251833
24	2.89	2.89087639585848	0.0356248234542288	-0.000876395858482492	0.841332090342454
25	2.63	2.66853365759167	-0.0318862069520319	-0.0385336575916663	-0.605076419511567
26	2.38	2.38017806480123	-0.0978198912733993	-0.000178064801229533	-0.500868009326136
27	1.69	1.68969848223087	-0.255486137837755	0.000301517769133157	-1.28597155724411
28	1.96	1.9600108479324	-0.115702053423195	-1.08479324012053e-05	1.14132477664591
29	2.19	2.19016170671847	-0.0237865087705708	-0.000161706718473785	0.750909991695025
30	1.87	1.87006680349765	-0.102523516395460	-6.68034976481764e-05	-0.643444668015577
31	1.6	1.60002740683248	-0.147034481757993	-2.74068324820226e-05	-0.363807147339418
32	1.63	1.63005798453742	-0.0999868016240103	-5.7984537419313e-05	0.384575132893068
33	1.22	1.22001866802329	-0.182370793751421	-1.86680232879242e-05	-0.673452115812668
34	1.21	1.2100347193065	-0.136565382413136	-3.47193064986828e-05	0.374448371751139
35	1.49	1.49006320208605	-0.0258695840351746	-6.32020860464097e-05	0.904924553515611
36	1.64	1.64007203174743	0.0208647354352649	-7.20317474337113e-05	0.382050202633907
37	1.66	1.65939566259889	0.0204592618845721	0.000604337401109234	-0.00352566004978326
38	1.77	1.76911046655366	0.0436077395985069	0.000889533446344546	0.179722773294015
39	1.82	1.81911429879570	0.0453088050520883	0.00088570120430393	0.0138826226222192
40	1.78	1.77907674501953	0.0226220372923013	0.000923254980471246	-0.185294770867888
41	1.28	1.27890784215043	-0.116312834470783	0.00109215784956788	-1.13523332962454
42	1.29	1.2889378142139	-0.0827400520468216	0.00106218578610103	0.274384797902431
43	1.37	1.36896616726506	-0.0394897462397275	0.00103383273494092	0.353520971912539
44	1.12	1.11893923805590	-0.0954324765261785	0.00106076194410383	-0.457297039205401
45	1.51	1.50898483428363	0.0335664555475019	0.00101516571636777	1.05452368023678
46	2.24	2.23903286643814	0.218633843757157	0.000967133561857926	1.51289389130264
47	2.94	2.93905724351461	0.346548984982855	0.000942756485394306	1.04569499849202
48	3.09	3.08904993496336	0.294319571179134	0.000950065036642202	-0.426973238420458
49	3.46	3.46321742823383	0.315381996492675	-0.00321742823383147	0.180367079065923
50	3.64	3.64086174585341	0.279476808837663	-0.000861745853407672	-0.282076803703573
51	4.39	4.39108571751962	0.40465218755776	-0.00108571751961551	1.02193085032645
52	4.15	4.15086045070918	0.233242722801421	-0.00086045070917501	-1.40025567161983
53	5.21	5.21107255667473	0.453010561917699	-0.00107255667472807	1.79590027974623
54	5.8	5.80109836079765	0.489419394679731	-0.00109836079764991	0.297579700584806
55	5.91	5.91104588468307	0.388586234884432	-0.00104588468306820	-0.824218253167346
56	5.39	5.39095361576778	0.147134300326672	-0.000953615767782762	-1.97375093812424
57	5.46	5.4609478641808	0.126636763850534	-0.000947864180795105	-0.167562034670224
58	4.72	4.72090041484098	-0.103658824080971	-0.00090041484098577	-1.88263533275908
59	3.14	3.14084106305233	-0.495971386420688	-0.000841063052330742	-3.20712861751377
60	2.63	2.63084064894165	-0.49969923791476	-0.000840648941646655	-0.0304750686363817

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 1.59 & 1.59 & 0 & 0 & 0 \tabularnewline
2 & 1.26 & 1.27664147880926 & -0.0266130193168101 & -0.0166414788092608 & -0.468949884678013 \tabularnewline
3 & 1.13 & 1.14658931093672 & -0.0426786025786395 & -0.0165893109367155 & -0.240877315287619 \tabularnewline
4 & 1.92 & 1.93692502223450 & 0.124687571458184 & -0.016925022234496 & 1.88692291413097 \tabularnewline
5 & 2.61 & 2.62710072633706 & 0.254193854788040 & -0.0171007263370595 & 1.25832718603289 \tabularnewline
6 & 2.26 & 2.27695902627387 & 0.105907435734632 & -0.0169590262738673 & -1.3305436525685 \tabularnewline
7 & 2.41 & 2.42696673419582 & 0.117134248415217 & -0.016966734195819 & 0.0965066188707478 \tabularnewline
8 & 2.26 & 2.27693216297358 & 0.0477619711295369 & -0.0169321629735759 & -0.582691676530388 \tabularnewline
9 & 2.03 & 2.04690565090215 & -0.0251393727433627 & -0.0169056509021519 & -0.60473942082146 \tabularnewline
10 & 2.86 & 2.87696572779066 & 0.200585771877503 & -0.0169657277906597 & 1.85989902742832 \tabularnewline
11 & 2.55 & 2.56693935484482 & 0.0653946804138398 & -0.0169393548448212 & -1.10989283844115 \tabularnewline
12 & 2.27 & 2.28692624597294 & -0.0262094864032349 & -0.0169262459729372 & -0.750582012439315 \tabularnewline
13 & 2.26 & 2.12697237175659 & -0.0604611290668771 & 0.133027628243410 & -0.337207095851677 \tabularnewline
14 & 2.57 & 2.57083166378842 & 0.0668687993113224 & -0.000831663788421312 & 0.915813897078617 \tabularnewline
15 & 3.07 & 3.07136231291933 & 0.182262255291627 & -0.0013623129193256 & 0.940473964105364 \tabularnewline
16 & 2.76 & 2.76091970240126 & 0.0512710137581165 & -0.000919702401255461 & -1.06909787240323 \tabularnewline
17 & 2.51 & 2.51072085498038 & -0.0288460150357446 & -0.000720854980381655 & -0.654378010343151 \tabularnewline
18 & 2.87 & 2.87090927715949 & 0.0745241277695391 & -0.00090927715949085 & 0.844648798105718 \tabularnewline
19 & 3.14 & 3.14097882258534 & 0.126479413233335 & -0.000978822585340527 & 0.424625741548868 \tabularnewline
20 & 3.11 & 3.11093794648578 & 0.084893123708108 & -0.000937946485777381 & -0.339921207557084 \tabularnewline
21 & 3.16 & 3.16093125384634 & 0.0756203577080185 & -0.000931253846337647 & -0.0757992934482249 \tabularnewline
22 & 2.47 & 2.47082342847113 & -0.127835522174789 & -0.000823428471132048 & -1.66318697082964 \tabularnewline
23 & 2.57 & 2.57084698879969 & -0.0672914854001537 & -0.000846988799694827 & 0.49493740251833 \tabularnewline
24 & 2.89 & 2.89087639585848 & 0.0356248234542288 & -0.000876395858482492 & 0.841332090342454 \tabularnewline
25 & 2.63 & 2.66853365759167 & -0.0318862069520319 & -0.0385336575916663 & -0.605076419511567 \tabularnewline
26 & 2.38 & 2.38017806480123 & -0.0978198912733993 & -0.000178064801229533 & -0.500868009326136 \tabularnewline
27 & 1.69 & 1.68969848223087 & -0.255486137837755 & 0.000301517769133157 & -1.28597155724411 \tabularnewline
28 & 1.96 & 1.9600108479324 & -0.115702053423195 & -1.08479324012053e-05 & 1.14132477664591 \tabularnewline
29 & 2.19 & 2.19016170671847 & -0.0237865087705708 & -0.000161706718473785 & 0.750909991695025 \tabularnewline
30 & 1.87 & 1.87006680349765 & -0.102523516395460 & -6.68034976481764e-05 & -0.643444668015577 \tabularnewline
31 & 1.6 & 1.60002740683248 & -0.147034481757993 & -2.74068324820226e-05 & -0.363807147339418 \tabularnewline
32 & 1.63 & 1.63005798453742 & -0.0999868016240103 & -5.7984537419313e-05 & 0.384575132893068 \tabularnewline
33 & 1.22 & 1.22001866802329 & -0.182370793751421 & -1.86680232879242e-05 & -0.673452115812668 \tabularnewline
34 & 1.21 & 1.2100347193065 & -0.136565382413136 & -3.47193064986828e-05 & 0.374448371751139 \tabularnewline
35 & 1.49 & 1.49006320208605 & -0.0258695840351746 & -6.32020860464097e-05 & 0.904924553515611 \tabularnewline
36 & 1.64 & 1.64007203174743 & 0.0208647354352649 & -7.20317474337113e-05 & 0.382050202633907 \tabularnewline
37 & 1.66 & 1.65939566259889 & 0.0204592618845721 & 0.000604337401109234 & -0.00352566004978326 \tabularnewline
38 & 1.77 & 1.76911046655366 & 0.0436077395985069 & 0.000889533446344546 & 0.179722773294015 \tabularnewline
39 & 1.82 & 1.81911429879570 & 0.0453088050520883 & 0.00088570120430393 & 0.0138826226222192 \tabularnewline
40 & 1.78 & 1.77907674501953 & 0.0226220372923013 & 0.000923254980471246 & -0.185294770867888 \tabularnewline
41 & 1.28 & 1.27890784215043 & -0.116312834470783 & 0.00109215784956788 & -1.13523332962454 \tabularnewline
42 & 1.29 & 1.2889378142139 & -0.0827400520468216 & 0.00106218578610103 & 0.274384797902431 \tabularnewline
43 & 1.37 & 1.36896616726506 & -0.0394897462397275 & 0.00103383273494092 & 0.353520971912539 \tabularnewline
44 & 1.12 & 1.11893923805590 & -0.0954324765261785 & 0.00106076194410383 & -0.457297039205401 \tabularnewline
45 & 1.51 & 1.50898483428363 & 0.0335664555475019 & 0.00101516571636777 & 1.05452368023678 \tabularnewline
46 & 2.24 & 2.23903286643814 & 0.218633843757157 & 0.000967133561857926 & 1.51289389130264 \tabularnewline
47 & 2.94 & 2.93905724351461 & 0.346548984982855 & 0.000942756485394306 & 1.04569499849202 \tabularnewline
48 & 3.09 & 3.08904993496336 & 0.294319571179134 & 0.000950065036642202 & -0.426973238420458 \tabularnewline
49 & 3.46 & 3.46321742823383 & 0.315381996492675 & -0.00321742823383147 & 0.180367079065923 \tabularnewline
50 & 3.64 & 3.64086174585341 & 0.279476808837663 & -0.000861745853407672 & -0.282076803703573 \tabularnewline
51 & 4.39 & 4.39108571751962 & 0.40465218755776 & -0.00108571751961551 & 1.02193085032645 \tabularnewline
52 & 4.15 & 4.15086045070918 & 0.233242722801421 & -0.00086045070917501 & -1.40025567161983 \tabularnewline
53 & 5.21 & 5.21107255667473 & 0.453010561917699 & -0.00107255667472807 & 1.79590027974623 \tabularnewline
54 & 5.8 & 5.80109836079765 & 0.489419394679731 & -0.00109836079764991 & 0.297579700584806 \tabularnewline
55 & 5.91 & 5.91104588468307 & 0.388586234884432 & -0.00104588468306820 & -0.824218253167346 \tabularnewline
56 & 5.39 & 5.39095361576778 & 0.147134300326672 & -0.000953615767782762 & -1.97375093812424 \tabularnewline
57 & 5.46 & 5.4609478641808 & 0.126636763850534 & -0.000947864180795105 & -0.167562034670224 \tabularnewline
58 & 4.72 & 4.72090041484098 & -0.103658824080971 & -0.00090041484098577 & -1.88263533275908 \tabularnewline
59 & 3.14 & 3.14084106305233 & -0.495971386420688 & -0.000841063052330742 & -3.20712861751377 \tabularnewline
60 & 2.63 & 2.63084064894165 & -0.49969923791476 & -0.000840648941646655 & -0.0304750686363817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63060&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]1.59[/C][C]1.59[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]1.26[/C][C]1.27664147880926[/C][C]-0.0266130193168101[/C][C]-0.0166414788092608[/C][C]-0.468949884678013[/C][/ROW]
[ROW][C]3[/C][C]1.13[/C][C]1.14658931093672[/C][C]-0.0426786025786395[/C][C]-0.0165893109367155[/C][C]-0.240877315287619[/C][/ROW]
[ROW][C]4[/C][C]1.92[/C][C]1.93692502223450[/C][C]0.124687571458184[/C][C]-0.016925022234496[/C][C]1.88692291413097[/C][/ROW]
[ROW][C]5[/C][C]2.61[/C][C]2.62710072633706[/C][C]0.254193854788040[/C][C]-0.0171007263370595[/C][C]1.25832718603289[/C][/ROW]
[ROW][C]6[/C][C]2.26[/C][C]2.27695902627387[/C][C]0.105907435734632[/C][C]-0.0169590262738673[/C][C]-1.3305436525685[/C][/ROW]
[ROW][C]7[/C][C]2.41[/C][C]2.42696673419582[/C][C]0.117134248415217[/C][C]-0.016966734195819[/C][C]0.0965066188707478[/C][/ROW]
[ROW][C]8[/C][C]2.26[/C][C]2.27693216297358[/C][C]0.0477619711295369[/C][C]-0.0169321629735759[/C][C]-0.582691676530388[/C][/ROW]
[ROW][C]9[/C][C]2.03[/C][C]2.04690565090215[/C][C]-0.0251393727433627[/C][C]-0.0169056509021519[/C][C]-0.60473942082146[/C][/ROW]
[ROW][C]10[/C][C]2.86[/C][C]2.87696572779066[/C][C]0.200585771877503[/C][C]-0.0169657277906597[/C][C]1.85989902742832[/C][/ROW]
[ROW][C]11[/C][C]2.55[/C][C]2.56693935484482[/C][C]0.0653946804138398[/C][C]-0.0169393548448212[/C][C]-1.10989283844115[/C][/ROW]
[ROW][C]12[/C][C]2.27[/C][C]2.28692624597294[/C][C]-0.0262094864032349[/C][C]-0.0169262459729372[/C][C]-0.750582012439315[/C][/ROW]
[ROW][C]13[/C][C]2.26[/C][C]2.12697237175659[/C][C]-0.0604611290668771[/C][C]0.133027628243410[/C][C]-0.337207095851677[/C][/ROW]
[ROW][C]14[/C][C]2.57[/C][C]2.57083166378842[/C][C]0.0668687993113224[/C][C]-0.000831663788421312[/C][C]0.915813897078617[/C][/ROW]
[ROW][C]15[/C][C]3.07[/C][C]3.07136231291933[/C][C]0.182262255291627[/C][C]-0.0013623129193256[/C][C]0.940473964105364[/C][/ROW]
[ROW][C]16[/C][C]2.76[/C][C]2.76091970240126[/C][C]0.0512710137581165[/C][C]-0.000919702401255461[/C][C]-1.06909787240323[/C][/ROW]
[ROW][C]17[/C][C]2.51[/C][C]2.51072085498038[/C][C]-0.0288460150357446[/C][C]-0.000720854980381655[/C][C]-0.654378010343151[/C][/ROW]
[ROW][C]18[/C][C]2.87[/C][C]2.87090927715949[/C][C]0.0745241277695391[/C][C]-0.00090927715949085[/C][C]0.844648798105718[/C][/ROW]
[ROW][C]19[/C][C]3.14[/C][C]3.14097882258534[/C][C]0.126479413233335[/C][C]-0.000978822585340527[/C][C]0.424625741548868[/C][/ROW]
[ROW][C]20[/C][C]3.11[/C][C]3.11093794648578[/C][C]0.084893123708108[/C][C]-0.000937946485777381[/C][C]-0.339921207557084[/C][/ROW]
[ROW][C]21[/C][C]3.16[/C][C]3.16093125384634[/C][C]0.0756203577080185[/C][C]-0.000931253846337647[/C][C]-0.0757992934482249[/C][/ROW]
[ROW][C]22[/C][C]2.47[/C][C]2.47082342847113[/C][C]-0.127835522174789[/C][C]-0.000823428471132048[/C][C]-1.66318697082964[/C][/ROW]
[ROW][C]23[/C][C]2.57[/C][C]2.57084698879969[/C][C]-0.0672914854001537[/C][C]-0.000846988799694827[/C][C]0.49493740251833[/C][/ROW]
[ROW][C]24[/C][C]2.89[/C][C]2.89087639585848[/C][C]0.0356248234542288[/C][C]-0.000876395858482492[/C][C]0.841332090342454[/C][/ROW]
[ROW][C]25[/C][C]2.63[/C][C]2.66853365759167[/C][C]-0.0318862069520319[/C][C]-0.0385336575916663[/C][C]-0.605076419511567[/C][/ROW]
[ROW][C]26[/C][C]2.38[/C][C]2.38017806480123[/C][C]-0.0978198912733993[/C][C]-0.000178064801229533[/C][C]-0.500868009326136[/C][/ROW]
[ROW][C]27[/C][C]1.69[/C][C]1.68969848223087[/C][C]-0.255486137837755[/C][C]0.000301517769133157[/C][C]-1.28597155724411[/C][/ROW]
[ROW][C]28[/C][C]1.96[/C][C]1.9600108479324[/C][C]-0.115702053423195[/C][C]-1.08479324012053e-05[/C][C]1.14132477664591[/C][/ROW]
[ROW][C]29[/C][C]2.19[/C][C]2.19016170671847[/C][C]-0.0237865087705708[/C][C]-0.000161706718473785[/C][C]0.750909991695025[/C][/ROW]
[ROW][C]30[/C][C]1.87[/C][C]1.87006680349765[/C][C]-0.102523516395460[/C][C]-6.68034976481764e-05[/C][C]-0.643444668015577[/C][/ROW]
[ROW][C]31[/C][C]1.6[/C][C]1.60002740683248[/C][C]-0.147034481757993[/C][C]-2.74068324820226e-05[/C][C]-0.363807147339418[/C][/ROW]
[ROW][C]32[/C][C]1.63[/C][C]1.63005798453742[/C][C]-0.0999868016240103[/C][C]-5.7984537419313e-05[/C][C]0.384575132893068[/C][/ROW]
[ROW][C]33[/C][C]1.22[/C][C]1.22001866802329[/C][C]-0.182370793751421[/C][C]-1.86680232879242e-05[/C][C]-0.673452115812668[/C][/ROW]
[ROW][C]34[/C][C]1.21[/C][C]1.2100347193065[/C][C]-0.136565382413136[/C][C]-3.47193064986828e-05[/C][C]0.374448371751139[/C][/ROW]
[ROW][C]35[/C][C]1.49[/C][C]1.49006320208605[/C][C]-0.0258695840351746[/C][C]-6.32020860464097e-05[/C][C]0.904924553515611[/C][/ROW]
[ROW][C]36[/C][C]1.64[/C][C]1.64007203174743[/C][C]0.0208647354352649[/C][C]-7.20317474337113e-05[/C][C]0.382050202633907[/C][/ROW]
[ROW][C]37[/C][C]1.66[/C][C]1.65939566259889[/C][C]0.0204592618845721[/C][C]0.000604337401109234[/C][C]-0.00352566004978326[/C][/ROW]
[ROW][C]38[/C][C]1.77[/C][C]1.76911046655366[/C][C]0.0436077395985069[/C][C]0.000889533446344546[/C][C]0.179722773294015[/C][/ROW]
[ROW][C]39[/C][C]1.82[/C][C]1.81911429879570[/C][C]0.0453088050520883[/C][C]0.00088570120430393[/C][C]0.0138826226222192[/C][/ROW]
[ROW][C]40[/C][C]1.78[/C][C]1.77907674501953[/C][C]0.0226220372923013[/C][C]0.000923254980471246[/C][C]-0.185294770867888[/C][/ROW]
[ROW][C]41[/C][C]1.28[/C][C]1.27890784215043[/C][C]-0.116312834470783[/C][C]0.00109215784956788[/C][C]-1.13523332962454[/C][/ROW]
[ROW][C]42[/C][C]1.29[/C][C]1.2889378142139[/C][C]-0.0827400520468216[/C][C]0.00106218578610103[/C][C]0.274384797902431[/C][/ROW]
[ROW][C]43[/C][C]1.37[/C][C]1.36896616726506[/C][C]-0.0394897462397275[/C][C]0.00103383273494092[/C][C]0.353520971912539[/C][/ROW]
[ROW][C]44[/C][C]1.12[/C][C]1.11893923805590[/C][C]-0.0954324765261785[/C][C]0.00106076194410383[/C][C]-0.457297039205401[/C][/ROW]
[ROW][C]45[/C][C]1.51[/C][C]1.50898483428363[/C][C]0.0335664555475019[/C][C]0.00101516571636777[/C][C]1.05452368023678[/C][/ROW]
[ROW][C]46[/C][C]2.24[/C][C]2.23903286643814[/C][C]0.218633843757157[/C][C]0.000967133561857926[/C][C]1.51289389130264[/C][/ROW]
[ROW][C]47[/C][C]2.94[/C][C]2.93905724351461[/C][C]0.346548984982855[/C][C]0.000942756485394306[/C][C]1.04569499849202[/C][/ROW]
[ROW][C]48[/C][C]3.09[/C][C]3.08904993496336[/C][C]0.294319571179134[/C][C]0.000950065036642202[/C][C]-0.426973238420458[/C][/ROW]
[ROW][C]49[/C][C]3.46[/C][C]3.46321742823383[/C][C]0.315381996492675[/C][C]-0.00321742823383147[/C][C]0.180367079065923[/C][/ROW]
[ROW][C]50[/C][C]3.64[/C][C]3.64086174585341[/C][C]0.279476808837663[/C][C]-0.000861745853407672[/C][C]-0.282076803703573[/C][/ROW]
[ROW][C]51[/C][C]4.39[/C][C]4.39108571751962[/C][C]0.40465218755776[/C][C]-0.00108571751961551[/C][C]1.02193085032645[/C][/ROW]
[ROW][C]52[/C][C]4.15[/C][C]4.15086045070918[/C][C]0.233242722801421[/C][C]-0.00086045070917501[/C][C]-1.40025567161983[/C][/ROW]
[ROW][C]53[/C][C]5.21[/C][C]5.21107255667473[/C][C]0.453010561917699[/C][C]-0.00107255667472807[/C][C]1.79590027974623[/C][/ROW]
[ROW][C]54[/C][C]5.8[/C][C]5.80109836079765[/C][C]0.489419394679731[/C][C]-0.00109836079764991[/C][C]0.297579700584806[/C][/ROW]
[ROW][C]55[/C][C]5.91[/C][C]5.91104588468307[/C][C]0.388586234884432[/C][C]-0.00104588468306820[/C][C]-0.824218253167346[/C][/ROW]
[ROW][C]56[/C][C]5.39[/C][C]5.39095361576778[/C][C]0.147134300326672[/C][C]-0.000953615767782762[/C][C]-1.97375093812424[/C][/ROW]
[ROW][C]57[/C][C]5.46[/C][C]5.4609478641808[/C][C]0.126636763850534[/C][C]-0.000947864180795105[/C][C]-0.167562034670224[/C][/ROW]
[ROW][C]58[/C][C]4.72[/C][C]4.72090041484098[/C][C]-0.103658824080971[/C][C]-0.00090041484098577[/C][C]-1.88263533275908[/C][/ROW]
[ROW][C]59[/C][C]3.14[/C][C]3.14084106305233[/C][C]-0.495971386420688[/C][C]-0.000841063052330742[/C][C]-3.20712861751377[/C][/ROW]
[ROW][C]60[/C][C]2.63[/C][C]2.63084064894165[/C][C]-0.49969923791476[/C][C]-0.000840648941646655[/C][C]-0.0304750686363817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63060&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63060&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
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	1.59	1.59	0	0	0
2	1.26	1.27664147880926	-0.0266130193168101	-0.0166414788092608	-0.468949884678013
3	1.13	1.14658931093672	-0.0426786025786395	-0.0165893109367155	-0.240877315287619
4	1.92	1.93692502223450	0.124687571458184	-0.016925022234496	1.88692291413097
5	2.61	2.62710072633706	0.254193854788040	-0.0171007263370595	1.25832718603289
6	2.26	2.27695902627387	0.105907435734632	-0.0169590262738673	-1.3305436525685
7	2.41	2.42696673419582	0.117134248415217	-0.016966734195819	0.0965066188707478
8	2.26	2.27693216297358	0.0477619711295369	-0.0169321629735759	-0.582691676530388
9	2.03	2.04690565090215	-0.0251393727433627	-0.0169056509021519	-0.60473942082146
10	2.86	2.87696572779066	0.200585771877503	-0.0169657277906597	1.85989902742832
11	2.55	2.56693935484482	0.0653946804138398	-0.0169393548448212	-1.10989283844115
12	2.27	2.28692624597294	-0.0262094864032349	-0.0169262459729372	-0.750582012439315
13	2.26	2.12697237175659	-0.0604611290668771	0.133027628243410	-0.337207095851677
14	2.57	2.57083166378842	0.0668687993113224	-0.000831663788421312	0.915813897078617
15	3.07	3.07136231291933	0.182262255291627	-0.0013623129193256	0.940473964105364
16	2.76	2.76091970240126	0.0512710137581165	-0.000919702401255461	-1.06909787240323
17	2.51	2.51072085498038	-0.0288460150357446	-0.000720854980381655	-0.654378010343151
18	2.87	2.87090927715949	0.0745241277695391	-0.00090927715949085	0.844648798105718
19	3.14	3.14097882258534	0.126479413233335	-0.000978822585340527	0.424625741548868
20	3.11	3.11093794648578	0.084893123708108	-0.000937946485777381	-0.339921207557084
21	3.16	3.16093125384634	0.0756203577080185	-0.000931253846337647	-0.0757992934482249
22	2.47	2.47082342847113	-0.127835522174789	-0.000823428471132048	-1.66318697082964
23	2.57	2.57084698879969	-0.0672914854001537	-0.000846988799694827	0.49493740251833
24	2.89	2.89087639585848	0.0356248234542288	-0.000876395858482492	0.841332090342454
25	2.63	2.66853365759167	-0.0318862069520319	-0.0385336575916663	-0.605076419511567
26	2.38	2.38017806480123	-0.0978198912733993	-0.000178064801229533	-0.500868009326136
27	1.69	1.68969848223087	-0.255486137837755	0.000301517769133157	-1.28597155724411
28	1.96	1.9600108479324	-0.115702053423195	-1.08479324012053e-05	1.14132477664591
29	2.19	2.19016170671847	-0.0237865087705708	-0.000161706718473785	0.750909991695025
30	1.87	1.87006680349765	-0.102523516395460	-6.68034976481764e-05	-0.643444668015577
31	1.6	1.60002740683248	-0.147034481757993	-2.74068324820226e-05	-0.363807147339418
32	1.63	1.63005798453742	-0.0999868016240103	-5.7984537419313e-05	0.384575132893068
33	1.22	1.22001866802329	-0.182370793751421	-1.86680232879242e-05	-0.673452115812668
34	1.21	1.2100347193065	-0.136565382413136	-3.47193064986828e-05	0.374448371751139
35	1.49	1.49006320208605	-0.0258695840351746	-6.32020860464097e-05	0.904924553515611
36	1.64	1.64007203174743	0.0208647354352649	-7.20317474337113e-05	0.382050202633907
37	1.66	1.65939566259889	0.0204592618845721	0.000604337401109234	-0.00352566004978326
38	1.77	1.76911046655366	0.0436077395985069	0.000889533446344546	0.179722773294015
39	1.82	1.81911429879570	0.0453088050520883	0.00088570120430393	0.0138826226222192
40	1.78	1.77907674501953	0.0226220372923013	0.000923254980471246	-0.185294770867888
41	1.28	1.27890784215043	-0.116312834470783	0.00109215784956788	-1.13523332962454
42	1.29	1.2889378142139	-0.0827400520468216	0.00106218578610103	0.274384797902431
43	1.37	1.36896616726506	-0.0394897462397275	0.00103383273494092	0.353520971912539
44	1.12	1.11893923805590	-0.0954324765261785	0.00106076194410383	-0.457297039205401
45	1.51	1.50898483428363	0.0335664555475019	0.00101516571636777	1.05452368023678
46	2.24	2.23903286643814	0.218633843757157	0.000967133561857926	1.51289389130264
47	2.94	2.93905724351461	0.346548984982855	0.000942756485394306	1.04569499849202
48	3.09	3.08904993496336	0.294319571179134	0.000950065036642202	-0.426973238420458
49	3.46	3.46321742823383	0.315381996492675	-0.00321742823383147	0.180367079065923
50	3.64	3.64086174585341	0.279476808837663	-0.000861745853407672	-0.282076803703573
51	4.39	4.39108571751962	0.40465218755776	-0.00108571751961551	1.02193085032645
52	4.15	4.15086045070918	0.233242722801421	-0.00086045070917501	-1.40025567161983
53	5.21	5.21107255667473	0.453010561917699	-0.00107255667472807	1.79590027974623
54	5.8	5.80109836079765	0.489419394679731	-0.00109836079764991	0.297579700584806
55	5.91	5.91104588468307	0.388586234884432	-0.00104588468306820	-0.824218253167346
56	5.39	5.39095361576778	0.147134300326672	-0.000953615767782762	-1.97375093812424
57	5.46	5.4609478641808	0.126636763850534	-0.000947864180795105	-0.167562034670224
58	4.72	4.72090041484098	-0.103658824080971	-0.00090041484098577	-1.88263533275908
59	3.14	3.14084106305233	-0.495971386420688	-0.000841063052330742	-3.20712861751377
60	2.63	2.63084064894165	-0.49969923791476	-0.000840648941646655	-0.0304750686363817

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code