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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Fri, 04 Dec 2009 12:58:05 -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/04/t1259956780699ffzkhgdtf705.htm/, Retrieved Sat, 27 Apr 2024 21:11:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64114, Retrieved Sat, 27 Apr 2024 21:11:14 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

ws9.10

Estimated Impact

119

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]
-         [Structural Time Series Models] [WS 9] [2009-12-03 15:13:13] [3e19a07d230ba260a720e0e03e0f40f2]
-   PD        [Structural Time Series Models] [ws9] [2009-12-04 19:58:05] [682632737e024f9e62885141c5f654cd] [Current]

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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=64114&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=64114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64114&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	126.51	126.51	0	0	0
2	131.02	130.917202557603	3.92246239849399	0.102797442396775	0.913847618431535
3	136.51	136.475050774094	5.4211963270669	0.0349492259064152	0.323228539519454
4	138.04	138.173301361872	2.03974118144753	-0.133301361871803	-0.735301004209409
5	132.92	133.129974122407	-4.40470661680805	-0.209974122406907	-1.40484469512538
6	129.61	129.480225546292	-3.71771194000801	0.129774453707634	0.149751215420113
7	122.96	123.045183923431	-6.19027272624965	-0.0851839234314419	-0.538970318236795
8	124.04	123.716827700687	0.0535258646267449	0.323172299312794	1.36102692742256
9	121.29	121.422930675273	-2.08245193375971	-0.132930675272830	-0.465601717116753
10	124.56	124.314127141518	2.44319451030242	0.245872858481893	0.986503116255774
11	118.53	118.859869616276	-4.74289199990166	-0.329869616275619	-1.56642743172016
12	113.14	113.072065188506	-5.69368359272046	0.067934811494016	-0.207254119571685
13	114.15	113.820056964336	0.137293918295319	0.329943035663569	1.30617668807452
14	122.17	121.948627069742	6.93900046753001	0.221372930258375	1.47143578272947
15	129.23	129.251133683834	7.26134583979489	-0.0211336838336444	0.0702956150792457
16	131.19	131.227140268583	2.59179533094804	-0.0371402685830076	-1.01410308589435
17	129.12	129.610135228349	-1.13022730994044	-0.490135228349003	-0.81138113179795
18	128.28	127.762037961368	-1.76540834426589	0.517962038632025	-0.138455307850871
19	126.83	127.221648312564	-0.681581329417607	-0.391648312564396	0.236253344661319
20	138.13	136.891532690192	8.47639142970118	1.23846730980816	1.99626004787833
21	140.52	141.496125790248	5.05100180883885	-0.976125790247784	-0.74666856805515
22	146.83	146.18202903809	4.72798641198333	0.647970961910118	-0.0704111087827684
23	135.14	136.055343646103	-8.4155049146763	-0.91534364610312	-2.86507463687213
24	131.84	131.499688352674	-5.00325927790722	0.340311647326001	0.744031465440659
25	125.7	126.360997728313	-5.12301346878176	-0.660997728313063	-0.0264407527440768
26	128.98	128.620932867865	1.19443231899773	0.359067132134668	1.36993223458147
27	133.25	132.851918209884	3.84495003071638	0.398081790116353	0.579569553661896
28	136.76	136.547502748048	3.71454245588471	0.212497251952143	-0.0283266193563843
29	133.24	133.965409953674	-1.78161478605764	-0.725409953673718	-1.19793769414372
30	128.54	127.911717517843	-5.51375707469794	0.62828248215724	-0.813530457709215
31	121.08	122.310659902517	-5.59002397324516	-1.23065990251707	-0.0166246282184823
32	120.23	118.583910619587	-3.96237669087060	1.64608938041287	0.354795577877309
33	119.08	120.204131792144	0.914229817306783	-1.12413179214442	1.06300566305370
34	125.75	123.634521300853	3.11237491401478	2.11547869914734	0.479156498736774
35	126.89	128.025524319659	4.22934775702417	-1.13552431965949	0.243479856030229
36	126.6	126.398505058157	-0.880357027193927	0.201494941842746	-1.11480800848040
37	121.89	123.409157055347	-2.72377114043586	-1.51915705534704	-0.404211138730694
38	123.44	123.244178250926	-0.529131087357738	0.195821749073722	0.476768191036138
39	126.46	126.085898453526	2.39064071431006	0.374101546474418	0.638570867909091
40	129.49	128.850332823347	2.71512017631326	0.639667176652758	0.0705390064677417
41	127.78	128.341115013476	-0.0810618756463612	-0.561115013476304	-0.609307726939597
42	125.29	124.751529462	-3.12645944513900	0.538470538000142	-0.663852200903137
43	119.02	120.215944328442	-4.34972998793681	-1.19594432844207	-0.266645656308553
44	119.96	118.472109226178	-2.08770905950752	1.48789077382238	0.493076694308836
45	122.86	123.708481274012	4.26988405475962	-0.848481274012393	1.38583280540139
46	131.89	130.04782269332	6.06638992233837	1.84217730667989	0.391610356978546
47	132.73	133.583967899546	3.8703892911244	-0.853967899546154	-0.478679383073456
48	135.01	134.687628993331	1.47156315686195	0.322371006669465	-0.523544218885862
49	136.71	138.225458287533	3.2660477324634	-1.51545828753304	0.392236526720319
50	142.73	142.802739606604	4.39140544766192	-0.0727396066035983	0.244751629264758
51	144.43	144.456256767502	2.02957335327447	-0.0262567675020932	-0.516298599702921
52	144.93	144.297405085110	0.136365799289824	0.632594914889814	-0.411906978939660
53	138.75	139.335339537302	-4.26872744002087	-0.585339537301886	-0.959709989279856
54	130.22	129.675203425735	-8.93054893681514	0.544796574264559	-1.01622860367565
55	122.19	123.117440954077	-6.87835319583681	-0.927440954076765	0.447330940491508
56	128.4	126.847246573552	2.29615983216228	1.55275342644837	1.99986096975472
57	140.43	140.854425058853	12.4245091137639	-0.424425058853141	2.20779437417532
58	153.5	151.659603295881	11.0239852637545	1.84039670411948	-0.305292617967822
59	149.33	150.660597521916	0.629629190843078	-1.33059752191579	-2.26577833702963
60	142.97	143.360339514032	-6.22189287681627	-0.390339514032104	-1.49545917193968

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 126.51 & 126.51 & 0 & 0 & 0 \tabularnewline
2 & 131.02 & 130.917202557603 & 3.92246239849399 & 0.102797442396775 & 0.913847618431535 \tabularnewline
3 & 136.51 & 136.475050774094 & 5.4211963270669 & 0.0349492259064152 & 0.323228539519454 \tabularnewline
4 & 138.04 & 138.173301361872 & 2.03974118144753 & -0.133301361871803 & -0.735301004209409 \tabularnewline
5 & 132.92 & 133.129974122407 & -4.40470661680805 & -0.209974122406907 & -1.40484469512538 \tabularnewline
6 & 129.61 & 129.480225546292 & -3.71771194000801 & 0.129774453707634 & 0.149751215420113 \tabularnewline
7 & 122.96 & 123.045183923431 & -6.19027272624965 & -0.0851839234314419 & -0.538970318236795 \tabularnewline
8 & 124.04 & 123.716827700687 & 0.0535258646267449 & 0.323172299312794 & 1.36102692742256 \tabularnewline
9 & 121.29 & 121.422930675273 & -2.08245193375971 & -0.132930675272830 & -0.465601717116753 \tabularnewline
10 & 124.56 & 124.314127141518 & 2.44319451030242 & 0.245872858481893 & 0.986503116255774 \tabularnewline
11 & 118.53 & 118.859869616276 & -4.74289199990166 & -0.329869616275619 & -1.56642743172016 \tabularnewline
12 & 113.14 & 113.072065188506 & -5.69368359272046 & 0.067934811494016 & -0.207254119571685 \tabularnewline
13 & 114.15 & 113.820056964336 & 0.137293918295319 & 0.329943035663569 & 1.30617668807452 \tabularnewline
14 & 122.17 & 121.948627069742 & 6.93900046753001 & 0.221372930258375 & 1.47143578272947 \tabularnewline
15 & 129.23 & 129.251133683834 & 7.26134583979489 & -0.0211336838336444 & 0.0702956150792457 \tabularnewline
16 & 131.19 & 131.227140268583 & 2.59179533094804 & -0.0371402685830076 & -1.01410308589435 \tabularnewline
17 & 129.12 & 129.610135228349 & -1.13022730994044 & -0.490135228349003 & -0.81138113179795 \tabularnewline
18 & 128.28 & 127.762037961368 & -1.76540834426589 & 0.517962038632025 & -0.138455307850871 \tabularnewline
19 & 126.83 & 127.221648312564 & -0.681581329417607 & -0.391648312564396 & 0.236253344661319 \tabularnewline
20 & 138.13 & 136.891532690192 & 8.47639142970118 & 1.23846730980816 & 1.99626004787833 \tabularnewline
21 & 140.52 & 141.496125790248 & 5.05100180883885 & -0.976125790247784 & -0.74666856805515 \tabularnewline
22 & 146.83 & 146.18202903809 & 4.72798641198333 & 0.647970961910118 & -0.0704111087827684 \tabularnewline
23 & 135.14 & 136.055343646103 & -8.4155049146763 & -0.91534364610312 & -2.86507463687213 \tabularnewline
24 & 131.84 & 131.499688352674 & -5.00325927790722 & 0.340311647326001 & 0.744031465440659 \tabularnewline
25 & 125.7 & 126.360997728313 & -5.12301346878176 & -0.660997728313063 & -0.0264407527440768 \tabularnewline
26 & 128.98 & 128.620932867865 & 1.19443231899773 & 0.359067132134668 & 1.36993223458147 \tabularnewline
27 & 133.25 & 132.851918209884 & 3.84495003071638 & 0.398081790116353 & 0.579569553661896 \tabularnewline
28 & 136.76 & 136.547502748048 & 3.71454245588471 & 0.212497251952143 & -0.0283266193563843 \tabularnewline
29 & 133.24 & 133.965409953674 & -1.78161478605764 & -0.725409953673718 & -1.19793769414372 \tabularnewline
30 & 128.54 & 127.911717517843 & -5.51375707469794 & 0.62828248215724 & -0.813530457709215 \tabularnewline
31 & 121.08 & 122.310659902517 & -5.59002397324516 & -1.23065990251707 & -0.0166246282184823 \tabularnewline
32 & 120.23 & 118.583910619587 & -3.96237669087060 & 1.64608938041287 & 0.354795577877309 \tabularnewline
33 & 119.08 & 120.204131792144 & 0.914229817306783 & -1.12413179214442 & 1.06300566305370 \tabularnewline
34 & 125.75 & 123.634521300853 & 3.11237491401478 & 2.11547869914734 & 0.479156498736774 \tabularnewline
35 & 126.89 & 128.025524319659 & 4.22934775702417 & -1.13552431965949 & 0.243479856030229 \tabularnewline
36 & 126.6 & 126.398505058157 & -0.880357027193927 & 0.201494941842746 & -1.11480800848040 \tabularnewline
37 & 121.89 & 123.409157055347 & -2.72377114043586 & -1.51915705534704 & -0.404211138730694 \tabularnewline
38 & 123.44 & 123.244178250926 & -0.529131087357738 & 0.195821749073722 & 0.476768191036138 \tabularnewline
39 & 126.46 & 126.085898453526 & 2.39064071431006 & 0.374101546474418 & 0.638570867909091 \tabularnewline
40 & 129.49 & 128.850332823347 & 2.71512017631326 & 0.639667176652758 & 0.0705390064677417 \tabularnewline
41 & 127.78 & 128.341115013476 & -0.0810618756463612 & -0.561115013476304 & -0.609307726939597 \tabularnewline
42 & 125.29 & 124.751529462 & -3.12645944513900 & 0.538470538000142 & -0.663852200903137 \tabularnewline
43 & 119.02 & 120.215944328442 & -4.34972998793681 & -1.19594432844207 & -0.266645656308553 \tabularnewline
44 & 119.96 & 118.472109226178 & -2.08770905950752 & 1.48789077382238 & 0.493076694308836 \tabularnewline
45 & 122.86 & 123.708481274012 & 4.26988405475962 & -0.848481274012393 & 1.38583280540139 \tabularnewline
46 & 131.89 & 130.04782269332 & 6.06638992233837 & 1.84217730667989 & 0.391610356978546 \tabularnewline
47 & 132.73 & 133.583967899546 & 3.8703892911244 & -0.853967899546154 & -0.478679383073456 \tabularnewline
48 & 135.01 & 134.687628993331 & 1.47156315686195 & 0.322371006669465 & -0.523544218885862 \tabularnewline
49 & 136.71 & 138.225458287533 & 3.2660477324634 & -1.51545828753304 & 0.392236526720319 \tabularnewline
50 & 142.73 & 142.802739606604 & 4.39140544766192 & -0.0727396066035983 & 0.244751629264758 \tabularnewline
51 & 144.43 & 144.456256767502 & 2.02957335327447 & -0.0262567675020932 & -0.516298599702921 \tabularnewline
52 & 144.93 & 144.297405085110 & 0.136365799289824 & 0.632594914889814 & -0.411906978939660 \tabularnewline
53 & 138.75 & 139.335339537302 & -4.26872744002087 & -0.585339537301886 & -0.959709989279856 \tabularnewline
54 & 130.22 & 129.675203425735 & -8.93054893681514 & 0.544796574264559 & -1.01622860367565 \tabularnewline
55 & 122.19 & 123.117440954077 & -6.87835319583681 & -0.927440954076765 & 0.447330940491508 \tabularnewline
56 & 128.4 & 126.847246573552 & 2.29615983216228 & 1.55275342644837 & 1.99986096975472 \tabularnewline
57 & 140.43 & 140.854425058853 & 12.4245091137639 & -0.424425058853141 & 2.20779437417532 \tabularnewline
58 & 153.5 & 151.659603295881 & 11.0239852637545 & 1.84039670411948 & -0.305292617967822 \tabularnewline
59 & 149.33 & 150.660597521916 & 0.629629190843078 & -1.33059752191579 & -2.26577833702963 \tabularnewline
60 & 142.97 & 143.360339514032 & -6.22189287681627 & -0.390339514032104 & -1.49545917193968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64114&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]126.51[/C][C]126.51[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]131.02[/C][C]130.917202557603[/C][C]3.92246239849399[/C][C]0.102797442396775[/C][C]0.913847618431535[/C][/ROW]
[ROW][C]3[/C][C]136.51[/C][C]136.475050774094[/C][C]5.4211963270669[/C][C]0.0349492259064152[/C][C]0.323228539519454[/C][/ROW]
[ROW][C]4[/C][C]138.04[/C][C]138.173301361872[/C][C]2.03974118144753[/C][C]-0.133301361871803[/C][C]-0.735301004209409[/C][/ROW]
[ROW][C]5[/C][C]132.92[/C][C]133.129974122407[/C][C]-4.40470661680805[/C][C]-0.209974122406907[/C][C]-1.40484469512538[/C][/ROW]
[ROW][C]6[/C][C]129.61[/C][C]129.480225546292[/C][C]-3.71771194000801[/C][C]0.129774453707634[/C][C]0.149751215420113[/C][/ROW]
[ROW][C]7[/C][C]122.96[/C][C]123.045183923431[/C][C]-6.19027272624965[/C][C]-0.0851839234314419[/C][C]-0.538970318236795[/C][/ROW]
[ROW][C]8[/C][C]124.04[/C][C]123.716827700687[/C][C]0.0535258646267449[/C][C]0.323172299312794[/C][C]1.36102692742256[/C][/ROW]
[ROW][C]9[/C][C]121.29[/C][C]121.422930675273[/C][C]-2.08245193375971[/C][C]-0.132930675272830[/C][C]-0.465601717116753[/C][/ROW]
[ROW][C]10[/C][C]124.56[/C][C]124.314127141518[/C][C]2.44319451030242[/C][C]0.245872858481893[/C][C]0.986503116255774[/C][/ROW]
[ROW][C]11[/C][C]118.53[/C][C]118.859869616276[/C][C]-4.74289199990166[/C][C]-0.329869616275619[/C][C]-1.56642743172016[/C][/ROW]
[ROW][C]12[/C][C]113.14[/C][C]113.072065188506[/C][C]-5.69368359272046[/C][C]0.067934811494016[/C][C]-0.207254119571685[/C][/ROW]
[ROW][C]13[/C][C]114.15[/C][C]113.820056964336[/C][C]0.137293918295319[/C][C]0.329943035663569[/C][C]1.30617668807452[/C][/ROW]
[ROW][C]14[/C][C]122.17[/C][C]121.948627069742[/C][C]6.93900046753001[/C][C]0.221372930258375[/C][C]1.47143578272947[/C][/ROW]
[ROW][C]15[/C][C]129.23[/C][C]129.251133683834[/C][C]7.26134583979489[/C][C]-0.0211336838336444[/C][C]0.0702956150792457[/C][/ROW]
[ROW][C]16[/C][C]131.19[/C][C]131.227140268583[/C][C]2.59179533094804[/C][C]-0.0371402685830076[/C][C]-1.01410308589435[/C][/ROW]
[ROW][C]17[/C][C]129.12[/C][C]129.610135228349[/C][C]-1.13022730994044[/C][C]-0.490135228349003[/C][C]-0.81138113179795[/C][/ROW]
[ROW][C]18[/C][C]128.28[/C][C]127.762037961368[/C][C]-1.76540834426589[/C][C]0.517962038632025[/C][C]-0.138455307850871[/C][/ROW]
[ROW][C]19[/C][C]126.83[/C][C]127.221648312564[/C][C]-0.681581329417607[/C][C]-0.391648312564396[/C][C]0.236253344661319[/C][/ROW]
[ROW][C]20[/C][C]138.13[/C][C]136.891532690192[/C][C]8.47639142970118[/C][C]1.23846730980816[/C][C]1.99626004787833[/C][/ROW]
[ROW][C]21[/C][C]140.52[/C][C]141.496125790248[/C][C]5.05100180883885[/C][C]-0.976125790247784[/C][C]-0.74666856805515[/C][/ROW]
[ROW][C]22[/C][C]146.83[/C][C]146.18202903809[/C][C]4.72798641198333[/C][C]0.647970961910118[/C][C]-0.0704111087827684[/C][/ROW]
[ROW][C]23[/C][C]135.14[/C][C]136.055343646103[/C][C]-8.4155049146763[/C][C]-0.91534364610312[/C][C]-2.86507463687213[/C][/ROW]
[ROW][C]24[/C][C]131.84[/C][C]131.499688352674[/C][C]-5.00325927790722[/C][C]0.340311647326001[/C][C]0.744031465440659[/C][/ROW]
[ROW][C]25[/C][C]125.7[/C][C]126.360997728313[/C][C]-5.12301346878176[/C][C]-0.660997728313063[/C][C]-0.0264407527440768[/C][/ROW]
[ROW][C]26[/C][C]128.98[/C][C]128.620932867865[/C][C]1.19443231899773[/C][C]0.359067132134668[/C][C]1.36993223458147[/C][/ROW]
[ROW][C]27[/C][C]133.25[/C][C]132.851918209884[/C][C]3.84495003071638[/C][C]0.398081790116353[/C][C]0.579569553661896[/C][/ROW]
[ROW][C]28[/C][C]136.76[/C][C]136.547502748048[/C][C]3.71454245588471[/C][C]0.212497251952143[/C][C]-0.0283266193563843[/C][/ROW]
[ROW][C]29[/C][C]133.24[/C][C]133.965409953674[/C][C]-1.78161478605764[/C][C]-0.725409953673718[/C][C]-1.19793769414372[/C][/ROW]
[ROW][C]30[/C][C]128.54[/C][C]127.911717517843[/C][C]-5.51375707469794[/C][C]0.62828248215724[/C][C]-0.813530457709215[/C][/ROW]
[ROW][C]31[/C][C]121.08[/C][C]122.310659902517[/C][C]-5.59002397324516[/C][C]-1.23065990251707[/C][C]-0.0166246282184823[/C][/ROW]
[ROW][C]32[/C][C]120.23[/C][C]118.583910619587[/C][C]-3.96237669087060[/C][C]1.64608938041287[/C][C]0.354795577877309[/C][/ROW]
[ROW][C]33[/C][C]119.08[/C][C]120.204131792144[/C][C]0.914229817306783[/C][C]-1.12413179214442[/C][C]1.06300566305370[/C][/ROW]
[ROW][C]34[/C][C]125.75[/C][C]123.634521300853[/C][C]3.11237491401478[/C][C]2.11547869914734[/C][C]0.479156498736774[/C][/ROW]
[ROW][C]35[/C][C]126.89[/C][C]128.025524319659[/C][C]4.22934775702417[/C][C]-1.13552431965949[/C][C]0.243479856030229[/C][/ROW]
[ROW][C]36[/C][C]126.6[/C][C]126.398505058157[/C][C]-0.880357027193927[/C][C]0.201494941842746[/C][C]-1.11480800848040[/C][/ROW]
[ROW][C]37[/C][C]121.89[/C][C]123.409157055347[/C][C]-2.72377114043586[/C][C]-1.51915705534704[/C][C]-0.404211138730694[/C][/ROW]
[ROW][C]38[/C][C]123.44[/C][C]123.244178250926[/C][C]-0.529131087357738[/C][C]0.195821749073722[/C][C]0.476768191036138[/C][/ROW]
[ROW][C]39[/C][C]126.46[/C][C]126.085898453526[/C][C]2.39064071431006[/C][C]0.374101546474418[/C][C]0.638570867909091[/C][/ROW]
[ROW][C]40[/C][C]129.49[/C][C]128.850332823347[/C][C]2.71512017631326[/C][C]0.639667176652758[/C][C]0.0705390064677417[/C][/ROW]
[ROW][C]41[/C][C]127.78[/C][C]128.341115013476[/C][C]-0.0810618756463612[/C][C]-0.561115013476304[/C][C]-0.609307726939597[/C][/ROW]
[ROW][C]42[/C][C]125.29[/C][C]124.751529462[/C][C]-3.12645944513900[/C][C]0.538470538000142[/C][C]-0.663852200903137[/C][/ROW]
[ROW][C]43[/C][C]119.02[/C][C]120.215944328442[/C][C]-4.34972998793681[/C][C]-1.19594432844207[/C][C]-0.266645656308553[/C][/ROW]
[ROW][C]44[/C][C]119.96[/C][C]118.472109226178[/C][C]-2.08770905950752[/C][C]1.48789077382238[/C][C]0.493076694308836[/C][/ROW]
[ROW][C]45[/C][C]122.86[/C][C]123.708481274012[/C][C]4.26988405475962[/C][C]-0.848481274012393[/C][C]1.38583280540139[/C][/ROW]
[ROW][C]46[/C][C]131.89[/C][C]130.04782269332[/C][C]6.06638992233837[/C][C]1.84217730667989[/C][C]0.391610356978546[/C][/ROW]
[ROW][C]47[/C][C]132.73[/C][C]133.583967899546[/C][C]3.8703892911244[/C][C]-0.853967899546154[/C][C]-0.478679383073456[/C][/ROW]
[ROW][C]48[/C][C]135.01[/C][C]134.687628993331[/C][C]1.47156315686195[/C][C]0.322371006669465[/C][C]-0.523544218885862[/C][/ROW]
[ROW][C]49[/C][C]136.71[/C][C]138.225458287533[/C][C]3.2660477324634[/C][C]-1.51545828753304[/C][C]0.392236526720319[/C][/ROW]
[ROW][C]50[/C][C]142.73[/C][C]142.802739606604[/C][C]4.39140544766192[/C][C]-0.0727396066035983[/C][C]0.244751629264758[/C][/ROW]
[ROW][C]51[/C][C]144.43[/C][C]144.456256767502[/C][C]2.02957335327447[/C][C]-0.0262567675020932[/C][C]-0.516298599702921[/C][/ROW]
[ROW][C]52[/C][C]144.93[/C][C]144.297405085110[/C][C]0.136365799289824[/C][C]0.632594914889814[/C][C]-0.411906978939660[/C][/ROW]
[ROW][C]53[/C][C]138.75[/C][C]139.335339537302[/C][C]-4.26872744002087[/C][C]-0.585339537301886[/C][C]-0.959709989279856[/C][/ROW]
[ROW][C]54[/C][C]130.22[/C][C]129.675203425735[/C][C]-8.93054893681514[/C][C]0.544796574264559[/C][C]-1.01622860367565[/C][/ROW]
[ROW][C]55[/C][C]122.19[/C][C]123.117440954077[/C][C]-6.87835319583681[/C][C]-0.927440954076765[/C][C]0.447330940491508[/C][/ROW]
[ROW][C]56[/C][C]128.4[/C][C]126.847246573552[/C][C]2.29615983216228[/C][C]1.55275342644837[/C][C]1.99986096975472[/C][/ROW]
[ROW][C]57[/C][C]140.43[/C][C]140.854425058853[/C][C]12.4245091137639[/C][C]-0.424425058853141[/C][C]2.20779437417532[/C][/ROW]
[ROW][C]58[/C][C]153.5[/C][C]151.659603295881[/C][C]11.0239852637545[/C][C]1.84039670411948[/C][C]-0.305292617967822[/C][/ROW]
[ROW][C]59[/C][C]149.33[/C][C]150.660597521916[/C][C]0.629629190843078[/C][C]-1.33059752191579[/C][C]-2.26577833702963[/C][/ROW]
[ROW][C]60[/C][C]142.97[/C][C]143.360339514032[/C][C]-6.22189287681627[/C][C]-0.390339514032104[/C][C]-1.49545917193968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64114&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	126.51	126.51	0	0	0
2	131.02	130.917202557603	3.92246239849399	0.102797442396775	0.913847618431535
3	136.51	136.475050774094	5.4211963270669	0.0349492259064152	0.323228539519454
4	138.04	138.173301361872	2.03974118144753	-0.133301361871803	-0.735301004209409
5	132.92	133.129974122407	-4.40470661680805	-0.209974122406907	-1.40484469512538
6	129.61	129.480225546292	-3.71771194000801	0.129774453707634	0.149751215420113
7	122.96	123.045183923431	-6.19027272624965	-0.0851839234314419	-0.538970318236795
8	124.04	123.716827700687	0.0535258646267449	0.323172299312794	1.36102692742256
9	121.29	121.422930675273	-2.08245193375971	-0.132930675272830	-0.465601717116753
10	124.56	124.314127141518	2.44319451030242	0.245872858481893	0.986503116255774
11	118.53	118.859869616276	-4.74289199990166	-0.329869616275619	-1.56642743172016
12	113.14	113.072065188506	-5.69368359272046	0.067934811494016	-0.207254119571685
13	114.15	113.820056964336	0.137293918295319	0.329943035663569	1.30617668807452
14	122.17	121.948627069742	6.93900046753001	0.221372930258375	1.47143578272947
15	129.23	129.251133683834	7.26134583979489	-0.0211336838336444	0.0702956150792457
16	131.19	131.227140268583	2.59179533094804	-0.0371402685830076	-1.01410308589435
17	129.12	129.610135228349	-1.13022730994044	-0.490135228349003	-0.81138113179795
18	128.28	127.762037961368	-1.76540834426589	0.517962038632025	-0.138455307850871
19	126.83	127.221648312564	-0.681581329417607	-0.391648312564396	0.236253344661319
20	138.13	136.891532690192	8.47639142970118	1.23846730980816	1.99626004787833
21	140.52	141.496125790248	5.05100180883885	-0.976125790247784	-0.74666856805515
22	146.83	146.18202903809	4.72798641198333	0.647970961910118	-0.0704111087827684
23	135.14	136.055343646103	-8.4155049146763	-0.91534364610312	-2.86507463687213
24	131.84	131.499688352674	-5.00325927790722	0.340311647326001	0.744031465440659
25	125.7	126.360997728313	-5.12301346878176	-0.660997728313063	-0.0264407527440768
26	128.98	128.620932867865	1.19443231899773	0.359067132134668	1.36993223458147
27	133.25	132.851918209884	3.84495003071638	0.398081790116353	0.579569553661896
28	136.76	136.547502748048	3.71454245588471	0.212497251952143	-0.0283266193563843
29	133.24	133.965409953674	-1.78161478605764	-0.725409953673718	-1.19793769414372
30	128.54	127.911717517843	-5.51375707469794	0.62828248215724	-0.813530457709215
31	121.08	122.310659902517	-5.59002397324516	-1.23065990251707	-0.0166246282184823
32	120.23	118.583910619587	-3.96237669087060	1.64608938041287	0.354795577877309
33	119.08	120.204131792144	0.914229817306783	-1.12413179214442	1.06300566305370
34	125.75	123.634521300853	3.11237491401478	2.11547869914734	0.479156498736774
35	126.89	128.025524319659	4.22934775702417	-1.13552431965949	0.243479856030229
36	126.6	126.398505058157	-0.880357027193927	0.201494941842746	-1.11480800848040
37	121.89	123.409157055347	-2.72377114043586	-1.51915705534704	-0.404211138730694
38	123.44	123.244178250926	-0.529131087357738	0.195821749073722	0.476768191036138
39	126.46	126.085898453526	2.39064071431006	0.374101546474418	0.638570867909091
40	129.49	128.850332823347	2.71512017631326	0.639667176652758	0.0705390064677417
41	127.78	128.341115013476	-0.0810618756463612	-0.561115013476304	-0.609307726939597
42	125.29	124.751529462	-3.12645944513900	0.538470538000142	-0.663852200903137
43	119.02	120.215944328442	-4.34972998793681	-1.19594432844207	-0.266645656308553
44	119.96	118.472109226178	-2.08770905950752	1.48789077382238	0.493076694308836
45	122.86	123.708481274012	4.26988405475962	-0.848481274012393	1.38583280540139
46	131.89	130.04782269332	6.06638992233837	1.84217730667989	0.391610356978546
47	132.73	133.583967899546	3.8703892911244	-0.853967899546154	-0.478679383073456
48	135.01	134.687628993331	1.47156315686195	0.322371006669465	-0.523544218885862
49	136.71	138.225458287533	3.2660477324634	-1.51545828753304	0.392236526720319
50	142.73	142.802739606604	4.39140544766192	-0.0727396066035983	0.244751629264758
51	144.43	144.456256767502	2.02957335327447	-0.0262567675020932	-0.516298599702921
52	144.93	144.297405085110	0.136365799289824	0.632594914889814	-0.411906978939660
53	138.75	139.335339537302	-4.26872744002087	-0.585339537301886	-0.959709989279856
54	130.22	129.675203425735	-8.93054893681514	0.544796574264559	-1.01622860367565
55	122.19	123.117440954077	-6.87835319583681	-0.927440954076765	0.447330940491508
56	128.4	126.847246573552	2.29615983216228	1.55275342644837	1.99986096975472
57	140.43	140.854425058853	12.4245091137639	-0.424425058853141	2.20779437417532
58	153.5	151.659603295881	11.0239852637545	1.84039670411948	-0.305292617967822
59	149.33	150.660597521916	0.629629190843078	-1.33059752191579	-2.26577833702963
60	142.97	143.360339514032	-6.22189287681627	-0.390339514032104	-1.49545917193968

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 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
nx <- length(x)
x <- ts(x,frequency=par1)
m <- StructTS(x,type='BSM')
m$coef
m$fitted
m$resid
mylevel <- as.numeric(m$fitted[,'level'])
myslope <- as.numeric(m$fitted[,'slope'])
myseas <- as.numeric(m$fitted[,'sea'])
myresid <- as.numeric(m$resid)
myfit <- mylevel+myseas
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(mylevel,main='Level')
spectrum(myseas,main='Seasonal')
spectrum(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(mylevel,main='Level')
cpgram(myseas,main='Seasonal')
cpgram(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
grid()
dev.off()
bitmap(file='test5.png')
op <- par(mfrow = c(2,2))
hist(m$resid,main='Residual Histogram')
plot(density(m$resid),main='Residual Kernel Density')
qqnorm(m$resid,main='Residual Normal QQ Plot')
qqline(m$resid)
plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Structural Time Series Model',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Level',header=TRUE)
a<-table.element(a,'Slope',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Stand. Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,mylevel[i])
a<-table.element(a,myslope[i])
a<-table.element(a,myseas[i])
a<-table.element(a,myresid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code