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R Software Module

rwasp_structuraltimeseries.wasp

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Structural Time Series Models

Date of computation

Sat, 05 Dec 2009 09:00:54 -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/05/t1260028897cea2wu14s537ruu.htm/, Retrieved Tue, 30 Apr 2024 06:57:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64286, Retrieved Tue, 30 Apr 2024 06:57:00 +0000

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Estimated Impact

168

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] [ws8] [2009-12-01 17:50:31] [757146c69eaf0537be37c7b0c18216d8]
-    D        [Structural Time Series Models] [verbetering workshop] [2009-12-05 16:00:54] [a931a0a30926b49d162330b43e89b999] [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=64286&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=64286&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64286&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	29.837	29.837	0	0	0
2	29.571	29.5904101308721	-0.0133242641154774	-0.0194101308721427	-0.17267886155883
3	30.167	30.1047348709764	-0.00590938438004926	0.0622651290236483	0.605236883566329
4	30.524	30.501641415157	-0.00417903817515478	0.0223585848429797	0.465018942038387
5	30.996	30.9600424996861	-0.00214542395880076	0.0359575003138614	0.533814451603976
6	31.033	31.043723916878	-0.0017382534660389	-0.0107239168779781	0.0990378455712055
7	31.198	31.1855986527485	-0.00105329284670538	0.01240134725154	0.165718174423698
8	30.937	30.9703722757926	-0.00206851236682920	-0.0333722757925578	-0.247137480390282
9	31.649	31.5683254629245	0.000760661631391484	0.0806745370755246	0.692367551695651
10	33.115	32.9669743553856	0.00732074457535167	0.148025644614448	1.61301391693064
11	34.106	34.0269515623201	0.0122377149963033	0.0790484376798525	1.21464204037963
12	33.926	33.9662886000061	0.0118987770802128	-0.0402886000060978	-0.0841180582279495
13	33.382	33.6425632170615	0.0253993900842476	-0.260563217061456	-0.454947411146312
14	32.851	32.9963494146691	0.0118802614321193	-0.145349414669093	-0.682761335064029
15	32.948	32.8862609121358	0.0104368688178878	0.0617390878641806	-0.138488356549693
16	36.112	35.6011716934161	0.0204899103276316	0.510828306583931	3.11982486439929
17	36.113	36.1232866813358	0.0216534239626073	-0.0102866813358405	0.578398052153586
18	35.21	35.3959929638746	0.0197223411603790	-0.185992963874635	-0.86342346026361
19	35.193	35.1273930394818	0.0189295563011004	0.0656069605182098	-0.332379312508679
20	34.383	34.5168948730419	0.0171866649800633	-0.133894873041891	-0.72560701664154
21	35.349	35.2129543572521	0.0190679567375678	0.136045642747878	0.782616549966365
22	37.058	36.7644373884433	0.0234988685972021	0.293562611556678	1.76682355991305
23	38.076	37.8789140331341	0.0267545980794345	0.197085966865948	1.25817438197546
24	36.63	36.8881578316953	0.026927063691355	-0.258157831695279	-1.17198633735714
25	36.045	36.3208491121141	0.0360231237032054	-0.27584911211414	-0.728019554868669
26	35.638	35.8028441233771	0.0303057283601594	-0.164844123377064	-0.604216925552623
27	35.114	35.4922457904971	0.0269064083517163	-0.378245790497122	-0.385678633268819
28	35.465	35.1078416922563	0.0251432391818264	0.357158307743745	-0.474070437016384
29	35.254	35.1309489535522	0.0251389230540861	0.123051046447826	-0.00234747396731997
30	35.299	35.3786071674434	0.0255792414598661	-0.079607167443401	0.256492010881536
31	35.916	35.6643018539543	0.0261433222416476	0.251698146045702	0.299795559696390
32	36.683	36.6809883039277	0.0283903192065436	0.00201169607229421	1.14162873663866
33	37.288	37.3092512456262	0.0298066248179012	-0.0212512456261751	0.691426217013282
34	38.536	38.2783273461031	0.0321700172215651	0.257672653896938	1.08289814159513
35	38.977	38.6287451142632	0.032820453995601	0.348254885736786	0.366842156635779
36	36.407	36.9702696155171	0.0354773476946675	-0.563269615517122	-1.94993671953989
37	34.955	35.4687542868128	0.0472402791711909	-0.513754286812814	-1.82215152704289
38	34.951	35.07878508354	0.0445433039359075	-0.12778508354	-0.489271776903668
39	32.68	33.3147926521765	0.0296570253826546	-0.634792652176517	-2.04713670542767
40	34.791	34.1383983148975	0.0333005671247641	0.652601685102509	0.91392495796003
41	34.178	34.0906078429291	0.0331142109332699	0.0873921570709282	-0.093497319211094
42	35.213	35.0898105368989	0.0348343563975296	0.123189463101124	1.11357427407276
43	34.871	34.8665057845926	0.0343493886836417	0.00449421540735816	-0.297500737433527
44	35.299	35.3057854497249	0.0351771726574544	-0.00678544972484978	0.466664131864935
45	35.443	35.6174933975068	0.0357874675447234	-0.174493397506826	0.318735557420587
46	37.108	36.7253405555779	0.0381806037267405	0.382659444422126	1.23593266476961
47	36.419	36.023511746824	0.0372140943133252	0.395488253175966	-0.852612568478296
48	34.471	35.0022252219839	0.0391053647949012	-0.531225221983899	-1.22132885973800
49	33.868	34.3673970309607	0.0419179790588139	-0.499397030960679	-0.787685747978609
50	34.385	34.1755654701942	0.0409393911958756	0.209434529805770	-0.264536020689637
51	33.643	34.3482376603558	0.0418350390695929	-0.705237660355794	0.149409793657213
52	34.627	34.0284823411038	0.040171274224534	0.59851765889616	-0.415727421471527
53	32.919	33.1735109419128	0.0379213262905128	-0.25451094191284	-1.03196235268091
54	35.5	34.8910700360098	0.0408777505529137	0.60892996399022	1.93610259308469
55	36.11	35.9834883657279	0.0427021565001535	0.126511634272121	1.21189797710201
56	37.086	36.9988758029568	0.0445614216097969	0.087124197043184	1.12100074569387
57	37.711	37.9519740959720	0.0464443933682000	-0.240974095972049	1.04722999082765
58	40.427	39.6105191373181	0.0495555495900842	0.816480862681941	1.85825418146147
59	39.884	39.4368915368361	0.0493750269561307	0.447108463163941	-0.257076126273345
60	38.512	39.0578136710353	0.0500524703842053	-0.545813671035337	-0.494451743531779
61	38.767	39.2268060893307	0.0497749784745955	-0.459806089330737	0.138046923122567

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 29.837 & 29.837 & 0 & 0 & 0 \tabularnewline
2 & 29.571 & 29.5904101308721 & -0.0133242641154774 & -0.0194101308721427 & -0.17267886155883 \tabularnewline
3 & 30.167 & 30.1047348709764 & -0.00590938438004926 & 0.0622651290236483 & 0.605236883566329 \tabularnewline
4 & 30.524 & 30.501641415157 & -0.00417903817515478 & 0.0223585848429797 & 0.465018942038387 \tabularnewline
5 & 30.996 & 30.9600424996861 & -0.00214542395880076 & 0.0359575003138614 & 0.533814451603976 \tabularnewline
6 & 31.033 & 31.043723916878 & -0.0017382534660389 & -0.0107239168779781 & 0.0990378455712055 \tabularnewline
7 & 31.198 & 31.1855986527485 & -0.00105329284670538 & 0.01240134725154 & 0.165718174423698 \tabularnewline
8 & 30.937 & 30.9703722757926 & -0.00206851236682920 & -0.0333722757925578 & -0.247137480390282 \tabularnewline
9 & 31.649 & 31.5683254629245 & 0.000760661631391484 & 0.0806745370755246 & 0.692367551695651 \tabularnewline
10 & 33.115 & 32.9669743553856 & 0.00732074457535167 & 0.148025644614448 & 1.61301391693064 \tabularnewline
11 & 34.106 & 34.0269515623201 & 0.0122377149963033 & 0.0790484376798525 & 1.21464204037963 \tabularnewline
12 & 33.926 & 33.9662886000061 & 0.0118987770802128 & -0.0402886000060978 & -0.0841180582279495 \tabularnewline
13 & 33.382 & 33.6425632170615 & 0.0253993900842476 & -0.260563217061456 & -0.454947411146312 \tabularnewline
14 & 32.851 & 32.9963494146691 & 0.0118802614321193 & -0.145349414669093 & -0.682761335064029 \tabularnewline
15 & 32.948 & 32.8862609121358 & 0.0104368688178878 & 0.0617390878641806 & -0.138488356549693 \tabularnewline
16 & 36.112 & 35.6011716934161 & 0.0204899103276316 & 0.510828306583931 & 3.11982486439929 \tabularnewline
17 & 36.113 & 36.1232866813358 & 0.0216534239626073 & -0.0102866813358405 & 0.578398052153586 \tabularnewline
18 & 35.21 & 35.3959929638746 & 0.0197223411603790 & -0.185992963874635 & -0.86342346026361 \tabularnewline
19 & 35.193 & 35.1273930394818 & 0.0189295563011004 & 0.0656069605182098 & -0.332379312508679 \tabularnewline
20 & 34.383 & 34.5168948730419 & 0.0171866649800633 & -0.133894873041891 & -0.72560701664154 \tabularnewline
21 & 35.349 & 35.2129543572521 & 0.0190679567375678 & 0.136045642747878 & 0.782616549966365 \tabularnewline
22 & 37.058 & 36.7644373884433 & 0.0234988685972021 & 0.293562611556678 & 1.76682355991305 \tabularnewline
23 & 38.076 & 37.8789140331341 & 0.0267545980794345 & 0.197085966865948 & 1.25817438197546 \tabularnewline
24 & 36.63 & 36.8881578316953 & 0.026927063691355 & -0.258157831695279 & -1.17198633735714 \tabularnewline
25 & 36.045 & 36.3208491121141 & 0.0360231237032054 & -0.27584911211414 & -0.728019554868669 \tabularnewline
26 & 35.638 & 35.8028441233771 & 0.0303057283601594 & -0.164844123377064 & -0.604216925552623 \tabularnewline
27 & 35.114 & 35.4922457904971 & 0.0269064083517163 & -0.378245790497122 & -0.385678633268819 \tabularnewline
28 & 35.465 & 35.1078416922563 & 0.0251432391818264 & 0.357158307743745 & -0.474070437016384 \tabularnewline
29 & 35.254 & 35.1309489535522 & 0.0251389230540861 & 0.123051046447826 & -0.00234747396731997 \tabularnewline
30 & 35.299 & 35.3786071674434 & 0.0255792414598661 & -0.079607167443401 & 0.256492010881536 \tabularnewline
31 & 35.916 & 35.6643018539543 & 0.0261433222416476 & 0.251698146045702 & 0.299795559696390 \tabularnewline
32 & 36.683 & 36.6809883039277 & 0.0283903192065436 & 0.00201169607229421 & 1.14162873663866 \tabularnewline
33 & 37.288 & 37.3092512456262 & 0.0298066248179012 & -0.0212512456261751 & 0.691426217013282 \tabularnewline
34 & 38.536 & 38.2783273461031 & 0.0321700172215651 & 0.257672653896938 & 1.08289814159513 \tabularnewline
35 & 38.977 & 38.6287451142632 & 0.032820453995601 & 0.348254885736786 & 0.366842156635779 \tabularnewline
36 & 36.407 & 36.9702696155171 & 0.0354773476946675 & -0.563269615517122 & -1.94993671953989 \tabularnewline
37 & 34.955 & 35.4687542868128 & 0.0472402791711909 & -0.513754286812814 & -1.82215152704289 \tabularnewline
38 & 34.951 & 35.07878508354 & 0.0445433039359075 & -0.12778508354 & -0.489271776903668 \tabularnewline
39 & 32.68 & 33.3147926521765 & 0.0296570253826546 & -0.634792652176517 & -2.04713670542767 \tabularnewline
40 & 34.791 & 34.1383983148975 & 0.0333005671247641 & 0.652601685102509 & 0.91392495796003 \tabularnewline
41 & 34.178 & 34.0906078429291 & 0.0331142109332699 & 0.0873921570709282 & -0.093497319211094 \tabularnewline
42 & 35.213 & 35.0898105368989 & 0.0348343563975296 & 0.123189463101124 & 1.11357427407276 \tabularnewline
43 & 34.871 & 34.8665057845926 & 0.0343493886836417 & 0.00449421540735816 & -0.297500737433527 \tabularnewline
44 & 35.299 & 35.3057854497249 & 0.0351771726574544 & -0.00678544972484978 & 0.466664131864935 \tabularnewline
45 & 35.443 & 35.6174933975068 & 0.0357874675447234 & -0.174493397506826 & 0.318735557420587 \tabularnewline
46 & 37.108 & 36.7253405555779 & 0.0381806037267405 & 0.382659444422126 & 1.23593266476961 \tabularnewline
47 & 36.419 & 36.023511746824 & 0.0372140943133252 & 0.395488253175966 & -0.852612568478296 \tabularnewline
48 & 34.471 & 35.0022252219839 & 0.0391053647949012 & -0.531225221983899 & -1.22132885973800 \tabularnewline
49 & 33.868 & 34.3673970309607 & 0.0419179790588139 & -0.499397030960679 & -0.787685747978609 \tabularnewline
50 & 34.385 & 34.1755654701942 & 0.0409393911958756 & 0.209434529805770 & -0.264536020689637 \tabularnewline
51 & 33.643 & 34.3482376603558 & 0.0418350390695929 & -0.705237660355794 & 0.149409793657213 \tabularnewline
52 & 34.627 & 34.0284823411038 & 0.040171274224534 & 0.59851765889616 & -0.415727421471527 \tabularnewline
53 & 32.919 & 33.1735109419128 & 0.0379213262905128 & -0.25451094191284 & -1.03196235268091 \tabularnewline
54 & 35.5 & 34.8910700360098 & 0.0408777505529137 & 0.60892996399022 & 1.93610259308469 \tabularnewline
55 & 36.11 & 35.9834883657279 & 0.0427021565001535 & 0.126511634272121 & 1.21189797710201 \tabularnewline
56 & 37.086 & 36.9988758029568 & 0.0445614216097969 & 0.087124197043184 & 1.12100074569387 \tabularnewline
57 & 37.711 & 37.9519740959720 & 0.0464443933682000 & -0.240974095972049 & 1.04722999082765 \tabularnewline
58 & 40.427 & 39.6105191373181 & 0.0495555495900842 & 0.816480862681941 & 1.85825418146147 \tabularnewline
59 & 39.884 & 39.4368915368361 & 0.0493750269561307 & 0.447108463163941 & -0.257076126273345 \tabularnewline
60 & 38.512 & 39.0578136710353 & 0.0500524703842053 & -0.545813671035337 & -0.494451743531779 \tabularnewline
61 & 38.767 & 39.2268060893307 & 0.0497749784745955 & -0.459806089330737 & 0.138046923122567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64286&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]29.837[/C][C]29.837[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]29.571[/C][C]29.5904101308721[/C][C]-0.0133242641154774[/C][C]-0.0194101308721427[/C][C]-0.17267886155883[/C][/ROW]
[ROW][C]3[/C][C]30.167[/C][C]30.1047348709764[/C][C]-0.00590938438004926[/C][C]0.0622651290236483[/C][C]0.605236883566329[/C][/ROW]
[ROW][C]4[/C][C]30.524[/C][C]30.501641415157[/C][C]-0.00417903817515478[/C][C]0.0223585848429797[/C][C]0.465018942038387[/C][/ROW]
[ROW][C]5[/C][C]30.996[/C][C]30.9600424996861[/C][C]-0.00214542395880076[/C][C]0.0359575003138614[/C][C]0.533814451603976[/C][/ROW]
[ROW][C]6[/C][C]31.033[/C][C]31.043723916878[/C][C]-0.0017382534660389[/C][C]-0.0107239168779781[/C][C]0.0990378455712055[/C][/ROW]
[ROW][C]7[/C][C]31.198[/C][C]31.1855986527485[/C][C]-0.00105329284670538[/C][C]0.01240134725154[/C][C]0.165718174423698[/C][/ROW]
[ROW][C]8[/C][C]30.937[/C][C]30.9703722757926[/C][C]-0.00206851236682920[/C][C]-0.0333722757925578[/C][C]-0.247137480390282[/C][/ROW]
[ROW][C]9[/C][C]31.649[/C][C]31.5683254629245[/C][C]0.000760661631391484[/C][C]0.0806745370755246[/C][C]0.692367551695651[/C][/ROW]
[ROW][C]10[/C][C]33.115[/C][C]32.9669743553856[/C][C]0.00732074457535167[/C][C]0.148025644614448[/C][C]1.61301391693064[/C][/ROW]
[ROW][C]11[/C][C]34.106[/C][C]34.0269515623201[/C][C]0.0122377149963033[/C][C]0.0790484376798525[/C][C]1.21464204037963[/C][/ROW]
[ROW][C]12[/C][C]33.926[/C][C]33.9662886000061[/C][C]0.0118987770802128[/C][C]-0.0402886000060978[/C][C]-0.0841180582279495[/C][/ROW]
[ROW][C]13[/C][C]33.382[/C][C]33.6425632170615[/C][C]0.0253993900842476[/C][C]-0.260563217061456[/C][C]-0.454947411146312[/C][/ROW]
[ROW][C]14[/C][C]32.851[/C][C]32.9963494146691[/C][C]0.0118802614321193[/C][C]-0.145349414669093[/C][C]-0.682761335064029[/C][/ROW]
[ROW][C]15[/C][C]32.948[/C][C]32.8862609121358[/C][C]0.0104368688178878[/C][C]0.0617390878641806[/C][C]-0.138488356549693[/C][/ROW]
[ROW][C]16[/C][C]36.112[/C][C]35.6011716934161[/C][C]0.0204899103276316[/C][C]0.510828306583931[/C][C]3.11982486439929[/C][/ROW]
[ROW][C]17[/C][C]36.113[/C][C]36.1232866813358[/C][C]0.0216534239626073[/C][C]-0.0102866813358405[/C][C]0.578398052153586[/C][/ROW]
[ROW][C]18[/C][C]35.21[/C][C]35.3959929638746[/C][C]0.0197223411603790[/C][C]-0.185992963874635[/C][C]-0.86342346026361[/C][/ROW]
[ROW][C]19[/C][C]35.193[/C][C]35.1273930394818[/C][C]0.0189295563011004[/C][C]0.0656069605182098[/C][C]-0.332379312508679[/C][/ROW]
[ROW][C]20[/C][C]34.383[/C][C]34.5168948730419[/C][C]0.0171866649800633[/C][C]-0.133894873041891[/C][C]-0.72560701664154[/C][/ROW]
[ROW][C]21[/C][C]35.349[/C][C]35.2129543572521[/C][C]0.0190679567375678[/C][C]0.136045642747878[/C][C]0.782616549966365[/C][/ROW]
[ROW][C]22[/C][C]37.058[/C][C]36.7644373884433[/C][C]0.0234988685972021[/C][C]0.293562611556678[/C][C]1.76682355991305[/C][/ROW]
[ROW][C]23[/C][C]38.076[/C][C]37.8789140331341[/C][C]0.0267545980794345[/C][C]0.197085966865948[/C][C]1.25817438197546[/C][/ROW]
[ROW][C]24[/C][C]36.63[/C][C]36.8881578316953[/C][C]0.026927063691355[/C][C]-0.258157831695279[/C][C]-1.17198633735714[/C][/ROW]
[ROW][C]25[/C][C]36.045[/C][C]36.3208491121141[/C][C]0.0360231237032054[/C][C]-0.27584911211414[/C][C]-0.728019554868669[/C][/ROW]
[ROW][C]26[/C][C]35.638[/C][C]35.8028441233771[/C][C]0.0303057283601594[/C][C]-0.164844123377064[/C][C]-0.604216925552623[/C][/ROW]
[ROW][C]27[/C][C]35.114[/C][C]35.4922457904971[/C][C]0.0269064083517163[/C][C]-0.378245790497122[/C][C]-0.385678633268819[/C][/ROW]
[ROW][C]28[/C][C]35.465[/C][C]35.1078416922563[/C][C]0.0251432391818264[/C][C]0.357158307743745[/C][C]-0.474070437016384[/C][/ROW]
[ROW][C]29[/C][C]35.254[/C][C]35.1309489535522[/C][C]0.0251389230540861[/C][C]0.123051046447826[/C][C]-0.00234747396731997[/C][/ROW]
[ROW][C]30[/C][C]35.299[/C][C]35.3786071674434[/C][C]0.0255792414598661[/C][C]-0.079607167443401[/C][C]0.256492010881536[/C][/ROW]
[ROW][C]31[/C][C]35.916[/C][C]35.6643018539543[/C][C]0.0261433222416476[/C][C]0.251698146045702[/C][C]0.299795559696390[/C][/ROW]
[ROW][C]32[/C][C]36.683[/C][C]36.6809883039277[/C][C]0.0283903192065436[/C][C]0.00201169607229421[/C][C]1.14162873663866[/C][/ROW]
[ROW][C]33[/C][C]37.288[/C][C]37.3092512456262[/C][C]0.0298066248179012[/C][C]-0.0212512456261751[/C][C]0.691426217013282[/C][/ROW]
[ROW][C]34[/C][C]38.536[/C][C]38.2783273461031[/C][C]0.0321700172215651[/C][C]0.257672653896938[/C][C]1.08289814159513[/C][/ROW]
[ROW][C]35[/C][C]38.977[/C][C]38.6287451142632[/C][C]0.032820453995601[/C][C]0.348254885736786[/C][C]0.366842156635779[/C][/ROW]
[ROW][C]36[/C][C]36.407[/C][C]36.9702696155171[/C][C]0.0354773476946675[/C][C]-0.563269615517122[/C][C]-1.94993671953989[/C][/ROW]
[ROW][C]37[/C][C]34.955[/C][C]35.4687542868128[/C][C]0.0472402791711909[/C][C]-0.513754286812814[/C][C]-1.82215152704289[/C][/ROW]
[ROW][C]38[/C][C]34.951[/C][C]35.07878508354[/C][C]0.0445433039359075[/C][C]-0.12778508354[/C][C]-0.489271776903668[/C][/ROW]
[ROW][C]39[/C][C]32.68[/C][C]33.3147926521765[/C][C]0.0296570253826546[/C][C]-0.634792652176517[/C][C]-2.04713670542767[/C][/ROW]
[ROW][C]40[/C][C]34.791[/C][C]34.1383983148975[/C][C]0.0333005671247641[/C][C]0.652601685102509[/C][C]0.91392495796003[/C][/ROW]
[ROW][C]41[/C][C]34.178[/C][C]34.0906078429291[/C][C]0.0331142109332699[/C][C]0.0873921570709282[/C][C]-0.093497319211094[/C][/ROW]
[ROW][C]42[/C][C]35.213[/C][C]35.0898105368989[/C][C]0.0348343563975296[/C][C]0.123189463101124[/C][C]1.11357427407276[/C][/ROW]
[ROW][C]43[/C][C]34.871[/C][C]34.8665057845926[/C][C]0.0343493886836417[/C][C]0.00449421540735816[/C][C]-0.297500737433527[/C][/ROW]
[ROW][C]44[/C][C]35.299[/C][C]35.3057854497249[/C][C]0.0351771726574544[/C][C]-0.00678544972484978[/C][C]0.466664131864935[/C][/ROW]
[ROW][C]45[/C][C]35.443[/C][C]35.6174933975068[/C][C]0.0357874675447234[/C][C]-0.174493397506826[/C][C]0.318735557420587[/C][/ROW]
[ROW][C]46[/C][C]37.108[/C][C]36.7253405555779[/C][C]0.0381806037267405[/C][C]0.382659444422126[/C][C]1.23593266476961[/C][/ROW]
[ROW][C]47[/C][C]36.419[/C][C]36.023511746824[/C][C]0.0372140943133252[/C][C]0.395488253175966[/C][C]-0.852612568478296[/C][/ROW]
[ROW][C]48[/C][C]34.471[/C][C]35.0022252219839[/C][C]0.0391053647949012[/C][C]-0.531225221983899[/C][C]-1.22132885973800[/C][/ROW]
[ROW][C]49[/C][C]33.868[/C][C]34.3673970309607[/C][C]0.0419179790588139[/C][C]-0.499397030960679[/C][C]-0.787685747978609[/C][/ROW]
[ROW][C]50[/C][C]34.385[/C][C]34.1755654701942[/C][C]0.0409393911958756[/C][C]0.209434529805770[/C][C]-0.264536020689637[/C][/ROW]
[ROW][C]51[/C][C]33.643[/C][C]34.3482376603558[/C][C]0.0418350390695929[/C][C]-0.705237660355794[/C][C]0.149409793657213[/C][/ROW]
[ROW][C]52[/C][C]34.627[/C][C]34.0284823411038[/C][C]0.040171274224534[/C][C]0.59851765889616[/C][C]-0.415727421471527[/C][/ROW]
[ROW][C]53[/C][C]32.919[/C][C]33.1735109419128[/C][C]0.0379213262905128[/C][C]-0.25451094191284[/C][C]-1.03196235268091[/C][/ROW]
[ROW][C]54[/C][C]35.5[/C][C]34.8910700360098[/C][C]0.0408777505529137[/C][C]0.60892996399022[/C][C]1.93610259308469[/C][/ROW]
[ROW][C]55[/C][C]36.11[/C][C]35.9834883657279[/C][C]0.0427021565001535[/C][C]0.126511634272121[/C][C]1.21189797710201[/C][/ROW]
[ROW][C]56[/C][C]37.086[/C][C]36.9988758029568[/C][C]0.0445614216097969[/C][C]0.087124197043184[/C][C]1.12100074569387[/C][/ROW]
[ROW][C]57[/C][C]37.711[/C][C]37.9519740959720[/C][C]0.0464443933682000[/C][C]-0.240974095972049[/C][C]1.04722999082765[/C][/ROW]
[ROW][C]58[/C][C]40.427[/C][C]39.6105191373181[/C][C]0.0495555495900842[/C][C]0.816480862681941[/C][C]1.85825418146147[/C][/ROW]
[ROW][C]59[/C][C]39.884[/C][C]39.4368915368361[/C][C]0.0493750269561307[/C][C]0.447108463163941[/C][C]-0.257076126273345[/C][/ROW]
[ROW][C]60[/C][C]38.512[/C][C]39.0578136710353[/C][C]0.0500524703842053[/C][C]-0.545813671035337[/C][C]-0.494451743531779[/C][/ROW]
[ROW][C]61[/C][C]38.767[/C][C]39.2268060893307[/C][C]0.0497749784745955[/C][C]-0.459806089330737[/C][C]0.138046923122567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64286&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64286&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	29.837	29.837	0	0	0
2	29.571	29.5904101308721	-0.0133242641154774	-0.0194101308721427	-0.17267886155883
3	30.167	30.1047348709764	-0.00590938438004926	0.0622651290236483	0.605236883566329
4	30.524	30.501641415157	-0.00417903817515478	0.0223585848429797	0.465018942038387
5	30.996	30.9600424996861	-0.00214542395880076	0.0359575003138614	0.533814451603976
6	31.033	31.043723916878	-0.0017382534660389	-0.0107239168779781	0.0990378455712055
7	31.198	31.1855986527485	-0.00105329284670538	0.01240134725154	0.165718174423698
8	30.937	30.9703722757926	-0.00206851236682920	-0.0333722757925578	-0.247137480390282
9	31.649	31.5683254629245	0.000760661631391484	0.0806745370755246	0.692367551695651
10	33.115	32.9669743553856	0.00732074457535167	0.148025644614448	1.61301391693064
11	34.106	34.0269515623201	0.0122377149963033	0.0790484376798525	1.21464204037963
12	33.926	33.9662886000061	0.0118987770802128	-0.0402886000060978	-0.0841180582279495
13	33.382	33.6425632170615	0.0253993900842476	-0.260563217061456	-0.454947411146312
14	32.851	32.9963494146691	0.0118802614321193	-0.145349414669093	-0.682761335064029
15	32.948	32.8862609121358	0.0104368688178878	0.0617390878641806	-0.138488356549693
16	36.112	35.6011716934161	0.0204899103276316	0.510828306583931	3.11982486439929
17	36.113	36.1232866813358	0.0216534239626073	-0.0102866813358405	0.578398052153586
18	35.21	35.3959929638746	0.0197223411603790	-0.185992963874635	-0.86342346026361
19	35.193	35.1273930394818	0.0189295563011004	0.0656069605182098	-0.332379312508679
20	34.383	34.5168948730419	0.0171866649800633	-0.133894873041891	-0.72560701664154
21	35.349	35.2129543572521	0.0190679567375678	0.136045642747878	0.782616549966365
22	37.058	36.7644373884433	0.0234988685972021	0.293562611556678	1.76682355991305
23	38.076	37.8789140331341	0.0267545980794345	0.197085966865948	1.25817438197546
24	36.63	36.8881578316953	0.026927063691355	-0.258157831695279	-1.17198633735714
25	36.045	36.3208491121141	0.0360231237032054	-0.27584911211414	-0.728019554868669
26	35.638	35.8028441233771	0.0303057283601594	-0.164844123377064	-0.604216925552623
27	35.114	35.4922457904971	0.0269064083517163	-0.378245790497122	-0.385678633268819
28	35.465	35.1078416922563	0.0251432391818264	0.357158307743745	-0.474070437016384
29	35.254	35.1309489535522	0.0251389230540861	0.123051046447826	-0.00234747396731997
30	35.299	35.3786071674434	0.0255792414598661	-0.079607167443401	0.256492010881536
31	35.916	35.6643018539543	0.0261433222416476	0.251698146045702	0.299795559696390
32	36.683	36.6809883039277	0.0283903192065436	0.00201169607229421	1.14162873663866
33	37.288	37.3092512456262	0.0298066248179012	-0.0212512456261751	0.691426217013282
34	38.536	38.2783273461031	0.0321700172215651	0.257672653896938	1.08289814159513
35	38.977	38.6287451142632	0.032820453995601	0.348254885736786	0.366842156635779
36	36.407	36.9702696155171	0.0354773476946675	-0.563269615517122	-1.94993671953989
37	34.955	35.4687542868128	0.0472402791711909	-0.513754286812814	-1.82215152704289
38	34.951	35.07878508354	0.0445433039359075	-0.12778508354	-0.489271776903668
39	32.68	33.3147926521765	0.0296570253826546	-0.634792652176517	-2.04713670542767
40	34.791	34.1383983148975	0.0333005671247641	0.652601685102509	0.91392495796003
41	34.178	34.0906078429291	0.0331142109332699	0.0873921570709282	-0.093497319211094
42	35.213	35.0898105368989	0.0348343563975296	0.123189463101124	1.11357427407276
43	34.871	34.8665057845926	0.0343493886836417	0.00449421540735816	-0.297500737433527
44	35.299	35.3057854497249	0.0351771726574544	-0.00678544972484978	0.466664131864935
45	35.443	35.6174933975068	0.0357874675447234	-0.174493397506826	0.318735557420587
46	37.108	36.7253405555779	0.0381806037267405	0.382659444422126	1.23593266476961
47	36.419	36.023511746824	0.0372140943133252	0.395488253175966	-0.852612568478296
48	34.471	35.0022252219839	0.0391053647949012	-0.531225221983899	-1.22132885973800
49	33.868	34.3673970309607	0.0419179790588139	-0.499397030960679	-0.787685747978609
50	34.385	34.1755654701942	0.0409393911958756	0.209434529805770	-0.264536020689637
51	33.643	34.3482376603558	0.0418350390695929	-0.705237660355794	0.149409793657213
52	34.627	34.0284823411038	0.040171274224534	0.59851765889616	-0.415727421471527
53	32.919	33.1735109419128	0.0379213262905128	-0.25451094191284	-1.03196235268091
54	35.5	34.8910700360098	0.0408777505529137	0.60892996399022	1.93610259308469
55	36.11	35.9834883657279	0.0427021565001535	0.126511634272121	1.21189797710201
56	37.086	36.9988758029568	0.0445614216097969	0.087124197043184	1.12100074569387
57	37.711	37.9519740959720	0.0464443933682000	-0.240974095972049	1.04722999082765
58	40.427	39.6105191373181	0.0495555495900842	0.816480862681941	1.85825418146147
59	39.884	39.4368915368361	0.0493750269561307	0.447108463163941	-0.257076126273345
60	38.512	39.0578136710353	0.0500524703842053	-0.545813671035337	-0.494451743531779
61	38.767	39.2268060893307	0.0497749784745955	-0.459806089330737	0.138046923122567

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