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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Tue, 01 Dec 2009 11:53:41 -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/01/t1259693682902t41val1f8nj6.htm/, Retrieved Thu, 25 Apr 2024 16:23:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62180, Retrieved Thu, 25 Apr 2024 16:23:30 +0000

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Estimated Impact

153

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]
- R PD      [Structural Time Series Models] [] [2009-12-01 18:53:41] [791a4a78a0a7ca497fb8791b982a539e] [Current]
- R PD        [Structural Time Series Models] [] [2009-12-04 16:26:06] [fa71ec4c741ffec745cb91dcbd756720] 

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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=62180&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=62180&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62180&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	785.8	785.8	0	0	0
2	819.3	817.609282416434	2.67691669634891	1.69071758356565	0.39719223433328
3	849.4	847.720422441074	6.8457719559912	1.67957755892550	0.533925998333214
4	880.4	878.728299666824	11.6089242081624	1.67170033317598	0.457582594189363
5	900.1	898.430343864027	13.4318026707852	1.66965613597312	0.150572765794228
6	937.2	935.534877703158	19.1547469770608	1.66512229684247	0.435741924222337
7	948.9	947.233808359028	17.2823436060088	1.66619164097247	-0.136394450123664
8	952.6	950.93235956639	13.8000063715200	1.66764043360883	-0.247639628313144
9	947.3	945.630850424226	8.84811679642649	1.66914957577367	-0.347566601463131
10	974.2	972.531904715653	13.5566759407004	1.66809528434752	0.3281445814981
11	1000.8	999.13246713868	16.9700300135244	1.66753286132071	0.236961926540982
12	1032.8	1031.13294532186	20.91030792724	1.66705467814030	0.272967387597524
13	1050.7	1064.19528093053	23.9861078329843	-13.4952809305295	0.256142096431306
14	1057.3	1056.77482598595	16.140104236904	0.525174014053045	-0.476856585731127
15	1075.4	1074.87717814867	16.6562750391262	0.522821851332131	0.0355656476534347
16	1118.4	1117.90047570500	23.5865448498081	0.499524295004611	0.478147592285431
17	1179.8	1179.32512473132	33.5280995815171	0.474875268683573	0.686401833691654
18	1227	1226.53169455762	37.1213936863546	0.468305442379223	0.248191353229814
19	1257.8	1257.32945512834	35.4602836533393	0.470544871660763	-0.114758419392082
20	1251.5	1251.01854819546	24.4877623896678	0.481451804534982	-0.758128365479101
21	1236.3	1235.81090598933	14.0603520655634	0.489094010668068	-0.720510051317063
22	1170.6	1170.09958259550	-6.89496964288594	0.500417404495105	-1.44801390892128
23	1213.1	1212.60475273339	6.08229481863566	0.495247266608715	0.896746339175407
24	1265.5	1265.00832708782	18.2509826282907	0.491672912180066	0.840881089688386
25	1300.8	1302.58843568902	23.2522482701005	-1.78843568902327	0.378965520562840
26	1348.4	1347.92035387033	28.8668834649575	0.479646129670325	0.360460365295743
27	1371.9	1371.41608794063	27.4542262841326	0.483912059369256	-0.0974010858232042
28	1403.3	1402.81839950051	28.4919255256697	0.481600499488614	0.0716210713320114
29	1451.8	1451.32703971248	33.7513787005342	0.472960287518644	0.363203749207738
30	1474.2	1473.72342600172	30.7682430707837	0.4765739982753	-0.206069355466187
31	1438.2	1437.70775553654	13.2240239121624	0.49224446345753	-1.21211965582312
32	1513.6	1513.11851407799	29.5603326892345	0.481485922008465	1.12876620314203
33	1562.2	1561.72094300987	34.5626687168323	0.4790569901292	0.345655853288744
34	1546.2	1545.71618730810	21.2785175141530	0.483812691902991	-0.917944182211116
35	1527.5	1527.01341499785	10.7752302529652	0.486585002153875	-0.725794894781744
36	1418.7	1418.20730152607	-20.6397594865404	0.492698473930562	-2.17084571764114
37	1448.5	1447.77614094509	-7.57910563285872	0.72385905490675	0.960074783422643
38	1492.1	1491.6213716054	5.61123607123262	0.47862839460027	0.865517533559587
39	1395.4	1394.86114539285	-21.3056704956263	0.538854607147992	-1.85696181010308
40	1403.7	1403.17399088462	-13.521747457278	0.526009115377599	0.537408060928477
41	1316.6	1316.05045698711	-32.8602069476179	0.549543012891735	-1.33569010807091
42	1274.5	1273.94827825169	-35.2882279703313	0.551721748310102	-0.167738647801777
43	1264.4	1263.85265703700	-28.6699786105155	0.547342962996684	0.457273961923214
44	1323.9	1323.36395757756	-5.50446386409072	0.536042422442138	1.60067779808003
45	1332.1	1331.56525257134	-1.90390376092505	0.534747428658438	0.248798403139152
46	1250.2	1249.65967937765	-22.9208508660966	0.540320622345836	-1.45229757317388
47	1096.7	1096.15297219280	-57.2269050840887	0.547027807197017	-2.37061674091869
48	1080.8	1080.25453725348	-46.369458607251	0.545462746522689	0.750275514409668
49	1039.2	1044.25763222343	-43.6643470865065	-5.05763222342639	0.195832418939757
50	792	793.278437919647	-97.1088401705711	-1.27843791964651	-3.54866067243658
51	746.6	747.902599241084	-83.5087750771732	-1.30259924108436	0.938570404677832
52	688.8	690.111454041365	-76.750486622232	-1.31145404136497	0.466683921680099
53	715.8	717.137797289207	-49.4842359072828	-1.33779728920699	1.88344525119048
54	672.9	674.239029796824	-47.7541191975249	-1.33902979682444	0.119530812847165
55	629.5	630.839630696876	-46.6100959362039	-1.33963069687565	0.0790462235088793
56	681.2	682.549633566706	-20.7807519469652	-1.34963356670612	1.78477045555338
57	755.4	756.756758657565	4.17325989438115	-1.35675865756537	1.72433530226900
58	760.6	761.956815444139	4.44300874407886	-1.35681544413915	0.0186400750996998
59	765.9	767.256850389777	4.66815896021728	-1.35685038977692	0.0155583692333735
60	836.8	838.158841592364	22.0686346454974	-1.35884159236399	1.20241617704689
61	904.9	887.949577141857	29.3093455405917	16.9504228581431	0.519368014977001

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 785.8 & 785.8 & 0 & 0 & 0 \tabularnewline
2 & 819.3 & 817.609282416434 & 2.67691669634891 & 1.69071758356565 & 0.39719223433328 \tabularnewline
3 & 849.4 & 847.720422441074 & 6.8457719559912 & 1.67957755892550 & 0.533925998333214 \tabularnewline
4 & 880.4 & 878.728299666824 & 11.6089242081624 & 1.67170033317598 & 0.457582594189363 \tabularnewline
5 & 900.1 & 898.430343864027 & 13.4318026707852 & 1.66965613597312 & 0.150572765794228 \tabularnewline
6 & 937.2 & 935.534877703158 & 19.1547469770608 & 1.66512229684247 & 0.435741924222337 \tabularnewline
7 & 948.9 & 947.233808359028 & 17.2823436060088 & 1.66619164097247 & -0.136394450123664 \tabularnewline
8 & 952.6 & 950.93235956639 & 13.8000063715200 & 1.66764043360883 & -0.247639628313144 \tabularnewline
9 & 947.3 & 945.630850424226 & 8.84811679642649 & 1.66914957577367 & -0.347566601463131 \tabularnewline
10 & 974.2 & 972.531904715653 & 13.5566759407004 & 1.66809528434752 & 0.3281445814981 \tabularnewline
11 & 1000.8 & 999.13246713868 & 16.9700300135244 & 1.66753286132071 & 0.236961926540982 \tabularnewline
12 & 1032.8 & 1031.13294532186 & 20.91030792724 & 1.66705467814030 & 0.272967387597524 \tabularnewline
13 & 1050.7 & 1064.19528093053 & 23.9861078329843 & -13.4952809305295 & 0.256142096431306 \tabularnewline
14 & 1057.3 & 1056.77482598595 & 16.140104236904 & 0.525174014053045 & -0.476856585731127 \tabularnewline
15 & 1075.4 & 1074.87717814867 & 16.6562750391262 & 0.522821851332131 & 0.0355656476534347 \tabularnewline
16 & 1118.4 & 1117.90047570500 & 23.5865448498081 & 0.499524295004611 & 0.478147592285431 \tabularnewline
17 & 1179.8 & 1179.32512473132 & 33.5280995815171 & 0.474875268683573 & 0.686401833691654 \tabularnewline
18 & 1227 & 1226.53169455762 & 37.1213936863546 & 0.468305442379223 & 0.248191353229814 \tabularnewline
19 & 1257.8 & 1257.32945512834 & 35.4602836533393 & 0.470544871660763 & -0.114758419392082 \tabularnewline
20 & 1251.5 & 1251.01854819546 & 24.4877623896678 & 0.481451804534982 & -0.758128365479101 \tabularnewline
21 & 1236.3 & 1235.81090598933 & 14.0603520655634 & 0.489094010668068 & -0.720510051317063 \tabularnewline
22 & 1170.6 & 1170.09958259550 & -6.89496964288594 & 0.500417404495105 & -1.44801390892128 \tabularnewline
23 & 1213.1 & 1212.60475273339 & 6.08229481863566 & 0.495247266608715 & 0.896746339175407 \tabularnewline
24 & 1265.5 & 1265.00832708782 & 18.2509826282907 & 0.491672912180066 & 0.840881089688386 \tabularnewline
25 & 1300.8 & 1302.58843568902 & 23.2522482701005 & -1.78843568902327 & 0.378965520562840 \tabularnewline
26 & 1348.4 & 1347.92035387033 & 28.8668834649575 & 0.479646129670325 & 0.360460365295743 \tabularnewline
27 & 1371.9 & 1371.41608794063 & 27.4542262841326 & 0.483912059369256 & -0.0974010858232042 \tabularnewline
28 & 1403.3 & 1402.81839950051 & 28.4919255256697 & 0.481600499488614 & 0.0716210713320114 \tabularnewline
29 & 1451.8 & 1451.32703971248 & 33.7513787005342 & 0.472960287518644 & 0.363203749207738 \tabularnewline
30 & 1474.2 & 1473.72342600172 & 30.7682430707837 & 0.4765739982753 & -0.206069355466187 \tabularnewline
31 & 1438.2 & 1437.70775553654 & 13.2240239121624 & 0.49224446345753 & -1.21211965582312 \tabularnewline
32 & 1513.6 & 1513.11851407799 & 29.5603326892345 & 0.481485922008465 & 1.12876620314203 \tabularnewline
33 & 1562.2 & 1561.72094300987 & 34.5626687168323 & 0.4790569901292 & 0.345655853288744 \tabularnewline
34 & 1546.2 & 1545.71618730810 & 21.2785175141530 & 0.483812691902991 & -0.917944182211116 \tabularnewline
35 & 1527.5 & 1527.01341499785 & 10.7752302529652 & 0.486585002153875 & -0.725794894781744 \tabularnewline
36 & 1418.7 & 1418.20730152607 & -20.6397594865404 & 0.492698473930562 & -2.17084571764114 \tabularnewline
37 & 1448.5 & 1447.77614094509 & -7.57910563285872 & 0.72385905490675 & 0.960074783422643 \tabularnewline
38 & 1492.1 & 1491.6213716054 & 5.61123607123262 & 0.47862839460027 & 0.865517533559587 \tabularnewline
39 & 1395.4 & 1394.86114539285 & -21.3056704956263 & 0.538854607147992 & -1.85696181010308 \tabularnewline
40 & 1403.7 & 1403.17399088462 & -13.521747457278 & 0.526009115377599 & 0.537408060928477 \tabularnewline
41 & 1316.6 & 1316.05045698711 & -32.8602069476179 & 0.549543012891735 & -1.33569010807091 \tabularnewline
42 & 1274.5 & 1273.94827825169 & -35.2882279703313 & 0.551721748310102 & -0.167738647801777 \tabularnewline
43 & 1264.4 & 1263.85265703700 & -28.6699786105155 & 0.547342962996684 & 0.457273961923214 \tabularnewline
44 & 1323.9 & 1323.36395757756 & -5.50446386409072 & 0.536042422442138 & 1.60067779808003 \tabularnewline
45 & 1332.1 & 1331.56525257134 & -1.90390376092505 & 0.534747428658438 & 0.248798403139152 \tabularnewline
46 & 1250.2 & 1249.65967937765 & -22.9208508660966 & 0.540320622345836 & -1.45229757317388 \tabularnewline
47 & 1096.7 & 1096.15297219280 & -57.2269050840887 & 0.547027807197017 & -2.37061674091869 \tabularnewline
48 & 1080.8 & 1080.25453725348 & -46.369458607251 & 0.545462746522689 & 0.750275514409668 \tabularnewline
49 & 1039.2 & 1044.25763222343 & -43.6643470865065 & -5.05763222342639 & 0.195832418939757 \tabularnewline
50 & 792 & 793.278437919647 & -97.1088401705711 & -1.27843791964651 & -3.54866067243658 \tabularnewline
51 & 746.6 & 747.902599241084 & -83.5087750771732 & -1.30259924108436 & 0.938570404677832 \tabularnewline
52 & 688.8 & 690.111454041365 & -76.750486622232 & -1.31145404136497 & 0.466683921680099 \tabularnewline
53 & 715.8 & 717.137797289207 & -49.4842359072828 & -1.33779728920699 & 1.88344525119048 \tabularnewline
54 & 672.9 & 674.239029796824 & -47.7541191975249 & -1.33902979682444 & 0.119530812847165 \tabularnewline
55 & 629.5 & 630.839630696876 & -46.6100959362039 & -1.33963069687565 & 0.0790462235088793 \tabularnewline
56 & 681.2 & 682.549633566706 & -20.7807519469652 & -1.34963356670612 & 1.78477045555338 \tabularnewline
57 & 755.4 & 756.756758657565 & 4.17325989438115 & -1.35675865756537 & 1.72433530226900 \tabularnewline
58 & 760.6 & 761.956815444139 & 4.44300874407886 & -1.35681544413915 & 0.0186400750996998 \tabularnewline
59 & 765.9 & 767.256850389777 & 4.66815896021728 & -1.35685038977692 & 0.0155583692333735 \tabularnewline
60 & 836.8 & 838.158841592364 & 22.0686346454974 & -1.35884159236399 & 1.20241617704689 \tabularnewline
61 & 904.9 & 887.949577141857 & 29.3093455405917 & 16.9504228581431 & 0.519368014977001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62180&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]785.8[/C][C]785.8[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]819.3[/C][C]817.609282416434[/C][C]2.67691669634891[/C][C]1.69071758356565[/C][C]0.39719223433328[/C][/ROW]
[ROW][C]3[/C][C]849.4[/C][C]847.720422441074[/C][C]6.8457719559912[/C][C]1.67957755892550[/C][C]0.533925998333214[/C][/ROW]
[ROW][C]4[/C][C]880.4[/C][C]878.728299666824[/C][C]11.6089242081624[/C][C]1.67170033317598[/C][C]0.457582594189363[/C][/ROW]
[ROW][C]5[/C][C]900.1[/C][C]898.430343864027[/C][C]13.4318026707852[/C][C]1.66965613597312[/C][C]0.150572765794228[/C][/ROW]
[ROW][C]6[/C][C]937.2[/C][C]935.534877703158[/C][C]19.1547469770608[/C][C]1.66512229684247[/C][C]0.435741924222337[/C][/ROW]
[ROW][C]7[/C][C]948.9[/C][C]947.233808359028[/C][C]17.2823436060088[/C][C]1.66619164097247[/C][C]-0.136394450123664[/C][/ROW]
[ROW][C]8[/C][C]952.6[/C][C]950.93235956639[/C][C]13.8000063715200[/C][C]1.66764043360883[/C][C]-0.247639628313144[/C][/ROW]
[ROW][C]9[/C][C]947.3[/C][C]945.630850424226[/C][C]8.84811679642649[/C][C]1.66914957577367[/C][C]-0.347566601463131[/C][/ROW]
[ROW][C]10[/C][C]974.2[/C][C]972.531904715653[/C][C]13.5566759407004[/C][C]1.66809528434752[/C][C]0.3281445814981[/C][/ROW]
[ROW][C]11[/C][C]1000.8[/C][C]999.13246713868[/C][C]16.9700300135244[/C][C]1.66753286132071[/C][C]0.236961926540982[/C][/ROW]
[ROW][C]12[/C][C]1032.8[/C][C]1031.13294532186[/C][C]20.91030792724[/C][C]1.66705467814030[/C][C]0.272967387597524[/C][/ROW]
[ROW][C]13[/C][C]1050.7[/C][C]1064.19528093053[/C][C]23.9861078329843[/C][C]-13.4952809305295[/C][C]0.256142096431306[/C][/ROW]
[ROW][C]14[/C][C]1057.3[/C][C]1056.77482598595[/C][C]16.140104236904[/C][C]0.525174014053045[/C][C]-0.476856585731127[/C][/ROW]
[ROW][C]15[/C][C]1075.4[/C][C]1074.87717814867[/C][C]16.6562750391262[/C][C]0.522821851332131[/C][C]0.0355656476534347[/C][/ROW]
[ROW][C]16[/C][C]1118.4[/C][C]1117.90047570500[/C][C]23.5865448498081[/C][C]0.499524295004611[/C][C]0.478147592285431[/C][/ROW]
[ROW][C]17[/C][C]1179.8[/C][C]1179.32512473132[/C][C]33.5280995815171[/C][C]0.474875268683573[/C][C]0.686401833691654[/C][/ROW]
[ROW][C]18[/C][C]1227[/C][C]1226.53169455762[/C][C]37.1213936863546[/C][C]0.468305442379223[/C][C]0.248191353229814[/C][/ROW]
[ROW][C]19[/C][C]1257.8[/C][C]1257.32945512834[/C][C]35.4602836533393[/C][C]0.470544871660763[/C][C]-0.114758419392082[/C][/ROW]
[ROW][C]20[/C][C]1251.5[/C][C]1251.01854819546[/C][C]24.4877623896678[/C][C]0.481451804534982[/C][C]-0.758128365479101[/C][/ROW]
[ROW][C]21[/C][C]1236.3[/C][C]1235.81090598933[/C][C]14.0603520655634[/C][C]0.489094010668068[/C][C]-0.720510051317063[/C][/ROW]
[ROW][C]22[/C][C]1170.6[/C][C]1170.09958259550[/C][C]-6.89496964288594[/C][C]0.500417404495105[/C][C]-1.44801390892128[/C][/ROW]
[ROW][C]23[/C][C]1213.1[/C][C]1212.60475273339[/C][C]6.08229481863566[/C][C]0.495247266608715[/C][C]0.896746339175407[/C][/ROW]
[ROW][C]24[/C][C]1265.5[/C][C]1265.00832708782[/C][C]18.2509826282907[/C][C]0.491672912180066[/C][C]0.840881089688386[/C][/ROW]
[ROW][C]25[/C][C]1300.8[/C][C]1302.58843568902[/C][C]23.2522482701005[/C][C]-1.78843568902327[/C][C]0.378965520562840[/C][/ROW]
[ROW][C]26[/C][C]1348.4[/C][C]1347.92035387033[/C][C]28.8668834649575[/C][C]0.479646129670325[/C][C]0.360460365295743[/C][/ROW]
[ROW][C]27[/C][C]1371.9[/C][C]1371.41608794063[/C][C]27.4542262841326[/C][C]0.483912059369256[/C][C]-0.0974010858232042[/C][/ROW]
[ROW][C]28[/C][C]1403.3[/C][C]1402.81839950051[/C][C]28.4919255256697[/C][C]0.481600499488614[/C][C]0.0716210713320114[/C][/ROW]
[ROW][C]29[/C][C]1451.8[/C][C]1451.32703971248[/C][C]33.7513787005342[/C][C]0.472960287518644[/C][C]0.363203749207738[/C][/ROW]
[ROW][C]30[/C][C]1474.2[/C][C]1473.72342600172[/C][C]30.7682430707837[/C][C]0.4765739982753[/C][C]-0.206069355466187[/C][/ROW]
[ROW][C]31[/C][C]1438.2[/C][C]1437.70775553654[/C][C]13.2240239121624[/C][C]0.49224446345753[/C][C]-1.21211965582312[/C][/ROW]
[ROW][C]32[/C][C]1513.6[/C][C]1513.11851407799[/C][C]29.5603326892345[/C][C]0.481485922008465[/C][C]1.12876620314203[/C][/ROW]
[ROW][C]33[/C][C]1562.2[/C][C]1561.72094300987[/C][C]34.5626687168323[/C][C]0.4790569901292[/C][C]0.345655853288744[/C][/ROW]
[ROW][C]34[/C][C]1546.2[/C][C]1545.71618730810[/C][C]21.2785175141530[/C][C]0.483812691902991[/C][C]-0.917944182211116[/C][/ROW]
[ROW][C]35[/C][C]1527.5[/C][C]1527.01341499785[/C][C]10.7752302529652[/C][C]0.486585002153875[/C][C]-0.725794894781744[/C][/ROW]
[ROW][C]36[/C][C]1418.7[/C][C]1418.20730152607[/C][C]-20.6397594865404[/C][C]0.492698473930562[/C][C]-2.17084571764114[/C][/ROW]
[ROW][C]37[/C][C]1448.5[/C][C]1447.77614094509[/C][C]-7.57910563285872[/C][C]0.72385905490675[/C][C]0.960074783422643[/C][/ROW]
[ROW][C]38[/C][C]1492.1[/C][C]1491.6213716054[/C][C]5.61123607123262[/C][C]0.47862839460027[/C][C]0.865517533559587[/C][/ROW]
[ROW][C]39[/C][C]1395.4[/C][C]1394.86114539285[/C][C]-21.3056704956263[/C][C]0.538854607147992[/C][C]-1.85696181010308[/C][/ROW]
[ROW][C]40[/C][C]1403.7[/C][C]1403.17399088462[/C][C]-13.521747457278[/C][C]0.526009115377599[/C][C]0.537408060928477[/C][/ROW]
[ROW][C]41[/C][C]1316.6[/C][C]1316.05045698711[/C][C]-32.8602069476179[/C][C]0.549543012891735[/C][C]-1.33569010807091[/C][/ROW]
[ROW][C]42[/C][C]1274.5[/C][C]1273.94827825169[/C][C]-35.2882279703313[/C][C]0.551721748310102[/C][C]-0.167738647801777[/C][/ROW]
[ROW][C]43[/C][C]1264.4[/C][C]1263.85265703700[/C][C]-28.6699786105155[/C][C]0.547342962996684[/C][C]0.457273961923214[/C][/ROW]
[ROW][C]44[/C][C]1323.9[/C][C]1323.36395757756[/C][C]-5.50446386409072[/C][C]0.536042422442138[/C][C]1.60067779808003[/C][/ROW]
[ROW][C]45[/C][C]1332.1[/C][C]1331.56525257134[/C][C]-1.90390376092505[/C][C]0.534747428658438[/C][C]0.248798403139152[/C][/ROW]
[ROW][C]46[/C][C]1250.2[/C][C]1249.65967937765[/C][C]-22.9208508660966[/C][C]0.540320622345836[/C][C]-1.45229757317388[/C][/ROW]
[ROW][C]47[/C][C]1096.7[/C][C]1096.15297219280[/C][C]-57.2269050840887[/C][C]0.547027807197017[/C][C]-2.37061674091869[/C][/ROW]
[ROW][C]48[/C][C]1080.8[/C][C]1080.25453725348[/C][C]-46.369458607251[/C][C]0.545462746522689[/C][C]0.750275514409668[/C][/ROW]
[ROW][C]49[/C][C]1039.2[/C][C]1044.25763222343[/C][C]-43.6643470865065[/C][C]-5.05763222342639[/C][C]0.195832418939757[/C][/ROW]
[ROW][C]50[/C][C]792[/C][C]793.278437919647[/C][C]-97.1088401705711[/C][C]-1.27843791964651[/C][C]-3.54866067243658[/C][/ROW]
[ROW][C]51[/C][C]746.6[/C][C]747.902599241084[/C][C]-83.5087750771732[/C][C]-1.30259924108436[/C][C]0.938570404677832[/C][/ROW]
[ROW][C]52[/C][C]688.8[/C][C]690.111454041365[/C][C]-76.750486622232[/C][C]-1.31145404136497[/C][C]0.466683921680099[/C][/ROW]
[ROW][C]53[/C][C]715.8[/C][C]717.137797289207[/C][C]-49.4842359072828[/C][C]-1.33779728920699[/C][C]1.88344525119048[/C][/ROW]
[ROW][C]54[/C][C]672.9[/C][C]674.239029796824[/C][C]-47.7541191975249[/C][C]-1.33902979682444[/C][C]0.119530812847165[/C][/ROW]
[ROW][C]55[/C][C]629.5[/C][C]630.839630696876[/C][C]-46.6100959362039[/C][C]-1.33963069687565[/C][C]0.0790462235088793[/C][/ROW]
[ROW][C]56[/C][C]681.2[/C][C]682.549633566706[/C][C]-20.7807519469652[/C][C]-1.34963356670612[/C][C]1.78477045555338[/C][/ROW]
[ROW][C]57[/C][C]755.4[/C][C]756.756758657565[/C][C]4.17325989438115[/C][C]-1.35675865756537[/C][C]1.72433530226900[/C][/ROW]
[ROW][C]58[/C][C]760.6[/C][C]761.956815444139[/C][C]4.44300874407886[/C][C]-1.35681544413915[/C][C]0.0186400750996998[/C][/ROW]
[ROW][C]59[/C][C]765.9[/C][C]767.256850389777[/C][C]4.66815896021728[/C][C]-1.35685038977692[/C][C]0.0155583692333735[/C][/ROW]
[ROW][C]60[/C][C]836.8[/C][C]838.158841592364[/C][C]22.0686346454974[/C][C]-1.35884159236399[/C][C]1.20241617704689[/C][/ROW]
[ROW][C]61[/C][C]904.9[/C][C]887.949577141857[/C][C]29.3093455405917[/C][C]16.9504228581431[/C][C]0.519368014977001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62180&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62180&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	785.8	785.8	0	0	0
2	819.3	817.609282416434	2.67691669634891	1.69071758356565	0.39719223433328
3	849.4	847.720422441074	6.8457719559912	1.67957755892550	0.533925998333214
4	880.4	878.728299666824	11.6089242081624	1.67170033317598	0.457582594189363
5	900.1	898.430343864027	13.4318026707852	1.66965613597312	0.150572765794228
6	937.2	935.534877703158	19.1547469770608	1.66512229684247	0.435741924222337
7	948.9	947.233808359028	17.2823436060088	1.66619164097247	-0.136394450123664
8	952.6	950.93235956639	13.8000063715200	1.66764043360883	-0.247639628313144
9	947.3	945.630850424226	8.84811679642649	1.66914957577367	-0.347566601463131
10	974.2	972.531904715653	13.5566759407004	1.66809528434752	0.3281445814981
11	1000.8	999.13246713868	16.9700300135244	1.66753286132071	0.236961926540982
12	1032.8	1031.13294532186	20.91030792724	1.66705467814030	0.272967387597524
13	1050.7	1064.19528093053	23.9861078329843	-13.4952809305295	0.256142096431306
14	1057.3	1056.77482598595	16.140104236904	0.525174014053045	-0.476856585731127
15	1075.4	1074.87717814867	16.6562750391262	0.522821851332131	0.0355656476534347
16	1118.4	1117.90047570500	23.5865448498081	0.499524295004611	0.478147592285431
17	1179.8	1179.32512473132	33.5280995815171	0.474875268683573	0.686401833691654
18	1227	1226.53169455762	37.1213936863546	0.468305442379223	0.248191353229814
19	1257.8	1257.32945512834	35.4602836533393	0.470544871660763	-0.114758419392082
20	1251.5	1251.01854819546	24.4877623896678	0.481451804534982	-0.758128365479101
21	1236.3	1235.81090598933	14.0603520655634	0.489094010668068	-0.720510051317063
22	1170.6	1170.09958259550	-6.89496964288594	0.500417404495105	-1.44801390892128
23	1213.1	1212.60475273339	6.08229481863566	0.495247266608715	0.896746339175407
24	1265.5	1265.00832708782	18.2509826282907	0.491672912180066	0.840881089688386
25	1300.8	1302.58843568902	23.2522482701005	-1.78843568902327	0.378965520562840
26	1348.4	1347.92035387033	28.8668834649575	0.479646129670325	0.360460365295743
27	1371.9	1371.41608794063	27.4542262841326	0.483912059369256	-0.0974010858232042
28	1403.3	1402.81839950051	28.4919255256697	0.481600499488614	0.0716210713320114
29	1451.8	1451.32703971248	33.7513787005342	0.472960287518644	0.363203749207738
30	1474.2	1473.72342600172	30.7682430707837	0.4765739982753	-0.206069355466187
31	1438.2	1437.70775553654	13.2240239121624	0.49224446345753	-1.21211965582312
32	1513.6	1513.11851407799	29.5603326892345	0.481485922008465	1.12876620314203
33	1562.2	1561.72094300987	34.5626687168323	0.4790569901292	0.345655853288744
34	1546.2	1545.71618730810	21.2785175141530	0.483812691902991	-0.917944182211116
35	1527.5	1527.01341499785	10.7752302529652	0.486585002153875	-0.725794894781744
36	1418.7	1418.20730152607	-20.6397594865404	0.492698473930562	-2.17084571764114
37	1448.5	1447.77614094509	-7.57910563285872	0.72385905490675	0.960074783422643
38	1492.1	1491.6213716054	5.61123607123262	0.47862839460027	0.865517533559587
39	1395.4	1394.86114539285	-21.3056704956263	0.538854607147992	-1.85696181010308
40	1403.7	1403.17399088462	-13.521747457278	0.526009115377599	0.537408060928477
41	1316.6	1316.05045698711	-32.8602069476179	0.549543012891735	-1.33569010807091
42	1274.5	1273.94827825169	-35.2882279703313	0.551721748310102	-0.167738647801777
43	1264.4	1263.85265703700	-28.6699786105155	0.547342962996684	0.457273961923214
44	1323.9	1323.36395757756	-5.50446386409072	0.536042422442138	1.60067779808003
45	1332.1	1331.56525257134	-1.90390376092505	0.534747428658438	0.248798403139152
46	1250.2	1249.65967937765	-22.9208508660966	0.540320622345836	-1.45229757317388
47	1096.7	1096.15297219280	-57.2269050840887	0.547027807197017	-2.37061674091869
48	1080.8	1080.25453725348	-46.369458607251	0.545462746522689	0.750275514409668
49	1039.2	1044.25763222343	-43.6643470865065	-5.05763222342639	0.195832418939757
50	792	793.278437919647	-97.1088401705711	-1.27843791964651	-3.54866067243658
51	746.6	747.902599241084	-83.5087750771732	-1.30259924108436	0.938570404677832
52	688.8	690.111454041365	-76.750486622232	-1.31145404136497	0.466683921680099
53	715.8	717.137797289207	-49.4842359072828	-1.33779728920699	1.88344525119048
54	672.9	674.239029796824	-47.7541191975249	-1.33902979682444	0.119530812847165
55	629.5	630.839630696876	-46.6100959362039	-1.33963069687565	0.0790462235088793
56	681.2	682.549633566706	-20.7807519469652	-1.34963356670612	1.78477045555338
57	755.4	756.756758657565	4.17325989438115	-1.35675865756537	1.72433530226900
58	760.6	761.956815444139	4.44300874407886	-1.35681544413915	0.0186400750996998
59	765.9	767.256850389777	4.66815896021728	-1.35685038977692	0.0155583692333735
60	836.8	838.158841592364	22.0686346454974	-1.35884159236399	1.20241617704689
61	904.9	887.949577141857	29.3093455405917	16.9504228581431	0.519368014977001

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 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 2 ; par7 = 1 ; par8 = 0 ; par9 = 0 ;

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