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R Software Module

rwasp_structuraltimeseries.wasp

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Structural Time Series Models

Date of computation

Sun, 19 Dec 2010 14:01:10 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t1292767189nranz4c5in4pdrm.htm/, Retrieved Sat, 04 May 2024 23:10:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112393, Retrieved Sat, 04 May 2024 23:10:43 +0000

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Estimated Impact

138

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] [Unemployment] [2010-11-30 13:26:46] [b98453cac15ba1066b407e146608df68]
-         [Structural Time Series Models] [] [2010-12-08 17:44:30] [58af523ef9b33032fd2497c80088399b]
-    D        [Structural Time Series Models] [] [2010-12-19 14:01:10] [7c1b7ddc8e9000e55b944088fdfb52dc] [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	4 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112393&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112393&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	4 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	41.85	41.85	0	0	0
2	41.75	41.7562066210638	-0.0065553124913993	-0.00511075876723255	-0.61157554965322
3	41.75	41.7549293310928	-0.00611880030325368	-0.00509238564705291	0.05512048631084
4	41.75	41.7549006548992	-0.00542960596175323	-0.00508223033860989	0.0623942577348153
5	41.58	41.5899273756818	-0.0272834162103662	-0.00530433967981116	-1.61054141317511
6	41.61	41.6137934117889	-0.0193904508997543	-0.00524428569938085	0.51065660381463
7	41.42	41.4299975197799	-0.0467618215237257	-0.00540492067399878	-1.62835288439185
8	41.37	41.3756214929032	-0.0480930062245208	-0.00541105014653086	-0.0749965969536968
9	41.37	41.3741024961183	-0.0396888198675224	-0.00538037049466777	0.456988108410448
10	41.33	41.3353541870175	-0.0395155883299458	-0.00537986584236436	0.00920458601168563
11	41.37	41.3732397749297	-0.0250679142824497	-0.00534613862050466	0.756197181506416
12	41.34	41.3454217860621	-0.0255857061126666	-0.00534710983358388	-0.0268366330650689
13	41.33	41.2866304499283	-0.0315349549944941	0.0442367032332191	-0.379472745287853
14	41.29	41.2924523769974	-0.0245981513681806	-0.00316262073635268	0.30718206069518
15	41.29	41.2924932016727	-0.0199060513396933	-0.00316016636394246	0.240024650589459
16	41.27	41.2731453597386	-0.0197995537619999	-0.0031604526808434	0.00543303450087765
17	41.04	41.0486067124392	-0.0588955580630466	-0.00307166391677844	-1.99266394346721
18	40.9	40.9053233476935	-0.07501943528306	-0.00304205230068141	-0.821335942029
19	40.89	40.8914075502777	-0.0633397589181768	-0.00305936976826737	0.594729161605545
20	40.72	40.7258005645861	-0.0828929751436773	-0.00303596358724405	-0.995406373780797
21	40.72	40.7209408838964	-0.0679704515706822	-0.00305038575273346	0.759548032383008
22	40.58	40.584880935154	-0.0809930601853865	-0.0030402238764905	-0.662774533557788
23	40.24	40.2498765743218	-0.12957887687454	-0.00300961263811978	-2.47256603372478
24	40.07	40.074250005569	-0.138387163676504	-0.00300513175741117	-0.448240041566728
25	40.12	40.0580117723527	-0.115378181635299	0.0587519071097328	1.29182115715795
26	40.1	40.0995831856281	-0.0859718846523846	-0.00301741916449247	1.38099087616352
27	40.1	40.1006658976651	-0.069316744924702	-0.00301951449875203	0.847468612686639
28	40.08	40.0816799407282	-0.0596852524074713	-0.00303995420800641	0.48973876224505
29	40.06	40.0619731689419	-0.0520358959661575	-0.00305356694032228	0.389041153149987
30	39.99	39.9934934700151	-0.0551819318808214	-0.0030490392240099	-0.160032460579175
31	40.05	40.0500535702964	-0.0338043730721001	-0.00307388392220129	1.08755401532798
32	39.66	39.672309155526	-0.0996027090958257	-0.00301213673390254	-3.34764306168403
33	39.66	39.6606476456903	-0.082779016086571	-0.00302488478620099	0.85598491682344
34	39.67	39.6705307872641	-0.06505216507212	-0.003035730814851	0.901965164401479
35	39.56	39.5641491185908	-0.0729587950225451	-0.00303182470087589	-0.40230767202018
36	39.64	39.6390459238431	-0.0446727744001233	-0.00304310805438549	1.43927720668671
37	39.73	39.6820643601204	-0.0280567372809125	0.0455963015402111	0.90311589298975
38	39.7	39.7024882658352	-0.0189263548958714	-0.00361426754759397	0.438957996625694
39	39.7	39.7030868391148	-0.0151907805904221	-0.00361471412272284	0.190072979452948
40	39.68	39.6837261335673	-0.0159887224179164	-0.00361344086647369	-0.0405798182735179
41	39.76	39.761113618057	0.00187739870114834	-0.00363733500949657	0.908756363295003
42	40	39.9973511872504	0.0467155761240067	-0.00368582901278298	2.28098674910422
43	39.96	39.9657886926001	0.031739844058584	-0.00367274976794332	-0.761904628319648
44	40.01	40.0132498863858	0.034747512134722	-0.00367487080253303	0.153026648064286
45	40.01	40.0145747520173	0.0283534337762807	-0.00367122986019488	-0.32533527697936
46	40.01	40.0144389015728	0.0229031579474176	-0.00366872392676351	-0.27732060894897
47	40	40.0045528351555	0.0166302431348601	-0.00366639511793735	-0.319183088499056
48	39.91	39.9164907405033	-0.00339856641637932	-0.00366039124057445	-1.01913112631678
49	39.86	39.8304526815677	-0.0190965970453849	0.0317594691201597	-0.83955993266865
50	39.79	39.7934720734949	-0.022475658488028	-0.0030426351700077	-0.164529041217416
51	39.79	39.7924626686976	-0.0183686811146941	-0.00304303188038616	0.20897249038329
52	39.8	39.8022878726012	-0.0129738145812875	-0.00304988158238495	0.274390633366302
53	39.64	39.6468710139236	-0.0402276741106775	-0.00302088063079823	-1.38636948088415
54	39.55	39.5544238270231	-0.0502183701235838	-0.00301228352088342	-0.508267825735278
55	39.36	39.3667107916579	-0.0765232218571488	-0.00299400490547728	-1.33832870702638
56	39.28	39.2831826190994	-0.0778633576636562	-0.00299325297617586	-0.06818602114093

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 41.85 & 41.85 & 0 & 0 & 0 \tabularnewline
2 & 41.75 & 41.7562066210638 & -0.0065553124913993 & -0.00511075876723255 & -0.61157554965322 \tabularnewline
3 & 41.75 & 41.7549293310928 & -0.00611880030325368 & -0.00509238564705291 & 0.05512048631084 \tabularnewline
4 & 41.75 & 41.7549006548992 & -0.00542960596175323 & -0.00508223033860989 & 0.0623942577348153 \tabularnewline
5 & 41.58 & 41.5899273756818 & -0.0272834162103662 & -0.00530433967981116 & -1.61054141317511 \tabularnewline
6 & 41.61 & 41.6137934117889 & -0.0193904508997543 & -0.00524428569938085 & 0.51065660381463 \tabularnewline
7 & 41.42 & 41.4299975197799 & -0.0467618215237257 & -0.00540492067399878 & -1.62835288439185 \tabularnewline
8 & 41.37 & 41.3756214929032 & -0.0480930062245208 & -0.00541105014653086 & -0.0749965969536968 \tabularnewline
9 & 41.37 & 41.3741024961183 & -0.0396888198675224 & -0.00538037049466777 & 0.456988108410448 \tabularnewline
10 & 41.33 & 41.3353541870175 & -0.0395155883299458 & -0.00537986584236436 & 0.00920458601168563 \tabularnewline
11 & 41.37 & 41.3732397749297 & -0.0250679142824497 & -0.00534613862050466 & 0.756197181506416 \tabularnewline
12 & 41.34 & 41.3454217860621 & -0.0255857061126666 & -0.00534710983358388 & -0.0268366330650689 \tabularnewline
13 & 41.33 & 41.2866304499283 & -0.0315349549944941 & 0.0442367032332191 & -0.379472745287853 \tabularnewline
14 & 41.29 & 41.2924523769974 & -0.0245981513681806 & -0.00316262073635268 & 0.30718206069518 \tabularnewline
15 & 41.29 & 41.2924932016727 & -0.0199060513396933 & -0.00316016636394246 & 0.240024650589459 \tabularnewline
16 & 41.27 & 41.2731453597386 & -0.0197995537619999 & -0.0031604526808434 & 0.00543303450087765 \tabularnewline
17 & 41.04 & 41.0486067124392 & -0.0588955580630466 & -0.00307166391677844 & -1.99266394346721 \tabularnewline
18 & 40.9 & 40.9053233476935 & -0.07501943528306 & -0.00304205230068141 & -0.821335942029 \tabularnewline
19 & 40.89 & 40.8914075502777 & -0.0633397589181768 & -0.00305936976826737 & 0.594729161605545 \tabularnewline
20 & 40.72 & 40.7258005645861 & -0.0828929751436773 & -0.00303596358724405 & -0.995406373780797 \tabularnewline
21 & 40.72 & 40.7209408838964 & -0.0679704515706822 & -0.00305038575273346 & 0.759548032383008 \tabularnewline
22 & 40.58 & 40.584880935154 & -0.0809930601853865 & -0.0030402238764905 & -0.662774533557788 \tabularnewline
23 & 40.24 & 40.2498765743218 & -0.12957887687454 & -0.00300961263811978 & -2.47256603372478 \tabularnewline
24 & 40.07 & 40.074250005569 & -0.138387163676504 & -0.00300513175741117 & -0.448240041566728 \tabularnewline
25 & 40.12 & 40.0580117723527 & -0.115378181635299 & 0.0587519071097328 & 1.29182115715795 \tabularnewline
26 & 40.1 & 40.0995831856281 & -0.0859718846523846 & -0.00301741916449247 & 1.38099087616352 \tabularnewline
27 & 40.1 & 40.1006658976651 & -0.069316744924702 & -0.00301951449875203 & 0.847468612686639 \tabularnewline
28 & 40.08 & 40.0816799407282 & -0.0596852524074713 & -0.00303995420800641 & 0.48973876224505 \tabularnewline
29 & 40.06 & 40.0619731689419 & -0.0520358959661575 & -0.00305356694032228 & 0.389041153149987 \tabularnewline
30 & 39.99 & 39.9934934700151 & -0.0551819318808214 & -0.0030490392240099 & -0.160032460579175 \tabularnewline
31 & 40.05 & 40.0500535702964 & -0.0338043730721001 & -0.00307388392220129 & 1.08755401532798 \tabularnewline
32 & 39.66 & 39.672309155526 & -0.0996027090958257 & -0.00301213673390254 & -3.34764306168403 \tabularnewline
33 & 39.66 & 39.6606476456903 & -0.082779016086571 & -0.00302488478620099 & 0.85598491682344 \tabularnewline
34 & 39.67 & 39.6705307872641 & -0.06505216507212 & -0.003035730814851 & 0.901965164401479 \tabularnewline
35 & 39.56 & 39.5641491185908 & -0.0729587950225451 & -0.00303182470087589 & -0.40230767202018 \tabularnewline
36 & 39.64 & 39.6390459238431 & -0.0446727744001233 & -0.00304310805438549 & 1.43927720668671 \tabularnewline
37 & 39.73 & 39.6820643601204 & -0.0280567372809125 & 0.0455963015402111 & 0.90311589298975 \tabularnewline
38 & 39.7 & 39.7024882658352 & -0.0189263548958714 & -0.00361426754759397 & 0.438957996625694 \tabularnewline
39 & 39.7 & 39.7030868391148 & -0.0151907805904221 & -0.00361471412272284 & 0.190072979452948 \tabularnewline
40 & 39.68 & 39.6837261335673 & -0.0159887224179164 & -0.00361344086647369 & -0.0405798182735179 \tabularnewline
41 & 39.76 & 39.761113618057 & 0.00187739870114834 & -0.00363733500949657 & 0.908756363295003 \tabularnewline
42 & 40 & 39.9973511872504 & 0.0467155761240067 & -0.00368582901278298 & 2.28098674910422 \tabularnewline
43 & 39.96 & 39.9657886926001 & 0.031739844058584 & -0.00367274976794332 & -0.761904628319648 \tabularnewline
44 & 40.01 & 40.0132498863858 & 0.034747512134722 & -0.00367487080253303 & 0.153026648064286 \tabularnewline
45 & 40.01 & 40.0145747520173 & 0.0283534337762807 & -0.00367122986019488 & -0.32533527697936 \tabularnewline
46 & 40.01 & 40.0144389015728 & 0.0229031579474176 & -0.00366872392676351 & -0.27732060894897 \tabularnewline
47 & 40 & 40.0045528351555 & 0.0166302431348601 & -0.00366639511793735 & -0.319183088499056 \tabularnewline
48 & 39.91 & 39.9164907405033 & -0.00339856641637932 & -0.00366039124057445 & -1.01913112631678 \tabularnewline
49 & 39.86 & 39.8304526815677 & -0.0190965970453849 & 0.0317594691201597 & -0.83955993266865 \tabularnewline
50 & 39.79 & 39.7934720734949 & -0.022475658488028 & -0.0030426351700077 & -0.164529041217416 \tabularnewline
51 & 39.79 & 39.7924626686976 & -0.0183686811146941 & -0.00304303188038616 & 0.20897249038329 \tabularnewline
52 & 39.8 & 39.8022878726012 & -0.0129738145812875 & -0.00304988158238495 & 0.274390633366302 \tabularnewline
53 & 39.64 & 39.6468710139236 & -0.0402276741106775 & -0.00302088063079823 & -1.38636948088415 \tabularnewline
54 & 39.55 & 39.5544238270231 & -0.0502183701235838 & -0.00301228352088342 & -0.508267825735278 \tabularnewline
55 & 39.36 & 39.3667107916579 & -0.0765232218571488 & -0.00299400490547728 & -1.33832870702638 \tabularnewline
56 & 39.28 & 39.2831826190994 & -0.0778633576636562 & -0.00299325297617586 & -0.06818602114093 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112393&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]41.85[/C][C]41.85[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]41.75[/C][C]41.7562066210638[/C][C]-0.0065553124913993[/C][C]-0.00511075876723255[/C][C]-0.61157554965322[/C][/ROW]
[ROW][C]3[/C][C]41.75[/C][C]41.7549293310928[/C][C]-0.00611880030325368[/C][C]-0.00509238564705291[/C][C]0.05512048631084[/C][/ROW]
[ROW][C]4[/C][C]41.75[/C][C]41.7549006548992[/C][C]-0.00542960596175323[/C][C]-0.00508223033860989[/C][C]0.0623942577348153[/C][/ROW]
[ROW][C]5[/C][C]41.58[/C][C]41.5899273756818[/C][C]-0.0272834162103662[/C][C]-0.00530433967981116[/C][C]-1.61054141317511[/C][/ROW]
[ROW][C]6[/C][C]41.61[/C][C]41.6137934117889[/C][C]-0.0193904508997543[/C][C]-0.00524428569938085[/C][C]0.51065660381463[/C][/ROW]
[ROW][C]7[/C][C]41.42[/C][C]41.4299975197799[/C][C]-0.0467618215237257[/C][C]-0.00540492067399878[/C][C]-1.62835288439185[/C][/ROW]
[ROW][C]8[/C][C]41.37[/C][C]41.3756214929032[/C][C]-0.0480930062245208[/C][C]-0.00541105014653086[/C][C]-0.0749965969536968[/C][/ROW]
[ROW][C]9[/C][C]41.37[/C][C]41.3741024961183[/C][C]-0.0396888198675224[/C][C]-0.00538037049466777[/C][C]0.456988108410448[/C][/ROW]
[ROW][C]10[/C][C]41.33[/C][C]41.3353541870175[/C][C]-0.0395155883299458[/C][C]-0.00537986584236436[/C][C]0.00920458601168563[/C][/ROW]
[ROW][C]11[/C][C]41.37[/C][C]41.3732397749297[/C][C]-0.0250679142824497[/C][C]-0.00534613862050466[/C][C]0.756197181506416[/C][/ROW]
[ROW][C]12[/C][C]41.34[/C][C]41.3454217860621[/C][C]-0.0255857061126666[/C][C]-0.00534710983358388[/C][C]-0.0268366330650689[/C][/ROW]
[ROW][C]13[/C][C]41.33[/C][C]41.2866304499283[/C][C]-0.0315349549944941[/C][C]0.0442367032332191[/C][C]-0.379472745287853[/C][/ROW]
[ROW][C]14[/C][C]41.29[/C][C]41.2924523769974[/C][C]-0.0245981513681806[/C][C]-0.00316262073635268[/C][C]0.30718206069518[/C][/ROW]
[ROW][C]15[/C][C]41.29[/C][C]41.2924932016727[/C][C]-0.0199060513396933[/C][C]-0.00316016636394246[/C][C]0.240024650589459[/C][/ROW]
[ROW][C]16[/C][C]41.27[/C][C]41.2731453597386[/C][C]-0.0197995537619999[/C][C]-0.0031604526808434[/C][C]0.00543303450087765[/C][/ROW]
[ROW][C]17[/C][C]41.04[/C][C]41.0486067124392[/C][C]-0.0588955580630466[/C][C]-0.00307166391677844[/C][C]-1.99266394346721[/C][/ROW]
[ROW][C]18[/C][C]40.9[/C][C]40.9053233476935[/C][C]-0.07501943528306[/C][C]-0.00304205230068141[/C][C]-0.821335942029[/C][/ROW]
[ROW][C]19[/C][C]40.89[/C][C]40.8914075502777[/C][C]-0.0633397589181768[/C][C]-0.00305936976826737[/C][C]0.594729161605545[/C][/ROW]
[ROW][C]20[/C][C]40.72[/C][C]40.7258005645861[/C][C]-0.0828929751436773[/C][C]-0.00303596358724405[/C][C]-0.995406373780797[/C][/ROW]
[ROW][C]21[/C][C]40.72[/C][C]40.7209408838964[/C][C]-0.0679704515706822[/C][C]-0.00305038575273346[/C][C]0.759548032383008[/C][/ROW]
[ROW][C]22[/C][C]40.58[/C][C]40.584880935154[/C][C]-0.0809930601853865[/C][C]-0.0030402238764905[/C][C]-0.662774533557788[/C][/ROW]
[ROW][C]23[/C][C]40.24[/C][C]40.2498765743218[/C][C]-0.12957887687454[/C][C]-0.00300961263811978[/C][C]-2.47256603372478[/C][/ROW]
[ROW][C]24[/C][C]40.07[/C][C]40.074250005569[/C][C]-0.138387163676504[/C][C]-0.00300513175741117[/C][C]-0.448240041566728[/C][/ROW]
[ROW][C]25[/C][C]40.12[/C][C]40.0580117723527[/C][C]-0.115378181635299[/C][C]0.0587519071097328[/C][C]1.29182115715795[/C][/ROW]
[ROW][C]26[/C][C]40.1[/C][C]40.0995831856281[/C][C]-0.0859718846523846[/C][C]-0.00301741916449247[/C][C]1.38099087616352[/C][/ROW]
[ROW][C]27[/C][C]40.1[/C][C]40.1006658976651[/C][C]-0.069316744924702[/C][C]-0.00301951449875203[/C][C]0.847468612686639[/C][/ROW]
[ROW][C]28[/C][C]40.08[/C][C]40.0816799407282[/C][C]-0.0596852524074713[/C][C]-0.00303995420800641[/C][C]0.48973876224505[/C][/ROW]
[ROW][C]29[/C][C]40.06[/C][C]40.0619731689419[/C][C]-0.0520358959661575[/C][C]-0.00305356694032228[/C][C]0.389041153149987[/C][/ROW]
[ROW][C]30[/C][C]39.99[/C][C]39.9934934700151[/C][C]-0.0551819318808214[/C][C]-0.0030490392240099[/C][C]-0.160032460579175[/C][/ROW]
[ROW][C]31[/C][C]40.05[/C][C]40.0500535702964[/C][C]-0.0338043730721001[/C][C]-0.00307388392220129[/C][C]1.08755401532798[/C][/ROW]
[ROW][C]32[/C][C]39.66[/C][C]39.672309155526[/C][C]-0.0996027090958257[/C][C]-0.00301213673390254[/C][C]-3.34764306168403[/C][/ROW]
[ROW][C]33[/C][C]39.66[/C][C]39.6606476456903[/C][C]-0.082779016086571[/C][C]-0.00302488478620099[/C][C]0.85598491682344[/C][/ROW]
[ROW][C]34[/C][C]39.67[/C][C]39.6705307872641[/C][C]-0.06505216507212[/C][C]-0.003035730814851[/C][C]0.901965164401479[/C][/ROW]
[ROW][C]35[/C][C]39.56[/C][C]39.5641491185908[/C][C]-0.0729587950225451[/C][C]-0.00303182470087589[/C][C]-0.40230767202018[/C][/ROW]
[ROW][C]36[/C][C]39.64[/C][C]39.6390459238431[/C][C]-0.0446727744001233[/C][C]-0.00304310805438549[/C][C]1.43927720668671[/C][/ROW]
[ROW][C]37[/C][C]39.73[/C][C]39.6820643601204[/C][C]-0.0280567372809125[/C][C]0.0455963015402111[/C][C]0.90311589298975[/C][/ROW]
[ROW][C]38[/C][C]39.7[/C][C]39.7024882658352[/C][C]-0.0189263548958714[/C][C]-0.00361426754759397[/C][C]0.438957996625694[/C][/ROW]
[ROW][C]39[/C][C]39.7[/C][C]39.7030868391148[/C][C]-0.0151907805904221[/C][C]-0.00361471412272284[/C][C]0.190072979452948[/C][/ROW]
[ROW][C]40[/C][C]39.68[/C][C]39.6837261335673[/C][C]-0.0159887224179164[/C][C]-0.00361344086647369[/C][C]-0.0405798182735179[/C][/ROW]
[ROW][C]41[/C][C]39.76[/C][C]39.761113618057[/C][C]0.00187739870114834[/C][C]-0.00363733500949657[/C][C]0.908756363295003[/C][/ROW]
[ROW][C]42[/C][C]40[/C][C]39.9973511872504[/C][C]0.0467155761240067[/C][C]-0.00368582901278298[/C][C]2.28098674910422[/C][/ROW]
[ROW][C]43[/C][C]39.96[/C][C]39.9657886926001[/C][C]0.031739844058584[/C][C]-0.00367274976794332[/C][C]-0.761904628319648[/C][/ROW]
[ROW][C]44[/C][C]40.01[/C][C]40.0132498863858[/C][C]0.034747512134722[/C][C]-0.00367487080253303[/C][C]0.153026648064286[/C][/ROW]
[ROW][C]45[/C][C]40.01[/C][C]40.0145747520173[/C][C]0.0283534337762807[/C][C]-0.00367122986019488[/C][C]-0.32533527697936[/C][/ROW]
[ROW][C]46[/C][C]40.01[/C][C]40.0144389015728[/C][C]0.0229031579474176[/C][C]-0.00366872392676351[/C][C]-0.27732060894897[/C][/ROW]
[ROW][C]47[/C][C]40[/C][C]40.0045528351555[/C][C]0.0166302431348601[/C][C]-0.00366639511793735[/C][C]-0.319183088499056[/C][/ROW]
[ROW][C]48[/C][C]39.91[/C][C]39.9164907405033[/C][C]-0.00339856641637932[/C][C]-0.00366039124057445[/C][C]-1.01913112631678[/C][/ROW]
[ROW][C]49[/C][C]39.86[/C][C]39.8304526815677[/C][C]-0.0190965970453849[/C][C]0.0317594691201597[/C][C]-0.83955993266865[/C][/ROW]
[ROW][C]50[/C][C]39.79[/C][C]39.7934720734949[/C][C]-0.022475658488028[/C][C]-0.0030426351700077[/C][C]-0.164529041217416[/C][/ROW]
[ROW][C]51[/C][C]39.79[/C][C]39.7924626686976[/C][C]-0.0183686811146941[/C][C]-0.00304303188038616[/C][C]0.20897249038329[/C][/ROW]
[ROW][C]52[/C][C]39.8[/C][C]39.8022878726012[/C][C]-0.0129738145812875[/C][C]-0.00304988158238495[/C][C]0.274390633366302[/C][/ROW]
[ROW][C]53[/C][C]39.64[/C][C]39.6468710139236[/C][C]-0.0402276741106775[/C][C]-0.00302088063079823[/C][C]-1.38636948088415[/C][/ROW]
[ROW][C]54[/C][C]39.55[/C][C]39.5544238270231[/C][C]-0.0502183701235838[/C][C]-0.00301228352088342[/C][C]-0.508267825735278[/C][/ROW]
[ROW][C]55[/C][C]39.36[/C][C]39.3667107916579[/C][C]-0.0765232218571488[/C][C]-0.00299400490547728[/C][C]-1.33832870702638[/C][/ROW]
[ROW][C]56[/C][C]39.28[/C][C]39.2831826190994[/C][C]-0.0778633576636562[/C][C]-0.00299325297617586[/C][C]-0.06818602114093[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112393&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	41.85	41.85	0	0	0
2	41.75	41.7562066210638	-0.0065553124913993	-0.00511075876723255	-0.61157554965322
3	41.75	41.7549293310928	-0.00611880030325368	-0.00509238564705291	0.05512048631084
4	41.75	41.7549006548992	-0.00542960596175323	-0.00508223033860989	0.0623942577348153
5	41.58	41.5899273756818	-0.0272834162103662	-0.00530433967981116	-1.61054141317511
6	41.61	41.6137934117889	-0.0193904508997543	-0.00524428569938085	0.51065660381463
7	41.42	41.4299975197799	-0.0467618215237257	-0.00540492067399878	-1.62835288439185
8	41.37	41.3756214929032	-0.0480930062245208	-0.00541105014653086	-0.0749965969536968
9	41.37	41.3741024961183	-0.0396888198675224	-0.00538037049466777	0.456988108410448
10	41.33	41.3353541870175	-0.0395155883299458	-0.00537986584236436	0.00920458601168563
11	41.37	41.3732397749297	-0.0250679142824497	-0.00534613862050466	0.756197181506416
12	41.34	41.3454217860621	-0.0255857061126666	-0.00534710983358388	-0.0268366330650689
13	41.33	41.2866304499283	-0.0315349549944941	0.0442367032332191	-0.379472745287853
14	41.29	41.2924523769974	-0.0245981513681806	-0.00316262073635268	0.30718206069518
15	41.29	41.2924932016727	-0.0199060513396933	-0.00316016636394246	0.240024650589459
16	41.27	41.2731453597386	-0.0197995537619999	-0.0031604526808434	0.00543303450087765
17	41.04	41.0486067124392	-0.0588955580630466	-0.00307166391677844	-1.99266394346721
18	40.9	40.9053233476935	-0.07501943528306	-0.00304205230068141	-0.821335942029
19	40.89	40.8914075502777	-0.0633397589181768	-0.00305936976826737	0.594729161605545
20	40.72	40.7258005645861	-0.0828929751436773	-0.00303596358724405	-0.995406373780797
21	40.72	40.7209408838964	-0.0679704515706822	-0.00305038575273346	0.759548032383008
22	40.58	40.584880935154	-0.0809930601853865	-0.0030402238764905	-0.662774533557788
23	40.24	40.2498765743218	-0.12957887687454	-0.00300961263811978	-2.47256603372478
24	40.07	40.074250005569	-0.138387163676504	-0.00300513175741117	-0.448240041566728
25	40.12	40.0580117723527	-0.115378181635299	0.0587519071097328	1.29182115715795
26	40.1	40.0995831856281	-0.0859718846523846	-0.00301741916449247	1.38099087616352
27	40.1	40.1006658976651	-0.069316744924702	-0.00301951449875203	0.847468612686639
28	40.08	40.0816799407282	-0.0596852524074713	-0.00303995420800641	0.48973876224505
29	40.06	40.0619731689419	-0.0520358959661575	-0.00305356694032228	0.389041153149987
30	39.99	39.9934934700151	-0.0551819318808214	-0.0030490392240099	-0.160032460579175
31	40.05	40.0500535702964	-0.0338043730721001	-0.00307388392220129	1.08755401532798
32	39.66	39.672309155526	-0.0996027090958257	-0.00301213673390254	-3.34764306168403
33	39.66	39.6606476456903	-0.082779016086571	-0.00302488478620099	0.85598491682344
34	39.67	39.6705307872641	-0.06505216507212	-0.003035730814851	0.901965164401479
35	39.56	39.5641491185908	-0.0729587950225451	-0.00303182470087589	-0.40230767202018
36	39.64	39.6390459238431	-0.0446727744001233	-0.00304310805438549	1.43927720668671
37	39.73	39.6820643601204	-0.0280567372809125	0.0455963015402111	0.90311589298975
38	39.7	39.7024882658352	-0.0189263548958714	-0.00361426754759397	0.438957996625694
39	39.7	39.7030868391148	-0.0151907805904221	-0.00361471412272284	0.190072979452948
40	39.68	39.6837261335673	-0.0159887224179164	-0.00361344086647369	-0.0405798182735179
41	39.76	39.761113618057	0.00187739870114834	-0.00363733500949657	0.908756363295003
42	40	39.9973511872504	0.0467155761240067	-0.00368582901278298	2.28098674910422
43	39.96	39.9657886926001	0.031739844058584	-0.00367274976794332	-0.761904628319648
44	40.01	40.0132498863858	0.034747512134722	-0.00367487080253303	0.153026648064286
45	40.01	40.0145747520173	0.0283534337762807	-0.00367122986019488	-0.32533527697936
46	40.01	40.0144389015728	0.0229031579474176	-0.00366872392676351	-0.27732060894897
47	40	40.0045528351555	0.0166302431348601	-0.00366639511793735	-0.319183088499056
48	39.91	39.9164907405033	-0.00339856641637932	-0.00366039124057445	-1.01913112631678
49	39.86	39.8304526815677	-0.0190965970453849	0.0317594691201597	-0.83955993266865
50	39.79	39.7934720734949	-0.022475658488028	-0.0030426351700077	-0.164529041217416
51	39.79	39.7924626686976	-0.0183686811146941	-0.00304303188038616	0.20897249038329
52	39.8	39.8022878726012	-0.0129738145812875	-0.00304988158238495	0.274390633366302
53	39.64	39.6468710139236	-0.0402276741106775	-0.00302088063079823	-1.38636948088415
54	39.55	39.5544238270231	-0.0502183701235838	-0.00301228352088342	-0.508267825735278
55	39.36	39.3667107916579	-0.0765232218571488	-0.00299400490547728	-1.33832870702638
56	39.28	39.2831826190994	-0.0778633576636562	-0.00299325297617586	-0.06818602114093

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