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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 05:11:14 -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/t1259928753w7kr4qs76bq8r68.htm/, Retrieved Sun, 28 Apr 2024 16:43:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63364, Retrieved Sun, 28 Apr 2024 16:43:08 +0000

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Estimated Impact

136

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]
-   PD    [Structural Time Series Models] [ws 8 Ad hoc forec...] [2009-12-02 20:13:08] [616e2df490b611f6cb7080068870ecbd]
-   PD        [Structural Time Series Models] [Workshop 9] [2009-12-04 12:11:14] [ee8fc1691ecec7724e0ca78f0c288737] [Current]
-    D          [Structural Time Series Models] [WS9] [2009-12-11 12:50:35] [4fe1472705bb0a32f118ba3ca90ffa8e] 

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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	3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63364&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]3 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=63364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63364&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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	130	130	0	0	0
2	136.7	136.367057828602	0.630208184674506	0.33294217139793	0.272842817566885
3	138.1	137.768724550275	0.794038097596958	0.331275449725199	0.0499837910544096
4	139.5	139.169692012107	0.953164950046443	0.330307987893046	0.0380816851227145
5	140.4	140.069631636707	0.937815643949498	0.330368363292941	-0.00328146923356395
6	144.6	144.272218645449	1.92194982112160	0.327781354551030	0.199505914391713
7	151.4	151.074895810215	3.42413007092849	0.325104189785074	0.296985923938357
8	147.9	147.572277302328	1.27117173613999	0.32772269767161	-0.420644306343971
9	141.5	141.170282422522	-1.12493196443187	0.329717577477688	-0.465548323432991
10	143.8	143.470894280492	-0.0528573227405167	0.329105719508506	0.207751253142674
11	143.6	143.270876230316	-0.0989624633882864	0.329123769683694	-0.00892340455994578
12	150.5	150.171465652433	2.09510767367058	0.328534347567275	0.424403096274875
13	150.1	153.314222495505	2.41269254797843	-3.21422249550453	0.0733323664042182
14	154.9	154.632046683188	2.09059321989080	0.267953316811941	-0.0550740527935843
15	162.1	161.840391276096	3.69973421064062	0.259608723904112	0.309496421253031
16	176.7	176.452599279098	7.12501872782178	0.247400720902381	0.660607469422424
17	186.6	186.354731580756	7.99611327774849	0.245268419243931	0.168217224225065
18	194.8	194.554839092645	8.060083831815	0.245160907355309	0.0123608491103113
19	196.3	196.052464976282	6.00230025392198	0.247535023718065	-0.397733162419592
20	228.8	228.559046820038	14.3132558776717	0.240953179962246	1.60657663713145
21	267.2	266.963153345359	21.8676301968556	0.236846654641158	1.46041567835275
22	237.2	236.957083821215	5.60067540458895	0.242916178784985	-3.14483021246542
23	254.7	254.458039571973	9.33255133199796	0.241960428026839	0.721479912865826
24	258.2	257.957718023774	7.50335166549481	0.242281976225541	-0.353639719235440
25	257.9	261.306046989247	6.22011184848393	-3.40604698924655	-0.271182100385260
26	269.6	269.265605797001	6.74385829763111	0.33439420299912	0.0944157221534327
27	266.9	266.555575730354	3.77388286423888	0.344424269646375	-0.572238442842766
28	269.6	269.254793351029	3.43665443749521	0.345206648971427	-0.0650923936875169
29	253.9	253.545226466808	-2.56862919323225	0.354773533192117	-1.16013337661295
30	258.6	258.247720289902	-0.28839848783271	0.352279710098033	0.440683416779277
31	274.2	273.851461673947	4.69516342349625	0.348538326053149	0.963317664498001
32	301.5	301.155115155358	11.7848944064614	0.344884844642375	1.37055962912208
33	304.5	304.154140609704	9.02971324150773	0.34585939029616	-0.532643318661363
34	285.1	284.751975891273	0.11352690597516	0.348024108727178	-1.72374891935216
35	287.7	287.352105841634	0.893333930100083	0.347894158366242	0.150759969462628
36	265.5	265.151277430633	-6.3491655007422	0.348722569367069	-1.40019739405715
37	264.1	266.984017672203	-3.80867081523427	-2.88401767220313	0.52129495213587
38	276.1	275.706428229419	0.00571458472281927	0.393571770580869	0.702245328349281
39	258.9	258.492909667148	-5.40137346438244	0.407090332851748	-1.04273022036732
40	239.1	238.685147965348	-9.9214001008343	0.41485203465207	-0.872826881480062
41	250.1	249.692887278613	-3.35709387020559	0.40711272138743	1.26837748428990
42	276.8	276.400518292493	6.07136162915467	0.399481707506643	1.82233684748827
43	297.6	297.203084808251	10.6909887667440	0.396915191749157	0.893008351968816
44	295.4	295.00154302172	6.64795512717441	0.398456978279838	-0.78159982278172
45	283	282.599979341105	0.674046795508806	0.400020658895461	-1.15491249164287
46	275.8	275.399535669419	-1.79541912412954	0.40046433058067	-0.477419207314867
47	279.7	279.299755939012	-0.00922642994470024	0.400244060988287	0.345325094484995
48	254.6	254.199089886348	-7.87815363636262	0.400910113652003	-1.5213066456228
49	234.6	239.59105373833	-9.97320162490814	-4.99105373832986	-0.423578758696938
50	176.9	176.883972691118	-26.1264252815684	0.0160273088820607	-3.00773987518483
51	148.1	148.082305938854	-26.9662706801057	0.0176940611455903	-0.162044253101789
52	122.7	122.682975962899	-26.4746839066591	0.0170240371013885	0.0949497145288048
53	124.9	124.891394112677	-17.4785492879924	0.0086058873233586	1.73846415536458
54	121.6	121.594250927976	-13.0311497014309	0.00574907202364687	0.859642457463539
55	128.4	128.396993439590	-6.81125309463789	0.00300656040985147	1.20238315363588
56	144.5	144.499168183160	0.374391004588585	0.000831816839605412	1.38914646959723
57	151.8	151.799619394261	2.54642267922465	0.000380605739477454	0.419912832725945
58	167.1	167.100189713847	6.54620280755454	-0.000189713847451409	0.773275288419044
59	173.8	173.800194434478	6.59443650791234	-0.000194434478038297	0.00932504549962803
60	203.7	203.700685429368	13.9034855252060	-0.000685429367630973	1.41306574068010
61	199.8	200.936451384707	8.70683387840304	-1.13645138470706	-1.04135052103551

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 130 & 130 & 0 & 0 & 0 \tabularnewline
2 & 136.7 & 136.367057828602 & 0.630208184674506 & 0.33294217139793 & 0.272842817566885 \tabularnewline
3 & 138.1 & 137.768724550275 & 0.794038097596958 & 0.331275449725199 & 0.0499837910544096 \tabularnewline
4 & 139.5 & 139.169692012107 & 0.953164950046443 & 0.330307987893046 & 0.0380816851227145 \tabularnewline
5 & 140.4 & 140.069631636707 & 0.937815643949498 & 0.330368363292941 & -0.00328146923356395 \tabularnewline
6 & 144.6 & 144.272218645449 & 1.92194982112160 & 0.327781354551030 & 0.199505914391713 \tabularnewline
7 & 151.4 & 151.074895810215 & 3.42413007092849 & 0.325104189785074 & 0.296985923938357 \tabularnewline
8 & 147.9 & 147.572277302328 & 1.27117173613999 & 0.32772269767161 & -0.420644306343971 \tabularnewline
9 & 141.5 & 141.170282422522 & -1.12493196443187 & 0.329717577477688 & -0.465548323432991 \tabularnewline
10 & 143.8 & 143.470894280492 & -0.0528573227405167 & 0.329105719508506 & 0.207751253142674 \tabularnewline
11 & 143.6 & 143.270876230316 & -0.0989624633882864 & 0.329123769683694 & -0.00892340455994578 \tabularnewline
12 & 150.5 & 150.171465652433 & 2.09510767367058 & 0.328534347567275 & 0.424403096274875 \tabularnewline
13 & 150.1 & 153.314222495505 & 2.41269254797843 & -3.21422249550453 & 0.0733323664042182 \tabularnewline
14 & 154.9 & 154.632046683188 & 2.09059321989080 & 0.267953316811941 & -0.0550740527935843 \tabularnewline
15 & 162.1 & 161.840391276096 & 3.69973421064062 & 0.259608723904112 & 0.309496421253031 \tabularnewline
16 & 176.7 & 176.452599279098 & 7.12501872782178 & 0.247400720902381 & 0.660607469422424 \tabularnewline
17 & 186.6 & 186.354731580756 & 7.99611327774849 & 0.245268419243931 & 0.168217224225065 \tabularnewline
18 & 194.8 & 194.554839092645 & 8.060083831815 & 0.245160907355309 & 0.0123608491103113 \tabularnewline
19 & 196.3 & 196.052464976282 & 6.00230025392198 & 0.247535023718065 & -0.397733162419592 \tabularnewline
20 & 228.8 & 228.559046820038 & 14.3132558776717 & 0.240953179962246 & 1.60657663713145 \tabularnewline
21 & 267.2 & 266.963153345359 & 21.8676301968556 & 0.236846654641158 & 1.46041567835275 \tabularnewline
22 & 237.2 & 236.957083821215 & 5.60067540458895 & 0.242916178784985 & -3.14483021246542 \tabularnewline
23 & 254.7 & 254.458039571973 & 9.33255133199796 & 0.241960428026839 & 0.721479912865826 \tabularnewline
24 & 258.2 & 257.957718023774 & 7.50335166549481 & 0.242281976225541 & -0.353639719235440 \tabularnewline
25 & 257.9 & 261.306046989247 & 6.22011184848393 & -3.40604698924655 & -0.271182100385260 \tabularnewline
26 & 269.6 & 269.265605797001 & 6.74385829763111 & 0.33439420299912 & 0.0944157221534327 \tabularnewline
27 & 266.9 & 266.555575730354 & 3.77388286423888 & 0.344424269646375 & -0.572238442842766 \tabularnewline
28 & 269.6 & 269.254793351029 & 3.43665443749521 & 0.345206648971427 & -0.0650923936875169 \tabularnewline
29 & 253.9 & 253.545226466808 & -2.56862919323225 & 0.354773533192117 & -1.16013337661295 \tabularnewline
30 & 258.6 & 258.247720289902 & -0.28839848783271 & 0.352279710098033 & 0.440683416779277 \tabularnewline
31 & 274.2 & 273.851461673947 & 4.69516342349625 & 0.348538326053149 & 0.963317664498001 \tabularnewline
32 & 301.5 & 301.155115155358 & 11.7848944064614 & 0.344884844642375 & 1.37055962912208 \tabularnewline
33 & 304.5 & 304.154140609704 & 9.02971324150773 & 0.34585939029616 & -0.532643318661363 \tabularnewline
34 & 285.1 & 284.751975891273 & 0.11352690597516 & 0.348024108727178 & -1.72374891935216 \tabularnewline
35 & 287.7 & 287.352105841634 & 0.893333930100083 & 0.347894158366242 & 0.150759969462628 \tabularnewline
36 & 265.5 & 265.151277430633 & -6.3491655007422 & 0.348722569367069 & -1.40019739405715 \tabularnewline
37 & 264.1 & 266.984017672203 & -3.80867081523427 & -2.88401767220313 & 0.52129495213587 \tabularnewline
38 & 276.1 & 275.706428229419 & 0.00571458472281927 & 0.393571770580869 & 0.702245328349281 \tabularnewline
39 & 258.9 & 258.492909667148 & -5.40137346438244 & 0.407090332851748 & -1.04273022036732 \tabularnewline
40 & 239.1 & 238.685147965348 & -9.9214001008343 & 0.41485203465207 & -0.872826881480062 \tabularnewline
41 & 250.1 & 249.692887278613 & -3.35709387020559 & 0.40711272138743 & 1.26837748428990 \tabularnewline
42 & 276.8 & 276.400518292493 & 6.07136162915467 & 0.399481707506643 & 1.82233684748827 \tabularnewline
43 & 297.6 & 297.203084808251 & 10.6909887667440 & 0.396915191749157 & 0.893008351968816 \tabularnewline
44 & 295.4 & 295.00154302172 & 6.64795512717441 & 0.398456978279838 & -0.78159982278172 \tabularnewline
45 & 283 & 282.599979341105 & 0.674046795508806 & 0.400020658895461 & -1.15491249164287 \tabularnewline
46 & 275.8 & 275.399535669419 & -1.79541912412954 & 0.40046433058067 & -0.477419207314867 \tabularnewline
47 & 279.7 & 279.299755939012 & -0.00922642994470024 & 0.400244060988287 & 0.345325094484995 \tabularnewline
48 & 254.6 & 254.199089886348 & -7.87815363636262 & 0.400910113652003 & -1.5213066456228 \tabularnewline
49 & 234.6 & 239.59105373833 & -9.97320162490814 & -4.99105373832986 & -0.423578758696938 \tabularnewline
50 & 176.9 & 176.883972691118 & -26.1264252815684 & 0.0160273088820607 & -3.00773987518483 \tabularnewline
51 & 148.1 & 148.082305938854 & -26.9662706801057 & 0.0176940611455903 & -0.162044253101789 \tabularnewline
52 & 122.7 & 122.682975962899 & -26.4746839066591 & 0.0170240371013885 & 0.0949497145288048 \tabularnewline
53 & 124.9 & 124.891394112677 & -17.4785492879924 & 0.0086058873233586 & 1.73846415536458 \tabularnewline
54 & 121.6 & 121.594250927976 & -13.0311497014309 & 0.00574907202364687 & 0.859642457463539 \tabularnewline
55 & 128.4 & 128.396993439590 & -6.81125309463789 & 0.00300656040985147 & 1.20238315363588 \tabularnewline
56 & 144.5 & 144.499168183160 & 0.374391004588585 & 0.000831816839605412 & 1.38914646959723 \tabularnewline
57 & 151.8 & 151.799619394261 & 2.54642267922465 & 0.000380605739477454 & 0.419912832725945 \tabularnewline
58 & 167.1 & 167.100189713847 & 6.54620280755454 & -0.000189713847451409 & 0.773275288419044 \tabularnewline
59 & 173.8 & 173.800194434478 & 6.59443650791234 & -0.000194434478038297 & 0.00932504549962803 \tabularnewline
60 & 203.7 & 203.700685429368 & 13.9034855252060 & -0.000685429367630973 & 1.41306574068010 \tabularnewline
61 & 199.8 & 200.936451384707 & 8.70683387840304 & -1.13645138470706 & -1.04135052103551 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63364&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]130[/C][C]130[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]136.7[/C][C]136.367057828602[/C][C]0.630208184674506[/C][C]0.33294217139793[/C][C]0.272842817566885[/C][/ROW]
[ROW][C]3[/C][C]138.1[/C][C]137.768724550275[/C][C]0.794038097596958[/C][C]0.331275449725199[/C][C]0.0499837910544096[/C][/ROW]
[ROW][C]4[/C][C]139.5[/C][C]139.169692012107[/C][C]0.953164950046443[/C][C]0.330307987893046[/C][C]0.0380816851227145[/C][/ROW]
[ROW][C]5[/C][C]140.4[/C][C]140.069631636707[/C][C]0.937815643949498[/C][C]0.330368363292941[/C][C]-0.00328146923356395[/C][/ROW]
[ROW][C]6[/C][C]144.6[/C][C]144.272218645449[/C][C]1.92194982112160[/C][C]0.327781354551030[/C][C]0.199505914391713[/C][/ROW]
[ROW][C]7[/C][C]151.4[/C][C]151.074895810215[/C][C]3.42413007092849[/C][C]0.325104189785074[/C][C]0.296985923938357[/C][/ROW]
[ROW][C]8[/C][C]147.9[/C][C]147.572277302328[/C][C]1.27117173613999[/C][C]0.32772269767161[/C][C]-0.420644306343971[/C][/ROW]
[ROW][C]9[/C][C]141.5[/C][C]141.170282422522[/C][C]-1.12493196443187[/C][C]0.329717577477688[/C][C]-0.465548323432991[/C][/ROW]
[ROW][C]10[/C][C]143.8[/C][C]143.470894280492[/C][C]-0.0528573227405167[/C][C]0.329105719508506[/C][C]0.207751253142674[/C][/ROW]
[ROW][C]11[/C][C]143.6[/C][C]143.270876230316[/C][C]-0.0989624633882864[/C][C]0.329123769683694[/C][C]-0.00892340455994578[/C][/ROW]
[ROW][C]12[/C][C]150.5[/C][C]150.171465652433[/C][C]2.09510767367058[/C][C]0.328534347567275[/C][C]0.424403096274875[/C][/ROW]
[ROW][C]13[/C][C]150.1[/C][C]153.314222495505[/C][C]2.41269254797843[/C][C]-3.21422249550453[/C][C]0.0733323664042182[/C][/ROW]
[ROW][C]14[/C][C]154.9[/C][C]154.632046683188[/C][C]2.09059321989080[/C][C]0.267953316811941[/C][C]-0.0550740527935843[/C][/ROW]
[ROW][C]15[/C][C]162.1[/C][C]161.840391276096[/C][C]3.69973421064062[/C][C]0.259608723904112[/C][C]0.309496421253031[/C][/ROW]
[ROW][C]16[/C][C]176.7[/C][C]176.452599279098[/C][C]7.12501872782178[/C][C]0.247400720902381[/C][C]0.660607469422424[/C][/ROW]
[ROW][C]17[/C][C]186.6[/C][C]186.354731580756[/C][C]7.99611327774849[/C][C]0.245268419243931[/C][C]0.168217224225065[/C][/ROW]
[ROW][C]18[/C][C]194.8[/C][C]194.554839092645[/C][C]8.060083831815[/C][C]0.245160907355309[/C][C]0.0123608491103113[/C][/ROW]
[ROW][C]19[/C][C]196.3[/C][C]196.052464976282[/C][C]6.00230025392198[/C][C]0.247535023718065[/C][C]-0.397733162419592[/C][/ROW]
[ROW][C]20[/C][C]228.8[/C][C]228.559046820038[/C][C]14.3132558776717[/C][C]0.240953179962246[/C][C]1.60657663713145[/C][/ROW]
[ROW][C]21[/C][C]267.2[/C][C]266.963153345359[/C][C]21.8676301968556[/C][C]0.236846654641158[/C][C]1.46041567835275[/C][/ROW]
[ROW][C]22[/C][C]237.2[/C][C]236.957083821215[/C][C]5.60067540458895[/C][C]0.242916178784985[/C][C]-3.14483021246542[/C][/ROW]
[ROW][C]23[/C][C]254.7[/C][C]254.458039571973[/C][C]9.33255133199796[/C][C]0.241960428026839[/C][C]0.721479912865826[/C][/ROW]
[ROW][C]24[/C][C]258.2[/C][C]257.957718023774[/C][C]7.50335166549481[/C][C]0.242281976225541[/C][C]-0.353639719235440[/C][/ROW]
[ROW][C]25[/C][C]257.9[/C][C]261.306046989247[/C][C]6.22011184848393[/C][C]-3.40604698924655[/C][C]-0.271182100385260[/C][/ROW]
[ROW][C]26[/C][C]269.6[/C][C]269.265605797001[/C][C]6.74385829763111[/C][C]0.33439420299912[/C][C]0.0944157221534327[/C][/ROW]
[ROW][C]27[/C][C]266.9[/C][C]266.555575730354[/C][C]3.77388286423888[/C][C]0.344424269646375[/C][C]-0.572238442842766[/C][/ROW]
[ROW][C]28[/C][C]269.6[/C][C]269.254793351029[/C][C]3.43665443749521[/C][C]0.345206648971427[/C][C]-0.0650923936875169[/C][/ROW]
[ROW][C]29[/C][C]253.9[/C][C]253.545226466808[/C][C]-2.56862919323225[/C][C]0.354773533192117[/C][C]-1.16013337661295[/C][/ROW]
[ROW][C]30[/C][C]258.6[/C][C]258.247720289902[/C][C]-0.28839848783271[/C][C]0.352279710098033[/C][C]0.440683416779277[/C][/ROW]
[ROW][C]31[/C][C]274.2[/C][C]273.851461673947[/C][C]4.69516342349625[/C][C]0.348538326053149[/C][C]0.963317664498001[/C][/ROW]
[ROW][C]32[/C][C]301.5[/C][C]301.155115155358[/C][C]11.7848944064614[/C][C]0.344884844642375[/C][C]1.37055962912208[/C][/ROW]
[ROW][C]33[/C][C]304.5[/C][C]304.154140609704[/C][C]9.02971324150773[/C][C]0.34585939029616[/C][C]-0.532643318661363[/C][/ROW]
[ROW][C]34[/C][C]285.1[/C][C]284.751975891273[/C][C]0.11352690597516[/C][C]0.348024108727178[/C][C]-1.72374891935216[/C][/ROW]
[ROW][C]35[/C][C]287.7[/C][C]287.352105841634[/C][C]0.893333930100083[/C][C]0.347894158366242[/C][C]0.150759969462628[/C][/ROW]
[ROW][C]36[/C][C]265.5[/C][C]265.151277430633[/C][C]-6.3491655007422[/C][C]0.348722569367069[/C][C]-1.40019739405715[/C][/ROW]
[ROW][C]37[/C][C]264.1[/C][C]266.984017672203[/C][C]-3.80867081523427[/C][C]-2.88401767220313[/C][C]0.52129495213587[/C][/ROW]
[ROW][C]38[/C][C]276.1[/C][C]275.706428229419[/C][C]0.00571458472281927[/C][C]0.393571770580869[/C][C]0.702245328349281[/C][/ROW]
[ROW][C]39[/C][C]258.9[/C][C]258.492909667148[/C][C]-5.40137346438244[/C][C]0.407090332851748[/C][C]-1.04273022036732[/C][/ROW]
[ROW][C]40[/C][C]239.1[/C][C]238.685147965348[/C][C]-9.9214001008343[/C][C]0.41485203465207[/C][C]-0.872826881480062[/C][/ROW]
[ROW][C]41[/C][C]250.1[/C][C]249.692887278613[/C][C]-3.35709387020559[/C][C]0.40711272138743[/C][C]1.26837748428990[/C][/ROW]
[ROW][C]42[/C][C]276.8[/C][C]276.400518292493[/C][C]6.07136162915467[/C][C]0.399481707506643[/C][C]1.82233684748827[/C][/ROW]
[ROW][C]43[/C][C]297.6[/C][C]297.203084808251[/C][C]10.6909887667440[/C][C]0.396915191749157[/C][C]0.893008351968816[/C][/ROW]
[ROW][C]44[/C][C]295.4[/C][C]295.00154302172[/C][C]6.64795512717441[/C][C]0.398456978279838[/C][C]-0.78159982278172[/C][/ROW]
[ROW][C]45[/C][C]283[/C][C]282.599979341105[/C][C]0.674046795508806[/C][C]0.400020658895461[/C][C]-1.15491249164287[/C][/ROW]
[ROW][C]46[/C][C]275.8[/C][C]275.399535669419[/C][C]-1.79541912412954[/C][C]0.40046433058067[/C][C]-0.477419207314867[/C][/ROW]
[ROW][C]47[/C][C]279.7[/C][C]279.299755939012[/C][C]-0.00922642994470024[/C][C]0.400244060988287[/C][C]0.345325094484995[/C][/ROW]
[ROW][C]48[/C][C]254.6[/C][C]254.199089886348[/C][C]-7.87815363636262[/C][C]0.400910113652003[/C][C]-1.5213066456228[/C][/ROW]
[ROW][C]49[/C][C]234.6[/C][C]239.59105373833[/C][C]-9.97320162490814[/C][C]-4.99105373832986[/C][C]-0.423578758696938[/C][/ROW]
[ROW][C]50[/C][C]176.9[/C][C]176.883972691118[/C][C]-26.1264252815684[/C][C]0.0160273088820607[/C][C]-3.00773987518483[/C][/ROW]
[ROW][C]51[/C][C]148.1[/C][C]148.082305938854[/C][C]-26.9662706801057[/C][C]0.0176940611455903[/C][C]-0.162044253101789[/C][/ROW]
[ROW][C]52[/C][C]122.7[/C][C]122.682975962899[/C][C]-26.4746839066591[/C][C]0.0170240371013885[/C][C]0.0949497145288048[/C][/ROW]
[ROW][C]53[/C][C]124.9[/C][C]124.891394112677[/C][C]-17.4785492879924[/C][C]0.0086058873233586[/C][C]1.73846415536458[/C][/ROW]
[ROW][C]54[/C][C]121.6[/C][C]121.594250927976[/C][C]-13.0311497014309[/C][C]0.00574907202364687[/C][C]0.859642457463539[/C][/ROW]
[ROW][C]55[/C][C]128.4[/C][C]128.396993439590[/C][C]-6.81125309463789[/C][C]0.00300656040985147[/C][C]1.20238315363588[/C][/ROW]
[ROW][C]56[/C][C]144.5[/C][C]144.499168183160[/C][C]0.374391004588585[/C][C]0.000831816839605412[/C][C]1.38914646959723[/C][/ROW]
[ROW][C]57[/C][C]151.8[/C][C]151.799619394261[/C][C]2.54642267922465[/C][C]0.000380605739477454[/C][C]0.419912832725945[/C][/ROW]
[ROW][C]58[/C][C]167.1[/C][C]167.100189713847[/C][C]6.54620280755454[/C][C]-0.000189713847451409[/C][C]0.773275288419044[/C][/ROW]
[ROW][C]59[/C][C]173.8[/C][C]173.800194434478[/C][C]6.59443650791234[/C][C]-0.000194434478038297[/C][C]0.00932504549962803[/C][/ROW]
[ROW][C]60[/C][C]203.7[/C][C]203.700685429368[/C][C]13.9034855252060[/C][C]-0.000685429367630973[/C][C]1.41306574068010[/C][/ROW]
[ROW][C]61[/C][C]199.8[/C][C]200.936451384707[/C][C]8.70683387840304[/C][C]-1.13645138470706[/C][C]-1.04135052103551[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63364&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	130	130	0	0	0
2	136.7	136.367057828602	0.630208184674506	0.33294217139793	0.272842817566885
3	138.1	137.768724550275	0.794038097596958	0.331275449725199	0.0499837910544096
4	139.5	139.169692012107	0.953164950046443	0.330307987893046	0.0380816851227145
5	140.4	140.069631636707	0.937815643949498	0.330368363292941	-0.00328146923356395
6	144.6	144.272218645449	1.92194982112160	0.327781354551030	0.199505914391713
7	151.4	151.074895810215	3.42413007092849	0.325104189785074	0.296985923938357
8	147.9	147.572277302328	1.27117173613999	0.32772269767161	-0.420644306343971
9	141.5	141.170282422522	-1.12493196443187	0.329717577477688	-0.465548323432991
10	143.8	143.470894280492	-0.0528573227405167	0.329105719508506	0.207751253142674
11	143.6	143.270876230316	-0.0989624633882864	0.329123769683694	-0.00892340455994578
12	150.5	150.171465652433	2.09510767367058	0.328534347567275	0.424403096274875
13	150.1	153.314222495505	2.41269254797843	-3.21422249550453	0.0733323664042182
14	154.9	154.632046683188	2.09059321989080	0.267953316811941	-0.0550740527935843
15	162.1	161.840391276096	3.69973421064062	0.259608723904112	0.309496421253031
16	176.7	176.452599279098	7.12501872782178	0.247400720902381	0.660607469422424
17	186.6	186.354731580756	7.99611327774849	0.245268419243931	0.168217224225065
18	194.8	194.554839092645	8.060083831815	0.245160907355309	0.0123608491103113
19	196.3	196.052464976282	6.00230025392198	0.247535023718065	-0.397733162419592
20	228.8	228.559046820038	14.3132558776717	0.240953179962246	1.60657663713145
21	267.2	266.963153345359	21.8676301968556	0.236846654641158	1.46041567835275
22	237.2	236.957083821215	5.60067540458895	0.242916178784985	-3.14483021246542
23	254.7	254.458039571973	9.33255133199796	0.241960428026839	0.721479912865826
24	258.2	257.957718023774	7.50335166549481	0.242281976225541	-0.353639719235440
25	257.9	261.306046989247	6.22011184848393	-3.40604698924655	-0.271182100385260
26	269.6	269.265605797001	6.74385829763111	0.33439420299912	0.0944157221534327
27	266.9	266.555575730354	3.77388286423888	0.344424269646375	-0.572238442842766
28	269.6	269.254793351029	3.43665443749521	0.345206648971427	-0.0650923936875169
29	253.9	253.545226466808	-2.56862919323225	0.354773533192117	-1.16013337661295
30	258.6	258.247720289902	-0.28839848783271	0.352279710098033	0.440683416779277
31	274.2	273.851461673947	4.69516342349625	0.348538326053149	0.963317664498001
32	301.5	301.155115155358	11.7848944064614	0.344884844642375	1.37055962912208
33	304.5	304.154140609704	9.02971324150773	0.34585939029616	-0.532643318661363
34	285.1	284.751975891273	0.11352690597516	0.348024108727178	-1.72374891935216
35	287.7	287.352105841634	0.893333930100083	0.347894158366242	0.150759969462628
36	265.5	265.151277430633	-6.3491655007422	0.348722569367069	-1.40019739405715
37	264.1	266.984017672203	-3.80867081523427	-2.88401767220313	0.52129495213587
38	276.1	275.706428229419	0.00571458472281927	0.393571770580869	0.702245328349281
39	258.9	258.492909667148	-5.40137346438244	0.407090332851748	-1.04273022036732
40	239.1	238.685147965348	-9.9214001008343	0.41485203465207	-0.872826881480062
41	250.1	249.692887278613	-3.35709387020559	0.40711272138743	1.26837748428990
42	276.8	276.400518292493	6.07136162915467	0.399481707506643	1.82233684748827
43	297.6	297.203084808251	10.6909887667440	0.396915191749157	0.893008351968816
44	295.4	295.00154302172	6.64795512717441	0.398456978279838	-0.78159982278172
45	283	282.599979341105	0.674046795508806	0.400020658895461	-1.15491249164287
46	275.8	275.399535669419	-1.79541912412954	0.40046433058067	-0.477419207314867
47	279.7	279.299755939012	-0.00922642994470024	0.400244060988287	0.345325094484995
48	254.6	254.199089886348	-7.87815363636262	0.400910113652003	-1.5213066456228
49	234.6	239.59105373833	-9.97320162490814	-4.99105373832986	-0.423578758696938
50	176.9	176.883972691118	-26.1264252815684	0.0160273088820607	-3.00773987518483
51	148.1	148.082305938854	-26.9662706801057	0.0176940611455903	-0.162044253101789
52	122.7	122.682975962899	-26.4746839066591	0.0170240371013885	0.0949497145288048
53	124.9	124.891394112677	-17.4785492879924	0.0086058873233586	1.73846415536458
54	121.6	121.594250927976	-13.0311497014309	0.00574907202364687	0.859642457463539
55	128.4	128.396993439590	-6.81125309463789	0.00300656040985147	1.20238315363588
56	144.5	144.499168183160	0.374391004588585	0.000831816839605412	1.38914646959723
57	151.8	151.799619394261	2.54642267922465	0.000380605739477454	0.419912832725945
58	167.1	167.100189713847	6.54620280755454	-0.000189713847451409	0.773275288419044
59	173.8	173.800194434478	6.59443650791234	-0.000194434478038297	0.00932504549962803
60	203.7	203.700685429368	13.9034855252060	-0.000685429367630973	1.41306574068010
61	199.8	200.936451384707	8.70683387840304	-1.13645138470706	-1.04135052103551

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