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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Wed, 08 Dec 2010 18:52:36 +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/08/t1291834251tu7yr8qbjwq70hh.htm/, Retrieved Fri, 03 May 2024 07:30:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107079, Retrieved Fri, 03 May 2024 07:30:59 +0000

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Estimated Impact

176

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   [Exponential Smoothing] [exponential smoot...] [2010-12-08 09:17:39] [d6e648f00513dd750579ba7880c5fbf5]
- RMP     [Structural Time Series Models] [] [2010-12-08 15:02:01] [dcd1a35a8985187cb1e9de87792355b2]
-    D        [Structural Time Series Models] [workshop 8: minit...] [2010-12-08 18:52:36] [95216a33d813bfae7986b08ea3322626] [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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107079&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107079&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107079&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	'George Udny Yule' @ 72.249.76.132

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	33	33	0	0	0
2	24	25.1903556387449	-0.610047262420502	-0.450144547718309	-0.963023421655199
3	24	24.4733601347727	-0.620940151387968	-0.451543461463715	-0.0198827854267806
4	31	30.1787841830944	0.239771363709969	-0.427215740355950	1.14921667958191
5	25	26.2288129291087	-0.440533594326057	-0.434942891838708	-0.742713084483823
6	28	28.0210582884723	-0.0379749772177109	-0.432166432667586	0.38919316971834
7	24	24.9779342291042	-0.614616794780569	-0.435004490680034	-0.518059771009083
8	25	25.2721263558739	-0.433603178356616	-0.434334791448820	0.155563788639703
9	16	17.7024380419771	-1.88716416120165	-0.438451521005782	-1.2160653434482
10	17	17.194661835341	-1.60237634158497	-0.437829359413632	0.234408638890516
11	11	12.0599508647134	-2.33761696390631	-0.439073054851426	-0.599236086482824
12	12	12.0330231837167	-1.85429295790152	-0.438438707548212	0.391572297318048
13	39	24.3167885329999	0.94738486405003	12.3192947927676	2.81025303082098
14	19	20.7925806847687	0.032237798145887	-1.23088084425629	-0.634235368158009
15	14	16.076950823633	-0.962808959179362	-1.24834167170857	-0.80328836083839
16	15	16.0796115596703	-0.759554864089283	-1.24853109004327	0.163313662388561
17	7	9.29693109312882	-2.02819363283425	-1.24409994266194	-1.01806081797757
18	12	12.357988819427	-0.956214024631568	-1.24758122260851	0.860231737992992
19	12	12.9736476978211	-0.625112611362688	-1.24845160259970	0.265731064749389
20	14	14.8177763312605	-0.104967215997169	-1.24952582485189	0.417490374580361
21	9	10.9127548237295	-0.905485232257669	-1.24823620557461	-0.642567275388757
22	8	9.36107559993452	-1.04161831882235	-1.24806543412147	-0.109276555287163
23	4	5.70482027844626	-1.59246359821649	-1.24752759291244	-0.442183509147414
24	7	7.63241270569157	-0.850841309577437	-1.24809114321748	0.595335122492025
25	3	-5.43772082590198	-3.37485503107380	10.5211638642697	-2.25361024116694
26	5	3.93071454974965	-0.74602263931394	-0.748788387677978	1.93339134881815
27	0	1.11503877430278	-1.18091753484906	-0.753605878263642	-0.350091592608624
28	-2	-1.07083210373207	-1.39270865507962	-0.753406384682896	-0.169955612780373
29	6	5.38557999839507	0.261575214782769	-0.757629669224546	1.32683300598187
30	11	10.8505477484856	1.35805819265193	-0.760190168034108	0.879651443606117
31	9	10.1238682238577	0.918798706430092	-0.759362534990196	-0.352478426150297
32	17	16.7611642055105	2.12364484507238	-0.761144704950777	0.96696643627517
33	21	21.3335011438028	2.63956010549129	-0.76173987876042	0.414095543860203
34	21	22.0906176054539	2.24294606516569	-0.761383608398902	-0.318358221409514
35	41	39.168793558609	5.36863380120591	-0.763568994312551	2.50904945708690
36	57	55.7956487522097	7.7407032271021	-0.764859726135171	1.90414715922798
37	65	58.3741914581075	6.66692930425877	7.51358395362737	-0.926778159402315
38	68	68.1725670864185	7.31633559516851	-0.644943931141612	0.48938205121411
39	73	73.9215005208736	6.98674708849556	-0.647655874052798	-0.265134064217428
40	71	73.0252437697251	5.32548263576433	-0.646469895810642	-1.33322574914109
41	71	72.6422213727454	4.12241690687484	-0.644169740685577	-0.965138447656826
42	70	71.5534156617387	3.02429414196163	-0.64225073362856	-0.881106963016065
43	69	70.3757828419728	2.13892316051264	-0.641002576810647	-0.710526565190972
44	65	66.6630095671488	0.9059792295439	-0.63963810437744	-0.989577579553343
45	57	59.1164306015566	-0.874945083090986	-0.638100990657305	-1.42949902586407
46	57	57.7278640607268	-0.98316365242145	-0.638028262186549	-0.0868679558690346
47	57	57.5051067301631	-0.822946802362558	-0.638112069065936	0.128610899515467
48	55	55.7934821405912	-1.01019234046785	-0.638035842242919	-0.150310111429313
49	65	57.2375227417504	-0.49801498783661	7.33857965424223	0.434439157825238
50	65	64.3999146470969	1.0957633912927	-0.5927434710817	1.21757324718585
51	64	64.7279652975532	0.934262810075358	-0.593801557162885	-0.129862427695030
52	60	61.3479053684302	0.0250841990802132	-0.5932838941088	-0.729690949199987
53	43	46.2353318657163	-3.16506613022563	-0.588421804687931	-2.55958571065827
54	47	46.9169092491301	-2.35449711859742	-0.58955092345406	0.650444582346629
55	40	41.1802299743272	-3.06714919028493	-0.58875010331673	-0.571951867356779
56	31	32.5590830818117	-4.23738691622008	-0.587717809587045	-0.939284314023068
57	27	27.6969061074955	-4.36903032551721	-0.587627243821579	-0.105668979398577
58	24	24.4001876604050	-4.14309341284519	-0.587748273612354	0.181363988632838
59	23	23.0921035779440	-3.54575062302940	-0.58799732923217	0.479509129300897
60	17	17.8794595760055	-3.89697179387457	-0.58788336264238	-0.281941902964288

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 33 & 33 & 0 & 0 & 0 \tabularnewline
2 & 24 & 25.1903556387449 & -0.610047262420502 & -0.450144547718309 & -0.963023421655199 \tabularnewline
3 & 24 & 24.4733601347727 & -0.620940151387968 & -0.451543461463715 & -0.0198827854267806 \tabularnewline
4 & 31 & 30.1787841830944 & 0.239771363709969 & -0.427215740355950 & 1.14921667958191 \tabularnewline
5 & 25 & 26.2288129291087 & -0.440533594326057 & -0.434942891838708 & -0.742713084483823 \tabularnewline
6 & 28 & 28.0210582884723 & -0.0379749772177109 & -0.432166432667586 & 0.38919316971834 \tabularnewline
7 & 24 & 24.9779342291042 & -0.614616794780569 & -0.435004490680034 & -0.518059771009083 \tabularnewline
8 & 25 & 25.2721263558739 & -0.433603178356616 & -0.434334791448820 & 0.155563788639703 \tabularnewline
9 & 16 & 17.7024380419771 & -1.88716416120165 & -0.438451521005782 & -1.2160653434482 \tabularnewline
10 & 17 & 17.194661835341 & -1.60237634158497 & -0.437829359413632 & 0.234408638890516 \tabularnewline
11 & 11 & 12.0599508647134 & -2.33761696390631 & -0.439073054851426 & -0.599236086482824 \tabularnewline
12 & 12 & 12.0330231837167 & -1.85429295790152 & -0.438438707548212 & 0.391572297318048 \tabularnewline
13 & 39 & 24.3167885329999 & 0.94738486405003 & 12.3192947927676 & 2.81025303082098 \tabularnewline
14 & 19 & 20.7925806847687 & 0.032237798145887 & -1.23088084425629 & -0.634235368158009 \tabularnewline
15 & 14 & 16.076950823633 & -0.962808959179362 & -1.24834167170857 & -0.80328836083839 \tabularnewline
16 & 15 & 16.0796115596703 & -0.759554864089283 & -1.24853109004327 & 0.163313662388561 \tabularnewline
17 & 7 & 9.29693109312882 & -2.02819363283425 & -1.24409994266194 & -1.01806081797757 \tabularnewline
18 & 12 & 12.357988819427 & -0.956214024631568 & -1.24758122260851 & 0.860231737992992 \tabularnewline
19 & 12 & 12.9736476978211 & -0.625112611362688 & -1.24845160259970 & 0.265731064749389 \tabularnewline
20 & 14 & 14.8177763312605 & -0.104967215997169 & -1.24952582485189 & 0.417490374580361 \tabularnewline
21 & 9 & 10.9127548237295 & -0.905485232257669 & -1.24823620557461 & -0.642567275388757 \tabularnewline
22 & 8 & 9.36107559993452 & -1.04161831882235 & -1.24806543412147 & -0.109276555287163 \tabularnewline
23 & 4 & 5.70482027844626 & -1.59246359821649 & -1.24752759291244 & -0.442183509147414 \tabularnewline
24 & 7 & 7.63241270569157 & -0.850841309577437 & -1.24809114321748 & 0.595335122492025 \tabularnewline
25 & 3 & -5.43772082590198 & -3.37485503107380 & 10.5211638642697 & -2.25361024116694 \tabularnewline
26 & 5 & 3.93071454974965 & -0.74602263931394 & -0.748788387677978 & 1.93339134881815 \tabularnewline
27 & 0 & 1.11503877430278 & -1.18091753484906 & -0.753605878263642 & -0.350091592608624 \tabularnewline
28 & -2 & -1.07083210373207 & -1.39270865507962 & -0.753406384682896 & -0.169955612780373 \tabularnewline
29 & 6 & 5.38557999839507 & 0.261575214782769 & -0.757629669224546 & 1.32683300598187 \tabularnewline
30 & 11 & 10.8505477484856 & 1.35805819265193 & -0.760190168034108 & 0.879651443606117 \tabularnewline
31 & 9 & 10.1238682238577 & 0.918798706430092 & -0.759362534990196 & -0.352478426150297 \tabularnewline
32 & 17 & 16.7611642055105 & 2.12364484507238 & -0.761144704950777 & 0.96696643627517 \tabularnewline
33 & 21 & 21.3335011438028 & 2.63956010549129 & -0.76173987876042 & 0.414095543860203 \tabularnewline
34 & 21 & 22.0906176054539 & 2.24294606516569 & -0.761383608398902 & -0.318358221409514 \tabularnewline
35 & 41 & 39.168793558609 & 5.36863380120591 & -0.763568994312551 & 2.50904945708690 \tabularnewline
36 & 57 & 55.7956487522097 & 7.7407032271021 & -0.764859726135171 & 1.90414715922798 \tabularnewline
37 & 65 & 58.3741914581075 & 6.66692930425877 & 7.51358395362737 & -0.926778159402315 \tabularnewline
38 & 68 & 68.1725670864185 & 7.31633559516851 & -0.644943931141612 & 0.48938205121411 \tabularnewline
39 & 73 & 73.9215005208736 & 6.98674708849556 & -0.647655874052798 & -0.265134064217428 \tabularnewline
40 & 71 & 73.0252437697251 & 5.32548263576433 & -0.646469895810642 & -1.33322574914109 \tabularnewline
41 & 71 & 72.6422213727454 & 4.12241690687484 & -0.644169740685577 & -0.965138447656826 \tabularnewline
42 & 70 & 71.5534156617387 & 3.02429414196163 & -0.64225073362856 & -0.881106963016065 \tabularnewline
43 & 69 & 70.3757828419728 & 2.13892316051264 & -0.641002576810647 & -0.710526565190972 \tabularnewline
44 & 65 & 66.6630095671488 & 0.9059792295439 & -0.63963810437744 & -0.989577579553343 \tabularnewline
45 & 57 & 59.1164306015566 & -0.874945083090986 & -0.638100990657305 & -1.42949902586407 \tabularnewline
46 & 57 & 57.7278640607268 & -0.98316365242145 & -0.638028262186549 & -0.0868679558690346 \tabularnewline
47 & 57 & 57.5051067301631 & -0.822946802362558 & -0.638112069065936 & 0.128610899515467 \tabularnewline
48 & 55 & 55.7934821405912 & -1.01019234046785 & -0.638035842242919 & -0.150310111429313 \tabularnewline
49 & 65 & 57.2375227417504 & -0.49801498783661 & 7.33857965424223 & 0.434439157825238 \tabularnewline
50 & 65 & 64.3999146470969 & 1.0957633912927 & -0.5927434710817 & 1.21757324718585 \tabularnewline
51 & 64 & 64.7279652975532 & 0.934262810075358 & -0.593801557162885 & -0.129862427695030 \tabularnewline
52 & 60 & 61.3479053684302 & 0.0250841990802132 & -0.5932838941088 & -0.729690949199987 \tabularnewline
53 & 43 & 46.2353318657163 & -3.16506613022563 & -0.588421804687931 & -2.55958571065827 \tabularnewline
54 & 47 & 46.9169092491301 & -2.35449711859742 & -0.58955092345406 & 0.650444582346629 \tabularnewline
55 & 40 & 41.1802299743272 & -3.06714919028493 & -0.58875010331673 & -0.571951867356779 \tabularnewline
56 & 31 & 32.5590830818117 & -4.23738691622008 & -0.587717809587045 & -0.939284314023068 \tabularnewline
57 & 27 & 27.6969061074955 & -4.36903032551721 & -0.587627243821579 & -0.105668979398577 \tabularnewline
58 & 24 & 24.4001876604050 & -4.14309341284519 & -0.587748273612354 & 0.181363988632838 \tabularnewline
59 & 23 & 23.0921035779440 & -3.54575062302940 & -0.58799732923217 & 0.479509129300897 \tabularnewline
60 & 17 & 17.8794595760055 & -3.89697179387457 & -0.58788336264238 & -0.281941902964288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107079&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]33[/C][C]33[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]24[/C][C]25.1903556387449[/C][C]-0.610047262420502[/C][C]-0.450144547718309[/C][C]-0.963023421655199[/C][/ROW]
[ROW][C]3[/C][C]24[/C][C]24.4733601347727[/C][C]-0.620940151387968[/C][C]-0.451543461463715[/C][C]-0.0198827854267806[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]30.1787841830944[/C][C]0.239771363709969[/C][C]-0.427215740355950[/C][C]1.14921667958191[/C][/ROW]
[ROW][C]5[/C][C]25[/C][C]26.2288129291087[/C][C]-0.440533594326057[/C][C]-0.434942891838708[/C][C]-0.742713084483823[/C][/ROW]
[ROW][C]6[/C][C]28[/C][C]28.0210582884723[/C][C]-0.0379749772177109[/C][C]-0.432166432667586[/C][C]0.38919316971834[/C][/ROW]
[ROW][C]7[/C][C]24[/C][C]24.9779342291042[/C][C]-0.614616794780569[/C][C]-0.435004490680034[/C][C]-0.518059771009083[/C][/ROW]
[ROW][C]8[/C][C]25[/C][C]25.2721263558739[/C][C]-0.433603178356616[/C][C]-0.434334791448820[/C][C]0.155563788639703[/C][/ROW]
[ROW][C]9[/C][C]16[/C][C]17.7024380419771[/C][C]-1.88716416120165[/C][C]-0.438451521005782[/C][C]-1.2160653434482[/C][/ROW]
[ROW][C]10[/C][C]17[/C][C]17.194661835341[/C][C]-1.60237634158497[/C][C]-0.437829359413632[/C][C]0.234408638890516[/C][/ROW]
[ROW][C]11[/C][C]11[/C][C]12.0599508647134[/C][C]-2.33761696390631[/C][C]-0.439073054851426[/C][C]-0.599236086482824[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]12.0330231837167[/C][C]-1.85429295790152[/C][C]-0.438438707548212[/C][C]0.391572297318048[/C][/ROW]
[ROW][C]13[/C][C]39[/C][C]24.3167885329999[/C][C]0.94738486405003[/C][C]12.3192947927676[/C][C]2.81025303082098[/C][/ROW]
[ROW][C]14[/C][C]19[/C][C]20.7925806847687[/C][C]0.032237798145887[/C][C]-1.23088084425629[/C][C]-0.634235368158009[/C][/ROW]
[ROW][C]15[/C][C]14[/C][C]16.076950823633[/C][C]-0.962808959179362[/C][C]-1.24834167170857[/C][C]-0.80328836083839[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]16.0796115596703[/C][C]-0.759554864089283[/C][C]-1.24853109004327[/C][C]0.163313662388561[/C][/ROW]
[ROW][C]17[/C][C]7[/C][C]9.29693109312882[/C][C]-2.02819363283425[/C][C]-1.24409994266194[/C][C]-1.01806081797757[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]12.357988819427[/C][C]-0.956214024631568[/C][C]-1.24758122260851[/C][C]0.860231737992992[/C][/ROW]
[ROW][C]19[/C][C]12[/C][C]12.9736476978211[/C][C]-0.625112611362688[/C][C]-1.24845160259970[/C][C]0.265731064749389[/C][/ROW]
[ROW][C]20[/C][C]14[/C][C]14.8177763312605[/C][C]-0.104967215997169[/C][C]-1.24952582485189[/C][C]0.417490374580361[/C][/ROW]
[ROW][C]21[/C][C]9[/C][C]10.9127548237295[/C][C]-0.905485232257669[/C][C]-1.24823620557461[/C][C]-0.642567275388757[/C][/ROW]
[ROW][C]22[/C][C]8[/C][C]9.36107559993452[/C][C]-1.04161831882235[/C][C]-1.24806543412147[/C][C]-0.109276555287163[/C][/ROW]
[ROW][C]23[/C][C]4[/C][C]5.70482027844626[/C][C]-1.59246359821649[/C][C]-1.24752759291244[/C][C]-0.442183509147414[/C][/ROW]
[ROW][C]24[/C][C]7[/C][C]7.63241270569157[/C][C]-0.850841309577437[/C][C]-1.24809114321748[/C][C]0.595335122492025[/C][/ROW]
[ROW][C]25[/C][C]3[/C][C]-5.43772082590198[/C][C]-3.37485503107380[/C][C]10.5211638642697[/C][C]-2.25361024116694[/C][/ROW]
[ROW][C]26[/C][C]5[/C][C]3.93071454974965[/C][C]-0.74602263931394[/C][C]-0.748788387677978[/C][C]1.93339134881815[/C][/ROW]
[ROW][C]27[/C][C]0[/C][C]1.11503877430278[/C][C]-1.18091753484906[/C][C]-0.753605878263642[/C][C]-0.350091592608624[/C][/ROW]
[ROW][C]28[/C][C]-2[/C][C]-1.07083210373207[/C][C]-1.39270865507962[/C][C]-0.753406384682896[/C][C]-0.169955612780373[/C][/ROW]
[ROW][C]29[/C][C]6[/C][C]5.38557999839507[/C][C]0.261575214782769[/C][C]-0.757629669224546[/C][C]1.32683300598187[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]10.8505477484856[/C][C]1.35805819265193[/C][C]-0.760190168034108[/C][C]0.879651443606117[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.1238682238577[/C][C]0.918798706430092[/C][C]-0.759362534990196[/C][C]-0.352478426150297[/C][/ROW]
[ROW][C]32[/C][C]17[/C][C]16.7611642055105[/C][C]2.12364484507238[/C][C]-0.761144704950777[/C][C]0.96696643627517[/C][/ROW]
[ROW][C]33[/C][C]21[/C][C]21.3335011438028[/C][C]2.63956010549129[/C][C]-0.76173987876042[/C][C]0.414095543860203[/C][/ROW]
[ROW][C]34[/C][C]21[/C][C]22.0906176054539[/C][C]2.24294606516569[/C][C]-0.761383608398902[/C][C]-0.318358221409514[/C][/ROW]
[ROW][C]35[/C][C]41[/C][C]39.168793558609[/C][C]5.36863380120591[/C][C]-0.763568994312551[/C][C]2.50904945708690[/C][/ROW]
[ROW][C]36[/C][C]57[/C][C]55.7956487522097[/C][C]7.7407032271021[/C][C]-0.764859726135171[/C][C]1.90414715922798[/C][/ROW]
[ROW][C]37[/C][C]65[/C][C]58.3741914581075[/C][C]6.66692930425877[/C][C]7.51358395362737[/C][C]-0.926778159402315[/C][/ROW]
[ROW][C]38[/C][C]68[/C][C]68.1725670864185[/C][C]7.31633559516851[/C][C]-0.644943931141612[/C][C]0.48938205121411[/C][/ROW]
[ROW][C]39[/C][C]73[/C][C]73.9215005208736[/C][C]6.98674708849556[/C][C]-0.647655874052798[/C][C]-0.265134064217428[/C][/ROW]
[ROW][C]40[/C][C]71[/C][C]73.0252437697251[/C][C]5.32548263576433[/C][C]-0.646469895810642[/C][C]-1.33322574914109[/C][/ROW]
[ROW][C]41[/C][C]71[/C][C]72.6422213727454[/C][C]4.12241690687484[/C][C]-0.644169740685577[/C][C]-0.965138447656826[/C][/ROW]
[ROW][C]42[/C][C]70[/C][C]71.5534156617387[/C][C]3.02429414196163[/C][C]-0.64225073362856[/C][C]-0.881106963016065[/C][/ROW]
[ROW][C]43[/C][C]69[/C][C]70.3757828419728[/C][C]2.13892316051264[/C][C]-0.641002576810647[/C][C]-0.710526565190972[/C][/ROW]
[ROW][C]44[/C][C]65[/C][C]66.6630095671488[/C][C]0.9059792295439[/C][C]-0.63963810437744[/C][C]-0.989577579553343[/C][/ROW]
[ROW][C]45[/C][C]57[/C][C]59.1164306015566[/C][C]-0.874945083090986[/C][C]-0.638100990657305[/C][C]-1.42949902586407[/C][/ROW]
[ROW][C]46[/C][C]57[/C][C]57.7278640607268[/C][C]-0.98316365242145[/C][C]-0.638028262186549[/C][C]-0.0868679558690346[/C][/ROW]
[ROW][C]47[/C][C]57[/C][C]57.5051067301631[/C][C]-0.822946802362558[/C][C]-0.638112069065936[/C][C]0.128610899515467[/C][/ROW]
[ROW][C]48[/C][C]55[/C][C]55.7934821405912[/C][C]-1.01019234046785[/C][C]-0.638035842242919[/C][C]-0.150310111429313[/C][/ROW]
[ROW][C]49[/C][C]65[/C][C]57.2375227417504[/C][C]-0.49801498783661[/C][C]7.33857965424223[/C][C]0.434439157825238[/C][/ROW]
[ROW][C]50[/C][C]65[/C][C]64.3999146470969[/C][C]1.0957633912927[/C][C]-0.5927434710817[/C][C]1.21757324718585[/C][/ROW]
[ROW][C]51[/C][C]64[/C][C]64.7279652975532[/C][C]0.934262810075358[/C][C]-0.593801557162885[/C][C]-0.129862427695030[/C][/ROW]
[ROW][C]52[/C][C]60[/C][C]61.3479053684302[/C][C]0.0250841990802132[/C][C]-0.5932838941088[/C][C]-0.729690949199987[/C][/ROW]
[ROW][C]53[/C][C]43[/C][C]46.2353318657163[/C][C]-3.16506613022563[/C][C]-0.588421804687931[/C][C]-2.55958571065827[/C][/ROW]
[ROW][C]54[/C][C]47[/C][C]46.9169092491301[/C][C]-2.35449711859742[/C][C]-0.58955092345406[/C][C]0.650444582346629[/C][/ROW]
[ROW][C]55[/C][C]40[/C][C]41.1802299743272[/C][C]-3.06714919028493[/C][C]-0.58875010331673[/C][C]-0.571951867356779[/C][/ROW]
[ROW][C]56[/C][C]31[/C][C]32.5590830818117[/C][C]-4.23738691622008[/C][C]-0.587717809587045[/C][C]-0.939284314023068[/C][/ROW]
[ROW][C]57[/C][C]27[/C][C]27.6969061074955[/C][C]-4.36903032551721[/C][C]-0.587627243821579[/C][C]-0.105668979398577[/C][/ROW]
[ROW][C]58[/C][C]24[/C][C]24.4001876604050[/C][C]-4.14309341284519[/C][C]-0.587748273612354[/C][C]0.181363988632838[/C][/ROW]
[ROW][C]59[/C][C]23[/C][C]23.0921035779440[/C][C]-3.54575062302940[/C][C]-0.58799732923217[/C][C]0.479509129300897[/C][/ROW]
[ROW][C]60[/C][C]17[/C][C]17.8794595760055[/C][C]-3.89697179387457[/C][C]-0.58788336264238[/C][C]-0.281941902964288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107079&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107079&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	33	33	0	0	0
2	24	25.1903556387449	-0.610047262420502	-0.450144547718309	-0.963023421655199
3	24	24.4733601347727	-0.620940151387968	-0.451543461463715	-0.0198827854267806
4	31	30.1787841830944	0.239771363709969	-0.427215740355950	1.14921667958191
5	25	26.2288129291087	-0.440533594326057	-0.434942891838708	-0.742713084483823
6	28	28.0210582884723	-0.0379749772177109	-0.432166432667586	0.38919316971834
7	24	24.9779342291042	-0.614616794780569	-0.435004490680034	-0.518059771009083
8	25	25.2721263558739	-0.433603178356616	-0.434334791448820	0.155563788639703
9	16	17.7024380419771	-1.88716416120165	-0.438451521005782	-1.2160653434482
10	17	17.194661835341	-1.60237634158497	-0.437829359413632	0.234408638890516
11	11	12.0599508647134	-2.33761696390631	-0.439073054851426	-0.599236086482824
12	12	12.0330231837167	-1.85429295790152	-0.438438707548212	0.391572297318048
13	39	24.3167885329999	0.94738486405003	12.3192947927676	2.81025303082098
14	19	20.7925806847687	0.032237798145887	-1.23088084425629	-0.634235368158009
15	14	16.076950823633	-0.962808959179362	-1.24834167170857	-0.80328836083839
16	15	16.0796115596703	-0.759554864089283	-1.24853109004327	0.163313662388561
17	7	9.29693109312882	-2.02819363283425	-1.24409994266194	-1.01806081797757
18	12	12.357988819427	-0.956214024631568	-1.24758122260851	0.860231737992992
19	12	12.9736476978211	-0.625112611362688	-1.24845160259970	0.265731064749389
20	14	14.8177763312605	-0.104967215997169	-1.24952582485189	0.417490374580361
21	9	10.9127548237295	-0.905485232257669	-1.24823620557461	-0.642567275388757
22	8	9.36107559993452	-1.04161831882235	-1.24806543412147	-0.109276555287163
23	4	5.70482027844626	-1.59246359821649	-1.24752759291244	-0.442183509147414
24	7	7.63241270569157	-0.850841309577437	-1.24809114321748	0.595335122492025
25	3	-5.43772082590198	-3.37485503107380	10.5211638642697	-2.25361024116694
26	5	3.93071454974965	-0.74602263931394	-0.748788387677978	1.93339134881815
27	0	1.11503877430278	-1.18091753484906	-0.753605878263642	-0.350091592608624
28	-2	-1.07083210373207	-1.39270865507962	-0.753406384682896	-0.169955612780373
29	6	5.38557999839507	0.261575214782769	-0.757629669224546	1.32683300598187
30	11	10.8505477484856	1.35805819265193	-0.760190168034108	0.879651443606117
31	9	10.1238682238577	0.918798706430092	-0.759362534990196	-0.352478426150297
32	17	16.7611642055105	2.12364484507238	-0.761144704950777	0.96696643627517
33	21	21.3335011438028	2.63956010549129	-0.76173987876042	0.414095543860203
34	21	22.0906176054539	2.24294606516569	-0.761383608398902	-0.318358221409514
35	41	39.168793558609	5.36863380120591	-0.763568994312551	2.50904945708690
36	57	55.7956487522097	7.7407032271021	-0.764859726135171	1.90414715922798
37	65	58.3741914581075	6.66692930425877	7.51358395362737	-0.926778159402315
38	68	68.1725670864185	7.31633559516851	-0.644943931141612	0.48938205121411
39	73	73.9215005208736	6.98674708849556	-0.647655874052798	-0.265134064217428
40	71	73.0252437697251	5.32548263576433	-0.646469895810642	-1.33322574914109
41	71	72.6422213727454	4.12241690687484	-0.644169740685577	-0.965138447656826
42	70	71.5534156617387	3.02429414196163	-0.64225073362856	-0.881106963016065
43	69	70.3757828419728	2.13892316051264	-0.641002576810647	-0.710526565190972
44	65	66.6630095671488	0.9059792295439	-0.63963810437744	-0.989577579553343
45	57	59.1164306015566	-0.874945083090986	-0.638100990657305	-1.42949902586407
46	57	57.7278640607268	-0.98316365242145	-0.638028262186549	-0.0868679558690346
47	57	57.5051067301631	-0.822946802362558	-0.638112069065936	0.128610899515467
48	55	55.7934821405912	-1.01019234046785	-0.638035842242919	-0.150310111429313
49	65	57.2375227417504	-0.49801498783661	7.33857965424223	0.434439157825238
50	65	64.3999146470969	1.0957633912927	-0.5927434710817	1.21757324718585
51	64	64.7279652975532	0.934262810075358	-0.593801557162885	-0.129862427695030
52	60	61.3479053684302	0.0250841990802132	-0.5932838941088	-0.729690949199987
53	43	46.2353318657163	-3.16506613022563	-0.588421804687931	-2.55958571065827
54	47	46.9169092491301	-2.35449711859742	-0.58955092345406	0.650444582346629
55	40	41.1802299743272	-3.06714919028493	-0.58875010331673	-0.571951867356779
56	31	32.5590830818117	-4.23738691622008	-0.587717809587045	-0.939284314023068
57	27	27.6969061074955	-4.36903032551721	-0.587627243821579	-0.105668979398577
58	24	24.4001876604050	-4.14309341284519	-0.587748273612354	0.181363988632838
59	23	23.0921035779440	-3.54575062302940	-0.58799732923217	0.479509129300897
60	17	17.8794595760055	-3.89697179387457	-0.58788336264238	-0.281941902964288

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