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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Mon, 27 Dec 2010 12:43:27 +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/27/t1293454098amkbd672yoskedk.htm/, Retrieved Mon, 06 May 2024 14:59:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115941, Retrieved Mon, 06 May 2024 14:59:19 +0000

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User-defined keywords

Structural Time Series Model - Gemiddelde bouwprijzen

Estimated Impact

105

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
-  MPD        [Structural Time Series Models] [Paper Statistiek ] [2010-12-27 12:43:27] [f6fdc0236f011c1845380977efc505f8] [Current]
-   PD          [Structural Time Series Models] [Paper Statistiek ] [2010-12-27 13:54:49] [82c18f3ebe9df70882495121eb816e07] 

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Dataseries X:

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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	'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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115941&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115941&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115941&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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	26	26	0	0	0
2	26	26	0	0	0
3	27	26.4885072347855	0.122153734869542	0.133847388049581	0.311760983373203
4	28	27.1342140507663	0.23311824673463	0.228731269700097	0.457903128645816
5	27	27.4402761398104	0.247518398811714	-0.618866011025374	0.107913243035474
6	29	28.1643886484897	0.334228847833608	0.269053410840415	0.406258323165324
7	27	27.8313690825885	0.214297167706663	0.123584922206004	-0.655240986100755
8	30	28.6681306494107	0.328271109943408	0.35405035208128	0.654335034038774
9	27	28.576317321562	0.243146163020616	-0.869867345353114	-0.473927411775527
10	30	29.1337628874529	0.300739692884556	0.394864744714539	0.319730896984165
11	32	30.3282472607551	0.466701979632872	0.289088806993994	0.931954385446869
12	30	30.3661383325944	0.385580902031455	0.30439219579371	-0.449556794087097
13	32	31.5406984939938	0.540958999188249	-0.71493877512563	0.816191289314981
14	33	32.3308096372961	0.588054594922128	0.289099785352401	0.257863813925656
15	34	33.2162678006596	0.644462653593476	0.327045445164039	0.309688871900484
16	32	33.1134457193897	0.501792720619522	0.0333057824407519	-0.776046862174301
17	34	34.008654119934	0.577398204151658	-0.58710785485183	0.403193878082839
18	37	35.3867462918656	0.730093190432383	0.403052074205044	0.826299175426268
19	37	36.316722751826	0.768221457622207	0.380058217828084	0.207164676898101
20	36	36.7045391387188	0.695527605608356	-0.126966403018158	-0.393774402828982
21	34	36.4234344849801	0.509339759241467	-0.978061212475755	-1.00499537425496
22	38	37.1447859549601	0.549826232698546	0.537152043775514	0.218276631897497
23	41	38.7261111165581	0.746739704924741	0.722375168594884	1.06586943848126
24	41	40.051835646218	0.857323465316116	0.0750966064658244	0.598406805604166
25	44	42.4186846862801	1.14480755991479	-0.660442329009606	1.55667184981305
26	42	42.9089628410352	1.01986481633982	0.0690264697580345	-0.673474327413291
27	45	44.0900904893035	1.05063598480811	0.668566466483218	0.166393242126038
28	45	45.1442502646329	1.05130858965528	-0.149538449644073	0.00363819199614165
29	49	47.4067457389236	1.28205233790169	-0.206433014708675	1.24926768508418
30	54	50.639090066362	1.654148468336	0.453092220188854	2.00708245691218
31	52	52.0253793239282	1.60306204629076	0.374314631884652	-0.276200561016786
32	53	53.5330229191274	1.58485775079644	-0.390314716962754	-0.098442644017665
33	51	53.8143587681823	1.33646050540347	-0.878126138597903	-1.3440302049865
34	55	54.8722489045787	1.28333136006269	0.542527272141132	-0.286763605978873
35	60	57.3719448247025	1.51524762661149	0.8163826553382	1.25381310449318
36	60	59.3928468945365	1.61168619852704	-0.147279755863603	0.521405424874104
37	63	62.0592725970851	1.81269194816893	-0.625363947786413	1.08713816958434
38	60	62.3855664351422	1.52927152021036	-0.174545350128675	-1.53043687322043
39	64	63.6492332048664	1.47863911662716	0.745870122729308	-0.273719438715818
40	65	65.1654641505836	1.48580698381513	-0.22145531398507	0.0387486134101313
41	75	69.7927887275753	2.08450328632359	0.5439036258708	3.2372342629851
42	70	71.3544359730276	1.98482304912494	-0.577247751785819	-0.538416634812738
43	72	72.6263342257513	1.84893187819805	0.43327509655402	-0.734582307536485
44	69	72.726341383867	1.51550795325048	-1.12452274634797	-1.80228975328815
45	75	74.2201765174614	1.51137767322435	0.811989190289589	-0.0223296173603243
46	74	75.2492004618061	1.41942939833184	-0.532600122988277	-0.496746875207814
47	74	75.4387940458657	1.18502542128246	0.388011891902151	-1.26703978914813
48	75	76.3956125126443	1.14152392319615	-1.05640100116612	-0.235129753300575
49	79	77.7158753559662	1.17558672014267	1.01888124341681	0.184136082383642
50	79	79.0564953373397	1.20704348825421	-0.30157772975425	0.169965468519296
51	85	81.8250755278947	1.50465498799256	0.856346515579268	1.60863265377257
52	78	81.85355671232	1.22328543212972	-1.66062818134754	-1.52077503364625
53	84	83.030073583634	1.21437265239625	1.03932369656857	-0.0481772494322569
54	85	84.6872449161486	1.2987689610205	-0.34463419906309	0.456044564723472
55	85	85.2537374905804	1.15920974745096	0.833250354993239	-0.754314765429988
56	82	85.4024490773193	0.966612620276884	-1.90192010580532	-1.04094519272034
57	91	87.6412294080345	1.20905140629166	1.47118761062908	1.31041896721792
58	90	89.3725787659999	1.30859587625757	-0.147833515032271	0.53793054646883
59	98	92.9981022820614	1.75015240691565	1.56330703668235	2.3865528577459
60	98	96.7594566280031	2.13346405375339	-1.74511373305005	2.07168574310596

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 26 & 26 & 0 & 0 & 0 \tabularnewline
2 & 26 & 26 & 0 & 0 & 0 \tabularnewline
3 & 27 & 26.4885072347855 & 0.122153734869542 & 0.133847388049581 & 0.311760983373203 \tabularnewline
4 & 28 & 27.1342140507663 & 0.23311824673463 & 0.228731269700097 & 0.457903128645816 \tabularnewline
5 & 27 & 27.4402761398104 & 0.247518398811714 & -0.618866011025374 & 0.107913243035474 \tabularnewline
6 & 29 & 28.1643886484897 & 0.334228847833608 & 0.269053410840415 & 0.406258323165324 \tabularnewline
7 & 27 & 27.8313690825885 & 0.214297167706663 & 0.123584922206004 & -0.655240986100755 \tabularnewline
8 & 30 & 28.6681306494107 & 0.328271109943408 & 0.35405035208128 & 0.654335034038774 \tabularnewline
9 & 27 & 28.576317321562 & 0.243146163020616 & -0.869867345353114 & -0.473927411775527 \tabularnewline
10 & 30 & 29.1337628874529 & 0.300739692884556 & 0.394864744714539 & 0.319730896984165 \tabularnewline
11 & 32 & 30.3282472607551 & 0.466701979632872 & 0.289088806993994 & 0.931954385446869 \tabularnewline
12 & 30 & 30.3661383325944 & 0.385580902031455 & 0.30439219579371 & -0.449556794087097 \tabularnewline
13 & 32 & 31.5406984939938 & 0.540958999188249 & -0.71493877512563 & 0.816191289314981 \tabularnewline
14 & 33 & 32.3308096372961 & 0.588054594922128 & 0.289099785352401 & 0.257863813925656 \tabularnewline
15 & 34 & 33.2162678006596 & 0.644462653593476 & 0.327045445164039 & 0.309688871900484 \tabularnewline
16 & 32 & 33.1134457193897 & 0.501792720619522 & 0.0333057824407519 & -0.776046862174301 \tabularnewline
17 & 34 & 34.008654119934 & 0.577398204151658 & -0.58710785485183 & 0.403193878082839 \tabularnewline
18 & 37 & 35.3867462918656 & 0.730093190432383 & 0.403052074205044 & 0.826299175426268 \tabularnewline
19 & 37 & 36.316722751826 & 0.768221457622207 & 0.380058217828084 & 0.207164676898101 \tabularnewline
20 & 36 & 36.7045391387188 & 0.695527605608356 & -0.126966403018158 & -0.393774402828982 \tabularnewline
21 & 34 & 36.4234344849801 & 0.509339759241467 & -0.978061212475755 & -1.00499537425496 \tabularnewline
22 & 38 & 37.1447859549601 & 0.549826232698546 & 0.537152043775514 & 0.218276631897497 \tabularnewline
23 & 41 & 38.7261111165581 & 0.746739704924741 & 0.722375168594884 & 1.06586943848126 \tabularnewline
24 & 41 & 40.051835646218 & 0.857323465316116 & 0.0750966064658244 & 0.598406805604166 \tabularnewline
25 & 44 & 42.4186846862801 & 1.14480755991479 & -0.660442329009606 & 1.55667184981305 \tabularnewline
26 & 42 & 42.9089628410352 & 1.01986481633982 & 0.0690264697580345 & -0.673474327413291 \tabularnewline
27 & 45 & 44.0900904893035 & 1.05063598480811 & 0.668566466483218 & 0.166393242126038 \tabularnewline
28 & 45 & 45.1442502646329 & 1.05130858965528 & -0.149538449644073 & 0.00363819199614165 \tabularnewline
29 & 49 & 47.4067457389236 & 1.28205233790169 & -0.206433014708675 & 1.24926768508418 \tabularnewline
30 & 54 & 50.639090066362 & 1.654148468336 & 0.453092220188854 & 2.00708245691218 \tabularnewline
31 & 52 & 52.0253793239282 & 1.60306204629076 & 0.374314631884652 & -0.276200561016786 \tabularnewline
32 & 53 & 53.5330229191274 & 1.58485775079644 & -0.390314716962754 & -0.098442644017665 \tabularnewline
33 & 51 & 53.8143587681823 & 1.33646050540347 & -0.878126138597903 & -1.3440302049865 \tabularnewline
34 & 55 & 54.8722489045787 & 1.28333136006269 & 0.542527272141132 & -0.286763605978873 \tabularnewline
35 & 60 & 57.3719448247025 & 1.51524762661149 & 0.8163826553382 & 1.25381310449318 \tabularnewline
36 & 60 & 59.3928468945365 & 1.61168619852704 & -0.147279755863603 & 0.521405424874104 \tabularnewline
37 & 63 & 62.0592725970851 & 1.81269194816893 & -0.625363947786413 & 1.08713816958434 \tabularnewline
38 & 60 & 62.3855664351422 & 1.52927152021036 & -0.174545350128675 & -1.53043687322043 \tabularnewline
39 & 64 & 63.6492332048664 & 1.47863911662716 & 0.745870122729308 & -0.273719438715818 \tabularnewline
40 & 65 & 65.1654641505836 & 1.48580698381513 & -0.22145531398507 & 0.0387486134101313 \tabularnewline
41 & 75 & 69.7927887275753 & 2.08450328632359 & 0.5439036258708 & 3.2372342629851 \tabularnewline
42 & 70 & 71.3544359730276 & 1.98482304912494 & -0.577247751785819 & -0.538416634812738 \tabularnewline
43 & 72 & 72.6263342257513 & 1.84893187819805 & 0.43327509655402 & -0.734582307536485 \tabularnewline
44 & 69 & 72.726341383867 & 1.51550795325048 & -1.12452274634797 & -1.80228975328815 \tabularnewline
45 & 75 & 74.2201765174614 & 1.51137767322435 & 0.811989190289589 & -0.0223296173603243 \tabularnewline
46 & 74 & 75.2492004618061 & 1.41942939833184 & -0.532600122988277 & -0.496746875207814 \tabularnewline
47 & 74 & 75.4387940458657 & 1.18502542128246 & 0.388011891902151 & -1.26703978914813 \tabularnewline
48 & 75 & 76.3956125126443 & 1.14152392319615 & -1.05640100116612 & -0.235129753300575 \tabularnewline
49 & 79 & 77.7158753559662 & 1.17558672014267 & 1.01888124341681 & 0.184136082383642 \tabularnewline
50 & 79 & 79.0564953373397 & 1.20704348825421 & -0.30157772975425 & 0.169965468519296 \tabularnewline
51 & 85 & 81.8250755278947 & 1.50465498799256 & 0.856346515579268 & 1.60863265377257 \tabularnewline
52 & 78 & 81.85355671232 & 1.22328543212972 & -1.66062818134754 & -1.52077503364625 \tabularnewline
53 & 84 & 83.030073583634 & 1.21437265239625 & 1.03932369656857 & -0.0481772494322569 \tabularnewline
54 & 85 & 84.6872449161486 & 1.2987689610205 & -0.34463419906309 & 0.456044564723472 \tabularnewline
55 & 85 & 85.2537374905804 & 1.15920974745096 & 0.833250354993239 & -0.754314765429988 \tabularnewline
56 & 82 & 85.4024490773193 & 0.966612620276884 & -1.90192010580532 & -1.04094519272034 \tabularnewline
57 & 91 & 87.6412294080345 & 1.20905140629166 & 1.47118761062908 & 1.31041896721792 \tabularnewline
58 & 90 & 89.3725787659999 & 1.30859587625757 & -0.147833515032271 & 0.53793054646883 \tabularnewline
59 & 98 & 92.9981022820614 & 1.75015240691565 & 1.56330703668235 & 2.3865528577459 \tabularnewline
60 & 98 & 96.7594566280031 & 2.13346405375339 & -1.74511373305005 & 2.07168574310596 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115941&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]26[/C][C]26[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]26[/C][C]26[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]27[/C][C]26.4885072347855[/C][C]0.122153734869542[/C][C]0.133847388049581[/C][C]0.311760983373203[/C][/ROW]
[ROW][C]4[/C][C]28[/C][C]27.1342140507663[/C][C]0.23311824673463[/C][C]0.228731269700097[/C][C]0.457903128645816[/C][/ROW]
[ROW][C]5[/C][C]27[/C][C]27.4402761398104[/C][C]0.247518398811714[/C][C]-0.618866011025374[/C][C]0.107913243035474[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]28.1643886484897[/C][C]0.334228847833608[/C][C]0.269053410840415[/C][C]0.406258323165324[/C][/ROW]
[ROW][C]7[/C][C]27[/C][C]27.8313690825885[/C][C]0.214297167706663[/C][C]0.123584922206004[/C][C]-0.655240986100755[/C][/ROW]
[ROW][C]8[/C][C]30[/C][C]28.6681306494107[/C][C]0.328271109943408[/C][C]0.35405035208128[/C][C]0.654335034038774[/C][/ROW]
[ROW][C]9[/C][C]27[/C][C]28.576317321562[/C][C]0.243146163020616[/C][C]-0.869867345353114[/C][C]-0.473927411775527[/C][/ROW]
[ROW][C]10[/C][C]30[/C][C]29.1337628874529[/C][C]0.300739692884556[/C][C]0.394864744714539[/C][C]0.319730896984165[/C][/ROW]
[ROW][C]11[/C][C]32[/C][C]30.3282472607551[/C][C]0.466701979632872[/C][C]0.289088806993994[/C][C]0.931954385446869[/C][/ROW]
[ROW][C]12[/C][C]30[/C][C]30.3661383325944[/C][C]0.385580902031455[/C][C]0.30439219579371[/C][C]-0.449556794087097[/C][/ROW]
[ROW][C]13[/C][C]32[/C][C]31.5406984939938[/C][C]0.540958999188249[/C][C]-0.71493877512563[/C][C]0.816191289314981[/C][/ROW]
[ROW][C]14[/C][C]33[/C][C]32.3308096372961[/C][C]0.588054594922128[/C][C]0.289099785352401[/C][C]0.257863813925656[/C][/ROW]
[ROW][C]15[/C][C]34[/C][C]33.2162678006596[/C][C]0.644462653593476[/C][C]0.327045445164039[/C][C]0.309688871900484[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.1134457193897[/C][C]0.501792720619522[/C][C]0.0333057824407519[/C][C]-0.776046862174301[/C][/ROW]
[ROW][C]17[/C][C]34[/C][C]34.008654119934[/C][C]0.577398204151658[/C][C]-0.58710785485183[/C][C]0.403193878082839[/C][/ROW]
[ROW][C]18[/C][C]37[/C][C]35.3867462918656[/C][C]0.730093190432383[/C][C]0.403052074205044[/C][C]0.826299175426268[/C][/ROW]
[ROW][C]19[/C][C]37[/C][C]36.316722751826[/C][C]0.768221457622207[/C][C]0.380058217828084[/C][C]0.207164676898101[/C][/ROW]
[ROW][C]20[/C][C]36[/C][C]36.7045391387188[/C][C]0.695527605608356[/C][C]-0.126966403018158[/C][C]-0.393774402828982[/C][/ROW]
[ROW][C]21[/C][C]34[/C][C]36.4234344849801[/C][C]0.509339759241467[/C][C]-0.978061212475755[/C][C]-1.00499537425496[/C][/ROW]
[ROW][C]22[/C][C]38[/C][C]37.1447859549601[/C][C]0.549826232698546[/C][C]0.537152043775514[/C][C]0.218276631897497[/C][/ROW]
[ROW][C]23[/C][C]41[/C][C]38.7261111165581[/C][C]0.746739704924741[/C][C]0.722375168594884[/C][C]1.06586943848126[/C][/ROW]
[ROW][C]24[/C][C]41[/C][C]40.051835646218[/C][C]0.857323465316116[/C][C]0.0750966064658244[/C][C]0.598406805604166[/C][/ROW]
[ROW][C]25[/C][C]44[/C][C]42.4186846862801[/C][C]1.14480755991479[/C][C]-0.660442329009606[/C][C]1.55667184981305[/C][/ROW]
[ROW][C]26[/C][C]42[/C][C]42.9089628410352[/C][C]1.01986481633982[/C][C]0.0690264697580345[/C][C]-0.673474327413291[/C][/ROW]
[ROW][C]27[/C][C]45[/C][C]44.0900904893035[/C][C]1.05063598480811[/C][C]0.668566466483218[/C][C]0.166393242126038[/C][/ROW]
[ROW][C]28[/C][C]45[/C][C]45.1442502646329[/C][C]1.05130858965528[/C][C]-0.149538449644073[/C][C]0.00363819199614165[/C][/ROW]
[ROW][C]29[/C][C]49[/C][C]47.4067457389236[/C][C]1.28205233790169[/C][C]-0.206433014708675[/C][C]1.24926768508418[/C][/ROW]
[ROW][C]30[/C][C]54[/C][C]50.639090066362[/C][C]1.654148468336[/C][C]0.453092220188854[/C][C]2.00708245691218[/C][/ROW]
[ROW][C]31[/C][C]52[/C][C]52.0253793239282[/C][C]1.60306204629076[/C][C]0.374314631884652[/C][C]-0.276200561016786[/C][/ROW]
[ROW][C]32[/C][C]53[/C][C]53.5330229191274[/C][C]1.58485775079644[/C][C]-0.390314716962754[/C][C]-0.098442644017665[/C][/ROW]
[ROW][C]33[/C][C]51[/C][C]53.8143587681823[/C][C]1.33646050540347[/C][C]-0.878126138597903[/C][C]-1.3440302049865[/C][/ROW]
[ROW][C]34[/C][C]55[/C][C]54.8722489045787[/C][C]1.28333136006269[/C][C]0.542527272141132[/C][C]-0.286763605978873[/C][/ROW]
[ROW][C]35[/C][C]60[/C][C]57.3719448247025[/C][C]1.51524762661149[/C][C]0.8163826553382[/C][C]1.25381310449318[/C][/ROW]
[ROW][C]36[/C][C]60[/C][C]59.3928468945365[/C][C]1.61168619852704[/C][C]-0.147279755863603[/C][C]0.521405424874104[/C][/ROW]
[ROW][C]37[/C][C]63[/C][C]62.0592725970851[/C][C]1.81269194816893[/C][C]-0.625363947786413[/C][C]1.08713816958434[/C][/ROW]
[ROW][C]38[/C][C]60[/C][C]62.3855664351422[/C][C]1.52927152021036[/C][C]-0.174545350128675[/C][C]-1.53043687322043[/C][/ROW]
[ROW][C]39[/C][C]64[/C][C]63.6492332048664[/C][C]1.47863911662716[/C][C]0.745870122729308[/C][C]-0.273719438715818[/C][/ROW]
[ROW][C]40[/C][C]65[/C][C]65.1654641505836[/C][C]1.48580698381513[/C][C]-0.22145531398507[/C][C]0.0387486134101313[/C][/ROW]
[ROW][C]41[/C][C]75[/C][C]69.7927887275753[/C][C]2.08450328632359[/C][C]0.5439036258708[/C][C]3.2372342629851[/C][/ROW]
[ROW][C]42[/C][C]70[/C][C]71.3544359730276[/C][C]1.98482304912494[/C][C]-0.577247751785819[/C][C]-0.538416634812738[/C][/ROW]
[ROW][C]43[/C][C]72[/C][C]72.6263342257513[/C][C]1.84893187819805[/C][C]0.43327509655402[/C][C]-0.734582307536485[/C][/ROW]
[ROW][C]44[/C][C]69[/C][C]72.726341383867[/C][C]1.51550795325048[/C][C]-1.12452274634797[/C][C]-1.80228975328815[/C][/ROW]
[ROW][C]45[/C][C]75[/C][C]74.2201765174614[/C][C]1.51137767322435[/C][C]0.811989190289589[/C][C]-0.0223296173603243[/C][/ROW]
[ROW][C]46[/C][C]74[/C][C]75.2492004618061[/C][C]1.41942939833184[/C][C]-0.532600122988277[/C][C]-0.496746875207814[/C][/ROW]
[ROW][C]47[/C][C]74[/C][C]75.4387940458657[/C][C]1.18502542128246[/C][C]0.388011891902151[/C][C]-1.26703978914813[/C][/ROW]
[ROW][C]48[/C][C]75[/C][C]76.3956125126443[/C][C]1.14152392319615[/C][C]-1.05640100116612[/C][C]-0.235129753300575[/C][/ROW]
[ROW][C]49[/C][C]79[/C][C]77.7158753559662[/C][C]1.17558672014267[/C][C]1.01888124341681[/C][C]0.184136082383642[/C][/ROW]
[ROW][C]50[/C][C]79[/C][C]79.0564953373397[/C][C]1.20704348825421[/C][C]-0.30157772975425[/C][C]0.169965468519296[/C][/ROW]
[ROW][C]51[/C][C]85[/C][C]81.8250755278947[/C][C]1.50465498799256[/C][C]0.856346515579268[/C][C]1.60863265377257[/C][/ROW]
[ROW][C]52[/C][C]78[/C][C]81.85355671232[/C][C]1.22328543212972[/C][C]-1.66062818134754[/C][C]-1.52077503364625[/C][/ROW]
[ROW][C]53[/C][C]84[/C][C]83.030073583634[/C][C]1.21437265239625[/C][C]1.03932369656857[/C][C]-0.0481772494322569[/C][/ROW]
[ROW][C]54[/C][C]85[/C][C]84.6872449161486[/C][C]1.2987689610205[/C][C]-0.34463419906309[/C][C]0.456044564723472[/C][/ROW]
[ROW][C]55[/C][C]85[/C][C]85.2537374905804[/C][C]1.15920974745096[/C][C]0.833250354993239[/C][C]-0.754314765429988[/C][/ROW]
[ROW][C]56[/C][C]82[/C][C]85.4024490773193[/C][C]0.966612620276884[/C][C]-1.90192010580532[/C][C]-1.04094519272034[/C][/ROW]
[ROW][C]57[/C][C]91[/C][C]87.6412294080345[/C][C]1.20905140629166[/C][C]1.47118761062908[/C][C]1.31041896721792[/C][/ROW]
[ROW][C]58[/C][C]90[/C][C]89.3725787659999[/C][C]1.30859587625757[/C][C]-0.147833515032271[/C][C]0.53793054646883[/C][/ROW]
[ROW][C]59[/C][C]98[/C][C]92.9981022820614[/C][C]1.75015240691565[/C][C]1.56330703668235[/C][C]2.3865528577459[/C][/ROW]
[ROW][C]60[/C][C]98[/C][C]96.7594566280031[/C][C]2.13346405375339[/C][C]-1.74511373305005[/C][C]2.07168574310596[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115941&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115941&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	26	26	0	0	0
2	26	26	0	0	0
3	27	26.4885072347855	0.122153734869542	0.133847388049581	0.311760983373203
4	28	27.1342140507663	0.23311824673463	0.228731269700097	0.457903128645816
5	27	27.4402761398104	0.247518398811714	-0.618866011025374	0.107913243035474
6	29	28.1643886484897	0.334228847833608	0.269053410840415	0.406258323165324
7	27	27.8313690825885	0.214297167706663	0.123584922206004	-0.655240986100755
8	30	28.6681306494107	0.328271109943408	0.35405035208128	0.654335034038774
9	27	28.576317321562	0.243146163020616	-0.869867345353114	-0.473927411775527
10	30	29.1337628874529	0.300739692884556	0.394864744714539	0.319730896984165
11	32	30.3282472607551	0.466701979632872	0.289088806993994	0.931954385446869
12	30	30.3661383325944	0.385580902031455	0.30439219579371	-0.449556794087097
13	32	31.5406984939938	0.540958999188249	-0.71493877512563	0.816191289314981
14	33	32.3308096372961	0.588054594922128	0.289099785352401	0.257863813925656
15	34	33.2162678006596	0.644462653593476	0.327045445164039	0.309688871900484
16	32	33.1134457193897	0.501792720619522	0.0333057824407519	-0.776046862174301
17	34	34.008654119934	0.577398204151658	-0.58710785485183	0.403193878082839
18	37	35.3867462918656	0.730093190432383	0.403052074205044	0.826299175426268
19	37	36.316722751826	0.768221457622207	0.380058217828084	0.207164676898101
20	36	36.7045391387188	0.695527605608356	-0.126966403018158	-0.393774402828982
21	34	36.4234344849801	0.509339759241467	-0.978061212475755	-1.00499537425496
22	38	37.1447859549601	0.549826232698546	0.537152043775514	0.218276631897497
23	41	38.7261111165581	0.746739704924741	0.722375168594884	1.06586943848126
24	41	40.051835646218	0.857323465316116	0.0750966064658244	0.598406805604166
25	44	42.4186846862801	1.14480755991479	-0.660442329009606	1.55667184981305
26	42	42.9089628410352	1.01986481633982	0.0690264697580345	-0.673474327413291
27	45	44.0900904893035	1.05063598480811	0.668566466483218	0.166393242126038
28	45	45.1442502646329	1.05130858965528	-0.149538449644073	0.00363819199614165
29	49	47.4067457389236	1.28205233790169	-0.206433014708675	1.24926768508418
30	54	50.639090066362	1.654148468336	0.453092220188854	2.00708245691218
31	52	52.0253793239282	1.60306204629076	0.374314631884652	-0.276200561016786
32	53	53.5330229191274	1.58485775079644	-0.390314716962754	-0.098442644017665
33	51	53.8143587681823	1.33646050540347	-0.878126138597903	-1.3440302049865
34	55	54.8722489045787	1.28333136006269	0.542527272141132	-0.286763605978873
35	60	57.3719448247025	1.51524762661149	0.8163826553382	1.25381310449318
36	60	59.3928468945365	1.61168619852704	-0.147279755863603	0.521405424874104
37	63	62.0592725970851	1.81269194816893	-0.625363947786413	1.08713816958434
38	60	62.3855664351422	1.52927152021036	-0.174545350128675	-1.53043687322043
39	64	63.6492332048664	1.47863911662716	0.745870122729308	-0.273719438715818
40	65	65.1654641505836	1.48580698381513	-0.22145531398507	0.0387486134101313
41	75	69.7927887275753	2.08450328632359	0.5439036258708	3.2372342629851
42	70	71.3544359730276	1.98482304912494	-0.577247751785819	-0.538416634812738
43	72	72.6263342257513	1.84893187819805	0.43327509655402	-0.734582307536485
44	69	72.726341383867	1.51550795325048	-1.12452274634797	-1.80228975328815
45	75	74.2201765174614	1.51137767322435	0.811989190289589	-0.0223296173603243
46	74	75.2492004618061	1.41942939833184	-0.532600122988277	-0.496746875207814
47	74	75.4387940458657	1.18502542128246	0.388011891902151	-1.26703978914813
48	75	76.3956125126443	1.14152392319615	-1.05640100116612	-0.235129753300575
49	79	77.7158753559662	1.17558672014267	1.01888124341681	0.184136082383642
50	79	79.0564953373397	1.20704348825421	-0.30157772975425	0.169965468519296
51	85	81.8250755278947	1.50465498799256	0.856346515579268	1.60863265377257
52	78	81.85355671232	1.22328543212972	-1.66062818134754	-1.52077503364625
53	84	83.030073583634	1.21437265239625	1.03932369656857	-0.0481772494322569
54	85	84.6872449161486	1.2987689610205	-0.34463419906309	0.456044564723472
55	85	85.2537374905804	1.15920974745096	0.833250354993239	-0.754314765429988
56	82	85.4024490773193	0.966612620276884	-1.90192010580532	-1.04094519272034
57	91	87.6412294080345	1.20905140629166	1.47118761062908	1.31041896721792
58	90	89.3725787659999	1.30859587625757	-0.147833515032271	0.53793054646883
59	98	92.9981022820614	1.75015240691565	1.56330703668235	2.3865528577459
60	98	96.7594566280031	2.13346405375339	-1.74511373305005	2.07168574310596

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 = 4 ;

Parameters (R input):

par1 = 4 ;

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$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
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='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