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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Sun, 26 Dec 2010 13:26:19 +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/26/t1293369912j6u4vhwo7v2qrow.htm/, Retrieved Tue, 07 May 2024 03:39:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115601, Retrieved Tue, 07 May 2024 03:39:50 +0000

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User-defined keywords

Structural Time Series Model bouwgrondprijzen: gemiddelde prijs(€/m²)

Estimated Impact

129

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] [Workshop 8 Time S...] [2010-12-09 10:56:42] [82c18f3ebe9df70882495121eb816e07]
-   PD      [Structural Time Series Models] [Paper Statistiek ] [2010-12-26 13:26:19] [f6fdc0236f011c1845380977efc505f8] [Current]
-   PD        [Structural Time Series Models] [Paper Statistiek ] [2010-12-27 13:51:50] [82c18f3ebe9df70882495121eb816e07] 

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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=115601&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=115601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115601&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	26	26	0	0	0
2	26	26	0	0	0
3	27	26.4885072084148	0.122153739677173	0.133847377390101	0.311760858102279
4	28	27.1342139787824	0.233118255632730	0.228731262357845	0.457902952748373
5	27	27.4402760855130	0.247518422173008	-0.618866072381305	0.107913249961221
6	29	28.1643885357689	0.334228863262016	0.269053415973408	0.406258176803948
7	27	27.8313691417159	0.214297196219431	0.123585017988838	-0.655240729634882
8	30	28.6681305761669	0.328271129587664	0.354050270433736	0.654334776357932
9	27	28.5763173732614	0.243146165322458	-0.869867284285748	-0.473927224296203
10	30	29.1337628643354	0.300739691199911	0.394864646113366	0.319730795081523
11	32	30.3282469900917	0.466701966869033	0.289088784018708	0.931954047212896
12	30	30.3661382898020	0.385580915727939	0.304392170664299	-0.449556493624059
13	32	31.5406982829708	0.540959024058378	-0.714938743274434	0.816190965739956
14	33	32.3308094633352	0.588054633367041	0.289099752490549	0.257863805577972
15	34	33.2162676644242	0.644462705894904	0.327045364309705	0.309688840936
16	32	33.1134458187647	0.501792772087465	0.0333059243567654	-0.776046584144826
17	34	34.0086541322497	0.577398247942449	-0.587107902519284	0.403193677854578
18	37	35.3867461481501	0.730093234935232	0.403051953665283	0.826298883541811
19	37	36.3167226811369	0.768221517323864	0.380058105126853	0.207164683675655
20	36	36.7045391454117	0.695527650284469	-0.126966174439744	-0.393774339235075
21	34	36.4234347165548	0.509339793078035	-0.978061075206743	-1.00499506364408
22	38	37.1447861304711	0.549826259669821	0.537151858628066	0.218276514321450
23	41	38.7261110735168	0.74673973519033	0.722374875997814	1.06586906159781
24	41	40.0518354376283	0.857323486112755	0.0750967143855673	0.598406534170209
25	44	42.4186841606676	1.14480758721019	-0.660442307976261	1.55667131929052
26	42	42.9089626793242	1.01986487631535	0.0690265686603976	-0.673473901677294
27	45	44.0900904776949	1.05063606975600	0.668566234223496	0.166393315635449
28	45	45.1442502396122	1.05130865599812	-0.149538279409317	0.00363809002217009
29	49	47.4067455162186	1.28205241149257	-0.206433208400234	1.24926726787648
30	54	50.6390895035875	1.65414855663668	0.45309209387698	2.00708179380598
31	52	52.0253791247045	1.60306217424042	0.374314600472984	-0.276200244826131
32	53	53.5330227905509	1.58485786323550	-0.39031443816904	-0.09844269171555
33	51	53.8143590714567	1.33646061649704	-0.878126048922161	-1.34402971906003
34	55	54.8722493068712	1.28333145550776	0.542527073932561	-0.286763584541826
35	60	57.3719448989305	1.51524769952023	0.816382397045657	1.25381252112246
36	60	59.3928467966224	1.61168624892955	-0.147279632574143	0.521405111518667
37	63	62.0592722838602	1.81269199830320	-0.62536393993839	1.08713776852673
38	60	62.3855666027673	1.52927158133358	-0.174545167455207	-1.53043624920666
39	64	63.6492334928828	1.47863917634907	0.745869923915414	-0.273719345577482
40	65	65.165464310073	1.48580700944209	-0.221455218277328	0.0387484148476624
41	75	69.7927881872859	2.08450332368169	0.543903161609824	3.23723313595437
42	70	71.3544356757763	1.98482310068779	-0.57724741234765	-0.538416359528932
43	72	72.6263342718263	1.84893195130445	0.433275091617407	-0.734581920792908
44	69	72.7263417447026	1.51550798876610	-1.12452229870255	-1.8022892935136
45	75	74.2201769798673	1.51137772029396	0.811988644194288	-0.0223295466831262
46	74	75.2492008126526	1.41942939210537	-0.53259991774425	-0.496746980013409
47	74	75.438794573858	1.18502539125921	0.388011908750471	-1.26703945153618
48	75	76.3956127336959	1.14152382947651	-1.05640065860976	-0.235130011074764
49	79	77.7158755895938	1.17558665520892	1.01888073381216	0.184136170260871
50	79	79.0564953622532	1.20704340379994	-0.301577650627588	0.169965300409228
51	85	81.8250751240503	1.50465491248330	0.85634639476333	1.60863211013474
52	78	81.8535565917786	1.22328535447966	-1.66062761274873	-1.52077448559197
53	84	83.0300736449797	1.21437262197530	1.03932328103317	-0.0481769764152994
54	85	84.6872447910746	1.29876892201547	-0.344634135817353	0.456044350314516
55	85	85.2537376281421	1.15920973097611	0.833250254835934	-0.754314366045447
56	82	85.4024491947146	0.966612554835191	-1.90191954722115	-1.04094507427672
57	91	87.6412293047514	1.20905137196067	1.47118710338695	1.31041865321177
58	90	89.3725785632114	1.30859585444345	-0.147833561319080	0.537930415956737
59	98	92.9981016668497	1.75015242124173	1.56330669799700	2.38655217471476
60	98	96.759455553512	2.13346407384452	-1.74511328831461	2.07168501175944

\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 & 26.4885072084148 & 0.122153739677173 & 0.133847377390101 & 0.311760858102279 \tabularnewline
4 & 28 & 27.1342139787824 & 0.233118255632730 & 0.228731262357845 & 0.457902952748373 \tabularnewline
5 & 27 & 27.4402760855130 & 0.247518422173008 & -0.618866072381305 & 0.107913249961221 \tabularnewline
6 & 29 & 28.1643885357689 & 0.334228863262016 & 0.269053415973408 & 0.406258176803948 \tabularnewline
7 & 27 & 27.8313691417159 & 0.214297196219431 & 0.123585017988838 & -0.655240729634882 \tabularnewline
8 & 30 & 28.6681305761669 & 0.328271129587664 & 0.354050270433736 & 0.654334776357932 \tabularnewline
9 & 27 & 28.5763173732614 & 0.243146165322458 & -0.869867284285748 & -0.473927224296203 \tabularnewline
10 & 30 & 29.1337628643354 & 0.300739691199911 & 0.394864646113366 & 0.319730795081523 \tabularnewline
11 & 32 & 30.3282469900917 & 0.466701966869033 & 0.289088784018708 & 0.931954047212896 \tabularnewline
12 & 30 & 30.3661382898020 & 0.385580915727939 & 0.304392170664299 & -0.449556493624059 \tabularnewline
13 & 32 & 31.5406982829708 & 0.540959024058378 & -0.714938743274434 & 0.816190965739956 \tabularnewline
14 & 33 & 32.3308094633352 & 0.588054633367041 & 0.289099752490549 & 0.257863805577972 \tabularnewline
15 & 34 & 33.2162676644242 & 0.644462705894904 & 0.327045364309705 & 0.309688840936 \tabularnewline
16 & 32 & 33.1134458187647 & 0.501792772087465 & 0.0333059243567654 & -0.776046584144826 \tabularnewline
17 & 34 & 34.0086541322497 & 0.577398247942449 & -0.587107902519284 & 0.403193677854578 \tabularnewline
18 & 37 & 35.3867461481501 & 0.730093234935232 & 0.403051953665283 & 0.826298883541811 \tabularnewline
19 & 37 & 36.3167226811369 & 0.768221517323864 & 0.380058105126853 & 0.207164683675655 \tabularnewline
20 & 36 & 36.7045391454117 & 0.695527650284469 & -0.126966174439744 & -0.393774339235075 \tabularnewline
21 & 34 & 36.4234347165548 & 0.509339793078035 & -0.978061075206743 & -1.00499506364408 \tabularnewline
22 & 38 & 37.1447861304711 & 0.549826259669821 & 0.537151858628066 & 0.218276514321450 \tabularnewline
23 & 41 & 38.7261110735168 & 0.74673973519033 & 0.722374875997814 & 1.06586906159781 \tabularnewline
24 & 41 & 40.0518354376283 & 0.857323486112755 & 0.0750967143855673 & 0.598406534170209 \tabularnewline
25 & 44 & 42.4186841606676 & 1.14480758721019 & -0.660442307976261 & 1.55667131929052 \tabularnewline
26 & 42 & 42.9089626793242 & 1.01986487631535 & 0.0690265686603976 & -0.673473901677294 \tabularnewline
27 & 45 & 44.0900904776949 & 1.05063606975600 & 0.668566234223496 & 0.166393315635449 \tabularnewline
28 & 45 & 45.1442502396122 & 1.05130865599812 & -0.149538279409317 & 0.00363809002217009 \tabularnewline
29 & 49 & 47.4067455162186 & 1.28205241149257 & -0.206433208400234 & 1.24926726787648 \tabularnewline
30 & 54 & 50.6390895035875 & 1.65414855663668 & 0.45309209387698 & 2.00708179380598 \tabularnewline
31 & 52 & 52.0253791247045 & 1.60306217424042 & 0.374314600472984 & -0.276200244826131 \tabularnewline
32 & 53 & 53.5330227905509 & 1.58485786323550 & -0.39031443816904 & -0.09844269171555 \tabularnewline
33 & 51 & 53.8143590714567 & 1.33646061649704 & -0.878126048922161 & -1.34402971906003 \tabularnewline
34 & 55 & 54.8722493068712 & 1.28333145550776 & 0.542527073932561 & -0.286763584541826 \tabularnewline
35 & 60 & 57.3719448989305 & 1.51524769952023 & 0.816382397045657 & 1.25381252112246 \tabularnewline
36 & 60 & 59.3928467966224 & 1.61168624892955 & -0.147279632574143 & 0.521405111518667 \tabularnewline
37 & 63 & 62.0592722838602 & 1.81269199830320 & -0.62536393993839 & 1.08713776852673 \tabularnewline
38 & 60 & 62.3855666027673 & 1.52927158133358 & -0.174545167455207 & -1.53043624920666 \tabularnewline
39 & 64 & 63.6492334928828 & 1.47863917634907 & 0.745869923915414 & -0.273719345577482 \tabularnewline
40 & 65 & 65.165464310073 & 1.48580700944209 & -0.221455218277328 & 0.0387484148476624 \tabularnewline
41 & 75 & 69.7927881872859 & 2.08450332368169 & 0.543903161609824 & 3.23723313595437 \tabularnewline
42 & 70 & 71.3544356757763 & 1.98482310068779 & -0.57724741234765 & -0.538416359528932 \tabularnewline
43 & 72 & 72.6263342718263 & 1.84893195130445 & 0.433275091617407 & -0.734581920792908 \tabularnewline
44 & 69 & 72.7263417447026 & 1.51550798876610 & -1.12452229870255 & -1.8022892935136 \tabularnewline
45 & 75 & 74.2201769798673 & 1.51137772029396 & 0.811988644194288 & -0.0223295466831262 \tabularnewline
46 & 74 & 75.2492008126526 & 1.41942939210537 & -0.53259991774425 & -0.496746980013409 \tabularnewline
47 & 74 & 75.438794573858 & 1.18502539125921 & 0.388011908750471 & -1.26703945153618 \tabularnewline
48 & 75 & 76.3956127336959 & 1.14152382947651 & -1.05640065860976 & -0.235130011074764 \tabularnewline
49 & 79 & 77.7158755895938 & 1.17558665520892 & 1.01888073381216 & 0.184136170260871 \tabularnewline
50 & 79 & 79.0564953622532 & 1.20704340379994 & -0.301577650627588 & 0.169965300409228 \tabularnewline
51 & 85 & 81.8250751240503 & 1.50465491248330 & 0.85634639476333 & 1.60863211013474 \tabularnewline
52 & 78 & 81.8535565917786 & 1.22328535447966 & -1.66062761274873 & -1.52077448559197 \tabularnewline
53 & 84 & 83.0300736449797 & 1.21437262197530 & 1.03932328103317 & -0.0481769764152994 \tabularnewline
54 & 85 & 84.6872447910746 & 1.29876892201547 & -0.344634135817353 & 0.456044350314516 \tabularnewline
55 & 85 & 85.2537376281421 & 1.15920973097611 & 0.833250254835934 & -0.754314366045447 \tabularnewline
56 & 82 & 85.4024491947146 & 0.966612554835191 & -1.90191954722115 & -1.04094507427672 \tabularnewline
57 & 91 & 87.6412293047514 & 1.20905137196067 & 1.47118710338695 & 1.31041865321177 \tabularnewline
58 & 90 & 89.3725785632114 & 1.30859585444345 & -0.147833561319080 & 0.537930415956737 \tabularnewline
59 & 98 & 92.9981016668497 & 1.75015242124173 & 1.56330669799700 & 2.38655217471476 \tabularnewline
60 & 98 & 96.759455553512 & 2.13346407384452 & -1.74511328831461 & 2.07168501175944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115601&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]26.4885072084148[/C][C]0.122153739677173[/C][C]0.133847377390101[/C][C]0.311760858102279[/C][/ROW]
[ROW][C]4[/C][C]28[/C][C]27.1342139787824[/C][C]0.233118255632730[/C][C]0.228731262357845[/C][C]0.457902952748373[/C][/ROW]
[ROW][C]5[/C][C]27[/C][C]27.4402760855130[/C][C]0.247518422173008[/C][C]-0.618866072381305[/C][C]0.107913249961221[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]28.1643885357689[/C][C]0.334228863262016[/C][C]0.269053415973408[/C][C]0.406258176803948[/C][/ROW]
[ROW][C]7[/C][C]27[/C][C]27.8313691417159[/C][C]0.214297196219431[/C][C]0.123585017988838[/C][C]-0.655240729634882[/C][/ROW]
[ROW][C]8[/C][C]30[/C][C]28.6681305761669[/C][C]0.328271129587664[/C][C]0.354050270433736[/C][C]0.654334776357932[/C][/ROW]
[ROW][C]9[/C][C]27[/C][C]28.5763173732614[/C][C]0.243146165322458[/C][C]-0.869867284285748[/C][C]-0.473927224296203[/C][/ROW]
[ROW][C]10[/C][C]30[/C][C]29.1337628643354[/C][C]0.300739691199911[/C][C]0.394864646113366[/C][C]0.319730795081523[/C][/ROW]
[ROW][C]11[/C][C]32[/C][C]30.3282469900917[/C][C]0.466701966869033[/C][C]0.289088784018708[/C][C]0.931954047212896[/C][/ROW]
[ROW][C]12[/C][C]30[/C][C]30.3661382898020[/C][C]0.385580915727939[/C][C]0.304392170664299[/C][C]-0.449556493624059[/C][/ROW]
[ROW][C]13[/C][C]32[/C][C]31.5406982829708[/C][C]0.540959024058378[/C][C]-0.714938743274434[/C][C]0.816190965739956[/C][/ROW]
[ROW][C]14[/C][C]33[/C][C]32.3308094633352[/C][C]0.588054633367041[/C][C]0.289099752490549[/C][C]0.257863805577972[/C][/ROW]
[ROW][C]15[/C][C]34[/C][C]33.2162676644242[/C][C]0.644462705894904[/C][C]0.327045364309705[/C][C]0.309688840936[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.1134458187647[/C][C]0.501792772087465[/C][C]0.0333059243567654[/C][C]-0.776046584144826[/C][/ROW]
[ROW][C]17[/C][C]34[/C][C]34.0086541322497[/C][C]0.577398247942449[/C][C]-0.587107902519284[/C][C]0.403193677854578[/C][/ROW]
[ROW][C]18[/C][C]37[/C][C]35.3867461481501[/C][C]0.730093234935232[/C][C]0.403051953665283[/C][C]0.826298883541811[/C][/ROW]
[ROW][C]19[/C][C]37[/C][C]36.3167226811369[/C][C]0.768221517323864[/C][C]0.380058105126853[/C][C]0.207164683675655[/C][/ROW]
[ROW][C]20[/C][C]36[/C][C]36.7045391454117[/C][C]0.695527650284469[/C][C]-0.126966174439744[/C][C]-0.393774339235075[/C][/ROW]
[ROW][C]21[/C][C]34[/C][C]36.4234347165548[/C][C]0.509339793078035[/C][C]-0.978061075206743[/C][C]-1.00499506364408[/C][/ROW]
[ROW][C]22[/C][C]38[/C][C]37.1447861304711[/C][C]0.549826259669821[/C][C]0.537151858628066[/C][C]0.218276514321450[/C][/ROW]
[ROW][C]23[/C][C]41[/C][C]38.7261110735168[/C][C]0.74673973519033[/C][C]0.722374875997814[/C][C]1.06586906159781[/C][/ROW]
[ROW][C]24[/C][C]41[/C][C]40.0518354376283[/C][C]0.857323486112755[/C][C]0.0750967143855673[/C][C]0.598406534170209[/C][/ROW]
[ROW][C]25[/C][C]44[/C][C]42.4186841606676[/C][C]1.14480758721019[/C][C]-0.660442307976261[/C][C]1.55667131929052[/C][/ROW]
[ROW][C]26[/C][C]42[/C][C]42.9089626793242[/C][C]1.01986487631535[/C][C]0.0690265686603976[/C][C]-0.673473901677294[/C][/ROW]
[ROW][C]27[/C][C]45[/C][C]44.0900904776949[/C][C]1.05063606975600[/C][C]0.668566234223496[/C][C]0.166393315635449[/C][/ROW]
[ROW][C]28[/C][C]45[/C][C]45.1442502396122[/C][C]1.05130865599812[/C][C]-0.149538279409317[/C][C]0.00363809002217009[/C][/ROW]
[ROW][C]29[/C][C]49[/C][C]47.4067455162186[/C][C]1.28205241149257[/C][C]-0.206433208400234[/C][C]1.24926726787648[/C][/ROW]
[ROW][C]30[/C][C]54[/C][C]50.6390895035875[/C][C]1.65414855663668[/C][C]0.45309209387698[/C][C]2.00708179380598[/C][/ROW]
[ROW][C]31[/C][C]52[/C][C]52.0253791247045[/C][C]1.60306217424042[/C][C]0.374314600472984[/C][C]-0.276200244826131[/C][/ROW]
[ROW][C]32[/C][C]53[/C][C]53.5330227905509[/C][C]1.58485786323550[/C][C]-0.39031443816904[/C][C]-0.09844269171555[/C][/ROW]
[ROW][C]33[/C][C]51[/C][C]53.8143590714567[/C][C]1.33646061649704[/C][C]-0.878126048922161[/C][C]-1.34402971906003[/C][/ROW]
[ROW][C]34[/C][C]55[/C][C]54.8722493068712[/C][C]1.28333145550776[/C][C]0.542527073932561[/C][C]-0.286763584541826[/C][/ROW]
[ROW][C]35[/C][C]60[/C][C]57.3719448989305[/C][C]1.51524769952023[/C][C]0.816382397045657[/C][C]1.25381252112246[/C][/ROW]
[ROW][C]36[/C][C]60[/C][C]59.3928467966224[/C][C]1.61168624892955[/C][C]-0.147279632574143[/C][C]0.521405111518667[/C][/ROW]
[ROW][C]37[/C][C]63[/C][C]62.0592722838602[/C][C]1.81269199830320[/C][C]-0.62536393993839[/C][C]1.08713776852673[/C][/ROW]
[ROW][C]38[/C][C]60[/C][C]62.3855666027673[/C][C]1.52927158133358[/C][C]-0.174545167455207[/C][C]-1.53043624920666[/C][/ROW]
[ROW][C]39[/C][C]64[/C][C]63.6492334928828[/C][C]1.47863917634907[/C][C]0.745869923915414[/C][C]-0.273719345577482[/C][/ROW]
[ROW][C]40[/C][C]65[/C][C]65.165464310073[/C][C]1.48580700944209[/C][C]-0.221455218277328[/C][C]0.0387484148476624[/C][/ROW]
[ROW][C]41[/C][C]75[/C][C]69.7927881872859[/C][C]2.08450332368169[/C][C]0.543903161609824[/C][C]3.23723313595437[/C][/ROW]
[ROW][C]42[/C][C]70[/C][C]71.3544356757763[/C][C]1.98482310068779[/C][C]-0.57724741234765[/C][C]-0.538416359528932[/C][/ROW]
[ROW][C]43[/C][C]72[/C][C]72.6263342718263[/C][C]1.84893195130445[/C][C]0.433275091617407[/C][C]-0.734581920792908[/C][/ROW]
[ROW][C]44[/C][C]69[/C][C]72.7263417447026[/C][C]1.51550798876610[/C][C]-1.12452229870255[/C][C]-1.8022892935136[/C][/ROW]
[ROW][C]45[/C][C]75[/C][C]74.2201769798673[/C][C]1.51137772029396[/C][C]0.811988644194288[/C][C]-0.0223295466831262[/C][/ROW]
[ROW][C]46[/C][C]74[/C][C]75.2492008126526[/C][C]1.41942939210537[/C][C]-0.53259991774425[/C][C]-0.496746980013409[/C][/ROW]
[ROW][C]47[/C][C]74[/C][C]75.438794573858[/C][C]1.18502539125921[/C][C]0.388011908750471[/C][C]-1.26703945153618[/C][/ROW]
[ROW][C]48[/C][C]75[/C][C]76.3956127336959[/C][C]1.14152382947651[/C][C]-1.05640065860976[/C][C]-0.235130011074764[/C][/ROW]
[ROW][C]49[/C][C]79[/C][C]77.7158755895938[/C][C]1.17558665520892[/C][C]1.01888073381216[/C][C]0.184136170260871[/C][/ROW]
[ROW][C]50[/C][C]79[/C][C]79.0564953622532[/C][C]1.20704340379994[/C][C]-0.301577650627588[/C][C]0.169965300409228[/C][/ROW]
[ROW][C]51[/C][C]85[/C][C]81.8250751240503[/C][C]1.50465491248330[/C][C]0.85634639476333[/C][C]1.60863211013474[/C][/ROW]
[ROW][C]52[/C][C]78[/C][C]81.8535565917786[/C][C]1.22328535447966[/C][C]-1.66062761274873[/C][C]-1.52077448559197[/C][/ROW]
[ROW][C]53[/C][C]84[/C][C]83.0300736449797[/C][C]1.21437262197530[/C][C]1.03932328103317[/C][C]-0.0481769764152994[/C][/ROW]
[ROW][C]54[/C][C]85[/C][C]84.6872447910746[/C][C]1.29876892201547[/C][C]-0.344634135817353[/C][C]0.456044350314516[/C][/ROW]
[ROW][C]55[/C][C]85[/C][C]85.2537376281421[/C][C]1.15920973097611[/C][C]0.833250254835934[/C][C]-0.754314366045447[/C][/ROW]
[ROW][C]56[/C][C]82[/C][C]85.4024491947146[/C][C]0.966612554835191[/C][C]-1.90191954722115[/C][C]-1.04094507427672[/C][/ROW]
[ROW][C]57[/C][C]91[/C][C]87.6412293047514[/C][C]1.20905137196067[/C][C]1.47118710338695[/C][C]1.31041865321177[/C][/ROW]
[ROW][C]58[/C][C]90[/C][C]89.3725785632114[/C][C]1.30859585444345[/C][C]-0.147833561319080[/C][C]0.537930415956737[/C][/ROW]
[ROW][C]59[/C][C]98[/C][C]92.9981016668497[/C][C]1.75015242124173[/C][C]1.56330669799700[/C][C]2.38655217471476[/C][/ROW]
[ROW][C]60[/C][C]98[/C][C]96.759455553512[/C][C]2.13346407384452[/C][C]-1.74511328831461[/C][C]2.07168501175944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115601&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	26.4885072084148	0.122153739677173	0.133847377390101	0.311760858102279
4	28	27.1342139787824	0.233118255632730	0.228731262357845	0.457902952748373
5	27	27.4402760855130	0.247518422173008	-0.618866072381305	0.107913249961221
6	29	28.1643885357689	0.334228863262016	0.269053415973408	0.406258176803948
7	27	27.8313691417159	0.214297196219431	0.123585017988838	-0.655240729634882
8	30	28.6681305761669	0.328271129587664	0.354050270433736	0.654334776357932
9	27	28.5763173732614	0.243146165322458	-0.869867284285748	-0.473927224296203
10	30	29.1337628643354	0.300739691199911	0.394864646113366	0.319730795081523
11	32	30.3282469900917	0.466701966869033	0.289088784018708	0.931954047212896
12	30	30.3661382898020	0.385580915727939	0.304392170664299	-0.449556493624059
13	32	31.5406982829708	0.540959024058378	-0.714938743274434	0.816190965739956
14	33	32.3308094633352	0.588054633367041	0.289099752490549	0.257863805577972
15	34	33.2162676644242	0.644462705894904	0.327045364309705	0.309688840936
16	32	33.1134458187647	0.501792772087465	0.0333059243567654	-0.776046584144826
17	34	34.0086541322497	0.577398247942449	-0.587107902519284	0.403193677854578
18	37	35.3867461481501	0.730093234935232	0.403051953665283	0.826298883541811
19	37	36.3167226811369	0.768221517323864	0.380058105126853	0.207164683675655
20	36	36.7045391454117	0.695527650284469	-0.126966174439744	-0.393774339235075
21	34	36.4234347165548	0.509339793078035	-0.978061075206743	-1.00499506364408
22	38	37.1447861304711	0.549826259669821	0.537151858628066	0.218276514321450
23	41	38.7261110735168	0.74673973519033	0.722374875997814	1.06586906159781
24	41	40.0518354376283	0.857323486112755	0.0750967143855673	0.598406534170209
25	44	42.4186841606676	1.14480758721019	-0.660442307976261	1.55667131929052
26	42	42.9089626793242	1.01986487631535	0.0690265686603976	-0.673473901677294
27	45	44.0900904776949	1.05063606975600	0.668566234223496	0.166393315635449
28	45	45.1442502396122	1.05130865599812	-0.149538279409317	0.00363809002217009
29	49	47.4067455162186	1.28205241149257	-0.206433208400234	1.24926726787648
30	54	50.6390895035875	1.65414855663668	0.45309209387698	2.00708179380598
31	52	52.0253791247045	1.60306217424042	0.374314600472984	-0.276200244826131
32	53	53.5330227905509	1.58485786323550	-0.39031443816904	-0.09844269171555
33	51	53.8143590714567	1.33646061649704	-0.878126048922161	-1.34402971906003
34	55	54.8722493068712	1.28333145550776	0.542527073932561	-0.286763584541826
35	60	57.3719448989305	1.51524769952023	0.816382397045657	1.25381252112246
36	60	59.3928467966224	1.61168624892955	-0.147279632574143	0.521405111518667
37	63	62.0592722838602	1.81269199830320	-0.62536393993839	1.08713776852673
38	60	62.3855666027673	1.52927158133358	-0.174545167455207	-1.53043624920666
39	64	63.6492334928828	1.47863917634907	0.745869923915414	-0.273719345577482
40	65	65.165464310073	1.48580700944209	-0.221455218277328	0.0387484148476624
41	75	69.7927881872859	2.08450332368169	0.543903161609824	3.23723313595437
42	70	71.3544356757763	1.98482310068779	-0.57724741234765	-0.538416359528932
43	72	72.6263342718263	1.84893195130445	0.433275091617407	-0.734581920792908
44	69	72.7263417447026	1.51550798876610	-1.12452229870255	-1.8022892935136
45	75	74.2201769798673	1.51137772029396	0.811988644194288	-0.0223295466831262
46	74	75.2492008126526	1.41942939210537	-0.53259991774425	-0.496746980013409
47	74	75.438794573858	1.18502539125921	0.388011908750471	-1.26703945153618
48	75	76.3956127336959	1.14152382947651	-1.05640065860976	-0.235130011074764
49	79	77.7158755895938	1.17558665520892	1.01888073381216	0.184136170260871
50	79	79.0564953622532	1.20704340379994	-0.301577650627588	0.169965300409228
51	85	81.8250751240503	1.50465491248330	0.85634639476333	1.60863211013474
52	78	81.8535565917786	1.22328535447966	-1.66062761274873	-1.52077448559197
53	84	83.0300736449797	1.21437262197530	1.03932328103317	-0.0481769764152994
54	85	84.6872447910746	1.29876892201547	-0.344634135817353	0.456044350314516
55	85	85.2537376281421	1.15920973097611	0.833250254835934	-0.754314366045447
56	82	85.4024491947146	0.966612554835191	-1.90191954722115	-1.04094507427672
57	91	87.6412293047514	1.20905137196067	1.47118710338695	1.31041865321177
58	90	89.3725785632114	1.30859585444345	-0.147833561319080	0.537930415956737
59	98	92.9981016668497	1.75015242124173	1.56330669799700	2.38655217471476
60	98	96.759455553512	2.13346407384452	-1.74511328831461	2.07168501175944

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$resid)
myfit <- mylevel+myseas
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(mylevel,main='Level')
spectrum(myseas,main='Seasonal')
spectrum(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(mylevel,main='Level')
cpgram(myseas,main='Seasonal')
cpgram(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test1.png')
plot(as.numeric(m$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