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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 10:20:25 -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/t1259947284gsa2gz0yu1ojto8.htm/, Retrieved Sun, 28 Apr 2024 00:41:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63931, Retrieved Sun, 28 Apr 2024 00:41:02 +0000

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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] [] [2009-11-27 15:02:30] [b98453cac15ba1066b407e146608df68]
-   PD      [Structural Time Series Models] [WS 9: Structural ...] [2009-12-04 17:20:25] [17b3de9cda9f51722106e41c76160a49] [Current]
-   P         [Structural Time Series Models] [WS 8: Structural ...] [2009-12-04 23:44:30] [8cf9233b7464ea02e32be3b30fdac052] 

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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	2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63931&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]2 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=63931&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63931&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	114	114	0	0	0
2	116	115.702643740845	1.66896046888063	0.297356259155059	0.294876726859141
3	153	146.494977853246	23.6504664783382	6.50502214675349	3.77191065445581
4	162	164.657147603009	19.3405364523551	-2.6571476030092	-0.69617385229692
5	161	164.271417160031	4.13027010648658	-3.27141716003076	-2.4403014219544
6	149	151.006279203135	-9.3017669835315	-2.00627920313463	-2.16432047714572
7	139	138.323670309618	-11.9161278671201	0.676329690382264	-0.420844255351675
8	135	133.119291410535	-6.72588941002604	1.88070858946505	0.835509735540786
9	130	129.442698120416	-4.36822244709808	0.557301879584154	0.379530882275775
10	127	126.544976299828	-3.23133584288738	0.455023700171893	0.183011992933156
11	122	122.008616712248	-4.24029804266581	-0.0086167122483617	-0.162419293972219
12	117	116.782540539251	-5.00245215283087	0.217459460748732	-0.122688952034130
13	112	112.417809433571	-4.51082158791396	-0.417809433571176	0.0797002276452974
14	113	118.483516781324	3.61573463897883	-5.48351678132422	1.32125872853874
15	149	139.917740853605	16.7862873934667	9.08225914639485	2.12504634107215
16	157	157.03439705099	17.0329433309658	-0.0343970509900763	0.0401053876743118
17	157	159.556040949644	6.22144182377092	-2.55604094964360	-1.73463267004782
18	147	150.467136773757	-5.139067873983	-3.46713677375708	-1.82834303326795
19	137	138.280202614551	-10.3766718097926	-1.28020261455135	-0.843443575154147
20	132	129.811872949628	-8.95761686001301	2.18812705037248	0.228425326005112
21	125	124.153732206407	-6.50408593852914	0.846267793592729	0.394959976351661
22	123	121.586522854044	-3.57671561258589	1.41347714595607	0.471252261252070
23	117	116.666836395995	-4.57508436362275	0.333163604005065	-0.160713623635738
24	114	112.455631237544	-4.30482307310549	1.54436876245557	0.0435266137913398
25	111	112.398667599700	-1.14896725404076	-1.39866759970020	0.509762418788215
26	112	120.975831256661	6.07006972133675	-8.9758312566607	1.16243049710649
27	144	135.128615923444	11.9974007739406	8.87138407655556	0.954012623437767
28	150	147.558492496076	12.315338916866	2.44150750392430	0.0514565998105306
29	149	150.041880899574	5.07198310554524	-1.04188089957386	-1.16503410900246
30	134	138.676504476299	-6.99633976396462	-4.67650447629897	-1.94055268562018
31	123	125.333643000286	-11.6566246577464	-2.33364300028565	-0.750425480833146
32	116	114.236926366921	-11.2451011132596	1.76307363307930	0.0662493528025322
33	117	114.576090563726	-2.72901846128121	2.4239094362744	1.37086005291596
34	111	109.638847384399	-4.35222547896544	1.36115261560106	-0.261311896628606
35	105	104.071272001815	-5.24513825011138	0.928727998185038	-0.143739878147149
36	102	100.340981746844	-4.13290623937157	1.65901825315618	0.179184125883452
37	95	98.3374693017223	-2.56826323028658	-3.33746930172227	0.252346669507806
38	93	103.360733953500	3.00199029217631	-10.3607339535002	0.896112984635853
39	124	114.989223032686	9.29529211996098	9.01077696731369	1.01286248787740
40	130	125.747309184084	10.3634582639752	4.25269081591565	0.172462513077168
41	124	123.471544186286	1.11387671322238	0.528455813714395	-1.48917829627881
42	115	118.488865605073	-3.33897121051313	-3.48886560507335	-0.716038457862916
43	106	109.459149885785	-7.49292439364667	-3.45914988578483	-0.668697041568339
44	105	105.487422199554	-4.92067445616287	-0.487422199554088	0.414114902367592
45	105	101.738001347294	-4.06476174723596	3.26199865270597	0.137779693616591
46	101	98.6953085037839	-3.31794982324852	2.30469149621614	0.120221876332748
47	95	94.026392137282	-4.30458588813939	0.973607862717959	-0.158838137405740
48	93	90.8887679874983	-3.45253923105605	2.11123201250169	0.137265939991958
49	84	89.0008258798454	-2.30945510230920	-5.00082587984536	0.184197483755488
50	87	98.0495670253244	5.97745504760098	-11.0495670253244	1.33313803269666
51	116	107.665841184860	8.62345687361788	8.33415881513967	0.425883314652667
52	120	113.447640074266	6.55611048482496	6.55235992573387	-0.333400597719954
53	117	115.688111400241	3.41104437742443	1.31188859975868	-0.50649753193152
54	109	112.283608379213	-1.55095811849093	-3.28360837921311	-0.798135745454033
55	105	109.550869706606	-2.41067338075168	-4.55086970660589	-0.138366145542324
56	107	107.751506809735	-1.96576160857763	-0.751506809735046	0.0716254325462566
57	109	105.873779996985	-1.90166524972071	3.12622000301535	0.0103180083492711
58	109	105.538888642367	-0.76101914592312	3.46111135763341	0.183618737321425
59	108	106.273776002188	0.327642145007529	1.72622399781244	0.17527493814258
60	107	105.196236799355	-0.695010965770706	1.80376320064542	-0.164730001410012

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 114 & 114 & 0 & 0 & 0 \tabularnewline
2 & 116 & 115.702643740845 & 1.66896046888063 & 0.297356259155059 & 0.294876726859141 \tabularnewline
3 & 153 & 146.494977853246 & 23.6504664783382 & 6.50502214675349 & 3.77191065445581 \tabularnewline
4 & 162 & 164.657147603009 & 19.3405364523551 & -2.6571476030092 & -0.69617385229692 \tabularnewline
5 & 161 & 164.271417160031 & 4.13027010648658 & -3.27141716003076 & -2.4403014219544 \tabularnewline
6 & 149 & 151.006279203135 & -9.3017669835315 & -2.00627920313463 & -2.16432047714572 \tabularnewline
7 & 139 & 138.323670309618 & -11.9161278671201 & 0.676329690382264 & -0.420844255351675 \tabularnewline
8 & 135 & 133.119291410535 & -6.72588941002604 & 1.88070858946505 & 0.835509735540786 \tabularnewline
9 & 130 & 129.442698120416 & -4.36822244709808 & 0.557301879584154 & 0.379530882275775 \tabularnewline
10 & 127 & 126.544976299828 & -3.23133584288738 & 0.455023700171893 & 0.183011992933156 \tabularnewline
11 & 122 & 122.008616712248 & -4.24029804266581 & -0.0086167122483617 & -0.162419293972219 \tabularnewline
12 & 117 & 116.782540539251 & -5.00245215283087 & 0.217459460748732 & -0.122688952034130 \tabularnewline
13 & 112 & 112.417809433571 & -4.51082158791396 & -0.417809433571176 & 0.0797002276452974 \tabularnewline
14 & 113 & 118.483516781324 & 3.61573463897883 & -5.48351678132422 & 1.32125872853874 \tabularnewline
15 & 149 & 139.917740853605 & 16.7862873934667 & 9.08225914639485 & 2.12504634107215 \tabularnewline
16 & 157 & 157.03439705099 & 17.0329433309658 & -0.0343970509900763 & 0.0401053876743118 \tabularnewline
17 & 157 & 159.556040949644 & 6.22144182377092 & -2.55604094964360 & -1.73463267004782 \tabularnewline
18 & 147 & 150.467136773757 & -5.139067873983 & -3.46713677375708 & -1.82834303326795 \tabularnewline
19 & 137 & 138.280202614551 & -10.3766718097926 & -1.28020261455135 & -0.843443575154147 \tabularnewline
20 & 132 & 129.811872949628 & -8.95761686001301 & 2.18812705037248 & 0.228425326005112 \tabularnewline
21 & 125 & 124.153732206407 & -6.50408593852914 & 0.846267793592729 & 0.394959976351661 \tabularnewline
22 & 123 & 121.586522854044 & -3.57671561258589 & 1.41347714595607 & 0.471252261252070 \tabularnewline
23 & 117 & 116.666836395995 & -4.57508436362275 & 0.333163604005065 & -0.160713623635738 \tabularnewline
24 & 114 & 112.455631237544 & -4.30482307310549 & 1.54436876245557 & 0.0435266137913398 \tabularnewline
25 & 111 & 112.398667599700 & -1.14896725404076 & -1.39866759970020 & 0.509762418788215 \tabularnewline
26 & 112 & 120.975831256661 & 6.07006972133675 & -8.9758312566607 & 1.16243049710649 \tabularnewline
27 & 144 & 135.128615923444 & 11.9974007739406 & 8.87138407655556 & 0.954012623437767 \tabularnewline
28 & 150 & 147.558492496076 & 12.315338916866 & 2.44150750392430 & 0.0514565998105306 \tabularnewline
29 & 149 & 150.041880899574 & 5.07198310554524 & -1.04188089957386 & -1.16503410900246 \tabularnewline
30 & 134 & 138.676504476299 & -6.99633976396462 & -4.67650447629897 & -1.94055268562018 \tabularnewline
31 & 123 & 125.333643000286 & -11.6566246577464 & -2.33364300028565 & -0.750425480833146 \tabularnewline
32 & 116 & 114.236926366921 & -11.2451011132596 & 1.76307363307930 & 0.0662493528025322 \tabularnewline
33 & 117 & 114.576090563726 & -2.72901846128121 & 2.4239094362744 & 1.37086005291596 \tabularnewline
34 & 111 & 109.638847384399 & -4.35222547896544 & 1.36115261560106 & -0.261311896628606 \tabularnewline
35 & 105 & 104.071272001815 & -5.24513825011138 & 0.928727998185038 & -0.143739878147149 \tabularnewline
36 & 102 & 100.340981746844 & -4.13290623937157 & 1.65901825315618 & 0.179184125883452 \tabularnewline
37 & 95 & 98.3374693017223 & -2.56826323028658 & -3.33746930172227 & 0.252346669507806 \tabularnewline
38 & 93 & 103.360733953500 & 3.00199029217631 & -10.3607339535002 & 0.896112984635853 \tabularnewline
39 & 124 & 114.989223032686 & 9.29529211996098 & 9.01077696731369 & 1.01286248787740 \tabularnewline
40 & 130 & 125.747309184084 & 10.3634582639752 & 4.25269081591565 & 0.172462513077168 \tabularnewline
41 & 124 & 123.471544186286 & 1.11387671322238 & 0.528455813714395 & -1.48917829627881 \tabularnewline
42 & 115 & 118.488865605073 & -3.33897121051313 & -3.48886560507335 & -0.716038457862916 \tabularnewline
43 & 106 & 109.459149885785 & -7.49292439364667 & -3.45914988578483 & -0.668697041568339 \tabularnewline
44 & 105 & 105.487422199554 & -4.92067445616287 & -0.487422199554088 & 0.414114902367592 \tabularnewline
45 & 105 & 101.738001347294 & -4.06476174723596 & 3.26199865270597 & 0.137779693616591 \tabularnewline
46 & 101 & 98.6953085037839 & -3.31794982324852 & 2.30469149621614 & 0.120221876332748 \tabularnewline
47 & 95 & 94.026392137282 & -4.30458588813939 & 0.973607862717959 & -0.158838137405740 \tabularnewline
48 & 93 & 90.8887679874983 & -3.45253923105605 & 2.11123201250169 & 0.137265939991958 \tabularnewline
49 & 84 & 89.0008258798454 & -2.30945510230920 & -5.00082587984536 & 0.184197483755488 \tabularnewline
50 & 87 & 98.0495670253244 & 5.97745504760098 & -11.0495670253244 & 1.33313803269666 \tabularnewline
51 & 116 & 107.665841184860 & 8.62345687361788 & 8.33415881513967 & 0.425883314652667 \tabularnewline
52 & 120 & 113.447640074266 & 6.55611048482496 & 6.55235992573387 & -0.333400597719954 \tabularnewline
53 & 117 & 115.688111400241 & 3.41104437742443 & 1.31188859975868 & -0.50649753193152 \tabularnewline
54 & 109 & 112.283608379213 & -1.55095811849093 & -3.28360837921311 & -0.798135745454033 \tabularnewline
55 & 105 & 109.550869706606 & -2.41067338075168 & -4.55086970660589 & -0.138366145542324 \tabularnewline
56 & 107 & 107.751506809735 & -1.96576160857763 & -0.751506809735046 & 0.0716254325462566 \tabularnewline
57 & 109 & 105.873779996985 & -1.90166524972071 & 3.12622000301535 & 0.0103180083492711 \tabularnewline
58 & 109 & 105.538888642367 & -0.76101914592312 & 3.46111135763341 & 0.183618737321425 \tabularnewline
59 & 108 & 106.273776002188 & 0.327642145007529 & 1.72622399781244 & 0.17527493814258 \tabularnewline
60 & 107 & 105.196236799355 & -0.695010965770706 & 1.80376320064542 & -0.164730001410012 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63931&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]114[/C][C]114[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]116[/C][C]115.702643740845[/C][C]1.66896046888063[/C][C]0.297356259155059[/C][C]0.294876726859141[/C][/ROW]
[ROW][C]3[/C][C]153[/C][C]146.494977853246[/C][C]23.6504664783382[/C][C]6.50502214675349[/C][C]3.77191065445581[/C][/ROW]
[ROW][C]4[/C][C]162[/C][C]164.657147603009[/C][C]19.3405364523551[/C][C]-2.6571476030092[/C][C]-0.69617385229692[/C][/ROW]
[ROW][C]5[/C][C]161[/C][C]164.271417160031[/C][C]4.13027010648658[/C][C]-3.27141716003076[/C][C]-2.4403014219544[/C][/ROW]
[ROW][C]6[/C][C]149[/C][C]151.006279203135[/C][C]-9.3017669835315[/C][C]-2.00627920313463[/C][C]-2.16432047714572[/C][/ROW]
[ROW][C]7[/C][C]139[/C][C]138.323670309618[/C][C]-11.9161278671201[/C][C]0.676329690382264[/C][C]-0.420844255351675[/C][/ROW]
[ROW][C]8[/C][C]135[/C][C]133.119291410535[/C][C]-6.72588941002604[/C][C]1.88070858946505[/C][C]0.835509735540786[/C][/ROW]
[ROW][C]9[/C][C]130[/C][C]129.442698120416[/C][C]-4.36822244709808[/C][C]0.557301879584154[/C][C]0.379530882275775[/C][/ROW]
[ROW][C]10[/C][C]127[/C][C]126.544976299828[/C][C]-3.23133584288738[/C][C]0.455023700171893[/C][C]0.183011992933156[/C][/ROW]
[ROW][C]11[/C][C]122[/C][C]122.008616712248[/C][C]-4.24029804266581[/C][C]-0.0086167122483617[/C][C]-0.162419293972219[/C][/ROW]
[ROW][C]12[/C][C]117[/C][C]116.782540539251[/C][C]-5.00245215283087[/C][C]0.217459460748732[/C][C]-0.122688952034130[/C][/ROW]
[ROW][C]13[/C][C]112[/C][C]112.417809433571[/C][C]-4.51082158791396[/C][C]-0.417809433571176[/C][C]0.0797002276452974[/C][/ROW]
[ROW][C]14[/C][C]113[/C][C]118.483516781324[/C][C]3.61573463897883[/C][C]-5.48351678132422[/C][C]1.32125872853874[/C][/ROW]
[ROW][C]15[/C][C]149[/C][C]139.917740853605[/C][C]16.7862873934667[/C][C]9.08225914639485[/C][C]2.12504634107215[/C][/ROW]
[ROW][C]16[/C][C]157[/C][C]157.03439705099[/C][C]17.0329433309658[/C][C]-0.0343970509900763[/C][C]0.0401053876743118[/C][/ROW]
[ROW][C]17[/C][C]157[/C][C]159.556040949644[/C][C]6.22144182377092[/C][C]-2.55604094964360[/C][C]-1.73463267004782[/C][/ROW]
[ROW][C]18[/C][C]147[/C][C]150.467136773757[/C][C]-5.139067873983[/C][C]-3.46713677375708[/C][C]-1.82834303326795[/C][/ROW]
[ROW][C]19[/C][C]137[/C][C]138.280202614551[/C][C]-10.3766718097926[/C][C]-1.28020261455135[/C][C]-0.843443575154147[/C][/ROW]
[ROW][C]20[/C][C]132[/C][C]129.811872949628[/C][C]-8.95761686001301[/C][C]2.18812705037248[/C][C]0.228425326005112[/C][/ROW]
[ROW][C]21[/C][C]125[/C][C]124.153732206407[/C][C]-6.50408593852914[/C][C]0.846267793592729[/C][C]0.394959976351661[/C][/ROW]
[ROW][C]22[/C][C]123[/C][C]121.586522854044[/C][C]-3.57671561258589[/C][C]1.41347714595607[/C][C]0.471252261252070[/C][/ROW]
[ROW][C]23[/C][C]117[/C][C]116.666836395995[/C][C]-4.57508436362275[/C][C]0.333163604005065[/C][C]-0.160713623635738[/C][/ROW]
[ROW][C]24[/C][C]114[/C][C]112.455631237544[/C][C]-4.30482307310549[/C][C]1.54436876245557[/C][C]0.0435266137913398[/C][/ROW]
[ROW][C]25[/C][C]111[/C][C]112.398667599700[/C][C]-1.14896725404076[/C][C]-1.39866759970020[/C][C]0.509762418788215[/C][/ROW]
[ROW][C]26[/C][C]112[/C][C]120.975831256661[/C][C]6.07006972133675[/C][C]-8.9758312566607[/C][C]1.16243049710649[/C][/ROW]
[ROW][C]27[/C][C]144[/C][C]135.128615923444[/C][C]11.9974007739406[/C][C]8.87138407655556[/C][C]0.954012623437767[/C][/ROW]
[ROW][C]28[/C][C]150[/C][C]147.558492496076[/C][C]12.315338916866[/C][C]2.44150750392430[/C][C]0.0514565998105306[/C][/ROW]
[ROW][C]29[/C][C]149[/C][C]150.041880899574[/C][C]5.07198310554524[/C][C]-1.04188089957386[/C][C]-1.16503410900246[/C][/ROW]
[ROW][C]30[/C][C]134[/C][C]138.676504476299[/C][C]-6.99633976396462[/C][C]-4.67650447629897[/C][C]-1.94055268562018[/C][/ROW]
[ROW][C]31[/C][C]123[/C][C]125.333643000286[/C][C]-11.6566246577464[/C][C]-2.33364300028565[/C][C]-0.750425480833146[/C][/ROW]
[ROW][C]32[/C][C]116[/C][C]114.236926366921[/C][C]-11.2451011132596[/C][C]1.76307363307930[/C][C]0.0662493528025322[/C][/ROW]
[ROW][C]33[/C][C]117[/C][C]114.576090563726[/C][C]-2.72901846128121[/C][C]2.4239094362744[/C][C]1.37086005291596[/C][/ROW]
[ROW][C]34[/C][C]111[/C][C]109.638847384399[/C][C]-4.35222547896544[/C][C]1.36115261560106[/C][C]-0.261311896628606[/C][/ROW]
[ROW][C]35[/C][C]105[/C][C]104.071272001815[/C][C]-5.24513825011138[/C][C]0.928727998185038[/C][C]-0.143739878147149[/C][/ROW]
[ROW][C]36[/C][C]102[/C][C]100.340981746844[/C][C]-4.13290623937157[/C][C]1.65901825315618[/C][C]0.179184125883452[/C][/ROW]
[ROW][C]37[/C][C]95[/C][C]98.3374693017223[/C][C]-2.56826323028658[/C][C]-3.33746930172227[/C][C]0.252346669507806[/C][/ROW]
[ROW][C]38[/C][C]93[/C][C]103.360733953500[/C][C]3.00199029217631[/C][C]-10.3607339535002[/C][C]0.896112984635853[/C][/ROW]
[ROW][C]39[/C][C]124[/C][C]114.989223032686[/C][C]9.29529211996098[/C][C]9.01077696731369[/C][C]1.01286248787740[/C][/ROW]
[ROW][C]40[/C][C]130[/C][C]125.747309184084[/C][C]10.3634582639752[/C][C]4.25269081591565[/C][C]0.172462513077168[/C][/ROW]
[ROW][C]41[/C][C]124[/C][C]123.471544186286[/C][C]1.11387671322238[/C][C]0.528455813714395[/C][C]-1.48917829627881[/C][/ROW]
[ROW][C]42[/C][C]115[/C][C]118.488865605073[/C][C]-3.33897121051313[/C][C]-3.48886560507335[/C][C]-0.716038457862916[/C][/ROW]
[ROW][C]43[/C][C]106[/C][C]109.459149885785[/C][C]-7.49292439364667[/C][C]-3.45914988578483[/C][C]-0.668697041568339[/C][/ROW]
[ROW][C]44[/C][C]105[/C][C]105.487422199554[/C][C]-4.92067445616287[/C][C]-0.487422199554088[/C][C]0.414114902367592[/C][/ROW]
[ROW][C]45[/C][C]105[/C][C]101.738001347294[/C][C]-4.06476174723596[/C][C]3.26199865270597[/C][C]0.137779693616591[/C][/ROW]
[ROW][C]46[/C][C]101[/C][C]98.6953085037839[/C][C]-3.31794982324852[/C][C]2.30469149621614[/C][C]0.120221876332748[/C][/ROW]
[ROW][C]47[/C][C]95[/C][C]94.026392137282[/C][C]-4.30458588813939[/C][C]0.973607862717959[/C][C]-0.158838137405740[/C][/ROW]
[ROW][C]48[/C][C]93[/C][C]90.8887679874983[/C][C]-3.45253923105605[/C][C]2.11123201250169[/C][C]0.137265939991958[/C][/ROW]
[ROW][C]49[/C][C]84[/C][C]89.0008258798454[/C][C]-2.30945510230920[/C][C]-5.00082587984536[/C][C]0.184197483755488[/C][/ROW]
[ROW][C]50[/C][C]87[/C][C]98.0495670253244[/C][C]5.97745504760098[/C][C]-11.0495670253244[/C][C]1.33313803269666[/C][/ROW]
[ROW][C]51[/C][C]116[/C][C]107.665841184860[/C][C]8.62345687361788[/C][C]8.33415881513967[/C][C]0.425883314652667[/C][/ROW]
[ROW][C]52[/C][C]120[/C][C]113.447640074266[/C][C]6.55611048482496[/C][C]6.55235992573387[/C][C]-0.333400597719954[/C][/ROW]
[ROW][C]53[/C][C]117[/C][C]115.688111400241[/C][C]3.41104437742443[/C][C]1.31188859975868[/C][C]-0.50649753193152[/C][/ROW]
[ROW][C]54[/C][C]109[/C][C]112.283608379213[/C][C]-1.55095811849093[/C][C]-3.28360837921311[/C][C]-0.798135745454033[/C][/ROW]
[ROW][C]55[/C][C]105[/C][C]109.550869706606[/C][C]-2.41067338075168[/C][C]-4.55086970660589[/C][C]-0.138366145542324[/C][/ROW]
[ROW][C]56[/C][C]107[/C][C]107.751506809735[/C][C]-1.96576160857763[/C][C]-0.751506809735046[/C][C]0.0716254325462566[/C][/ROW]
[ROW][C]57[/C][C]109[/C][C]105.873779996985[/C][C]-1.90166524972071[/C][C]3.12622000301535[/C][C]0.0103180083492711[/C][/ROW]
[ROW][C]58[/C][C]109[/C][C]105.538888642367[/C][C]-0.76101914592312[/C][C]3.46111135763341[/C][C]0.183618737321425[/C][/ROW]
[ROW][C]59[/C][C]108[/C][C]106.273776002188[/C][C]0.327642145007529[/C][C]1.72622399781244[/C][C]0.17527493814258[/C][/ROW]
[ROW][C]60[/C][C]107[/C][C]105.196236799355[/C][C]-0.695010965770706[/C][C]1.80376320064542[/C][C]-0.164730001410012[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63931&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63931&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	114	114	0	0	0
2	116	115.702643740845	1.66896046888063	0.297356259155059	0.294876726859141
3	153	146.494977853246	23.6504664783382	6.50502214675349	3.77191065445581
4	162	164.657147603009	19.3405364523551	-2.6571476030092	-0.69617385229692
5	161	164.271417160031	4.13027010648658	-3.27141716003076	-2.4403014219544
6	149	151.006279203135	-9.3017669835315	-2.00627920313463	-2.16432047714572
7	139	138.323670309618	-11.9161278671201	0.676329690382264	-0.420844255351675
8	135	133.119291410535	-6.72588941002604	1.88070858946505	0.835509735540786
9	130	129.442698120416	-4.36822244709808	0.557301879584154	0.379530882275775
10	127	126.544976299828	-3.23133584288738	0.455023700171893	0.183011992933156
11	122	122.008616712248	-4.24029804266581	-0.0086167122483617	-0.162419293972219
12	117	116.782540539251	-5.00245215283087	0.217459460748732	-0.122688952034130
13	112	112.417809433571	-4.51082158791396	-0.417809433571176	0.0797002276452974
14	113	118.483516781324	3.61573463897883	-5.48351678132422	1.32125872853874
15	149	139.917740853605	16.7862873934667	9.08225914639485	2.12504634107215
16	157	157.03439705099	17.0329433309658	-0.0343970509900763	0.0401053876743118
17	157	159.556040949644	6.22144182377092	-2.55604094964360	-1.73463267004782
18	147	150.467136773757	-5.139067873983	-3.46713677375708	-1.82834303326795
19	137	138.280202614551	-10.3766718097926	-1.28020261455135	-0.843443575154147
20	132	129.811872949628	-8.95761686001301	2.18812705037248	0.228425326005112
21	125	124.153732206407	-6.50408593852914	0.846267793592729	0.394959976351661
22	123	121.586522854044	-3.57671561258589	1.41347714595607	0.471252261252070
23	117	116.666836395995	-4.57508436362275	0.333163604005065	-0.160713623635738
24	114	112.455631237544	-4.30482307310549	1.54436876245557	0.0435266137913398
25	111	112.398667599700	-1.14896725404076	-1.39866759970020	0.509762418788215
26	112	120.975831256661	6.07006972133675	-8.9758312566607	1.16243049710649
27	144	135.128615923444	11.9974007739406	8.87138407655556	0.954012623437767
28	150	147.558492496076	12.315338916866	2.44150750392430	0.0514565998105306
29	149	150.041880899574	5.07198310554524	-1.04188089957386	-1.16503410900246
30	134	138.676504476299	-6.99633976396462	-4.67650447629897	-1.94055268562018
31	123	125.333643000286	-11.6566246577464	-2.33364300028565	-0.750425480833146
32	116	114.236926366921	-11.2451011132596	1.76307363307930	0.0662493528025322
33	117	114.576090563726	-2.72901846128121	2.4239094362744	1.37086005291596
34	111	109.638847384399	-4.35222547896544	1.36115261560106	-0.261311896628606
35	105	104.071272001815	-5.24513825011138	0.928727998185038	-0.143739878147149
36	102	100.340981746844	-4.13290623937157	1.65901825315618	0.179184125883452
37	95	98.3374693017223	-2.56826323028658	-3.33746930172227	0.252346669507806
38	93	103.360733953500	3.00199029217631	-10.3607339535002	0.896112984635853
39	124	114.989223032686	9.29529211996098	9.01077696731369	1.01286248787740
40	130	125.747309184084	10.3634582639752	4.25269081591565	0.172462513077168
41	124	123.471544186286	1.11387671322238	0.528455813714395	-1.48917829627881
42	115	118.488865605073	-3.33897121051313	-3.48886560507335	-0.716038457862916
43	106	109.459149885785	-7.49292439364667	-3.45914988578483	-0.668697041568339
44	105	105.487422199554	-4.92067445616287	-0.487422199554088	0.414114902367592
45	105	101.738001347294	-4.06476174723596	3.26199865270597	0.137779693616591
46	101	98.6953085037839	-3.31794982324852	2.30469149621614	0.120221876332748
47	95	94.026392137282	-4.30458588813939	0.973607862717959	-0.158838137405740
48	93	90.8887679874983	-3.45253923105605	2.11123201250169	0.137265939991958
49	84	89.0008258798454	-2.30945510230920	-5.00082587984536	0.184197483755488
50	87	98.0495670253244	5.97745504760098	-11.0495670253244	1.33313803269666
51	116	107.665841184860	8.62345687361788	8.33415881513967	0.425883314652667
52	120	113.447640074266	6.55611048482496	6.55235992573387	-0.333400597719954
53	117	115.688111400241	3.41104437742443	1.31188859975868	-0.50649753193152
54	109	112.283608379213	-1.55095811849093	-3.28360837921311	-0.798135745454033
55	105	109.550869706606	-2.41067338075168	-4.55086970660589	-0.138366145542324
56	107	107.751506809735	-1.96576160857763	-0.751506809735046	0.0716254325462566
57	109	105.873779996985	-1.90166524972071	3.12622000301535	0.0103180083492711
58	109	105.538888642367	-0.76101914592312	3.46111135763341	0.183618737321425
59	108	106.273776002188	0.327642145007529	1.72622399781244	0.17527493814258
60	107	105.196236799355	-0.695010965770706	1.80376320064542	-0.164730001410012

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 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

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