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R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Wed, 02 Dec 2009 09:58:42 -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/02/t1259773167lki0g47i64ixffs.htm/, Retrieved Sun, 28 Apr 2024 16:21:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62438, Retrieved Sun, 28 Apr 2024 16:21:10 +0000

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Estimated Impact

139

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]
-    D      [Structural Time Series Models] [WS9 Berekening4 TVD] [2009-12-02 16:58:42] [37de18e38c1490dd77c2b362ed87f3bb] [Current]
-             [Structural Time Series Models] [BDM 10] [2009-12-02 17:28:45] [f5d341d4bbba73282fc6e80153a6d315] 
-             [Structural Time Series Models] [TG 10] [2009-12-02 18:05:04] [a21bac9c8d3d56fdec8be4e719e2c7ed] 
-   P           [Structural Time Series Models] [WorkShop9 (SHW)] [2009-12-04 14:55:40] [37daf76adc256428993ec4063536c760] 
-    D        [Structural Time Series Models] [blog 6] [2009-12-07 20:49:52] [42ad1186d39724f834063794eac7cea3] 

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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=62438&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=62438&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62438&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	101.3	101.3	0	0	0
2	106.3	104.214006471146	0.0950062801624158	2.08599352885424	0.447447058145163
3	94	99.39966707179	-0.207922227625704	-5.39966707179006	-0.687108020950798
4	102.8	100.196558655041	-0.157342240981717	2.6034413449593	0.175345760322466
5	102	101.199747263407	-0.119201453808518	0.80025273659299	0.219498693200026
6	105.1	103.223536569398	-0.071129232488973	1.87646343060191	0.410901272935821
7	92.4	98.8267283887178	-0.152804901053942	-6.42672838871779	-0.829283867924895
8	81.4	89.8272510505545	-0.320209529801329	-8.42725105055453	-1.69234534330147
9	105.8	94.8965094344412	-0.211772494102814	10.9034905655588	1.02868501165805
10	120.3	107.755246854008	0.0672674423526715	12.5447531459919	2.49028569073384
11	100.7	107.739044343927	0.0654049630693266	-7.03904434392734	-0.0158819431339166
12	88.8	99.1136547833746	-0.134930985717269	-10.3136547833746	-1.65182396586731
13	94.3	95.1593102063048	-0.100821345736164	-0.859310206304814	-0.768141142536768
14	99.9	94.2922916800573	-0.107430624730257	5.60770831994272	-0.149414461653315
15	103.4	101.257596755986	0.101809909703785	2.14240324401429	1.25307160113486
16	103.3	102.812735761520	0.155633044279499	0.487264238480176	0.256924680209239
17	98.8	100.842881384158	0.0800696892956578	-2.04288138415795	-0.389731720871818
18	104.2	99.2331759824747	0.0272720872041723	4.96682401752527	-0.316655341379635
19	91.2	96.6569042093132	-0.045195344353165	-5.45690420931323	-0.491006386506582
20	74.7	92.5488505158513	-0.151723341657588	-17.8488505158513	-0.766641461541962
21	108.5	96.816096188491	-0.0376845999406179	11.6839038115089	0.833056577762395
22	114.5	99.0681666426773	0.0207694749683654	15.4318333573227	0.430987608964762
23	96.9	99.198904759861	0.0234471925796431	-2.29890475986105	0.0206575619472181
24	89.6	98.7295493342962	0.0126902555790541	-9.1295493342962	-0.0926258204521036
25	97.1	98.943294177289	0.0165901977284168	-1.84329417728896	0.038099331235521
26	100.3	99.0443111130218	0.0185110505590353	1.25568888697815	0.0158621389810876
27	122.6	108.782264055651	0.299272024976968	13.8177359443491	1.77836717360949
28	115.4	112.818349641899	0.423256070242572	2.58165035810096	0.676506629766847
29	109	112.161003050230	0.386085485094583	-3.16100305022984	-0.197595747620276
30	129.1	116.502531435913	0.518716436128943	12.5974685640872	0.732886931818238
31	102.8	113.393277218075	0.402672327916866	-10.5932772180748	-0.67696424561187
32	96.2	114.424587803287	0.421916798725934	-18.2245878032866	0.117499545515079
33	127.7	115.899871772494	0.453067578244399	11.8001282275059	0.1967132827489
34	128.9	115.081534023519	0.41662603306461	13.8184659764814	-0.237021438382784
35	126.5	120.896499954458	0.566297849715985	5.60350004554206	1.00525025425144
36	119.8	126.094893672473	0.691244340258048	-6.29489367247338	0.863372346335079
37	113.2	123.666936831546	0.606847619849919	-10.4669368315465	-0.582139215172333
38	114.1	121.494169957612	0.52752565619629	-7.39416995761165	-0.516345059193209
39	134.1	121.693581092896	0.517413522755159	12.4064189071039	-0.060334709064372
40	130	124.484182974030	0.591897862502222	5.51581702596952	0.415524874777907
41	121.8	126.017800289786	0.62365598237389	-4.21780028978636	0.17262975603495
42	132.1	122.782956564835	0.493586555160052	9.31704343516464	-0.712155485370253
43	105.3	119.543864975955	0.370029835388014	-14.2438649759546	-0.692388051535697
44	103	120.149756103951	0.377643836973305	-17.1497561039512	0.04381539213603
45	117.1	114.288418315698	0.181280366013081	2.81158168430225	-1.15798088991910
46	126.3	114.129656116889	0.170818395581281	12.1703438831107	-0.0630240826391854
47	138.1	122.992539919784	0.43360121166405	15.1074600802158	1.61023620003582
48	119.5	125.014625250710	0.481265094280177	-5.5146252507102	0.294501426267522
49	138	135.197080484896	0.77469200579795	2.80291951510445	1.79917344278048
50	135.5	141.005296619259	0.9306340175301	-5.50529661925949	0.931172358834538
51	178.6	154.105898756442	1.31980625980542	24.4941012435584	2.24070443832966
52	162.2	157.962644092120	1.4032112657594	4.23735590788031	0.465623035106344
53	176.9	167.995533775593	1.69152201597383	8.9044662244071	1.58528662520268
54	204.9	181.476683682301	2.08659463918171	23.4233163176987	2.17334989709797
55	132.2	168.679508222397	1.59142105448855	-36.479508222397	-2.75211569125429
56	142.5	161.396813711404	1.30000795767089	-18.8968137114036	-1.64250237419826
57	164.3	161.439682790546	1.25933029014661	2.86031720945422	-0.232522813337484
58	174.9	165.096427260474	1.33588073241949	9.80357273952622	0.442988044003135
59	175.4	165.718906408964	1.31330901105027	9.6810935910357	-0.131793433990577
60	143	162.03659300682	1.15568239395441	-19.0365930068201	-0.923432101039032

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 101.3 & 101.3 & 0 & 0 & 0 \tabularnewline
2 & 106.3 & 104.214006471146 & 0.0950062801624158 & 2.08599352885424 & 0.447447058145163 \tabularnewline
3 & 94 & 99.39966707179 & -0.207922227625704 & -5.39966707179006 & -0.687108020950798 \tabularnewline
4 & 102.8 & 100.196558655041 & -0.157342240981717 & 2.6034413449593 & 0.175345760322466 \tabularnewline
5 & 102 & 101.199747263407 & -0.119201453808518 & 0.80025273659299 & 0.219498693200026 \tabularnewline
6 & 105.1 & 103.223536569398 & -0.071129232488973 & 1.87646343060191 & 0.410901272935821 \tabularnewline
7 & 92.4 & 98.8267283887178 & -0.152804901053942 & -6.42672838871779 & -0.829283867924895 \tabularnewline
8 & 81.4 & 89.8272510505545 & -0.320209529801329 & -8.42725105055453 & -1.69234534330147 \tabularnewline
9 & 105.8 & 94.8965094344412 & -0.211772494102814 & 10.9034905655588 & 1.02868501165805 \tabularnewline
10 & 120.3 & 107.755246854008 & 0.0672674423526715 & 12.5447531459919 & 2.49028569073384 \tabularnewline
11 & 100.7 & 107.739044343927 & 0.0654049630693266 & -7.03904434392734 & -0.0158819431339166 \tabularnewline
12 & 88.8 & 99.1136547833746 & -0.134930985717269 & -10.3136547833746 & -1.65182396586731 \tabularnewline
13 & 94.3 & 95.1593102063048 & -0.100821345736164 & -0.859310206304814 & -0.768141142536768 \tabularnewline
14 & 99.9 & 94.2922916800573 & -0.107430624730257 & 5.60770831994272 & -0.149414461653315 \tabularnewline
15 & 103.4 & 101.257596755986 & 0.101809909703785 & 2.14240324401429 & 1.25307160113486 \tabularnewline
16 & 103.3 & 102.812735761520 & 0.155633044279499 & 0.487264238480176 & 0.256924680209239 \tabularnewline
17 & 98.8 & 100.842881384158 & 0.0800696892956578 & -2.04288138415795 & -0.389731720871818 \tabularnewline
18 & 104.2 & 99.2331759824747 & 0.0272720872041723 & 4.96682401752527 & -0.316655341379635 \tabularnewline
19 & 91.2 & 96.6569042093132 & -0.045195344353165 & -5.45690420931323 & -0.491006386506582 \tabularnewline
20 & 74.7 & 92.5488505158513 & -0.151723341657588 & -17.8488505158513 & -0.766641461541962 \tabularnewline
21 & 108.5 & 96.816096188491 & -0.0376845999406179 & 11.6839038115089 & 0.833056577762395 \tabularnewline
22 & 114.5 & 99.0681666426773 & 0.0207694749683654 & 15.4318333573227 & 0.430987608964762 \tabularnewline
23 & 96.9 & 99.198904759861 & 0.0234471925796431 & -2.29890475986105 & 0.0206575619472181 \tabularnewline
24 & 89.6 & 98.7295493342962 & 0.0126902555790541 & -9.1295493342962 & -0.0926258204521036 \tabularnewline
25 & 97.1 & 98.943294177289 & 0.0165901977284168 & -1.84329417728896 & 0.038099331235521 \tabularnewline
26 & 100.3 & 99.0443111130218 & 0.0185110505590353 & 1.25568888697815 & 0.0158621389810876 \tabularnewline
27 & 122.6 & 108.782264055651 & 0.299272024976968 & 13.8177359443491 & 1.77836717360949 \tabularnewline
28 & 115.4 & 112.818349641899 & 0.423256070242572 & 2.58165035810096 & 0.676506629766847 \tabularnewline
29 & 109 & 112.161003050230 & 0.386085485094583 & -3.16100305022984 & -0.197595747620276 \tabularnewline
30 & 129.1 & 116.502531435913 & 0.518716436128943 & 12.5974685640872 & 0.732886931818238 \tabularnewline
31 & 102.8 & 113.393277218075 & 0.402672327916866 & -10.5932772180748 & -0.67696424561187 \tabularnewline
32 & 96.2 & 114.424587803287 & 0.421916798725934 & -18.2245878032866 & 0.117499545515079 \tabularnewline
33 & 127.7 & 115.899871772494 & 0.453067578244399 & 11.8001282275059 & 0.1967132827489 \tabularnewline
34 & 128.9 & 115.081534023519 & 0.41662603306461 & 13.8184659764814 & -0.237021438382784 \tabularnewline
35 & 126.5 & 120.896499954458 & 0.566297849715985 & 5.60350004554206 & 1.00525025425144 \tabularnewline
36 & 119.8 & 126.094893672473 & 0.691244340258048 & -6.29489367247338 & 0.863372346335079 \tabularnewline
37 & 113.2 & 123.666936831546 & 0.606847619849919 & -10.4669368315465 & -0.582139215172333 \tabularnewline
38 & 114.1 & 121.494169957612 & 0.52752565619629 & -7.39416995761165 & -0.516345059193209 \tabularnewline
39 & 134.1 & 121.693581092896 & 0.517413522755159 & 12.4064189071039 & -0.060334709064372 \tabularnewline
40 & 130 & 124.484182974030 & 0.591897862502222 & 5.51581702596952 & 0.415524874777907 \tabularnewline
41 & 121.8 & 126.017800289786 & 0.62365598237389 & -4.21780028978636 & 0.17262975603495 \tabularnewline
42 & 132.1 & 122.782956564835 & 0.493586555160052 & 9.31704343516464 & -0.712155485370253 \tabularnewline
43 & 105.3 & 119.543864975955 & 0.370029835388014 & -14.2438649759546 & -0.692388051535697 \tabularnewline
44 & 103 & 120.149756103951 & 0.377643836973305 & -17.1497561039512 & 0.04381539213603 \tabularnewline
45 & 117.1 & 114.288418315698 & 0.181280366013081 & 2.81158168430225 & -1.15798088991910 \tabularnewline
46 & 126.3 & 114.129656116889 & 0.170818395581281 & 12.1703438831107 & -0.0630240826391854 \tabularnewline
47 & 138.1 & 122.992539919784 & 0.43360121166405 & 15.1074600802158 & 1.61023620003582 \tabularnewline
48 & 119.5 & 125.014625250710 & 0.481265094280177 & -5.5146252507102 & 0.294501426267522 \tabularnewline
49 & 138 & 135.197080484896 & 0.77469200579795 & 2.80291951510445 & 1.79917344278048 \tabularnewline
50 & 135.5 & 141.005296619259 & 0.9306340175301 & -5.50529661925949 & 0.931172358834538 \tabularnewline
51 & 178.6 & 154.105898756442 & 1.31980625980542 & 24.4941012435584 & 2.24070443832966 \tabularnewline
52 & 162.2 & 157.962644092120 & 1.4032112657594 & 4.23735590788031 & 0.465623035106344 \tabularnewline
53 & 176.9 & 167.995533775593 & 1.69152201597383 & 8.9044662244071 & 1.58528662520268 \tabularnewline
54 & 204.9 & 181.476683682301 & 2.08659463918171 & 23.4233163176987 & 2.17334989709797 \tabularnewline
55 & 132.2 & 168.679508222397 & 1.59142105448855 & -36.479508222397 & -2.75211569125429 \tabularnewline
56 & 142.5 & 161.396813711404 & 1.30000795767089 & -18.8968137114036 & -1.64250237419826 \tabularnewline
57 & 164.3 & 161.439682790546 & 1.25933029014661 & 2.86031720945422 & -0.232522813337484 \tabularnewline
58 & 174.9 & 165.096427260474 & 1.33588073241949 & 9.80357273952622 & 0.442988044003135 \tabularnewline
59 & 175.4 & 165.718906408964 & 1.31330901105027 & 9.6810935910357 & -0.131793433990577 \tabularnewline
60 & 143 & 162.03659300682 & 1.15568239395441 & -19.0365930068201 & -0.923432101039032 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62438&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]101.3[/C][C]101.3[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]106.3[/C][C]104.214006471146[/C][C]0.0950062801624158[/C][C]2.08599352885424[/C][C]0.447447058145163[/C][/ROW]
[ROW][C]3[/C][C]94[/C][C]99.39966707179[/C][C]-0.207922227625704[/C][C]-5.39966707179006[/C][C]-0.687108020950798[/C][/ROW]
[ROW][C]4[/C][C]102.8[/C][C]100.196558655041[/C][C]-0.157342240981717[/C][C]2.6034413449593[/C][C]0.175345760322466[/C][/ROW]
[ROW][C]5[/C][C]102[/C][C]101.199747263407[/C][C]-0.119201453808518[/C][C]0.80025273659299[/C][C]0.219498693200026[/C][/ROW]
[ROW][C]6[/C][C]105.1[/C][C]103.223536569398[/C][C]-0.071129232488973[/C][C]1.87646343060191[/C][C]0.410901272935821[/C][/ROW]
[ROW][C]7[/C][C]92.4[/C][C]98.8267283887178[/C][C]-0.152804901053942[/C][C]-6.42672838871779[/C][C]-0.829283867924895[/C][/ROW]
[ROW][C]8[/C][C]81.4[/C][C]89.8272510505545[/C][C]-0.320209529801329[/C][C]-8.42725105055453[/C][C]-1.69234534330147[/C][/ROW]
[ROW][C]9[/C][C]105.8[/C][C]94.8965094344412[/C][C]-0.211772494102814[/C][C]10.9034905655588[/C][C]1.02868501165805[/C][/ROW]
[ROW][C]10[/C][C]120.3[/C][C]107.755246854008[/C][C]0.0672674423526715[/C][C]12.5447531459919[/C][C]2.49028569073384[/C][/ROW]
[ROW][C]11[/C][C]100.7[/C][C]107.739044343927[/C][C]0.0654049630693266[/C][C]-7.03904434392734[/C][C]-0.0158819431339166[/C][/ROW]
[ROW][C]12[/C][C]88.8[/C][C]99.1136547833746[/C][C]-0.134930985717269[/C][C]-10.3136547833746[/C][C]-1.65182396586731[/C][/ROW]
[ROW][C]13[/C][C]94.3[/C][C]95.1593102063048[/C][C]-0.100821345736164[/C][C]-0.859310206304814[/C][C]-0.768141142536768[/C][/ROW]
[ROW][C]14[/C][C]99.9[/C][C]94.2922916800573[/C][C]-0.107430624730257[/C][C]5.60770831994272[/C][C]-0.149414461653315[/C][/ROW]
[ROW][C]15[/C][C]103.4[/C][C]101.257596755986[/C][C]0.101809909703785[/C][C]2.14240324401429[/C][C]1.25307160113486[/C][/ROW]
[ROW][C]16[/C][C]103.3[/C][C]102.812735761520[/C][C]0.155633044279499[/C][C]0.487264238480176[/C][C]0.256924680209239[/C][/ROW]
[ROW][C]17[/C][C]98.8[/C][C]100.842881384158[/C][C]0.0800696892956578[/C][C]-2.04288138415795[/C][C]-0.389731720871818[/C][/ROW]
[ROW][C]18[/C][C]104.2[/C][C]99.2331759824747[/C][C]0.0272720872041723[/C][C]4.96682401752527[/C][C]-0.316655341379635[/C][/ROW]
[ROW][C]19[/C][C]91.2[/C][C]96.6569042093132[/C][C]-0.045195344353165[/C][C]-5.45690420931323[/C][C]-0.491006386506582[/C][/ROW]
[ROW][C]20[/C][C]74.7[/C][C]92.5488505158513[/C][C]-0.151723341657588[/C][C]-17.8488505158513[/C][C]-0.766641461541962[/C][/ROW]
[ROW][C]21[/C][C]108.5[/C][C]96.816096188491[/C][C]-0.0376845999406179[/C][C]11.6839038115089[/C][C]0.833056577762395[/C][/ROW]
[ROW][C]22[/C][C]114.5[/C][C]99.0681666426773[/C][C]0.0207694749683654[/C][C]15.4318333573227[/C][C]0.430987608964762[/C][/ROW]
[ROW][C]23[/C][C]96.9[/C][C]99.198904759861[/C][C]0.0234471925796431[/C][C]-2.29890475986105[/C][C]0.0206575619472181[/C][/ROW]
[ROW][C]24[/C][C]89.6[/C][C]98.7295493342962[/C][C]0.0126902555790541[/C][C]-9.1295493342962[/C][C]-0.0926258204521036[/C][/ROW]
[ROW][C]25[/C][C]97.1[/C][C]98.943294177289[/C][C]0.0165901977284168[/C][C]-1.84329417728896[/C][C]0.038099331235521[/C][/ROW]
[ROW][C]26[/C][C]100.3[/C][C]99.0443111130218[/C][C]0.0185110505590353[/C][C]1.25568888697815[/C][C]0.0158621389810876[/C][/ROW]
[ROW][C]27[/C][C]122.6[/C][C]108.782264055651[/C][C]0.299272024976968[/C][C]13.8177359443491[/C][C]1.77836717360949[/C][/ROW]
[ROW][C]28[/C][C]115.4[/C][C]112.818349641899[/C][C]0.423256070242572[/C][C]2.58165035810096[/C][C]0.676506629766847[/C][/ROW]
[ROW][C]29[/C][C]109[/C][C]112.161003050230[/C][C]0.386085485094583[/C][C]-3.16100305022984[/C][C]-0.197595747620276[/C][/ROW]
[ROW][C]30[/C][C]129.1[/C][C]116.502531435913[/C][C]0.518716436128943[/C][C]12.5974685640872[/C][C]0.732886931818238[/C][/ROW]
[ROW][C]31[/C][C]102.8[/C][C]113.393277218075[/C][C]0.402672327916866[/C][C]-10.5932772180748[/C][C]-0.67696424561187[/C][/ROW]
[ROW][C]32[/C][C]96.2[/C][C]114.424587803287[/C][C]0.421916798725934[/C][C]-18.2245878032866[/C][C]0.117499545515079[/C][/ROW]
[ROW][C]33[/C][C]127.7[/C][C]115.899871772494[/C][C]0.453067578244399[/C][C]11.8001282275059[/C][C]0.1967132827489[/C][/ROW]
[ROW][C]34[/C][C]128.9[/C][C]115.081534023519[/C][C]0.41662603306461[/C][C]13.8184659764814[/C][C]-0.237021438382784[/C][/ROW]
[ROW][C]35[/C][C]126.5[/C][C]120.896499954458[/C][C]0.566297849715985[/C][C]5.60350004554206[/C][C]1.00525025425144[/C][/ROW]
[ROW][C]36[/C][C]119.8[/C][C]126.094893672473[/C][C]0.691244340258048[/C][C]-6.29489367247338[/C][C]0.863372346335079[/C][/ROW]
[ROW][C]37[/C][C]113.2[/C][C]123.666936831546[/C][C]0.606847619849919[/C][C]-10.4669368315465[/C][C]-0.582139215172333[/C][/ROW]
[ROW][C]38[/C][C]114.1[/C][C]121.494169957612[/C][C]0.52752565619629[/C][C]-7.39416995761165[/C][C]-0.516345059193209[/C][/ROW]
[ROW][C]39[/C][C]134.1[/C][C]121.693581092896[/C][C]0.517413522755159[/C][C]12.4064189071039[/C][C]-0.060334709064372[/C][/ROW]
[ROW][C]40[/C][C]130[/C][C]124.484182974030[/C][C]0.591897862502222[/C][C]5.51581702596952[/C][C]0.415524874777907[/C][/ROW]
[ROW][C]41[/C][C]121.8[/C][C]126.017800289786[/C][C]0.62365598237389[/C][C]-4.21780028978636[/C][C]0.17262975603495[/C][/ROW]
[ROW][C]42[/C][C]132.1[/C][C]122.782956564835[/C][C]0.493586555160052[/C][C]9.31704343516464[/C][C]-0.712155485370253[/C][/ROW]
[ROW][C]43[/C][C]105.3[/C][C]119.543864975955[/C][C]0.370029835388014[/C][C]-14.2438649759546[/C][C]-0.692388051535697[/C][/ROW]
[ROW][C]44[/C][C]103[/C][C]120.149756103951[/C][C]0.377643836973305[/C][C]-17.1497561039512[/C][C]0.04381539213603[/C][/ROW]
[ROW][C]45[/C][C]117.1[/C][C]114.288418315698[/C][C]0.181280366013081[/C][C]2.81158168430225[/C][C]-1.15798088991910[/C][/ROW]
[ROW][C]46[/C][C]126.3[/C][C]114.129656116889[/C][C]0.170818395581281[/C][C]12.1703438831107[/C][C]-0.0630240826391854[/C][/ROW]
[ROW][C]47[/C][C]138.1[/C][C]122.992539919784[/C][C]0.43360121166405[/C][C]15.1074600802158[/C][C]1.61023620003582[/C][/ROW]
[ROW][C]48[/C][C]119.5[/C][C]125.014625250710[/C][C]0.481265094280177[/C][C]-5.5146252507102[/C][C]0.294501426267522[/C][/ROW]
[ROW][C]49[/C][C]138[/C][C]135.197080484896[/C][C]0.77469200579795[/C][C]2.80291951510445[/C][C]1.79917344278048[/C][/ROW]
[ROW][C]50[/C][C]135.5[/C][C]141.005296619259[/C][C]0.9306340175301[/C][C]-5.50529661925949[/C][C]0.931172358834538[/C][/ROW]
[ROW][C]51[/C][C]178.6[/C][C]154.105898756442[/C][C]1.31980625980542[/C][C]24.4941012435584[/C][C]2.24070443832966[/C][/ROW]
[ROW][C]52[/C][C]162.2[/C][C]157.962644092120[/C][C]1.4032112657594[/C][C]4.23735590788031[/C][C]0.465623035106344[/C][/ROW]
[ROW][C]53[/C][C]176.9[/C][C]167.995533775593[/C][C]1.69152201597383[/C][C]8.9044662244071[/C][C]1.58528662520268[/C][/ROW]
[ROW][C]54[/C][C]204.9[/C][C]181.476683682301[/C][C]2.08659463918171[/C][C]23.4233163176987[/C][C]2.17334989709797[/C][/ROW]
[ROW][C]55[/C][C]132.2[/C][C]168.679508222397[/C][C]1.59142105448855[/C][C]-36.479508222397[/C][C]-2.75211569125429[/C][/ROW]
[ROW][C]56[/C][C]142.5[/C][C]161.396813711404[/C][C]1.30000795767089[/C][C]-18.8968137114036[/C][C]-1.64250237419826[/C][/ROW]
[ROW][C]57[/C][C]164.3[/C][C]161.439682790546[/C][C]1.25933029014661[/C][C]2.86031720945422[/C][C]-0.232522813337484[/C][/ROW]
[ROW][C]58[/C][C]174.9[/C][C]165.096427260474[/C][C]1.33588073241949[/C][C]9.80357273952622[/C][C]0.442988044003135[/C][/ROW]
[ROW][C]59[/C][C]175.4[/C][C]165.718906408964[/C][C]1.31330901105027[/C][C]9.6810935910357[/C][C]-0.131793433990577[/C][/ROW]
[ROW][C]60[/C][C]143[/C][C]162.03659300682[/C][C]1.15568239395441[/C][C]-19.0365930068201[/C][C]-0.923432101039032[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62438&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62438&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	101.3	101.3	0	0	0
2	106.3	104.214006471146	0.0950062801624158	2.08599352885424	0.447447058145163
3	94	99.39966707179	-0.207922227625704	-5.39966707179006	-0.687108020950798
4	102.8	100.196558655041	-0.157342240981717	2.6034413449593	0.175345760322466
5	102	101.199747263407	-0.119201453808518	0.80025273659299	0.219498693200026
6	105.1	103.223536569398	-0.071129232488973	1.87646343060191	0.410901272935821
7	92.4	98.8267283887178	-0.152804901053942	-6.42672838871779	-0.829283867924895
8	81.4	89.8272510505545	-0.320209529801329	-8.42725105055453	-1.69234534330147
9	105.8	94.8965094344412	-0.211772494102814	10.9034905655588	1.02868501165805
10	120.3	107.755246854008	0.0672674423526715	12.5447531459919	2.49028569073384
11	100.7	107.739044343927	0.0654049630693266	-7.03904434392734	-0.0158819431339166
12	88.8	99.1136547833746	-0.134930985717269	-10.3136547833746	-1.65182396586731
13	94.3	95.1593102063048	-0.100821345736164	-0.859310206304814	-0.768141142536768
14	99.9	94.2922916800573	-0.107430624730257	5.60770831994272	-0.149414461653315
15	103.4	101.257596755986	0.101809909703785	2.14240324401429	1.25307160113486
16	103.3	102.812735761520	0.155633044279499	0.487264238480176	0.256924680209239
17	98.8	100.842881384158	0.0800696892956578	-2.04288138415795	-0.389731720871818
18	104.2	99.2331759824747	0.0272720872041723	4.96682401752527	-0.316655341379635
19	91.2	96.6569042093132	-0.045195344353165	-5.45690420931323	-0.491006386506582
20	74.7	92.5488505158513	-0.151723341657588	-17.8488505158513	-0.766641461541962
21	108.5	96.816096188491	-0.0376845999406179	11.6839038115089	0.833056577762395
22	114.5	99.0681666426773	0.0207694749683654	15.4318333573227	0.430987608964762
23	96.9	99.198904759861	0.0234471925796431	-2.29890475986105	0.0206575619472181
24	89.6	98.7295493342962	0.0126902555790541	-9.1295493342962	-0.0926258204521036
25	97.1	98.943294177289	0.0165901977284168	-1.84329417728896	0.038099331235521
26	100.3	99.0443111130218	0.0185110505590353	1.25568888697815	0.0158621389810876
27	122.6	108.782264055651	0.299272024976968	13.8177359443491	1.77836717360949
28	115.4	112.818349641899	0.423256070242572	2.58165035810096	0.676506629766847
29	109	112.161003050230	0.386085485094583	-3.16100305022984	-0.197595747620276
30	129.1	116.502531435913	0.518716436128943	12.5974685640872	0.732886931818238
31	102.8	113.393277218075	0.402672327916866	-10.5932772180748	-0.67696424561187
32	96.2	114.424587803287	0.421916798725934	-18.2245878032866	0.117499545515079
33	127.7	115.899871772494	0.453067578244399	11.8001282275059	0.1967132827489
34	128.9	115.081534023519	0.41662603306461	13.8184659764814	-0.237021438382784
35	126.5	120.896499954458	0.566297849715985	5.60350004554206	1.00525025425144
36	119.8	126.094893672473	0.691244340258048	-6.29489367247338	0.863372346335079
37	113.2	123.666936831546	0.606847619849919	-10.4669368315465	-0.582139215172333
38	114.1	121.494169957612	0.52752565619629	-7.39416995761165	-0.516345059193209
39	134.1	121.693581092896	0.517413522755159	12.4064189071039	-0.060334709064372
40	130	124.484182974030	0.591897862502222	5.51581702596952	0.415524874777907
41	121.8	126.017800289786	0.62365598237389	-4.21780028978636	0.17262975603495
42	132.1	122.782956564835	0.493586555160052	9.31704343516464	-0.712155485370253
43	105.3	119.543864975955	0.370029835388014	-14.2438649759546	-0.692388051535697
44	103	120.149756103951	0.377643836973305	-17.1497561039512	0.04381539213603
45	117.1	114.288418315698	0.181280366013081	2.81158168430225	-1.15798088991910
46	126.3	114.129656116889	0.170818395581281	12.1703438831107	-0.0630240826391854
47	138.1	122.992539919784	0.43360121166405	15.1074600802158	1.61023620003582
48	119.5	125.014625250710	0.481265094280177	-5.5146252507102	0.294501426267522
49	138	135.197080484896	0.77469200579795	2.80291951510445	1.79917344278048
50	135.5	141.005296619259	0.9306340175301	-5.50529661925949	0.931172358834538
51	178.6	154.105898756442	1.31980625980542	24.4941012435584	2.24070443832966
52	162.2	157.962644092120	1.4032112657594	4.23735590788031	0.465623035106344
53	176.9	167.995533775593	1.69152201597383	8.9044662244071	1.58528662520268
54	204.9	181.476683682301	2.08659463918171	23.4233163176987	2.17334989709797
55	132.2	168.679508222397	1.59142105448855	-36.479508222397	-2.75211569125429
56	142.5	161.396813711404	1.30000795767089	-18.8968137114036	-1.64250237419826
57	164.3	161.439682790546	1.25933029014661	2.86031720945422	-0.232522813337484
58	174.9	165.096427260474	1.33588073241949	9.80357273952622	0.442988044003135
59	175.4	165.718906408964	1.31330901105027	9.6810935910357	-0.131793433990577
60	143	162.03659300682	1.15568239395441	-19.0365930068201	-0.923432101039032

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