Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Thu, 10 Dec 2009 10:10:47 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/10/t1260465098oef22y0o3ce5kev.htm/, Retrieved Wed, 24 Apr 2024 22:43:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65612, Retrieved Wed, 24 Apr 2024 22:43:36 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

144

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] [workshop 9] [2009-12-04 13:49:41] [3d8acb8ffdb376c5fec19e610f8198c2]
-    D        [Structural Time Series Models] [verbetering] [2009-12-10 17:10:47] [5edea6bc5a9a9483633d9320282a2734] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65612&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]1 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=65612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65612&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	102.86	102.86	0	0	0
2	102.55	102.565682179366	-0.0241017981932413	-0.0156821793657601	-0.418447443081315
3	102.28	102.295654255638	-0.0590197890480614	-0.0156542556376815	-0.547626616947499
4	102.26	102.275657863465	-0.0517706878412844	-0.0156578634650731	0.0846528878937142
5	102.57	102.585684161599	0.0255774064202126	-0.0156841615986339	0.77123147447451
6	103.08	103.095711249913	0.137359171386002	-0.0157112499134435	1.02151188726503
7	102.76	102.775691829632	0.0272945100648635	-0.0156918296321747	-0.958216547410568
8	102.51	102.525682955471	-0.041008229438491	-0.0156829554710754	-0.578790293818229
9	102.87	102.885692586588	0.0590525893512763	-0.0156925865878397	0.835233604496448
10	103.14	103.155696379665	0.112068676529851	-0.0156963796646531	0.438841052469211
11	103.12	103.135694604142	0.0787435722540339	-0.0156946041417716	-0.274561944132307
12	103.16	103.175694215	0.068945530657078	-0.0156942149998998	-0.0805149633735772
13	102.48	102.575864924310	-0.0942567935268288	-0.0958649243103273	-1.61460401257669
14	102.57	102.559541291563	-0.0754164330562679	0.0104587084371704	0.135582455788541
15	102.88	102.869974655270	0.0225296918861205	0.0100253447304229	0.80029042560907
16	102.63	102.619746024090	-0.0466648981590681	0.0102539759095662	-0.565977416656666
17	102.38	102.369618730044	-0.0982647580710872	0.0103812699560964	-0.422313943435951
18	101.69	101.679342265555	-0.248385199123064	0.0106577344450224	-1.22905562572630
19	101.96	101.949523026306	-0.116894197066505	0.0104769736944682	1.07673397188970
20	102.19	102.179613308323	-0.0289105295560245	0.0103866916769103	0.720542140046447
21	101.87	101.859556763784	-0.102736662499294	0.0104432362158988	-0.604633885219041
22	101.6	101.589532512824	-0.145156837857006	0.0104674871757102	-0.347431163266818
23	101.63	101.619551467726	-0.100735446744689	0.0104485322743415	0.363828098679409
24	101.22	101.209526487745	-0.179167124240111	0.0104735122548333	-0.642391691130274
25	101.21	101.278359709834	-0.117221366123082	-0.068359709833807	0.556644237990322
26	101.49	101.479211673508	-0.0390324828583465	0.0107883264921917	0.594617454136453
27	101.64	101.629353480429	0.0089910937788323	0.0106465195709939	0.392534199004252
28	101.66	101.649359642584	0.0117857285541051	0.0106403574155241	0.0228634951773747
29	101.77	101.759400667893	0.0367068525134991	0.0105993321074123	0.203988177108418
30	101.82	101.809404811985	0.040079074733847	0.0105951880150128	0.027610610650106
31	101.78	101.769386179755	0.0197672426005779	0.0106138202445912	-0.16633251119359
32	101.28	101.269295916727	-0.112060395788408	0.0107040832726320	-1.07962398180594
33	101.29	101.279311737844	-0.0811037254439684	0.0106882621560814	0.253537069583334
34	101.37	101.359327323774	-0.0402459262768263	0.010672676225837	0.334637023681791
35	101.12	101.109312177555	-0.0934413378146773	0.0106878224453378	-0.435692178920362
36	101.51	101.499338233413	0.0291626009788227	0.0106617665869096	1.00418487210583
37	102.24	102.266203225094	0.214411009207366	-0.0262032250935371	1.61463476533749
38	102.94	102.932823149750	0.326494681902529	0.00717685025042731	0.871317560731968
39	103.09	103.082725058048	0.281676616384881	0.00727494195247039	-0.366527153335146
40	103.46	103.452761687947	0.304092045455078	0.0072383120526583	0.183439465808140
41	103.64	103.632723280672	0.272609057234745	0.0072767193277125	-0.257741715202036
42	104.39	104.382833556325	0.393704706663714	0.00716644367481712	0.991580874127709
43	104.15	104.142724300902	0.232974299582409	0.00727569909844755	-1.31627989799212
44	105.21	105.202830723504	0.442726256121331	0.00716927649549986	1.71784674455270
45	105.8	105.792844868524	0.480076970899705	0.00715513147573213	0.305909538284946
46	105.91	105.902818338589	0.386221807156536	0.0071816614112087	-0.768707330585288
47	105.39	105.382769849284	0.156397238797767	0.00723015071617186	-1.88236647106921
48	105.46	105.452766398805	0.134486375664457	0.00723360119541531	-0.179460935387349
49	104.72	104.865725642857	-0.047162469548292	-0.145725642857173	-1.55911141587972
50	103.14	103.140841115573	-0.465004433973417	-0.000841115573391832	-3.28718271230301
51	102.63	102.630821263224	-0.476427293630119	-0.000821263223674354	-0.093446718219952
52	102.32	102.320876057764	-0.434196321776809	-0.000876057763634722	0.345662807929606
53	101.93	101.930886917534	-0.422984349636314	-0.000886917534437867	0.0917979615088299
54	100.62	100.620724247123	-0.647975545765978	-0.000724247123189815	-1.84242012302064
55	100.6	100.600810202774	-0.488702372453864	-0.00081020277419643	1.30438547197669
56	99.63	99.6307610320795	-0.610768309656651	-0.000761032079550974	-0.999724171123227
57	98.9	98.9007519403006	-0.641006918798332	-0.000751940300637301	-0.247662346523827
58	98.32	98.3207554124853	-0.625535032553002	-0.000755412485319058	0.126720939011964
59	99.22	99.2208202182434	-0.23864900116482	-0.00082021824338226	3.16877963671013
60	98.81	98.81081478516	-0.282104592272321	-0.000814785160120457	-0.355923617417946

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 102.86 & 102.86 & 0 & 0 & 0 \tabularnewline
2 & 102.55 & 102.565682179366 & -0.0241017981932413 & -0.0156821793657601 & -0.418447443081315 \tabularnewline
3 & 102.28 & 102.295654255638 & -0.0590197890480614 & -0.0156542556376815 & -0.547626616947499 \tabularnewline
4 & 102.26 & 102.275657863465 & -0.0517706878412844 & -0.0156578634650731 & 0.0846528878937142 \tabularnewline
5 & 102.57 & 102.585684161599 & 0.0255774064202126 & -0.0156841615986339 & 0.77123147447451 \tabularnewline
6 & 103.08 & 103.095711249913 & 0.137359171386002 & -0.0157112499134435 & 1.02151188726503 \tabularnewline
7 & 102.76 & 102.775691829632 & 0.0272945100648635 & -0.0156918296321747 & -0.958216547410568 \tabularnewline
8 & 102.51 & 102.525682955471 & -0.041008229438491 & -0.0156829554710754 & -0.578790293818229 \tabularnewline
9 & 102.87 & 102.885692586588 & 0.0590525893512763 & -0.0156925865878397 & 0.835233604496448 \tabularnewline
10 & 103.14 & 103.155696379665 & 0.112068676529851 & -0.0156963796646531 & 0.438841052469211 \tabularnewline
11 & 103.12 & 103.135694604142 & 0.0787435722540339 & -0.0156946041417716 & -0.274561944132307 \tabularnewline
12 & 103.16 & 103.175694215 & 0.068945530657078 & -0.0156942149998998 & -0.0805149633735772 \tabularnewline
13 & 102.48 & 102.575864924310 & -0.0942567935268288 & -0.0958649243103273 & -1.61460401257669 \tabularnewline
14 & 102.57 & 102.559541291563 & -0.0754164330562679 & 0.0104587084371704 & 0.135582455788541 \tabularnewline
15 & 102.88 & 102.869974655270 & 0.0225296918861205 & 0.0100253447304229 & 0.80029042560907 \tabularnewline
16 & 102.63 & 102.619746024090 & -0.0466648981590681 & 0.0102539759095662 & -0.565977416656666 \tabularnewline
17 & 102.38 & 102.369618730044 & -0.0982647580710872 & 0.0103812699560964 & -0.422313943435951 \tabularnewline
18 & 101.69 & 101.679342265555 & -0.248385199123064 & 0.0106577344450224 & -1.22905562572630 \tabularnewline
19 & 101.96 & 101.949523026306 & -0.116894197066505 & 0.0104769736944682 & 1.07673397188970 \tabularnewline
20 & 102.19 & 102.179613308323 & -0.0289105295560245 & 0.0103866916769103 & 0.720542140046447 \tabularnewline
21 & 101.87 & 101.859556763784 & -0.102736662499294 & 0.0104432362158988 & -0.604633885219041 \tabularnewline
22 & 101.6 & 101.589532512824 & -0.145156837857006 & 0.0104674871757102 & -0.347431163266818 \tabularnewline
23 & 101.63 & 101.619551467726 & -0.100735446744689 & 0.0104485322743415 & 0.363828098679409 \tabularnewline
24 & 101.22 & 101.209526487745 & -0.179167124240111 & 0.0104735122548333 & -0.642391691130274 \tabularnewline
25 & 101.21 & 101.278359709834 & -0.117221366123082 & -0.068359709833807 & 0.556644237990322 \tabularnewline
26 & 101.49 & 101.479211673508 & -0.0390324828583465 & 0.0107883264921917 & 0.594617454136453 \tabularnewline
27 & 101.64 & 101.629353480429 & 0.0089910937788323 & 0.0106465195709939 & 0.392534199004252 \tabularnewline
28 & 101.66 & 101.649359642584 & 0.0117857285541051 & 0.0106403574155241 & 0.0228634951773747 \tabularnewline
29 & 101.77 & 101.759400667893 & 0.0367068525134991 & 0.0105993321074123 & 0.203988177108418 \tabularnewline
30 & 101.82 & 101.809404811985 & 0.040079074733847 & 0.0105951880150128 & 0.027610610650106 \tabularnewline
31 & 101.78 & 101.769386179755 & 0.0197672426005779 & 0.0106138202445912 & -0.16633251119359 \tabularnewline
32 & 101.28 & 101.269295916727 & -0.112060395788408 & 0.0107040832726320 & -1.07962398180594 \tabularnewline
33 & 101.29 & 101.279311737844 & -0.0811037254439684 & 0.0106882621560814 & 0.253537069583334 \tabularnewline
34 & 101.37 & 101.359327323774 & -0.0402459262768263 & 0.010672676225837 & 0.334637023681791 \tabularnewline
35 & 101.12 & 101.109312177555 & -0.0934413378146773 & 0.0106878224453378 & -0.435692178920362 \tabularnewline
36 & 101.51 & 101.499338233413 & 0.0291626009788227 & 0.0106617665869096 & 1.00418487210583 \tabularnewline
37 & 102.24 & 102.266203225094 & 0.214411009207366 & -0.0262032250935371 & 1.61463476533749 \tabularnewline
38 & 102.94 & 102.932823149750 & 0.326494681902529 & 0.00717685025042731 & 0.871317560731968 \tabularnewline
39 & 103.09 & 103.082725058048 & 0.281676616384881 & 0.00727494195247039 & -0.366527153335146 \tabularnewline
40 & 103.46 & 103.452761687947 & 0.304092045455078 & 0.0072383120526583 & 0.183439465808140 \tabularnewline
41 & 103.64 & 103.632723280672 & 0.272609057234745 & 0.0072767193277125 & -0.257741715202036 \tabularnewline
42 & 104.39 & 104.382833556325 & 0.393704706663714 & 0.00716644367481712 & 0.991580874127709 \tabularnewline
43 & 104.15 & 104.142724300902 & 0.232974299582409 & 0.00727569909844755 & -1.31627989799212 \tabularnewline
44 & 105.21 & 105.202830723504 & 0.442726256121331 & 0.00716927649549986 & 1.71784674455270 \tabularnewline
45 & 105.8 & 105.792844868524 & 0.480076970899705 & 0.00715513147573213 & 0.305909538284946 \tabularnewline
46 & 105.91 & 105.902818338589 & 0.386221807156536 & 0.0071816614112087 & -0.768707330585288 \tabularnewline
47 & 105.39 & 105.382769849284 & 0.156397238797767 & 0.00723015071617186 & -1.88236647106921 \tabularnewline
48 & 105.46 & 105.452766398805 & 0.134486375664457 & 0.00723360119541531 & -0.179460935387349 \tabularnewline
49 & 104.72 & 104.865725642857 & -0.047162469548292 & -0.145725642857173 & -1.55911141587972 \tabularnewline
50 & 103.14 & 103.140841115573 & -0.465004433973417 & -0.000841115573391832 & -3.28718271230301 \tabularnewline
51 & 102.63 & 102.630821263224 & -0.476427293630119 & -0.000821263223674354 & -0.093446718219952 \tabularnewline
52 & 102.32 & 102.320876057764 & -0.434196321776809 & -0.000876057763634722 & 0.345662807929606 \tabularnewline
53 & 101.93 & 101.930886917534 & -0.422984349636314 & -0.000886917534437867 & 0.0917979615088299 \tabularnewline
54 & 100.62 & 100.620724247123 & -0.647975545765978 & -0.000724247123189815 & -1.84242012302064 \tabularnewline
55 & 100.6 & 100.600810202774 & -0.488702372453864 & -0.00081020277419643 & 1.30438547197669 \tabularnewline
56 & 99.63 & 99.6307610320795 & -0.610768309656651 & -0.000761032079550974 & -0.999724171123227 \tabularnewline
57 & 98.9 & 98.9007519403006 & -0.641006918798332 & -0.000751940300637301 & -0.247662346523827 \tabularnewline
58 & 98.32 & 98.3207554124853 & -0.625535032553002 & -0.000755412485319058 & 0.126720939011964 \tabularnewline
59 & 99.22 & 99.2208202182434 & -0.23864900116482 & -0.00082021824338226 & 3.16877963671013 \tabularnewline
60 & 98.81 & 98.81081478516 & -0.282104592272321 & -0.000814785160120457 & -0.355923617417946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65612&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]102.86[/C][C]102.86[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]102.55[/C][C]102.565682179366[/C][C]-0.0241017981932413[/C][C]-0.0156821793657601[/C][C]-0.418447443081315[/C][/ROW]
[ROW][C]3[/C][C]102.28[/C][C]102.295654255638[/C][C]-0.0590197890480614[/C][C]-0.0156542556376815[/C][C]-0.547626616947499[/C][/ROW]
[ROW][C]4[/C][C]102.26[/C][C]102.275657863465[/C][C]-0.0517706878412844[/C][C]-0.0156578634650731[/C][C]0.0846528878937142[/C][/ROW]
[ROW][C]5[/C][C]102.57[/C][C]102.585684161599[/C][C]0.0255774064202126[/C][C]-0.0156841615986339[/C][C]0.77123147447451[/C][/ROW]
[ROW][C]6[/C][C]103.08[/C][C]103.095711249913[/C][C]0.137359171386002[/C][C]-0.0157112499134435[/C][C]1.02151188726503[/C][/ROW]
[ROW][C]7[/C][C]102.76[/C][C]102.775691829632[/C][C]0.0272945100648635[/C][C]-0.0156918296321747[/C][C]-0.958216547410568[/C][/ROW]
[ROW][C]8[/C][C]102.51[/C][C]102.525682955471[/C][C]-0.041008229438491[/C][C]-0.0156829554710754[/C][C]-0.578790293818229[/C][/ROW]
[ROW][C]9[/C][C]102.87[/C][C]102.885692586588[/C][C]0.0590525893512763[/C][C]-0.0156925865878397[/C][C]0.835233604496448[/C][/ROW]
[ROW][C]10[/C][C]103.14[/C][C]103.155696379665[/C][C]0.112068676529851[/C][C]-0.0156963796646531[/C][C]0.438841052469211[/C][/ROW]
[ROW][C]11[/C][C]103.12[/C][C]103.135694604142[/C][C]0.0787435722540339[/C][C]-0.0156946041417716[/C][C]-0.274561944132307[/C][/ROW]
[ROW][C]12[/C][C]103.16[/C][C]103.175694215[/C][C]0.068945530657078[/C][C]-0.0156942149998998[/C][C]-0.0805149633735772[/C][/ROW]
[ROW][C]13[/C][C]102.48[/C][C]102.575864924310[/C][C]-0.0942567935268288[/C][C]-0.0958649243103273[/C][C]-1.61460401257669[/C][/ROW]
[ROW][C]14[/C][C]102.57[/C][C]102.559541291563[/C][C]-0.0754164330562679[/C][C]0.0104587084371704[/C][C]0.135582455788541[/C][/ROW]
[ROW][C]15[/C][C]102.88[/C][C]102.869974655270[/C][C]0.0225296918861205[/C][C]0.0100253447304229[/C][C]0.80029042560907[/C][/ROW]
[ROW][C]16[/C][C]102.63[/C][C]102.619746024090[/C][C]-0.0466648981590681[/C][C]0.0102539759095662[/C][C]-0.565977416656666[/C][/ROW]
[ROW][C]17[/C][C]102.38[/C][C]102.369618730044[/C][C]-0.0982647580710872[/C][C]0.0103812699560964[/C][C]-0.422313943435951[/C][/ROW]
[ROW][C]18[/C][C]101.69[/C][C]101.679342265555[/C][C]-0.248385199123064[/C][C]0.0106577344450224[/C][C]-1.22905562572630[/C][/ROW]
[ROW][C]19[/C][C]101.96[/C][C]101.949523026306[/C][C]-0.116894197066505[/C][C]0.0104769736944682[/C][C]1.07673397188970[/C][/ROW]
[ROW][C]20[/C][C]102.19[/C][C]102.179613308323[/C][C]-0.0289105295560245[/C][C]0.0103866916769103[/C][C]0.720542140046447[/C][/ROW]
[ROW][C]21[/C][C]101.87[/C][C]101.859556763784[/C][C]-0.102736662499294[/C][C]0.0104432362158988[/C][C]-0.604633885219041[/C][/ROW]
[ROW][C]22[/C][C]101.6[/C][C]101.589532512824[/C][C]-0.145156837857006[/C][C]0.0104674871757102[/C][C]-0.347431163266818[/C][/ROW]
[ROW][C]23[/C][C]101.63[/C][C]101.619551467726[/C][C]-0.100735446744689[/C][C]0.0104485322743415[/C][C]0.363828098679409[/C][/ROW]
[ROW][C]24[/C][C]101.22[/C][C]101.209526487745[/C][C]-0.179167124240111[/C][C]0.0104735122548333[/C][C]-0.642391691130274[/C][/ROW]
[ROW][C]25[/C][C]101.21[/C][C]101.278359709834[/C][C]-0.117221366123082[/C][C]-0.068359709833807[/C][C]0.556644237990322[/C][/ROW]
[ROW][C]26[/C][C]101.49[/C][C]101.479211673508[/C][C]-0.0390324828583465[/C][C]0.0107883264921917[/C][C]0.594617454136453[/C][/ROW]
[ROW][C]27[/C][C]101.64[/C][C]101.629353480429[/C][C]0.0089910937788323[/C][C]0.0106465195709939[/C][C]0.392534199004252[/C][/ROW]
[ROW][C]28[/C][C]101.66[/C][C]101.649359642584[/C][C]0.0117857285541051[/C][C]0.0106403574155241[/C][C]0.0228634951773747[/C][/ROW]
[ROW][C]29[/C][C]101.77[/C][C]101.759400667893[/C][C]0.0367068525134991[/C][C]0.0105993321074123[/C][C]0.203988177108418[/C][/ROW]
[ROW][C]30[/C][C]101.82[/C][C]101.809404811985[/C][C]0.040079074733847[/C][C]0.0105951880150128[/C][C]0.027610610650106[/C][/ROW]
[ROW][C]31[/C][C]101.78[/C][C]101.769386179755[/C][C]0.0197672426005779[/C][C]0.0106138202445912[/C][C]-0.16633251119359[/C][/ROW]
[ROW][C]32[/C][C]101.28[/C][C]101.269295916727[/C][C]-0.112060395788408[/C][C]0.0107040832726320[/C][C]-1.07962398180594[/C][/ROW]
[ROW][C]33[/C][C]101.29[/C][C]101.279311737844[/C][C]-0.0811037254439684[/C][C]0.0106882621560814[/C][C]0.253537069583334[/C][/ROW]
[ROW][C]34[/C][C]101.37[/C][C]101.359327323774[/C][C]-0.0402459262768263[/C][C]0.010672676225837[/C][C]0.334637023681791[/C][/ROW]
[ROW][C]35[/C][C]101.12[/C][C]101.109312177555[/C][C]-0.0934413378146773[/C][C]0.0106878224453378[/C][C]-0.435692178920362[/C][/ROW]
[ROW][C]36[/C][C]101.51[/C][C]101.499338233413[/C][C]0.0291626009788227[/C][C]0.0106617665869096[/C][C]1.00418487210583[/C][/ROW]
[ROW][C]37[/C][C]102.24[/C][C]102.266203225094[/C][C]0.214411009207366[/C][C]-0.0262032250935371[/C][C]1.61463476533749[/C][/ROW]
[ROW][C]38[/C][C]102.94[/C][C]102.932823149750[/C][C]0.326494681902529[/C][C]0.00717685025042731[/C][C]0.871317560731968[/C][/ROW]
[ROW][C]39[/C][C]103.09[/C][C]103.082725058048[/C][C]0.281676616384881[/C][C]0.00727494195247039[/C][C]-0.366527153335146[/C][/ROW]
[ROW][C]40[/C][C]103.46[/C][C]103.452761687947[/C][C]0.304092045455078[/C][C]0.0072383120526583[/C][C]0.183439465808140[/C][/ROW]
[ROW][C]41[/C][C]103.64[/C][C]103.632723280672[/C][C]0.272609057234745[/C][C]0.0072767193277125[/C][C]-0.257741715202036[/C][/ROW]
[ROW][C]42[/C][C]104.39[/C][C]104.382833556325[/C][C]0.393704706663714[/C][C]0.00716644367481712[/C][C]0.991580874127709[/C][/ROW]
[ROW][C]43[/C][C]104.15[/C][C]104.142724300902[/C][C]0.232974299582409[/C][C]0.00727569909844755[/C][C]-1.31627989799212[/C][/ROW]
[ROW][C]44[/C][C]105.21[/C][C]105.202830723504[/C][C]0.442726256121331[/C][C]0.00716927649549986[/C][C]1.71784674455270[/C][/ROW]
[ROW][C]45[/C][C]105.8[/C][C]105.792844868524[/C][C]0.480076970899705[/C][C]0.00715513147573213[/C][C]0.305909538284946[/C][/ROW]
[ROW][C]46[/C][C]105.91[/C][C]105.902818338589[/C][C]0.386221807156536[/C][C]0.0071816614112087[/C][C]-0.768707330585288[/C][/ROW]
[ROW][C]47[/C][C]105.39[/C][C]105.382769849284[/C][C]0.156397238797767[/C][C]0.00723015071617186[/C][C]-1.88236647106921[/C][/ROW]
[ROW][C]48[/C][C]105.46[/C][C]105.452766398805[/C][C]0.134486375664457[/C][C]0.00723360119541531[/C][C]-0.179460935387349[/C][/ROW]
[ROW][C]49[/C][C]104.72[/C][C]104.865725642857[/C][C]-0.047162469548292[/C][C]-0.145725642857173[/C][C]-1.55911141587972[/C][/ROW]
[ROW][C]50[/C][C]103.14[/C][C]103.140841115573[/C][C]-0.465004433973417[/C][C]-0.000841115573391832[/C][C]-3.28718271230301[/C][/ROW]
[ROW][C]51[/C][C]102.63[/C][C]102.630821263224[/C][C]-0.476427293630119[/C][C]-0.000821263223674354[/C][C]-0.093446718219952[/C][/ROW]
[ROW][C]52[/C][C]102.32[/C][C]102.320876057764[/C][C]-0.434196321776809[/C][C]-0.000876057763634722[/C][C]0.345662807929606[/C][/ROW]
[ROW][C]53[/C][C]101.93[/C][C]101.930886917534[/C][C]-0.422984349636314[/C][C]-0.000886917534437867[/C][C]0.0917979615088299[/C][/ROW]
[ROW][C]54[/C][C]100.62[/C][C]100.620724247123[/C][C]-0.647975545765978[/C][C]-0.000724247123189815[/C][C]-1.84242012302064[/C][/ROW]
[ROW][C]55[/C][C]100.6[/C][C]100.600810202774[/C][C]-0.488702372453864[/C][C]-0.00081020277419643[/C][C]1.30438547197669[/C][/ROW]
[ROW][C]56[/C][C]99.63[/C][C]99.6307610320795[/C][C]-0.610768309656651[/C][C]-0.000761032079550974[/C][C]-0.999724171123227[/C][/ROW]
[ROW][C]57[/C][C]98.9[/C][C]98.9007519403006[/C][C]-0.641006918798332[/C][C]-0.000751940300637301[/C][C]-0.247662346523827[/C][/ROW]
[ROW][C]58[/C][C]98.32[/C][C]98.3207554124853[/C][C]-0.625535032553002[/C][C]-0.000755412485319058[/C][C]0.126720939011964[/C][/ROW]
[ROW][C]59[/C][C]99.22[/C][C]99.2208202182434[/C][C]-0.23864900116482[/C][C]-0.00082021824338226[/C][C]3.16877963671013[/C][/ROW]
[ROW][C]60[/C][C]98.81[/C][C]98.81081478516[/C][C]-0.282104592272321[/C][C]-0.000814785160120457[/C][C]-0.355923617417946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65612&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	102.86	102.86	0	0	0
2	102.55	102.565682179366	-0.0241017981932413	-0.0156821793657601	-0.418447443081315
3	102.28	102.295654255638	-0.0590197890480614	-0.0156542556376815	-0.547626616947499
4	102.26	102.275657863465	-0.0517706878412844	-0.0156578634650731	0.0846528878937142
5	102.57	102.585684161599	0.0255774064202126	-0.0156841615986339	0.77123147447451
6	103.08	103.095711249913	0.137359171386002	-0.0157112499134435	1.02151188726503
7	102.76	102.775691829632	0.0272945100648635	-0.0156918296321747	-0.958216547410568
8	102.51	102.525682955471	-0.041008229438491	-0.0156829554710754	-0.578790293818229
9	102.87	102.885692586588	0.0590525893512763	-0.0156925865878397	0.835233604496448
10	103.14	103.155696379665	0.112068676529851	-0.0156963796646531	0.438841052469211
11	103.12	103.135694604142	0.0787435722540339	-0.0156946041417716	-0.274561944132307
12	103.16	103.175694215	0.068945530657078	-0.0156942149998998	-0.0805149633735772
13	102.48	102.575864924310	-0.0942567935268288	-0.0958649243103273	-1.61460401257669
14	102.57	102.559541291563	-0.0754164330562679	0.0104587084371704	0.135582455788541
15	102.88	102.869974655270	0.0225296918861205	0.0100253447304229	0.80029042560907
16	102.63	102.619746024090	-0.0466648981590681	0.0102539759095662	-0.565977416656666
17	102.38	102.369618730044	-0.0982647580710872	0.0103812699560964	-0.422313943435951
18	101.69	101.679342265555	-0.248385199123064	0.0106577344450224	-1.22905562572630
19	101.96	101.949523026306	-0.116894197066505	0.0104769736944682	1.07673397188970
20	102.19	102.179613308323	-0.0289105295560245	0.0103866916769103	0.720542140046447
21	101.87	101.859556763784	-0.102736662499294	0.0104432362158988	-0.604633885219041
22	101.6	101.589532512824	-0.145156837857006	0.0104674871757102	-0.347431163266818
23	101.63	101.619551467726	-0.100735446744689	0.0104485322743415	0.363828098679409
24	101.22	101.209526487745	-0.179167124240111	0.0104735122548333	-0.642391691130274
25	101.21	101.278359709834	-0.117221366123082	-0.068359709833807	0.556644237990322
26	101.49	101.479211673508	-0.0390324828583465	0.0107883264921917	0.594617454136453
27	101.64	101.629353480429	0.0089910937788323	0.0106465195709939	0.392534199004252
28	101.66	101.649359642584	0.0117857285541051	0.0106403574155241	0.0228634951773747
29	101.77	101.759400667893	0.0367068525134991	0.0105993321074123	0.203988177108418
30	101.82	101.809404811985	0.040079074733847	0.0105951880150128	0.027610610650106
31	101.78	101.769386179755	0.0197672426005779	0.0106138202445912	-0.16633251119359
32	101.28	101.269295916727	-0.112060395788408	0.0107040832726320	-1.07962398180594
33	101.29	101.279311737844	-0.0811037254439684	0.0106882621560814	0.253537069583334
34	101.37	101.359327323774	-0.0402459262768263	0.010672676225837	0.334637023681791
35	101.12	101.109312177555	-0.0934413378146773	0.0106878224453378	-0.435692178920362
36	101.51	101.499338233413	0.0291626009788227	0.0106617665869096	1.00418487210583
37	102.24	102.266203225094	0.214411009207366	-0.0262032250935371	1.61463476533749
38	102.94	102.932823149750	0.326494681902529	0.00717685025042731	0.871317560731968
39	103.09	103.082725058048	0.281676616384881	0.00727494195247039	-0.366527153335146
40	103.46	103.452761687947	0.304092045455078	0.0072383120526583	0.183439465808140
41	103.64	103.632723280672	0.272609057234745	0.0072767193277125	-0.257741715202036
42	104.39	104.382833556325	0.393704706663714	0.00716644367481712	0.991580874127709
43	104.15	104.142724300902	0.232974299582409	0.00727569909844755	-1.31627989799212
44	105.21	105.202830723504	0.442726256121331	0.00716927649549986	1.71784674455270
45	105.8	105.792844868524	0.480076970899705	0.00715513147573213	0.305909538284946
46	105.91	105.902818338589	0.386221807156536	0.0071816614112087	-0.768707330585288
47	105.39	105.382769849284	0.156397238797767	0.00723015071617186	-1.88236647106921
48	105.46	105.452766398805	0.134486375664457	0.00723360119541531	-0.179460935387349
49	104.72	104.865725642857	-0.047162469548292	-0.145725642857173	-1.55911141587972
50	103.14	103.140841115573	-0.465004433973417	-0.000841115573391832	-3.28718271230301
51	102.63	102.630821263224	-0.476427293630119	-0.000821263223674354	-0.093446718219952
52	102.32	102.320876057764	-0.434196321776809	-0.000876057763634722	0.345662807929606
53	101.93	101.930886917534	-0.422984349636314	-0.000886917534437867	0.0917979615088299
54	100.62	100.620724247123	-0.647975545765978	-0.000724247123189815	-1.84242012302064
55	100.6	100.600810202774	-0.488702372453864	-0.00081020277419643	1.30438547197669
56	99.63	99.6307610320795	-0.610768309656651	-0.000761032079550974	-0.999724171123227
57	98.9	98.9007519403006	-0.641006918798332	-0.000751940300637301	-0.247662346523827
58	98.32	98.3207554124853	-0.625535032553002	-0.000755412485319058	0.126720939011964
59	99.22	99.2208202182434	-0.23864900116482	-0.00082021824338226	3.16877963671013
60	98.81	98.81081478516	-0.282104592272321	-0.000814785160120457	-0.355923617417946

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