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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationMon, 21 Dec 2009 14:51:31 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/21/t1261432337crsq096phfa94s1.htm/, Retrieved Sun, 05 May 2024 09:53:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70405, Retrieved Sun, 05 May 2024 09:53:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD        [Structural Time Series Models] [Paper] [2009-12-21 21:51:31] [e339dd08bcbfc073ac7494f09a949034] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.6
23.7
22
21.3
20.7
20.4
20.3
20.4
19.8
19.5
23.1
23.5
23.5
22.9
21.9
21.5
20.5
20.2
19.4
19.2
18.8
18.8
22.6
23.3
23
21.4
19.9
18.8
18.6
18.4
18.6
19.9
19.2
18.4
21.1
20.5
19.1
18.1
17
17.1
17.4
16.8
15.3
14.3
13.4
15.3
22.1
23.7
22.2
19.5
16.6
17.3
19.8
21.2
21.5
20.6
19.1
19.6
23.5
24

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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=70405&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=70405&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70405&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
125.625.6000
223.723.7748301328505-1.83135417540214-0.0748301328505352-1.44810168374356
32221.9465372012102-1.828587821622490.05346279878977120.00223915999513986
421.321.2147836974749-0.841543776764460.08521630252507750.762499701415953
520.720.6960169894596-0.5516656091205590.003983010540433140.224942038467864
620.420.3864496111449-0.3340394983559090.01355038885507890.168803164391284
720.320.2854751743608-0.1245262408067920.01452482563917640.162510907529433
820.420.38591278391870.07769222192049410.01408721608125040.156852187410448
919.819.8500810490141-0.473795942760007-0.0500810490140693-0.427765696544395
1019.519.4780164212245-0.3823505277534030.02198357877545290.070930282436396
1123.122.81507864763782.961001912453920.2849213523621782.59329494336066
1223.523.73149505767651.12314013941252-0.231495057676515-1.42555047010573
1323.523.5622425604115-0.0377602015796381-0.0622425604114833-0.90134728997822
1422.922.9521955245003-0.552642969998991-0.0521955245002888-0.40294974639098
1521.921.9706969947931-0.922509942553642-0.0706969947931021-0.290274379802242
1621.521.3900118177106-0.625344264288970.1099881822894480.230478927215265
1720.520.5307927472549-0.827683523507809-0.0307927472549413-0.156886744404214
1820.220.1588994712089-0.4330220163103370.04110052879113760.306170675989697
1919.419.4887954702558-0.638360236265276-0.0887954702558011-0.159269963078949
2019.219.0657634775065-0.4518695803813730.1342365224934700.144653294991571
2118.818.6805102261044-0.3941775326635600.1194897738956160.0447492369805966
2218.819.16574069442480.367427207661509-0.3657406944248390.590744251909306
2322.621.94499500681952.456237564406930.6550049931804871.62020863417254
2423.323.56283719451161.73025116135588-0.262837194511553-0.56312255012981
252323.2244276416474-0.0602066067708931-0.224427641647447-1.39058359824642
2621.421.5227040000091-1.48276851213894-0.122704000009090-1.10542355132324
2719.919.9850042003555-1.52962624574123-0.0850042003554598-0.0364664986028825
2818.818.6068530924527-1.399753807884400.1931469075472540.100894234343623
2918.618.5638121856395-0.2399217724623790.03618781436051980.898864720290756
3018.418.3456330967770-0.2213351769014650.05436690322302430.0144194645201181
3118.618.66349997703770.239799162959192-0.06349997703767880.357682098145959
3219.919.61318702948560.8469237110733420.2868129705143530.470919293061608
3319.219.2094264779113-0.222672912896664-0.00942647791128964-0.829640810164218
3418.419.1290634011095-0.100967612841749-0.7290634011095020.0944018439297358
3521.120.32600882516931.009011481797250.7739911748307260.860967642123709
3620.520.65565564492110.428193039487809-0.155655644921101-0.450547456268020
3719.119.2964161808192-1.09994836037982-0.196416180819169-1.18680540313525
3818.118.1709759820258-1.12174323724086-0.0709759820258269-0.0169063811079794
391717.0352854081878-1.13358183698342-0.0352854081877549-0.00919402025465744
4017.116.9665961484334-0.2271267354547290.1334038515666210.704217799230097
4117.417.27576471682220.2288093204037390.1242352831778420.353379938932194
4216.816.8944635864297-0.289560415791683-0.09446358642972-0.402100881756414
4315.315.6214506212061-1.12550080591388-0.3214506212061-0.648429295827709
4414.313.8443364896018-1.679432202108000.455663510398215-0.429656037037202
4513.413.2543344898595-0.7533237522794210.1456655101404530.718344339003485
4615.315.93589152943172.16659309092805-0.6358915294317052.26487757993197
4722.121.04003032794094.663526599544771.059969672059091.93675298877730
4823.723.83026718004253.07172722790736-0.130267180042515-1.23489682234395
4922.222.8068540711887-0.408988081556008-0.606854071188698-2.70245694173248
5019.519.7612055099355-2.64881609368622-0.261205509935523-1.73680562086236
5116.616.7838923072824-2.92676321861172-0.18389230728238-0.215719083988144
5217.316.9630543452069-0.2943578437347790.3369456547930672.04447234367712
5319.819.38607954015362.007911945561790.4139204598464491.78481278060656
5421.221.19058118536761.835712744140420.00941881463237196-0.133558544746134
5521.521.71836438930440.728111053498361-0.218364389304364-0.859176709977856
5620.620.2821364371752-1.105030886382800.317863562824792-1.42187340015066
5719.119.3444888265633-0.96325943109401-0.2444888265632780.109966450751919
5819.620.62826480160240.939906914563213-1.028264801602361.47622697555587
5923.522.34596264447051.598574810947971.154037355529510.510895478470541
602423.68239076040551.376634380167310.317609239594518-0.172190609779713

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 25.6 & 25.6 & 0 & 0 & 0 \tabularnewline
2 & 23.7 & 23.7748301328505 & -1.83135417540214 & -0.0748301328505352 & -1.44810168374356 \tabularnewline
3 & 22 & 21.9465372012102 & -1.82858782162249 & 0.0534627987897712 & 0.00223915999513986 \tabularnewline
4 & 21.3 & 21.2147836974749 & -0.84154377676446 & 0.0852163025250775 & 0.762499701415953 \tabularnewline
5 & 20.7 & 20.6960169894596 & -0.551665609120559 & 0.00398301054043314 & 0.224942038467864 \tabularnewline
6 & 20.4 & 20.3864496111449 & -0.334039498355909 & 0.0135503888550789 & 0.168803164391284 \tabularnewline
7 & 20.3 & 20.2854751743608 & -0.124526240806792 & 0.0145248256391764 & 0.162510907529433 \tabularnewline
8 & 20.4 & 20.3859127839187 & 0.0776922219204941 & 0.0140872160812504 & 0.156852187410448 \tabularnewline
9 & 19.8 & 19.8500810490141 & -0.473795942760007 & -0.0500810490140693 & -0.427765696544395 \tabularnewline
10 & 19.5 & 19.4780164212245 & -0.382350527753403 & 0.0219835787754529 & 0.070930282436396 \tabularnewline
11 & 23.1 & 22.8150786476378 & 2.96100191245392 & 0.284921352362178 & 2.59329494336066 \tabularnewline
12 & 23.5 & 23.7314950576765 & 1.12314013941252 & -0.231495057676515 & -1.42555047010573 \tabularnewline
13 & 23.5 & 23.5622425604115 & -0.0377602015796381 & -0.0622425604114833 & -0.90134728997822 \tabularnewline
14 & 22.9 & 22.9521955245003 & -0.552642969998991 & -0.0521955245002888 & -0.40294974639098 \tabularnewline
15 & 21.9 & 21.9706969947931 & -0.922509942553642 & -0.0706969947931021 & -0.290274379802242 \tabularnewline
16 & 21.5 & 21.3900118177106 & -0.62534426428897 & 0.109988182289448 & 0.230478927215265 \tabularnewline
17 & 20.5 & 20.5307927472549 & -0.827683523507809 & -0.0307927472549413 & -0.156886744404214 \tabularnewline
18 & 20.2 & 20.1588994712089 & -0.433022016310337 & 0.0411005287911376 & 0.306170675989697 \tabularnewline
19 & 19.4 & 19.4887954702558 & -0.638360236265276 & -0.0887954702558011 & -0.159269963078949 \tabularnewline
20 & 19.2 & 19.0657634775065 & -0.451869580381373 & 0.134236522493470 & 0.144653294991571 \tabularnewline
21 & 18.8 & 18.6805102261044 & -0.394177532663560 & 0.119489773895616 & 0.0447492369805966 \tabularnewline
22 & 18.8 & 19.1657406944248 & 0.367427207661509 & -0.365740694424839 & 0.590744251909306 \tabularnewline
23 & 22.6 & 21.9449950068195 & 2.45623756440693 & 0.655004993180487 & 1.62020863417254 \tabularnewline
24 & 23.3 & 23.5628371945116 & 1.73025116135588 & -0.262837194511553 & -0.56312255012981 \tabularnewline
25 & 23 & 23.2244276416474 & -0.0602066067708931 & -0.224427641647447 & -1.39058359824642 \tabularnewline
26 & 21.4 & 21.5227040000091 & -1.48276851213894 & -0.122704000009090 & -1.10542355132324 \tabularnewline
27 & 19.9 & 19.9850042003555 & -1.52962624574123 & -0.0850042003554598 & -0.0364664986028825 \tabularnewline
28 & 18.8 & 18.6068530924527 & -1.39975380788440 & 0.193146907547254 & 0.100894234343623 \tabularnewline
29 & 18.6 & 18.5638121856395 & -0.239921772462379 & 0.0361878143605198 & 0.898864720290756 \tabularnewline
30 & 18.4 & 18.3456330967770 & -0.221335176901465 & 0.0543669032230243 & 0.0144194645201181 \tabularnewline
31 & 18.6 & 18.6634999770377 & 0.239799162959192 & -0.0634999770376788 & 0.357682098145959 \tabularnewline
32 & 19.9 & 19.6131870294856 & 0.846923711073342 & 0.286812970514353 & 0.470919293061608 \tabularnewline
33 & 19.2 & 19.2094264779113 & -0.222672912896664 & -0.00942647791128964 & -0.829640810164218 \tabularnewline
34 & 18.4 & 19.1290634011095 & -0.100967612841749 & -0.729063401109502 & 0.0944018439297358 \tabularnewline
35 & 21.1 & 20.3260088251693 & 1.00901148179725 & 0.773991174830726 & 0.860967642123709 \tabularnewline
36 & 20.5 & 20.6556556449211 & 0.428193039487809 & -0.155655644921101 & -0.450547456268020 \tabularnewline
37 & 19.1 & 19.2964161808192 & -1.09994836037982 & -0.196416180819169 & -1.18680540313525 \tabularnewline
38 & 18.1 & 18.1709759820258 & -1.12174323724086 & -0.0709759820258269 & -0.0169063811079794 \tabularnewline
39 & 17 & 17.0352854081878 & -1.13358183698342 & -0.0352854081877549 & -0.00919402025465744 \tabularnewline
40 & 17.1 & 16.9665961484334 & -0.227126735454729 & 0.133403851566621 & 0.704217799230097 \tabularnewline
41 & 17.4 & 17.2757647168222 & 0.228809320403739 & 0.124235283177842 & 0.353379938932194 \tabularnewline
42 & 16.8 & 16.8944635864297 & -0.289560415791683 & -0.09446358642972 & -0.402100881756414 \tabularnewline
43 & 15.3 & 15.6214506212061 & -1.12550080591388 & -0.3214506212061 & -0.648429295827709 \tabularnewline
44 & 14.3 & 13.8443364896018 & -1.67943220210800 & 0.455663510398215 & -0.429656037037202 \tabularnewline
45 & 13.4 & 13.2543344898595 & -0.753323752279421 & 0.145665510140453 & 0.718344339003485 \tabularnewline
46 & 15.3 & 15.9358915294317 & 2.16659309092805 & -0.635891529431705 & 2.26487757993197 \tabularnewline
47 & 22.1 & 21.0400303279409 & 4.66352659954477 & 1.05996967205909 & 1.93675298877730 \tabularnewline
48 & 23.7 & 23.8302671800425 & 3.07172722790736 & -0.130267180042515 & -1.23489682234395 \tabularnewline
49 & 22.2 & 22.8068540711887 & -0.408988081556008 & -0.606854071188698 & -2.70245694173248 \tabularnewline
50 & 19.5 & 19.7612055099355 & -2.64881609368622 & -0.261205509935523 & -1.73680562086236 \tabularnewline
51 & 16.6 & 16.7838923072824 & -2.92676321861172 & -0.18389230728238 & -0.215719083988144 \tabularnewline
52 & 17.3 & 16.9630543452069 & -0.294357843734779 & 0.336945654793067 & 2.04447234367712 \tabularnewline
53 & 19.8 & 19.3860795401536 & 2.00791194556179 & 0.413920459846449 & 1.78481278060656 \tabularnewline
54 & 21.2 & 21.1905811853676 & 1.83571274414042 & 0.00941881463237196 & -0.133558544746134 \tabularnewline
55 & 21.5 & 21.7183643893044 & 0.728111053498361 & -0.218364389304364 & -0.859176709977856 \tabularnewline
56 & 20.6 & 20.2821364371752 & -1.10503088638280 & 0.317863562824792 & -1.42187340015066 \tabularnewline
57 & 19.1 & 19.3444888265633 & -0.96325943109401 & -0.244488826563278 & 0.109966450751919 \tabularnewline
58 & 19.6 & 20.6282648016024 & 0.939906914563213 & -1.02826480160236 & 1.47622697555587 \tabularnewline
59 & 23.5 & 22.3459626444705 & 1.59857481094797 & 1.15403735552951 & 0.510895478470541 \tabularnewline
60 & 24 & 23.6823907604055 & 1.37663438016731 & 0.317609239594518 & -0.172190609779713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70405&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]25.6[/C][C]25.6[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]23.7[/C][C]23.7748301328505[/C][C]-1.83135417540214[/C][C]-0.0748301328505352[/C][C]-1.44810168374356[/C][/ROW]
[ROW][C]3[/C][C]22[/C][C]21.9465372012102[/C][C]-1.82858782162249[/C][C]0.0534627987897712[/C][C]0.00223915999513986[/C][/ROW]
[ROW][C]4[/C][C]21.3[/C][C]21.2147836974749[/C][C]-0.84154377676446[/C][C]0.0852163025250775[/C][C]0.762499701415953[/C][/ROW]
[ROW][C]5[/C][C]20.7[/C][C]20.6960169894596[/C][C]-0.551665609120559[/C][C]0.00398301054043314[/C][C]0.224942038467864[/C][/ROW]
[ROW][C]6[/C][C]20.4[/C][C]20.3864496111449[/C][C]-0.334039498355909[/C][C]0.0135503888550789[/C][C]0.168803164391284[/C][/ROW]
[ROW][C]7[/C][C]20.3[/C][C]20.2854751743608[/C][C]-0.124526240806792[/C][C]0.0145248256391764[/C][C]0.162510907529433[/C][/ROW]
[ROW][C]8[/C][C]20.4[/C][C]20.3859127839187[/C][C]0.0776922219204941[/C][C]0.0140872160812504[/C][C]0.156852187410448[/C][/ROW]
[ROW][C]9[/C][C]19.8[/C][C]19.8500810490141[/C][C]-0.473795942760007[/C][C]-0.0500810490140693[/C][C]-0.427765696544395[/C][/ROW]
[ROW][C]10[/C][C]19.5[/C][C]19.4780164212245[/C][C]-0.382350527753403[/C][C]0.0219835787754529[/C][C]0.070930282436396[/C][/ROW]
[ROW][C]11[/C][C]23.1[/C][C]22.8150786476378[/C][C]2.96100191245392[/C][C]0.284921352362178[/C][C]2.59329494336066[/C][/ROW]
[ROW][C]12[/C][C]23.5[/C][C]23.7314950576765[/C][C]1.12314013941252[/C][C]-0.231495057676515[/C][C]-1.42555047010573[/C][/ROW]
[ROW][C]13[/C][C]23.5[/C][C]23.5622425604115[/C][C]-0.0377602015796381[/C][C]-0.0622425604114833[/C][C]-0.90134728997822[/C][/ROW]
[ROW][C]14[/C][C]22.9[/C][C]22.9521955245003[/C][C]-0.552642969998991[/C][C]-0.0521955245002888[/C][C]-0.40294974639098[/C][/ROW]
[ROW][C]15[/C][C]21.9[/C][C]21.9706969947931[/C][C]-0.922509942553642[/C][C]-0.0706969947931021[/C][C]-0.290274379802242[/C][/ROW]
[ROW][C]16[/C][C]21.5[/C][C]21.3900118177106[/C][C]-0.62534426428897[/C][C]0.109988182289448[/C][C]0.230478927215265[/C][/ROW]
[ROW][C]17[/C][C]20.5[/C][C]20.5307927472549[/C][C]-0.827683523507809[/C][C]-0.0307927472549413[/C][C]-0.156886744404214[/C][/ROW]
[ROW][C]18[/C][C]20.2[/C][C]20.1588994712089[/C][C]-0.433022016310337[/C][C]0.0411005287911376[/C][C]0.306170675989697[/C][/ROW]
[ROW][C]19[/C][C]19.4[/C][C]19.4887954702558[/C][C]-0.638360236265276[/C][C]-0.0887954702558011[/C][C]-0.159269963078949[/C][/ROW]
[ROW][C]20[/C][C]19.2[/C][C]19.0657634775065[/C][C]-0.451869580381373[/C][C]0.134236522493470[/C][C]0.144653294991571[/C][/ROW]
[ROW][C]21[/C][C]18.8[/C][C]18.6805102261044[/C][C]-0.394177532663560[/C][C]0.119489773895616[/C][C]0.0447492369805966[/C][/ROW]
[ROW][C]22[/C][C]18.8[/C][C]19.1657406944248[/C][C]0.367427207661509[/C][C]-0.365740694424839[/C][C]0.590744251909306[/C][/ROW]
[ROW][C]23[/C][C]22.6[/C][C]21.9449950068195[/C][C]2.45623756440693[/C][C]0.655004993180487[/C][C]1.62020863417254[/C][/ROW]
[ROW][C]24[/C][C]23.3[/C][C]23.5628371945116[/C][C]1.73025116135588[/C][C]-0.262837194511553[/C][C]-0.56312255012981[/C][/ROW]
[ROW][C]25[/C][C]23[/C][C]23.2244276416474[/C][C]-0.0602066067708931[/C][C]-0.224427641647447[/C][C]-1.39058359824642[/C][/ROW]
[ROW][C]26[/C][C]21.4[/C][C]21.5227040000091[/C][C]-1.48276851213894[/C][C]-0.122704000009090[/C][C]-1.10542355132324[/C][/ROW]
[ROW][C]27[/C][C]19.9[/C][C]19.9850042003555[/C][C]-1.52962624574123[/C][C]-0.0850042003554598[/C][C]-0.0364664986028825[/C][/ROW]
[ROW][C]28[/C][C]18.8[/C][C]18.6068530924527[/C][C]-1.39975380788440[/C][C]0.193146907547254[/C][C]0.100894234343623[/C][/ROW]
[ROW][C]29[/C][C]18.6[/C][C]18.5638121856395[/C][C]-0.239921772462379[/C][C]0.0361878143605198[/C][C]0.898864720290756[/C][/ROW]
[ROW][C]30[/C][C]18.4[/C][C]18.3456330967770[/C][C]-0.221335176901465[/C][C]0.0543669032230243[/C][C]0.0144194645201181[/C][/ROW]
[ROW][C]31[/C][C]18.6[/C][C]18.6634999770377[/C][C]0.239799162959192[/C][C]-0.0634999770376788[/C][C]0.357682098145959[/C][/ROW]
[ROW][C]32[/C][C]19.9[/C][C]19.6131870294856[/C][C]0.846923711073342[/C][C]0.286812970514353[/C][C]0.470919293061608[/C][/ROW]
[ROW][C]33[/C][C]19.2[/C][C]19.2094264779113[/C][C]-0.222672912896664[/C][C]-0.00942647791128964[/C][C]-0.829640810164218[/C][/ROW]
[ROW][C]34[/C][C]18.4[/C][C]19.1290634011095[/C][C]-0.100967612841749[/C][C]-0.729063401109502[/C][C]0.0944018439297358[/C][/ROW]
[ROW][C]35[/C][C]21.1[/C][C]20.3260088251693[/C][C]1.00901148179725[/C][C]0.773991174830726[/C][C]0.860967642123709[/C][/ROW]
[ROW][C]36[/C][C]20.5[/C][C]20.6556556449211[/C][C]0.428193039487809[/C][C]-0.155655644921101[/C][C]-0.450547456268020[/C][/ROW]
[ROW][C]37[/C][C]19.1[/C][C]19.2964161808192[/C][C]-1.09994836037982[/C][C]-0.196416180819169[/C][C]-1.18680540313525[/C][/ROW]
[ROW][C]38[/C][C]18.1[/C][C]18.1709759820258[/C][C]-1.12174323724086[/C][C]-0.0709759820258269[/C][C]-0.0169063811079794[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]17.0352854081878[/C][C]-1.13358183698342[/C][C]-0.0352854081877549[/C][C]-0.00919402025465744[/C][/ROW]
[ROW][C]40[/C][C]17.1[/C][C]16.9665961484334[/C][C]-0.227126735454729[/C][C]0.133403851566621[/C][C]0.704217799230097[/C][/ROW]
[ROW][C]41[/C][C]17.4[/C][C]17.2757647168222[/C][C]0.228809320403739[/C][C]0.124235283177842[/C][C]0.353379938932194[/C][/ROW]
[ROW][C]42[/C][C]16.8[/C][C]16.8944635864297[/C][C]-0.289560415791683[/C][C]-0.09446358642972[/C][C]-0.402100881756414[/C][/ROW]
[ROW][C]43[/C][C]15.3[/C][C]15.6214506212061[/C][C]-1.12550080591388[/C][C]-0.3214506212061[/C][C]-0.648429295827709[/C][/ROW]
[ROW][C]44[/C][C]14.3[/C][C]13.8443364896018[/C][C]-1.67943220210800[/C][C]0.455663510398215[/C][C]-0.429656037037202[/C][/ROW]
[ROW][C]45[/C][C]13.4[/C][C]13.2543344898595[/C][C]-0.753323752279421[/C][C]0.145665510140453[/C][C]0.718344339003485[/C][/ROW]
[ROW][C]46[/C][C]15.3[/C][C]15.9358915294317[/C][C]2.16659309092805[/C][C]-0.635891529431705[/C][C]2.26487757993197[/C][/ROW]
[ROW][C]47[/C][C]22.1[/C][C]21.0400303279409[/C][C]4.66352659954477[/C][C]1.05996967205909[/C][C]1.93675298877730[/C][/ROW]
[ROW][C]48[/C][C]23.7[/C][C]23.8302671800425[/C][C]3.07172722790736[/C][C]-0.130267180042515[/C][C]-1.23489682234395[/C][/ROW]
[ROW][C]49[/C][C]22.2[/C][C]22.8068540711887[/C][C]-0.408988081556008[/C][C]-0.606854071188698[/C][C]-2.70245694173248[/C][/ROW]
[ROW][C]50[/C][C]19.5[/C][C]19.7612055099355[/C][C]-2.64881609368622[/C][C]-0.261205509935523[/C][C]-1.73680562086236[/C][/ROW]
[ROW][C]51[/C][C]16.6[/C][C]16.7838923072824[/C][C]-2.92676321861172[/C][C]-0.18389230728238[/C][C]-0.215719083988144[/C][/ROW]
[ROW][C]52[/C][C]17.3[/C][C]16.9630543452069[/C][C]-0.294357843734779[/C][C]0.336945654793067[/C][C]2.04447234367712[/C][/ROW]
[ROW][C]53[/C][C]19.8[/C][C]19.3860795401536[/C][C]2.00791194556179[/C][C]0.413920459846449[/C][C]1.78481278060656[/C][/ROW]
[ROW][C]54[/C][C]21.2[/C][C]21.1905811853676[/C][C]1.83571274414042[/C][C]0.00941881463237196[/C][C]-0.133558544746134[/C][/ROW]
[ROW][C]55[/C][C]21.5[/C][C]21.7183643893044[/C][C]0.728111053498361[/C][C]-0.218364389304364[/C][C]-0.859176709977856[/C][/ROW]
[ROW][C]56[/C][C]20.6[/C][C]20.2821364371752[/C][C]-1.10503088638280[/C][C]0.317863562824792[/C][C]-1.42187340015066[/C][/ROW]
[ROW][C]57[/C][C]19.1[/C][C]19.3444888265633[/C][C]-0.96325943109401[/C][C]-0.244488826563278[/C][C]0.109966450751919[/C][/ROW]
[ROW][C]58[/C][C]19.6[/C][C]20.6282648016024[/C][C]0.939906914563213[/C][C]-1.02826480160236[/C][C]1.47622697555587[/C][/ROW]
[ROW][C]59[/C][C]23.5[/C][C]22.3459626444705[/C][C]1.59857481094797[/C][C]1.15403735552951[/C][C]0.510895478470541[/C][/ROW]
[ROW][C]60[/C][C]24[/C][C]23.6823907604055[/C][C]1.37663438016731[/C][C]0.317609239594518[/C][C]-0.172190609779713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70405&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70405&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
125.625.6000
223.723.7748301328505-1.83135417540214-0.0748301328505352-1.44810168374356
32221.9465372012102-1.828587821622490.05346279878977120.00223915999513986
421.321.2147836974749-0.841543776764460.08521630252507750.762499701415953
520.720.6960169894596-0.5516656091205590.003983010540433140.224942038467864
620.420.3864496111449-0.3340394983559090.01355038885507890.168803164391284
720.320.2854751743608-0.1245262408067920.01452482563917640.162510907529433
820.420.38591278391870.07769222192049410.01408721608125040.156852187410448
919.819.8500810490141-0.473795942760007-0.0500810490140693-0.427765696544395
1019.519.4780164212245-0.3823505277534030.02198357877545290.070930282436396
1123.122.81507864763782.961001912453920.2849213523621782.59329494336066
1223.523.73149505767651.12314013941252-0.231495057676515-1.42555047010573
1323.523.5622425604115-0.0377602015796381-0.0622425604114833-0.90134728997822
1422.922.9521955245003-0.552642969998991-0.0521955245002888-0.40294974639098
1521.921.9706969947931-0.922509942553642-0.0706969947931021-0.290274379802242
1621.521.3900118177106-0.625344264288970.1099881822894480.230478927215265
1720.520.5307927472549-0.827683523507809-0.0307927472549413-0.156886744404214
1820.220.1588994712089-0.4330220163103370.04110052879113760.306170675989697
1919.419.4887954702558-0.638360236265276-0.0887954702558011-0.159269963078949
2019.219.0657634775065-0.4518695803813730.1342365224934700.144653294991571
2118.818.6805102261044-0.3941775326635600.1194897738956160.0447492369805966
2218.819.16574069442480.367427207661509-0.3657406944248390.590744251909306
2322.621.94499500681952.456237564406930.6550049931804871.62020863417254
2423.323.56283719451161.73025116135588-0.262837194511553-0.56312255012981
252323.2244276416474-0.0602066067708931-0.224427641647447-1.39058359824642
2621.421.5227040000091-1.48276851213894-0.122704000009090-1.10542355132324
2719.919.9850042003555-1.52962624574123-0.0850042003554598-0.0364664986028825
2818.818.6068530924527-1.399753807884400.1931469075472540.100894234343623
2918.618.5638121856395-0.2399217724623790.03618781436051980.898864720290756
3018.418.3456330967770-0.2213351769014650.05436690322302430.0144194645201181
3118.618.66349997703770.239799162959192-0.06349997703767880.357682098145959
3219.919.61318702948560.8469237110733420.2868129705143530.470919293061608
3319.219.2094264779113-0.222672912896664-0.00942647791128964-0.829640810164218
3418.419.1290634011095-0.100967612841749-0.7290634011095020.0944018439297358
3521.120.32600882516931.009011481797250.7739911748307260.860967642123709
3620.520.65565564492110.428193039487809-0.155655644921101-0.450547456268020
3719.119.2964161808192-1.09994836037982-0.196416180819169-1.18680540313525
3818.118.1709759820258-1.12174323724086-0.0709759820258269-0.0169063811079794
391717.0352854081878-1.13358183698342-0.0352854081877549-0.00919402025465744
4017.116.9665961484334-0.2271267354547290.1334038515666210.704217799230097
4117.417.27576471682220.2288093204037390.1242352831778420.353379938932194
4216.816.8944635864297-0.289560415791683-0.09446358642972-0.402100881756414
4315.315.6214506212061-1.12550080591388-0.3214506212061-0.648429295827709
4414.313.8443364896018-1.679432202108000.455663510398215-0.429656037037202
4513.413.2543344898595-0.7533237522794210.1456655101404530.718344339003485
4615.315.93589152943172.16659309092805-0.6358915294317052.26487757993197
4722.121.04003032794094.663526599544771.059969672059091.93675298877730
4823.723.83026718004253.07172722790736-0.130267180042515-1.23489682234395
4922.222.8068540711887-0.408988081556008-0.606854071188698-2.70245694173248
5019.519.7612055099355-2.64881609368622-0.261205509935523-1.73680562086236
5116.616.7838923072824-2.92676321861172-0.18389230728238-0.215719083988144
5217.316.9630543452069-0.2943578437347790.3369456547930672.04447234367712
5319.819.38607954015362.007911945561790.4139204598464491.78481278060656
5421.221.19058118536761.835712744140420.00941881463237196-0.133558544746134
5521.521.71836438930440.728111053498361-0.218364389304364-0.859176709977856
5620.620.2821364371752-1.105030886382800.317863562824792-1.42187340015066
5719.119.3444888265633-0.96325943109401-0.2444888265632780.109966450751919
5819.620.62826480160240.939906914563213-1.028264801602361.47622697555587
5923.522.34596264447051.598574810947971.154037355529510.510895478470541
602423.68239076040551.376634380167310.317609239594518-0.172190609779713


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 1 ; par4 = 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')