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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 computationWed, 19 Nov 2014 08:04:29 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/19/t141638429525unqtoah6bb8sm.htm/, Retrieved Sun, 19 May 2024 05:43:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=256296, Retrieved Sun, 19 May 2024 05:43:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD          [Structural Time Series Models] [WS8,2] [2014-11-19 08:04:29] [8eaf8ca403eea369f03debd8dc66ae53] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9492	
8641	
9793	
9603	
9238	
9535	
10295	
9941	
9984	
9563	
8872	
9302
9215	
8834	
9998	
9604	
9507	
9718	
10095	
9583	
9883	
9365	
8919	
9449
9769	
9321	
9939	
9336	
10195	
9464	
10010	
10213	
9563	
9890	
9305	
9391
9928	
8686	
9843	
9627	
10074
9503	
10119	
10000	
9313	
9866	
9172	
9241
9659	
8904	
9755	
9080	
9435	
8971	
10063	
9793	
9454	
9759	
8820
9403
9676	
8642	
9402	
9610	
9294	
9448	
10319	
9548	
9801	
9596	
8923	
9746
9829	
9125	
9782	
9441	
9162	
9915	
10444	
10209	
9985	
9842	
9429	
10132

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256296&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256296&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'Gertrude Mary Cox' @ cox.wessa.net






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
194929492000
286419353.94675535422-14.1763242829604-312.863474726726-2.86177407322438
397939416.36640186067-3.60123666065379279.8826368666880.800569883902058
496039480.184217773544.4278155814580742.38693094529720.68179076371538
592389428.06060894123-1.24807013308052-116.768759157127-0.611984931994796
695359445.623019580380.36216728717893562.90459139915020.217455524679907
7102959655.8637378406315.9896842779578324.3798163845832.55372677090375
899419767.4993098936322.30773469219223.12899834375741.20916817550014
999849846.2910893608325.675792307379745.73437561027960.734804371409984
1095639805.8558288304922.0654087343402-132.321438635546-0.878856432349081
1188729596.3101176475110.344354431694-329.149313851174-3.13053925819834
1293029494.438006771675.032160954740162.06480013525061-1.53657312834543
1392159424.042734131598.23427224974114-34.5748547786858-1.42957841862997
1488349366.881853556016.86659523021322-420.995987672133-0.931841826458495
1599989439.052051372179.6691616564476464.4770326219290.813725178084009
1696049479.33689124911.111301530356381.20325932633520.378398993286193
1795079534.3435486714613.1018662213817-91.8216319304170.560084328408633
1897189610.2785161825815.735555749099811.60486306782620.830318775240127
19100959684.288832501217.9734855926502318.5211247557450.792329820359799
2095839691.3155145077617.5867910035805-90.5550144756991-0.152032056204648
2198839716.773274923317.8444007986565153.2165339348440.111029176963398
2293659652.8122434144515.3593384765695-150.62913108257-1.16772792986873
2389199548.5796761261912.0698429576238-426.24275897335-1.72566013840191
2494499497.8016148600910.718969945407860.5080203148325-0.92285826339194
2597699543.3863264576610.772139987645160.1957803110590.552289689978326
2693219610.2211819980411.5413952666034-386.95596519110.831002989627975
2799399613.8546423353311.3485978028962337.940158633545-0.110258096121086
2893369561.646656229919.50943100671437-125.607467281517-0.86897065814571
29101959716.7905816112913.8438312150448248.1576263434062.00227414334139
3094649711.6931047943613.2979830277125-217.304207762617-0.264206560452499
31100109714.0428067699813.0002253106494313.829948654509-0.155063421350295
32102139831.8220521440615.6623336363005207.463995756491.50380717506524
3395639763.9076115923713.69087517696-60.5425748912911-1.21255915963381
3498909791.5392142693613.992002197194374.78410831638560.204095537965611
3593059786.3893533275513.6287283616734-448.50715456236-0.282728427787302
3693919716.8296239295912.3943659269667-180.726049786608-1.24380670444812
3799289728.3067500749212.3863286206358201.330916775221-0.0140062787991646
3886869612.2708927898410.812244810547-702.655880788241-1.91759554816735
3998439571.831247935889.92477062564051357.350799254206-0.743519903366182
4096279624.0434976789710.7910657614726-66.79492889718370.604655162015811
41100749676.7573640726811.7011184697912328.3137989323550.598814574725271
4295039705.348471007412.0668080840641-230.2847891970030.242740744021456
43101199749.4853845814712.7366540050059315.9642791437250.4649027630007
44100009761.4692658048712.7217817347363239.800316381631-0.0110075025168472
4593139697.7694121003811.315636231006-254.676442797325-1.12622399422695
4698669700.6991054028911.1747996326693179.699091143438-0.124439645705827
4791729675.5127158318410.636543064683-440.554099250272-0.543145919381603
4892419620.691859496239.8290584101595-265.320765442519-0.984876283981306
4996599563.234307564849.15130417499438214.236624006562-1.01880834475512
5089049559.9111597429.01011821661432-634.181159629412-0.187080005254644
5197559542.061301385378.63854699339328258.919083849631-0.397026971840815
5290809475.69156409647.45025725836888-268.832863340717-1.0984662133797
5394359400.037404640016.04698458207407174.96307108974-1.21425059015095
5489719352.925224853515.13800204598096-292.18049823897-0.778739828698852
55100639414.307042054926.07933436657351553.2322788623470.828059991174772
5697939440.589012305246.40258244149893317.8976216852020.299140000427056
5794549493.774466282117.10460309391838-120.2262511791210.696565119365473
5897599512.828709139587.2694681282793225.491791601160.178831596697814
5988209459.415913113666.51741748875254-533.775103581447-0.91241601705493
6094039478.264533032716.65213493735144-96.84663930996090.18619088309623
6196769474.958588534016.55338067477008218.517264387148-0.150657322379099
6286429429.802262251626.01395852775606-697.536682997939-0.778581969298486
6394029353.892158795685.05162371416358189.799386916563-1.22403693760687
6496109425.864557617095.9207045031015669.24823221192420.994125579074142
6592949380.948464057575.221394708347280.0476478343998679-0.753633829792347
6694489453.790262692286.16862456953285-121.5799689879841.00351834981624
67103199534.503202100987.1999015379491656.4565849831681.10955985933959
6895489504.368432895966.70162810914865108.034546839623-0.557817385145915
6998019578.976830018197.55935385395701104.337252317221.0185728184384
7095969549.644399911317.12574809832176110.581676282173-0.555406314259543
7189239531.364028204216.85168361136631-563.950517615728-0.383744571975294
7297469583.390821894717.298207424938283.38080620772530.684051213753553
7398299591.933483182967.30985416168793234.8816616675190.018856238378301
7491259632.995780742617.63353233819984-567.0821284806530.510079555708074
7597829648.663210768327.71632971907493119.3451287948710.120889382038398
7694419604.114195466427.1378710704332-72.5025715691366-0.783669701668493
7791629532.688834866176.22652450157933-234.799104230591-1.17614738885665
7899159626.377849686227.2598668974721137.3289948413531.30992760867347
79104449674.929653813877.74417841809187697.5120658260960.619548141567886
80102099776.393644141898.81257100105285269.727744745671.40974537752263
8199859815.5312517459.14282210391568116.5940129533350.457410328318757
8298429813.927695245329.0325201253844746.8703933052008-0.162522662357679
8394299860.818430719059.39597319487175-498.2320044767310.573853161197481
84101329912.319544943039.7758724382756145.6653662080320.639225017732111

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 9492 & 9492 & 0 & 0 & 0 \tabularnewline
2 & 8641 & 9353.94675535422 & -14.1763242829604 & -312.863474726726 & -2.86177407322438 \tabularnewline
3 & 9793 & 9416.36640186067 & -3.60123666065379 & 279.882636866688 & 0.800569883902058 \tabularnewline
4 & 9603 & 9480.18421777354 & 4.42781558145807 & 42.3869309452972 & 0.68179076371538 \tabularnewline
5 & 9238 & 9428.06060894123 & -1.24807013308052 & -116.768759157127 & -0.611984931994796 \tabularnewline
6 & 9535 & 9445.62301958038 & 0.362167287178935 & 62.9045913991502 & 0.217455524679907 \tabularnewline
7 & 10295 & 9655.86373784063 & 15.9896842779578 & 324.379816384583 & 2.55372677090375 \tabularnewline
8 & 9941 & 9767.49930989363 & 22.307734692192 & 23.1289983437574 & 1.20916817550014 \tabularnewline
9 & 9984 & 9846.29108936083 & 25.6757923073797 & 45.7343756102796 & 0.734804371409984 \tabularnewline
10 & 9563 & 9805.85582883049 & 22.0654087343402 & -132.321438635546 & -0.878856432349081 \tabularnewline
11 & 8872 & 9596.31011764751 & 10.344354431694 & -329.149313851174 & -3.13053925819834 \tabularnewline
12 & 9302 & 9494.43800677167 & 5.03216095474016 & 2.06480013525061 & -1.53657312834543 \tabularnewline
13 & 9215 & 9424.04273413159 & 8.23427224974114 & -34.5748547786858 & -1.42957841862997 \tabularnewline
14 & 8834 & 9366.88185355601 & 6.86659523021322 & -420.995987672133 & -0.931841826458495 \tabularnewline
15 & 9998 & 9439.05205137217 & 9.6691616564476 & 464.477032621929 & 0.813725178084009 \tabularnewline
16 & 9604 & 9479.336891249 & 11.1113015303563 & 81.2032593263352 & 0.378398993286193 \tabularnewline
17 & 9507 & 9534.34354867146 & 13.1018662213817 & -91.821631930417 & 0.560084328408633 \tabularnewline
18 & 9718 & 9610.27851618258 & 15.7355557490998 & 11.6048630678262 & 0.830318775240127 \tabularnewline
19 & 10095 & 9684.2888325012 & 17.9734855926502 & 318.521124755745 & 0.792329820359799 \tabularnewline
20 & 9583 & 9691.31551450776 & 17.5867910035805 & -90.5550144756991 & -0.152032056204648 \tabularnewline
21 & 9883 & 9716.7732749233 & 17.8444007986565 & 153.216533934844 & 0.111029176963398 \tabularnewline
22 & 9365 & 9652.81224341445 & 15.3593384765695 & -150.62913108257 & -1.16772792986873 \tabularnewline
23 & 8919 & 9548.57967612619 & 12.0698429576238 & -426.24275897335 & -1.72566013840191 \tabularnewline
24 & 9449 & 9497.80161486009 & 10.7189699454078 & 60.5080203148325 & -0.92285826339194 \tabularnewline
25 & 9769 & 9543.38632645766 & 10.772139987645 & 160.195780311059 & 0.552289689978326 \tabularnewline
26 & 9321 & 9610.22118199804 & 11.5413952666034 & -386.9559651911 & 0.831002989627975 \tabularnewline
27 & 9939 & 9613.85464233533 & 11.3485978028962 & 337.940158633545 & -0.110258096121086 \tabularnewline
28 & 9336 & 9561.64665622991 & 9.50943100671437 & -125.607467281517 & -0.86897065814571 \tabularnewline
29 & 10195 & 9716.79058161129 & 13.8438312150448 & 248.157626343406 & 2.00227414334139 \tabularnewline
30 & 9464 & 9711.69310479436 & 13.2979830277125 & -217.304207762617 & -0.264206560452499 \tabularnewline
31 & 10010 & 9714.04280676998 & 13.0002253106494 & 313.829948654509 & -0.155063421350295 \tabularnewline
32 & 10213 & 9831.82205214406 & 15.6623336363005 & 207.46399575649 & 1.50380717506524 \tabularnewline
33 & 9563 & 9763.90761159237 & 13.69087517696 & -60.5425748912911 & -1.21255915963381 \tabularnewline
34 & 9890 & 9791.53921426936 & 13.9920021971943 & 74.7841083163856 & 0.204095537965611 \tabularnewline
35 & 9305 & 9786.38935332755 & 13.6287283616734 & -448.50715456236 & -0.282728427787302 \tabularnewline
36 & 9391 & 9716.82962392959 & 12.3943659269667 & -180.726049786608 & -1.24380670444812 \tabularnewline
37 & 9928 & 9728.30675007492 & 12.3863286206358 & 201.330916775221 & -0.0140062787991646 \tabularnewline
38 & 8686 & 9612.27089278984 & 10.812244810547 & -702.655880788241 & -1.91759554816735 \tabularnewline
39 & 9843 & 9571.83124793588 & 9.92477062564051 & 357.350799254206 & -0.743519903366182 \tabularnewline
40 & 9627 & 9624.04349767897 & 10.7910657614726 & -66.7949288971837 & 0.604655162015811 \tabularnewline
41 & 10074 & 9676.75736407268 & 11.7011184697912 & 328.313798932355 & 0.598814574725271 \tabularnewline
42 & 9503 & 9705.3484710074 & 12.0668080840641 & -230.284789197003 & 0.242740744021456 \tabularnewline
43 & 10119 & 9749.48538458147 & 12.7366540050059 & 315.964279143725 & 0.4649027630007 \tabularnewline
44 & 10000 & 9761.46926580487 & 12.7217817347363 & 239.800316381631 & -0.0110075025168472 \tabularnewline
45 & 9313 & 9697.76941210038 & 11.315636231006 & -254.676442797325 & -1.12622399422695 \tabularnewline
46 & 9866 & 9700.69910540289 & 11.1747996326693 & 179.699091143438 & -0.124439645705827 \tabularnewline
47 & 9172 & 9675.51271583184 & 10.636543064683 & -440.554099250272 & -0.543145919381603 \tabularnewline
48 & 9241 & 9620.69185949623 & 9.8290584101595 & -265.320765442519 & -0.984876283981306 \tabularnewline
49 & 9659 & 9563.23430756484 & 9.15130417499438 & 214.236624006562 & -1.01880834475512 \tabularnewline
50 & 8904 & 9559.911159742 & 9.01011821661432 & -634.181159629412 & -0.187080005254644 \tabularnewline
51 & 9755 & 9542.06130138537 & 8.63854699339328 & 258.919083849631 & -0.397026971840815 \tabularnewline
52 & 9080 & 9475.6915640964 & 7.45025725836888 & -268.832863340717 & -1.0984662133797 \tabularnewline
53 & 9435 & 9400.03740464001 & 6.04698458207407 & 174.96307108974 & -1.21425059015095 \tabularnewline
54 & 8971 & 9352.92522485351 & 5.13800204598096 & -292.18049823897 & -0.778739828698852 \tabularnewline
55 & 10063 & 9414.30704205492 & 6.07933436657351 & 553.232278862347 & 0.828059991174772 \tabularnewline
56 & 9793 & 9440.58901230524 & 6.40258244149893 & 317.897621685202 & 0.299140000427056 \tabularnewline
57 & 9454 & 9493.77446628211 & 7.10460309391838 & -120.226251179121 & 0.696565119365473 \tabularnewline
58 & 9759 & 9512.82870913958 & 7.2694681282793 & 225.49179160116 & 0.178831596697814 \tabularnewline
59 & 8820 & 9459.41591311366 & 6.51741748875254 & -533.775103581447 & -0.91241601705493 \tabularnewline
60 & 9403 & 9478.26453303271 & 6.65213493735144 & -96.8466393099609 & 0.18619088309623 \tabularnewline
61 & 9676 & 9474.95858853401 & 6.55338067477008 & 218.517264387148 & -0.150657322379099 \tabularnewline
62 & 8642 & 9429.80226225162 & 6.01395852775606 & -697.536682997939 & -0.778581969298486 \tabularnewline
63 & 9402 & 9353.89215879568 & 5.05162371416358 & 189.799386916563 & -1.22403693760687 \tabularnewline
64 & 9610 & 9425.86455761709 & 5.92070450310156 & 69.2482322119242 & 0.994125579074142 \tabularnewline
65 & 9294 & 9380.94846405757 & 5.22139470834728 & 0.0476478343998679 & -0.753633829792347 \tabularnewline
66 & 9448 & 9453.79026269228 & 6.16862456953285 & -121.579968987984 & 1.00351834981624 \tabularnewline
67 & 10319 & 9534.50320210098 & 7.1999015379491 & 656.456584983168 & 1.10955985933959 \tabularnewline
68 & 9548 & 9504.36843289596 & 6.70162810914865 & 108.034546839623 & -0.557817385145915 \tabularnewline
69 & 9801 & 9578.97683001819 & 7.55935385395701 & 104.33725231722 & 1.0185728184384 \tabularnewline
70 & 9596 & 9549.64439991131 & 7.12574809832176 & 110.581676282173 & -0.555406314259543 \tabularnewline
71 & 8923 & 9531.36402820421 & 6.85168361136631 & -563.950517615728 & -0.383744571975294 \tabularnewline
72 & 9746 & 9583.39082189471 & 7.2982074249382 & 83.3808062077253 & 0.684051213753553 \tabularnewline
73 & 9829 & 9591.93348318296 & 7.30985416168793 & 234.881661667519 & 0.018856238378301 \tabularnewline
74 & 9125 & 9632.99578074261 & 7.63353233819984 & -567.082128480653 & 0.510079555708074 \tabularnewline
75 & 9782 & 9648.66321076832 & 7.71632971907493 & 119.345128794871 & 0.120889382038398 \tabularnewline
76 & 9441 & 9604.11419546642 & 7.1378710704332 & -72.5025715691366 & -0.783669701668493 \tabularnewline
77 & 9162 & 9532.68883486617 & 6.22652450157933 & -234.799104230591 & -1.17614738885665 \tabularnewline
78 & 9915 & 9626.37784968622 & 7.2598668974721 & 137.328994841353 & 1.30992760867347 \tabularnewline
79 & 10444 & 9674.92965381387 & 7.74417841809187 & 697.512065826096 & 0.619548141567886 \tabularnewline
80 & 10209 & 9776.39364414189 & 8.81257100105285 & 269.72774474567 & 1.40974537752263 \tabularnewline
81 & 9985 & 9815.531251745 & 9.14282210391568 & 116.594012953335 & 0.457410328318757 \tabularnewline
82 & 9842 & 9813.92769524532 & 9.03252012538447 & 46.8703933052008 & -0.162522662357679 \tabularnewline
83 & 9429 & 9860.81843071905 & 9.39597319487175 & -498.232004476731 & 0.573853161197481 \tabularnewline
84 & 10132 & 9912.31954494303 & 9.7758724382756 & 145.665366208032 & 0.639225017732111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256296&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]9492[/C][C]9492[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]8641[/C][C]9353.94675535422[/C][C]-14.1763242829604[/C][C]-312.863474726726[/C][C]-2.86177407322438[/C][/ROW]
[ROW][C]3[/C][C]9793[/C][C]9416.36640186067[/C][C]-3.60123666065379[/C][C]279.882636866688[/C][C]0.800569883902058[/C][/ROW]
[ROW][C]4[/C][C]9603[/C][C]9480.18421777354[/C][C]4.42781558145807[/C][C]42.3869309452972[/C][C]0.68179076371538[/C][/ROW]
[ROW][C]5[/C][C]9238[/C][C]9428.06060894123[/C][C]-1.24807013308052[/C][C]-116.768759157127[/C][C]-0.611984931994796[/C][/ROW]
[ROW][C]6[/C][C]9535[/C][C]9445.62301958038[/C][C]0.362167287178935[/C][C]62.9045913991502[/C][C]0.217455524679907[/C][/ROW]
[ROW][C]7[/C][C]10295[/C][C]9655.86373784063[/C][C]15.9896842779578[/C][C]324.379816384583[/C][C]2.55372677090375[/C][/ROW]
[ROW][C]8[/C][C]9941[/C][C]9767.49930989363[/C][C]22.307734692192[/C][C]23.1289983437574[/C][C]1.20916817550014[/C][/ROW]
[ROW][C]9[/C][C]9984[/C][C]9846.29108936083[/C][C]25.6757923073797[/C][C]45.7343756102796[/C][C]0.734804371409984[/C][/ROW]
[ROW][C]10[/C][C]9563[/C][C]9805.85582883049[/C][C]22.0654087343402[/C][C]-132.321438635546[/C][C]-0.878856432349081[/C][/ROW]
[ROW][C]11[/C][C]8872[/C][C]9596.31011764751[/C][C]10.344354431694[/C][C]-329.149313851174[/C][C]-3.13053925819834[/C][/ROW]
[ROW][C]12[/C][C]9302[/C][C]9494.43800677167[/C][C]5.03216095474016[/C][C]2.06480013525061[/C][C]-1.53657312834543[/C][/ROW]
[ROW][C]13[/C][C]9215[/C][C]9424.04273413159[/C][C]8.23427224974114[/C][C]-34.5748547786858[/C][C]-1.42957841862997[/C][/ROW]
[ROW][C]14[/C][C]8834[/C][C]9366.88185355601[/C][C]6.86659523021322[/C][C]-420.995987672133[/C][C]-0.931841826458495[/C][/ROW]
[ROW][C]15[/C][C]9998[/C][C]9439.05205137217[/C][C]9.6691616564476[/C][C]464.477032621929[/C][C]0.813725178084009[/C][/ROW]
[ROW][C]16[/C][C]9604[/C][C]9479.336891249[/C][C]11.1113015303563[/C][C]81.2032593263352[/C][C]0.378398993286193[/C][/ROW]
[ROW][C]17[/C][C]9507[/C][C]9534.34354867146[/C][C]13.1018662213817[/C][C]-91.821631930417[/C][C]0.560084328408633[/C][/ROW]
[ROW][C]18[/C][C]9718[/C][C]9610.27851618258[/C][C]15.7355557490998[/C][C]11.6048630678262[/C][C]0.830318775240127[/C][/ROW]
[ROW][C]19[/C][C]10095[/C][C]9684.2888325012[/C][C]17.9734855926502[/C][C]318.521124755745[/C][C]0.792329820359799[/C][/ROW]
[ROW][C]20[/C][C]9583[/C][C]9691.31551450776[/C][C]17.5867910035805[/C][C]-90.5550144756991[/C][C]-0.152032056204648[/C][/ROW]
[ROW][C]21[/C][C]9883[/C][C]9716.7732749233[/C][C]17.8444007986565[/C][C]153.216533934844[/C][C]0.111029176963398[/C][/ROW]
[ROW][C]22[/C][C]9365[/C][C]9652.81224341445[/C][C]15.3593384765695[/C][C]-150.62913108257[/C][C]-1.16772792986873[/C][/ROW]
[ROW][C]23[/C][C]8919[/C][C]9548.57967612619[/C][C]12.0698429576238[/C][C]-426.24275897335[/C][C]-1.72566013840191[/C][/ROW]
[ROW][C]24[/C][C]9449[/C][C]9497.80161486009[/C][C]10.7189699454078[/C][C]60.5080203148325[/C][C]-0.92285826339194[/C][/ROW]
[ROW][C]25[/C][C]9769[/C][C]9543.38632645766[/C][C]10.772139987645[/C][C]160.195780311059[/C][C]0.552289689978326[/C][/ROW]
[ROW][C]26[/C][C]9321[/C][C]9610.22118199804[/C][C]11.5413952666034[/C][C]-386.9559651911[/C][C]0.831002989627975[/C][/ROW]
[ROW][C]27[/C][C]9939[/C][C]9613.85464233533[/C][C]11.3485978028962[/C][C]337.940158633545[/C][C]-0.110258096121086[/C][/ROW]
[ROW][C]28[/C][C]9336[/C][C]9561.64665622991[/C][C]9.50943100671437[/C][C]-125.607467281517[/C][C]-0.86897065814571[/C][/ROW]
[ROW][C]29[/C][C]10195[/C][C]9716.79058161129[/C][C]13.8438312150448[/C][C]248.157626343406[/C][C]2.00227414334139[/C][/ROW]
[ROW][C]30[/C][C]9464[/C][C]9711.69310479436[/C][C]13.2979830277125[/C][C]-217.304207762617[/C][C]-0.264206560452499[/C][/ROW]
[ROW][C]31[/C][C]10010[/C][C]9714.04280676998[/C][C]13.0002253106494[/C][C]313.829948654509[/C][C]-0.155063421350295[/C][/ROW]
[ROW][C]32[/C][C]10213[/C][C]9831.82205214406[/C][C]15.6623336363005[/C][C]207.46399575649[/C][C]1.50380717506524[/C][/ROW]
[ROW][C]33[/C][C]9563[/C][C]9763.90761159237[/C][C]13.69087517696[/C][C]-60.5425748912911[/C][C]-1.21255915963381[/C][/ROW]
[ROW][C]34[/C][C]9890[/C][C]9791.53921426936[/C][C]13.9920021971943[/C][C]74.7841083163856[/C][C]0.204095537965611[/C][/ROW]
[ROW][C]35[/C][C]9305[/C][C]9786.38935332755[/C][C]13.6287283616734[/C][C]-448.50715456236[/C][C]-0.282728427787302[/C][/ROW]
[ROW][C]36[/C][C]9391[/C][C]9716.82962392959[/C][C]12.3943659269667[/C][C]-180.726049786608[/C][C]-1.24380670444812[/C][/ROW]
[ROW][C]37[/C][C]9928[/C][C]9728.30675007492[/C][C]12.3863286206358[/C][C]201.330916775221[/C][C]-0.0140062787991646[/C][/ROW]
[ROW][C]38[/C][C]8686[/C][C]9612.27089278984[/C][C]10.812244810547[/C][C]-702.655880788241[/C][C]-1.91759554816735[/C][/ROW]
[ROW][C]39[/C][C]9843[/C][C]9571.83124793588[/C][C]9.92477062564051[/C][C]357.350799254206[/C][C]-0.743519903366182[/C][/ROW]
[ROW][C]40[/C][C]9627[/C][C]9624.04349767897[/C][C]10.7910657614726[/C][C]-66.7949288971837[/C][C]0.604655162015811[/C][/ROW]
[ROW][C]41[/C][C]10074[/C][C]9676.75736407268[/C][C]11.7011184697912[/C][C]328.313798932355[/C][C]0.598814574725271[/C][/ROW]
[ROW][C]42[/C][C]9503[/C][C]9705.3484710074[/C][C]12.0668080840641[/C][C]-230.284789197003[/C][C]0.242740744021456[/C][/ROW]
[ROW][C]43[/C][C]10119[/C][C]9749.48538458147[/C][C]12.7366540050059[/C][C]315.964279143725[/C][C]0.4649027630007[/C][/ROW]
[ROW][C]44[/C][C]10000[/C][C]9761.46926580487[/C][C]12.7217817347363[/C][C]239.800316381631[/C][C]-0.0110075025168472[/C][/ROW]
[ROW][C]45[/C][C]9313[/C][C]9697.76941210038[/C][C]11.315636231006[/C][C]-254.676442797325[/C][C]-1.12622399422695[/C][/ROW]
[ROW][C]46[/C][C]9866[/C][C]9700.69910540289[/C][C]11.1747996326693[/C][C]179.699091143438[/C][C]-0.124439645705827[/C][/ROW]
[ROW][C]47[/C][C]9172[/C][C]9675.51271583184[/C][C]10.636543064683[/C][C]-440.554099250272[/C][C]-0.543145919381603[/C][/ROW]
[ROW][C]48[/C][C]9241[/C][C]9620.69185949623[/C][C]9.8290584101595[/C][C]-265.320765442519[/C][C]-0.984876283981306[/C][/ROW]
[ROW][C]49[/C][C]9659[/C][C]9563.23430756484[/C][C]9.15130417499438[/C][C]214.236624006562[/C][C]-1.01880834475512[/C][/ROW]
[ROW][C]50[/C][C]8904[/C][C]9559.911159742[/C][C]9.01011821661432[/C][C]-634.181159629412[/C][C]-0.187080005254644[/C][/ROW]
[ROW][C]51[/C][C]9755[/C][C]9542.06130138537[/C][C]8.63854699339328[/C][C]258.919083849631[/C][C]-0.397026971840815[/C][/ROW]
[ROW][C]52[/C][C]9080[/C][C]9475.6915640964[/C][C]7.45025725836888[/C][C]-268.832863340717[/C][C]-1.0984662133797[/C][/ROW]
[ROW][C]53[/C][C]9435[/C][C]9400.03740464001[/C][C]6.04698458207407[/C][C]174.96307108974[/C][C]-1.21425059015095[/C][/ROW]
[ROW][C]54[/C][C]8971[/C][C]9352.92522485351[/C][C]5.13800204598096[/C][C]-292.18049823897[/C][C]-0.778739828698852[/C][/ROW]
[ROW][C]55[/C][C]10063[/C][C]9414.30704205492[/C][C]6.07933436657351[/C][C]553.232278862347[/C][C]0.828059991174772[/C][/ROW]
[ROW][C]56[/C][C]9793[/C][C]9440.58901230524[/C][C]6.40258244149893[/C][C]317.897621685202[/C][C]0.299140000427056[/C][/ROW]
[ROW][C]57[/C][C]9454[/C][C]9493.77446628211[/C][C]7.10460309391838[/C][C]-120.226251179121[/C][C]0.696565119365473[/C][/ROW]
[ROW][C]58[/C][C]9759[/C][C]9512.82870913958[/C][C]7.2694681282793[/C][C]225.49179160116[/C][C]0.178831596697814[/C][/ROW]
[ROW][C]59[/C][C]8820[/C][C]9459.41591311366[/C][C]6.51741748875254[/C][C]-533.775103581447[/C][C]-0.91241601705493[/C][/ROW]
[ROW][C]60[/C][C]9403[/C][C]9478.26453303271[/C][C]6.65213493735144[/C][C]-96.8466393099609[/C][C]0.18619088309623[/C][/ROW]
[ROW][C]61[/C][C]9676[/C][C]9474.95858853401[/C][C]6.55338067477008[/C][C]218.517264387148[/C][C]-0.150657322379099[/C][/ROW]
[ROW][C]62[/C][C]8642[/C][C]9429.80226225162[/C][C]6.01395852775606[/C][C]-697.536682997939[/C][C]-0.778581969298486[/C][/ROW]
[ROW][C]63[/C][C]9402[/C][C]9353.89215879568[/C][C]5.05162371416358[/C][C]189.799386916563[/C][C]-1.22403693760687[/C][/ROW]
[ROW][C]64[/C][C]9610[/C][C]9425.86455761709[/C][C]5.92070450310156[/C][C]69.2482322119242[/C][C]0.994125579074142[/C][/ROW]
[ROW][C]65[/C][C]9294[/C][C]9380.94846405757[/C][C]5.22139470834728[/C][C]0.0476478343998679[/C][C]-0.753633829792347[/C][/ROW]
[ROW][C]66[/C][C]9448[/C][C]9453.79026269228[/C][C]6.16862456953285[/C][C]-121.579968987984[/C][C]1.00351834981624[/C][/ROW]
[ROW][C]67[/C][C]10319[/C][C]9534.50320210098[/C][C]7.1999015379491[/C][C]656.456584983168[/C][C]1.10955985933959[/C][/ROW]
[ROW][C]68[/C][C]9548[/C][C]9504.36843289596[/C][C]6.70162810914865[/C][C]108.034546839623[/C][C]-0.557817385145915[/C][/ROW]
[ROW][C]69[/C][C]9801[/C][C]9578.97683001819[/C][C]7.55935385395701[/C][C]104.33725231722[/C][C]1.0185728184384[/C][/ROW]
[ROW][C]70[/C][C]9596[/C][C]9549.64439991131[/C][C]7.12574809832176[/C][C]110.581676282173[/C][C]-0.555406314259543[/C][/ROW]
[ROW][C]71[/C][C]8923[/C][C]9531.36402820421[/C][C]6.85168361136631[/C][C]-563.950517615728[/C][C]-0.383744571975294[/C][/ROW]
[ROW][C]72[/C][C]9746[/C][C]9583.39082189471[/C][C]7.2982074249382[/C][C]83.3808062077253[/C][C]0.684051213753553[/C][/ROW]
[ROW][C]73[/C][C]9829[/C][C]9591.93348318296[/C][C]7.30985416168793[/C][C]234.881661667519[/C][C]0.018856238378301[/C][/ROW]
[ROW][C]74[/C][C]9125[/C][C]9632.99578074261[/C][C]7.63353233819984[/C][C]-567.082128480653[/C][C]0.510079555708074[/C][/ROW]
[ROW][C]75[/C][C]9782[/C][C]9648.66321076832[/C][C]7.71632971907493[/C][C]119.345128794871[/C][C]0.120889382038398[/C][/ROW]
[ROW][C]76[/C][C]9441[/C][C]9604.11419546642[/C][C]7.1378710704332[/C][C]-72.5025715691366[/C][C]-0.783669701668493[/C][/ROW]
[ROW][C]77[/C][C]9162[/C][C]9532.68883486617[/C][C]6.22652450157933[/C][C]-234.799104230591[/C][C]-1.17614738885665[/C][/ROW]
[ROW][C]78[/C][C]9915[/C][C]9626.37784968622[/C][C]7.2598668974721[/C][C]137.328994841353[/C][C]1.30992760867347[/C][/ROW]
[ROW][C]79[/C][C]10444[/C][C]9674.92965381387[/C][C]7.74417841809187[/C][C]697.512065826096[/C][C]0.619548141567886[/C][/ROW]
[ROW][C]80[/C][C]10209[/C][C]9776.39364414189[/C][C]8.81257100105285[/C][C]269.72774474567[/C][C]1.40974537752263[/C][/ROW]
[ROW][C]81[/C][C]9985[/C][C]9815.531251745[/C][C]9.14282210391568[/C][C]116.594012953335[/C][C]0.457410328318757[/C][/ROW]
[ROW][C]82[/C][C]9842[/C][C]9813.92769524532[/C][C]9.03252012538447[/C][C]46.8703933052008[/C][C]-0.162522662357679[/C][/ROW]
[ROW][C]83[/C][C]9429[/C][C]9860.81843071905[/C][C]9.39597319487175[/C][C]-498.232004476731[/C][C]0.573853161197481[/C][/ROW]
[ROW][C]84[/C][C]10132[/C][C]9912.31954494303[/C][C]9.7758724382756[/C][C]145.665366208032[/C][C]0.639225017732111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256296&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
194929492000
286419353.94675535422-14.1763242829604-312.863474726726-2.86177407322438
397939416.36640186067-3.60123666065379279.8826368666880.800569883902058
496039480.184217773544.4278155814580742.38693094529720.68179076371538
592389428.06060894123-1.24807013308052-116.768759157127-0.611984931994796
695359445.623019580380.36216728717893562.90459139915020.217455524679907
7102959655.8637378406315.9896842779578324.3798163845832.55372677090375
899419767.4993098936322.30773469219223.12899834375741.20916817550014
999849846.2910893608325.675792307379745.73437561027960.734804371409984
1095639805.8558288304922.0654087343402-132.321438635546-0.878856432349081
1188729596.3101176475110.344354431694-329.149313851174-3.13053925819834
1293029494.438006771675.032160954740162.06480013525061-1.53657312834543
1392159424.042734131598.23427224974114-34.5748547786858-1.42957841862997
1488349366.881853556016.86659523021322-420.995987672133-0.931841826458495
1599989439.052051372179.6691616564476464.4770326219290.813725178084009
1696049479.33689124911.111301530356381.20325932633520.378398993286193
1795079534.3435486714613.1018662213817-91.8216319304170.560084328408633
1897189610.2785161825815.735555749099811.60486306782620.830318775240127
19100959684.288832501217.9734855926502318.5211247557450.792329820359799
2095839691.3155145077617.5867910035805-90.5550144756991-0.152032056204648
2198839716.773274923317.8444007986565153.2165339348440.111029176963398
2293659652.8122434144515.3593384765695-150.62913108257-1.16772792986873
2389199548.5796761261912.0698429576238-426.24275897335-1.72566013840191
2494499497.8016148600910.718969945407860.5080203148325-0.92285826339194
2597699543.3863264576610.772139987645160.1957803110590.552289689978326
2693219610.2211819980411.5413952666034-386.95596519110.831002989627975
2799399613.8546423353311.3485978028962337.940158633545-0.110258096121086
2893369561.646656229919.50943100671437-125.607467281517-0.86897065814571
29101959716.7905816112913.8438312150448248.1576263434062.00227414334139
3094649711.6931047943613.2979830277125-217.304207762617-0.264206560452499
31100109714.0428067699813.0002253106494313.829948654509-0.155063421350295
32102139831.8220521440615.6623336363005207.463995756491.50380717506524
3395639763.9076115923713.69087517696-60.5425748912911-1.21255915963381
3498909791.5392142693613.992002197194374.78410831638560.204095537965611
3593059786.3893533275513.6287283616734-448.50715456236-0.282728427787302
3693919716.8296239295912.3943659269667-180.726049786608-1.24380670444812
3799289728.3067500749212.3863286206358201.330916775221-0.0140062787991646
3886869612.2708927898410.812244810547-702.655880788241-1.91759554816735
3998439571.831247935889.92477062564051357.350799254206-0.743519903366182
4096279624.0434976789710.7910657614726-66.79492889718370.604655162015811
41100749676.7573640726811.7011184697912328.3137989323550.598814574725271
4295039705.348471007412.0668080840641-230.2847891970030.242740744021456
43101199749.4853845814712.7366540050059315.9642791437250.4649027630007
44100009761.4692658048712.7217817347363239.800316381631-0.0110075025168472
4593139697.7694121003811.315636231006-254.676442797325-1.12622399422695
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7694419604.114195466427.1378710704332-72.5025715691366-0.783669701668493
7791629532.688834866176.22652450157933-234.799104230591-1.17614738885665
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79104449674.929653813877.74417841809187697.5120658260960.619548141567886
80102099776.393644141898.81257100105285269.727744745671.40974537752263
8199859815.5312517459.14282210391568116.5940129533350.457410328318757
8298429813.927695245329.0325201253844746.8703933052008-0.162522662357679
8394299860.818430719059.39597319487175-498.2320044767310.573853161197481
84101329912.319544943039.7758724382756145.6653662080320.639225017732111


Figures (Output of Computation)

Input Parameters & R Code

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')