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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationSun, 11 Nov 2012 11:51:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/11/t13526527339arsfj970swazv9.htm/, Retrieved Fri, 03 May 2024 10:22:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187541, Retrieved Fri, 03 May 2024 10:22:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [test 3] [2012-11-11 16:51:51] [09a8c52255f1f9505addc8ea27636e79] [Current]
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Dataseries X:
9.676
8.642
9.402
9.610
9.294
9.448
10.319
9.548
9.801
9.596
8.923
9.746
9.829
9.125
9.782
9.441
9.162
9.915
10.444
10.209
9.985
9.842
9.429
10.132
9.849
9.172
10.313
9.819
9.955
10.048
10.082
10.541
10.208
10.233
9.439
9.963
10.158
9.225
10.474
9.757
10.490
10.281
10.444
10.640
10.695
10.786
9.832
9.747
10.411
9.511
10.402
9.701
10.540
10.112
10.915
11.183
10.384
10.834
9.886
10.216
10.943
9.867
10.203
10.837
10.573
10.647
11.502
10.656
10.866
10.835
9.945
10.331
10.718
9.462
10.579
10.633
10.346
10.757
11.207
11.013
11.015
10.765
10.042
10.661




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 5 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187541&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187541&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
19.6769.676000
28.6429.603967695992480.0037394895423648-0.635058359433444-3.47443271267423
39.4029.45401077342991-0.01831337970764450.0917052633369661-1.7839977791407
49.619.43894767543408-0.01788047047981530.1686843182694670.0319664407104806
59.2949.39464770528669-0.0209346464613445-0.0795135764902457-0.283132125202997
69.4489.38938852884792-0.019377461811760.04425487797773170.187641947747878
710.3199.58042412606209-0.001304010524922510.5236361233911542.75166179230744
89.5489.627878577306530.00236634682640294-0.1337931073460510.680043723035899
99.8019.676496327674380.005466457907320640.07039356868627880.6754774252295
109.5969.677485128304920.00519504145954117-0.0760304554521848-0.0675980843382872
118.9239.53814577187952-0.0028374757067737-0.433800968321019-2.23560178201297
129.7469.53267329017727-0.002973287942299660.21670642319818-0.0415040319391615
139.8299.53144970730544-0.002984065215540540.2947858055234680.0347006197747974
149.1259.5440510591881-0.00271303345401848-0.4404804092510160.271745824741238
159.7829.57494981318903-0.001453570764017240.1676437984273320.513030534567471
169.4419.52939855088511-0.00347671029563411-0.0401051136396316-0.640253557225453
179.1629.47664406780267-0.00582601190212476-0.260770145080189-0.718434981877873
189.9159.56351469535383-0.001536637780393490.2474010818898391.38630358411364
1910.4449.659368574089450.002702710304378730.671606300492031.49962559961438
2010.2099.81044376443880.008695219734197810.2210618851256472.34501331825596
219.9859.868643711164750.01053851608878190.05561506325712170.799334414619553
229.8429.878913153374220.0105293543427928-0.0365759965042006-0.00442061204912929
239.4299.885739690761590.0104168171042543-0.45201073500547-0.0617673854028371
2410.1329.900954985530480.01053737226294040.224778503298110.0814923110828912
259.8499.865036702839590.009820665486109750.0471643893365732-0.819407515218257
269.1729.824479958809970.00894473785376252-0.585339933389858-0.871909808635459
2710.3139.864745027055250.00966147106601620.408328514309150.522128326411872
289.8199.885500738708960.00996257825657431-0.08019868939930880.180396640687546
299.9559.979538436661840.012424873216196-0.1271550297410111.35713037262053
3010.04810.01134460400730.01300118409139020.01292171836334340.314314062753663
3110.0829.956126505196670.01101835153963960.210328891185492-1.11790152955937
3210.54110.01352354251930.01230399682899740.4692766202107940.769202123806266
3310.20810.05733637405170.01312198843914850.1105823679393030.528690174813661
3410.23310.10883376206790.01403850769719910.07472489655360910.65073156662347
359.43910.09367855624110.0134117634359361-0.616613469478362-0.499867084694306
369.96310.0324191631790.01201513664685160.0290963087014454-1.29087481916628
3710.15810.03041098608580.01179032760956960.146284556190881-0.244544275281895
389.22510.01025301595030.011276453434801-0.742873049128375-0.554458089892897
3910.47410.02687859584780.0113715488763770.4401291452427820.0916806477567964
409.75710.02011874678690.0110155592217956-0.239740626635693-0.307389283023547
4110.4910.12019235586690.01287775668764420.2558154572430381.5020972558923
4210.28110.17349923266250.01374443268643580.05578743839353060.682176649897095
4310.44410.21622901241580.0143618914114430.1905473055702560.491083845982409
4410.6410.23467926362860.01444636089616610.4000360733518790.0696772944863721
4510.69510.30414730653120.01552772630468240.3191977781659250.943787080721844
4610.78610.38571526351560.01674217178710560.3136318448670391.13991971802078
479.83210.41559489677770.0169651240943325-0.6009549404997620.228079657951756
489.74710.32287315511190.0152586102821331-0.430047057760226-1.91366749822315
4910.41110.29423652191120.01462259194018370.175339599888201-0.768054900182843
509.51110.29202888714180.0143814938328919-0.758603369680746-0.294033238808511
5110.40210.25392108238490.01360061465996340.217640024590396-0.912760057357238
529.70110.21993885449980.0128551596982026-0.456252344583077-0.82351506394424
5310.5410.23686025858680.01292152069360010.2978032964023110.0701789779402011
5410.11210.22724161799070.0125460783776696-0.0856874764630684-0.388909784963529
5510.91510.31504086915880.01379816796891410.5011289169124821.30072142449968
5611.18310.4312541265550.01546783105623090.6167973012731821.77561284754979
5710.38410.42132750038010.0150686594822864-0.00372583921285353-0.441878884865934
5810.83410.43401761457950.01503305895894150.403143566019176-0.0415421102982172
599.88610.43170699725620.0147877419138621-0.522561024739936-0.303946992021462
6010.21610.46169321576590.0149910490924513-0.2660441636350580.267070645235596
6110.94310.51814949223690.01552309907204060.3692259758635270.729655586561197
629.86710.54938864271090.0157221167674807-0.7034637391613170.276430728992788
6310.20310.47521054830550.0145688699435745-0.151907956700221-1.57839772441336
6410.83710.59360614119380.01593446039016660.1048121336417361.81913824844548
6510.57310.59216656165230.01570059867034390.00398009754127546-0.303994953119957
6610.64710.64159948140890.0161605224267335-0.03951452286496670.590087109561325
6711.50210.73471491296270.01720898211949150.6647391847301391.34736691222468
6810.65610.65951088227790.01596793640934010.119855528505717-1.62072258870195
6910.86610.68039638066910.01603226150114690.179023082206290.0864255845019666
7010.83510.6567749794120.01553145794752130.231427802690694-0.698459897223181
719.94510.63510414525430.0150797617375863-0.640066837854304-0.656624372683265
7210.33110.63765767526440.0149332571183332-0.289776685931933-0.221441162176421
7310.71810.60174341906280.01435492577613650.184857754549448-0.899666091475739
749.46210.52602055061360.0133432056316908-0.942483441113585-1.59376740793004
7510.57910.559040733470.0135646677495032-0.006569291391897810.347915434691131
7610.63310.57022428781330.01353758621276260.0659824559773204-0.042064790946943
7710.34610.55153186955930.0131668518619567-0.162162767251075-0.569033146205613
7810.75710.59404394826010.01350652918125810.1234781168480810.518065669507745
7911.20710.58765254938210.0132766533922680.64612826997795-0.351460810256383
8011.01310.6347534025220.01366312930592280.3326743226120970.598029424747637
8111.01510.67461525013760.01395677352980530.3050354952564690.46379596005622
8210.76510.66149849513960.01366087759914350.140089604859237-0.479937306128604
8310.04210.65963116093560.013495819622295-0.596613824671237-0.275621354469652
8410.66110.69692709671140.0137422631743604-0.06817999951120970.422869443064775

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 9.676 & 9.676 & 0 & 0 & 0 \tabularnewline
2 & 8.642 & 9.60396769599248 & 0.0037394895423648 & -0.635058359433444 & -3.47443271267423 \tabularnewline
3 & 9.402 & 9.45401077342991 & -0.0183133797076445 & 0.0917052633369661 & -1.7839977791407 \tabularnewline
4 & 9.61 & 9.43894767543408 & -0.0178804704798153 & 0.168684318269467 & 0.0319664407104806 \tabularnewline
5 & 9.294 & 9.39464770528669 & -0.0209346464613445 & -0.0795135764902457 & -0.283132125202997 \tabularnewline
6 & 9.448 & 9.38938852884792 & -0.01937746181176 & 0.0442548779777317 & 0.187641947747878 \tabularnewline
7 & 10.319 & 9.58042412606209 & -0.00130401052492251 & 0.523636123391154 & 2.75166179230744 \tabularnewline
8 & 9.548 & 9.62787857730653 & 0.00236634682640294 & -0.133793107346051 & 0.680043723035899 \tabularnewline
9 & 9.801 & 9.67649632767438 & 0.00546645790732064 & 0.0703935686862788 & 0.6754774252295 \tabularnewline
10 & 9.596 & 9.67748512830492 & 0.00519504145954117 & -0.0760304554521848 & -0.0675980843382872 \tabularnewline
11 & 8.923 & 9.53814577187952 & -0.0028374757067737 & -0.433800968321019 & -2.23560178201297 \tabularnewline
12 & 9.746 & 9.53267329017727 & -0.00297328794229966 & 0.21670642319818 & -0.0415040319391615 \tabularnewline
13 & 9.829 & 9.53144970730544 & -0.00298406521554054 & 0.294785805523468 & 0.0347006197747974 \tabularnewline
14 & 9.125 & 9.5440510591881 & -0.00271303345401848 & -0.440480409251016 & 0.271745824741238 \tabularnewline
15 & 9.782 & 9.57494981318903 & -0.00145357076401724 & 0.167643798427332 & 0.513030534567471 \tabularnewline
16 & 9.441 & 9.52939855088511 & -0.00347671029563411 & -0.0401051136396316 & -0.640253557225453 \tabularnewline
17 & 9.162 & 9.47664406780267 & -0.00582601190212476 & -0.260770145080189 & -0.718434981877873 \tabularnewline
18 & 9.915 & 9.56351469535383 & -0.00153663778039349 & 0.247401081889839 & 1.38630358411364 \tabularnewline
19 & 10.444 & 9.65936857408945 & 0.00270271030437873 & 0.67160630049203 & 1.49962559961438 \tabularnewline
20 & 10.209 & 9.8104437644388 & 0.00869521973419781 & 0.221061885125647 & 2.34501331825596 \tabularnewline
21 & 9.985 & 9.86864371116475 & 0.0105385160887819 & 0.0556150632571217 & 0.799334414619553 \tabularnewline
22 & 9.842 & 9.87891315337422 & 0.0105293543427928 & -0.0365759965042006 & -0.00442061204912929 \tabularnewline
23 & 9.429 & 9.88573969076159 & 0.0104168171042543 & -0.45201073500547 & -0.0617673854028371 \tabularnewline
24 & 10.132 & 9.90095498553048 & 0.0105373722629404 & 0.22477850329811 & 0.0814923110828912 \tabularnewline
25 & 9.849 & 9.86503670283959 & 0.00982066548610975 & 0.0471643893365732 & -0.819407515218257 \tabularnewline
26 & 9.172 & 9.82447995880997 & 0.00894473785376252 & -0.585339933389858 & -0.871909808635459 \tabularnewline
27 & 10.313 & 9.86474502705525 & 0.0096614710660162 & 0.40832851430915 & 0.522128326411872 \tabularnewline
28 & 9.819 & 9.88550073870896 & 0.00996257825657431 & -0.0801986893993088 & 0.180396640687546 \tabularnewline
29 & 9.955 & 9.97953843666184 & 0.012424873216196 & -0.127155029741011 & 1.35713037262053 \tabularnewline
30 & 10.048 & 10.0113446040073 & 0.0130011840913902 & 0.0129217183633434 & 0.314314062753663 \tabularnewline
31 & 10.082 & 9.95612650519667 & 0.0110183515396396 & 0.210328891185492 & -1.11790152955937 \tabularnewline
32 & 10.541 & 10.0135235425193 & 0.0123039968289974 & 0.469276620210794 & 0.769202123806266 \tabularnewline
33 & 10.208 & 10.0573363740517 & 0.0131219884391485 & 0.110582367939303 & 0.528690174813661 \tabularnewline
34 & 10.233 & 10.1088337620679 & 0.0140385076971991 & 0.0747248965536091 & 0.65073156662347 \tabularnewline
35 & 9.439 & 10.0936785562411 & 0.0134117634359361 & -0.616613469478362 & -0.499867084694306 \tabularnewline
36 & 9.963 & 10.032419163179 & 0.0120151366468516 & 0.0290963087014454 & -1.29087481916628 \tabularnewline
37 & 10.158 & 10.0304109860858 & 0.0117903276095696 & 0.146284556190881 & -0.244544275281895 \tabularnewline
38 & 9.225 & 10.0102530159503 & 0.011276453434801 & -0.742873049128375 & -0.554458089892897 \tabularnewline
39 & 10.474 & 10.0268785958478 & 0.011371548876377 & 0.440129145242782 & 0.0916806477567964 \tabularnewline
40 & 9.757 & 10.0201187467869 & 0.0110155592217956 & -0.239740626635693 & -0.307389283023547 \tabularnewline
41 & 10.49 & 10.1201923558669 & 0.0128777566876442 & 0.255815457243038 & 1.5020972558923 \tabularnewline
42 & 10.281 & 10.1734992326625 & 0.0137444326864358 & 0.0557874383935306 & 0.682176649897095 \tabularnewline
43 & 10.444 & 10.2162290124158 & 0.014361891411443 & 0.190547305570256 & 0.491083845982409 \tabularnewline
44 & 10.64 & 10.2346792636286 & 0.0144463608961661 & 0.400036073351879 & 0.0696772944863721 \tabularnewline
45 & 10.695 & 10.3041473065312 & 0.0155277263046824 & 0.319197778165925 & 0.943787080721844 \tabularnewline
46 & 10.786 & 10.3857152635156 & 0.0167421717871056 & 0.313631844867039 & 1.13991971802078 \tabularnewline
47 & 9.832 & 10.4155948967777 & 0.0169651240943325 & -0.600954940499762 & 0.228079657951756 \tabularnewline
48 & 9.747 & 10.3228731551119 & 0.0152586102821331 & -0.430047057760226 & -1.91366749822315 \tabularnewline
49 & 10.411 & 10.2942365219112 & 0.0146225919401837 & 0.175339599888201 & -0.768054900182843 \tabularnewline
50 & 9.511 & 10.2920288871418 & 0.0143814938328919 & -0.758603369680746 & -0.294033238808511 \tabularnewline
51 & 10.402 & 10.2539210823849 & 0.0136006146599634 & 0.217640024590396 & -0.912760057357238 \tabularnewline
52 & 9.701 & 10.2199388544998 & 0.0128551596982026 & -0.456252344583077 & -0.82351506394424 \tabularnewline
53 & 10.54 & 10.2368602585868 & 0.0129215206936001 & 0.297803296402311 & 0.0701789779402011 \tabularnewline
54 & 10.112 & 10.2272416179907 & 0.0125460783776696 & -0.0856874764630684 & -0.388909784963529 \tabularnewline
55 & 10.915 & 10.3150408691588 & 0.0137981679689141 & 0.501128916912482 & 1.30072142449968 \tabularnewline
56 & 11.183 & 10.431254126555 & 0.0154678310562309 & 0.616797301273182 & 1.77561284754979 \tabularnewline
57 & 10.384 & 10.4213275003801 & 0.0150686594822864 & -0.00372583921285353 & -0.441878884865934 \tabularnewline
58 & 10.834 & 10.4340176145795 & 0.0150330589589415 & 0.403143566019176 & -0.0415421102982172 \tabularnewline
59 & 9.886 & 10.4317069972562 & 0.0147877419138621 & -0.522561024739936 & -0.303946992021462 \tabularnewline
60 & 10.216 & 10.4616932157659 & 0.0149910490924513 & -0.266044163635058 & 0.267070645235596 \tabularnewline
61 & 10.943 & 10.5181494922369 & 0.0155230990720406 & 0.369225975863527 & 0.729655586561197 \tabularnewline
62 & 9.867 & 10.5493886427109 & 0.0157221167674807 & -0.703463739161317 & 0.276430728992788 \tabularnewline
63 & 10.203 & 10.4752105483055 & 0.0145688699435745 & -0.151907956700221 & -1.57839772441336 \tabularnewline
64 & 10.837 & 10.5936061411938 & 0.0159344603901666 & 0.104812133641736 & 1.81913824844548 \tabularnewline
65 & 10.573 & 10.5921665616523 & 0.0157005986703439 & 0.00398009754127546 & -0.303994953119957 \tabularnewline
66 & 10.647 & 10.6415994814089 & 0.0161605224267335 & -0.0395145228649667 & 0.590087109561325 \tabularnewline
67 & 11.502 & 10.7347149129627 & 0.0172089821194915 & 0.664739184730139 & 1.34736691222468 \tabularnewline
68 & 10.656 & 10.6595108822779 & 0.0159679364093401 & 0.119855528505717 & -1.62072258870195 \tabularnewline
69 & 10.866 & 10.6803963806691 & 0.0160322615011469 & 0.17902308220629 & 0.0864255845019666 \tabularnewline
70 & 10.835 & 10.656774979412 & 0.0155314579475213 & 0.231427802690694 & -0.698459897223181 \tabularnewline
71 & 9.945 & 10.6351041452543 & 0.0150797617375863 & -0.640066837854304 & -0.656624372683265 \tabularnewline
72 & 10.331 & 10.6376576752644 & 0.0149332571183332 & -0.289776685931933 & -0.221441162176421 \tabularnewline
73 & 10.718 & 10.6017434190628 & 0.0143549257761365 & 0.184857754549448 & -0.899666091475739 \tabularnewline
74 & 9.462 & 10.5260205506136 & 0.0133432056316908 & -0.942483441113585 & -1.59376740793004 \tabularnewline
75 & 10.579 & 10.55904073347 & 0.0135646677495032 & -0.00656929139189781 & 0.347915434691131 \tabularnewline
76 & 10.633 & 10.5702242878133 & 0.0135375862127626 & 0.0659824559773204 & -0.042064790946943 \tabularnewline
77 & 10.346 & 10.5515318695593 & 0.0131668518619567 & -0.162162767251075 & -0.569033146205613 \tabularnewline
78 & 10.757 & 10.5940439482601 & 0.0135065291812581 & 0.123478116848081 & 0.518065669507745 \tabularnewline
79 & 11.207 & 10.5876525493821 & 0.013276653392268 & 0.64612826997795 & -0.351460810256383 \tabularnewline
80 & 11.013 & 10.634753402522 & 0.0136631293059228 & 0.332674322612097 & 0.598029424747637 \tabularnewline
81 & 11.015 & 10.6746152501376 & 0.0139567735298053 & 0.305035495256469 & 0.46379596005622 \tabularnewline
82 & 10.765 & 10.6614984951396 & 0.0136608775991435 & 0.140089604859237 & -0.479937306128604 \tabularnewline
83 & 10.042 & 10.6596311609356 & 0.013495819622295 & -0.596613824671237 & -0.275621354469652 \tabularnewline
84 & 10.661 & 10.6969270967114 & 0.0137422631743604 & -0.0681799995112097 & 0.422869443064775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187541&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]9.676[/C][C]9.676[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]8.642[/C][C]9.60396769599248[/C][C]0.0037394895423648[/C][C]-0.635058359433444[/C][C]-3.47443271267423[/C][/ROW]
[ROW][C]3[/C][C]9.402[/C][C]9.45401077342991[/C][C]-0.0183133797076445[/C][C]0.0917052633369661[/C][C]-1.7839977791407[/C][/ROW]
[ROW][C]4[/C][C]9.61[/C][C]9.43894767543408[/C][C]-0.0178804704798153[/C][C]0.168684318269467[/C][C]0.0319664407104806[/C][/ROW]
[ROW][C]5[/C][C]9.294[/C][C]9.39464770528669[/C][C]-0.0209346464613445[/C][C]-0.0795135764902457[/C][C]-0.283132125202997[/C][/ROW]
[ROW][C]6[/C][C]9.448[/C][C]9.38938852884792[/C][C]-0.01937746181176[/C][C]0.0442548779777317[/C][C]0.187641947747878[/C][/ROW]
[ROW][C]7[/C][C]10.319[/C][C]9.58042412606209[/C][C]-0.00130401052492251[/C][C]0.523636123391154[/C][C]2.75166179230744[/C][/ROW]
[ROW][C]8[/C][C]9.548[/C][C]9.62787857730653[/C][C]0.00236634682640294[/C][C]-0.133793107346051[/C][C]0.680043723035899[/C][/ROW]
[ROW][C]9[/C][C]9.801[/C][C]9.67649632767438[/C][C]0.00546645790732064[/C][C]0.0703935686862788[/C][C]0.6754774252295[/C][/ROW]
[ROW][C]10[/C][C]9.596[/C][C]9.67748512830492[/C][C]0.00519504145954117[/C][C]-0.0760304554521848[/C][C]-0.0675980843382872[/C][/ROW]
[ROW][C]11[/C][C]8.923[/C][C]9.53814577187952[/C][C]-0.0028374757067737[/C][C]-0.433800968321019[/C][C]-2.23560178201297[/C][/ROW]
[ROW][C]12[/C][C]9.746[/C][C]9.53267329017727[/C][C]-0.00297328794229966[/C][C]0.21670642319818[/C][C]-0.0415040319391615[/C][/ROW]
[ROW][C]13[/C][C]9.829[/C][C]9.53144970730544[/C][C]-0.00298406521554054[/C][C]0.294785805523468[/C][C]0.0347006197747974[/C][/ROW]
[ROW][C]14[/C][C]9.125[/C][C]9.5440510591881[/C][C]-0.00271303345401848[/C][C]-0.440480409251016[/C][C]0.271745824741238[/C][/ROW]
[ROW][C]15[/C][C]9.782[/C][C]9.57494981318903[/C][C]-0.00145357076401724[/C][C]0.167643798427332[/C][C]0.513030534567471[/C][/ROW]
[ROW][C]16[/C][C]9.441[/C][C]9.52939855088511[/C][C]-0.00347671029563411[/C][C]-0.0401051136396316[/C][C]-0.640253557225453[/C][/ROW]
[ROW][C]17[/C][C]9.162[/C][C]9.47664406780267[/C][C]-0.00582601190212476[/C][C]-0.260770145080189[/C][C]-0.718434981877873[/C][/ROW]
[ROW][C]18[/C][C]9.915[/C][C]9.56351469535383[/C][C]-0.00153663778039349[/C][C]0.247401081889839[/C][C]1.38630358411364[/C][/ROW]
[ROW][C]19[/C][C]10.444[/C][C]9.65936857408945[/C][C]0.00270271030437873[/C][C]0.67160630049203[/C][C]1.49962559961438[/C][/ROW]
[ROW][C]20[/C][C]10.209[/C][C]9.8104437644388[/C][C]0.00869521973419781[/C][C]0.221061885125647[/C][C]2.34501331825596[/C][/ROW]
[ROW][C]21[/C][C]9.985[/C][C]9.86864371116475[/C][C]0.0105385160887819[/C][C]0.0556150632571217[/C][C]0.799334414619553[/C][/ROW]
[ROW][C]22[/C][C]9.842[/C][C]9.87891315337422[/C][C]0.0105293543427928[/C][C]-0.0365759965042006[/C][C]-0.00442061204912929[/C][/ROW]
[ROW][C]23[/C][C]9.429[/C][C]9.88573969076159[/C][C]0.0104168171042543[/C][C]-0.45201073500547[/C][C]-0.0617673854028371[/C][/ROW]
[ROW][C]24[/C][C]10.132[/C][C]9.90095498553048[/C][C]0.0105373722629404[/C][C]0.22477850329811[/C][C]0.0814923110828912[/C][/ROW]
[ROW][C]25[/C][C]9.849[/C][C]9.86503670283959[/C][C]0.00982066548610975[/C][C]0.0471643893365732[/C][C]-0.819407515218257[/C][/ROW]
[ROW][C]26[/C][C]9.172[/C][C]9.82447995880997[/C][C]0.00894473785376252[/C][C]-0.585339933389858[/C][C]-0.871909808635459[/C][/ROW]
[ROW][C]27[/C][C]10.313[/C][C]9.86474502705525[/C][C]0.0096614710660162[/C][C]0.40832851430915[/C][C]0.522128326411872[/C][/ROW]
[ROW][C]28[/C][C]9.819[/C][C]9.88550073870896[/C][C]0.00996257825657431[/C][C]-0.0801986893993088[/C][C]0.180396640687546[/C][/ROW]
[ROW][C]29[/C][C]9.955[/C][C]9.97953843666184[/C][C]0.012424873216196[/C][C]-0.127155029741011[/C][C]1.35713037262053[/C][/ROW]
[ROW][C]30[/C][C]10.048[/C][C]10.0113446040073[/C][C]0.0130011840913902[/C][C]0.0129217183633434[/C][C]0.314314062753663[/C][/ROW]
[ROW][C]31[/C][C]10.082[/C][C]9.95612650519667[/C][C]0.0110183515396396[/C][C]0.210328891185492[/C][C]-1.11790152955937[/C][/ROW]
[ROW][C]32[/C][C]10.541[/C][C]10.0135235425193[/C][C]0.0123039968289974[/C][C]0.469276620210794[/C][C]0.769202123806266[/C][/ROW]
[ROW][C]33[/C][C]10.208[/C][C]10.0573363740517[/C][C]0.0131219884391485[/C][C]0.110582367939303[/C][C]0.528690174813661[/C][/ROW]
[ROW][C]34[/C][C]10.233[/C][C]10.1088337620679[/C][C]0.0140385076971991[/C][C]0.0747248965536091[/C][C]0.65073156662347[/C][/ROW]
[ROW][C]35[/C][C]9.439[/C][C]10.0936785562411[/C][C]0.0134117634359361[/C][C]-0.616613469478362[/C][C]-0.499867084694306[/C][/ROW]
[ROW][C]36[/C][C]9.963[/C][C]10.032419163179[/C][C]0.0120151366468516[/C][C]0.0290963087014454[/C][C]-1.29087481916628[/C][/ROW]
[ROW][C]37[/C][C]10.158[/C][C]10.0304109860858[/C][C]0.0117903276095696[/C][C]0.146284556190881[/C][C]-0.244544275281895[/C][/ROW]
[ROW][C]38[/C][C]9.225[/C][C]10.0102530159503[/C][C]0.011276453434801[/C][C]-0.742873049128375[/C][C]-0.554458089892897[/C][/ROW]
[ROW][C]39[/C][C]10.474[/C][C]10.0268785958478[/C][C]0.011371548876377[/C][C]0.440129145242782[/C][C]0.0916806477567964[/C][/ROW]
[ROW][C]40[/C][C]9.757[/C][C]10.0201187467869[/C][C]0.0110155592217956[/C][C]-0.239740626635693[/C][C]-0.307389283023547[/C][/ROW]
[ROW][C]41[/C][C]10.49[/C][C]10.1201923558669[/C][C]0.0128777566876442[/C][C]0.255815457243038[/C][C]1.5020972558923[/C][/ROW]
[ROW][C]42[/C][C]10.281[/C][C]10.1734992326625[/C][C]0.0137444326864358[/C][C]0.0557874383935306[/C][C]0.682176649897095[/C][/ROW]
[ROW][C]43[/C][C]10.444[/C][C]10.2162290124158[/C][C]0.014361891411443[/C][C]0.190547305570256[/C][C]0.491083845982409[/C][/ROW]
[ROW][C]44[/C][C]10.64[/C][C]10.2346792636286[/C][C]0.0144463608961661[/C][C]0.400036073351879[/C][C]0.0696772944863721[/C][/ROW]
[ROW][C]45[/C][C]10.695[/C][C]10.3041473065312[/C][C]0.0155277263046824[/C][C]0.319197778165925[/C][C]0.943787080721844[/C][/ROW]
[ROW][C]46[/C][C]10.786[/C][C]10.3857152635156[/C][C]0.0167421717871056[/C][C]0.313631844867039[/C][C]1.13991971802078[/C][/ROW]
[ROW][C]47[/C][C]9.832[/C][C]10.4155948967777[/C][C]0.0169651240943325[/C][C]-0.600954940499762[/C][C]0.228079657951756[/C][/ROW]
[ROW][C]48[/C][C]9.747[/C][C]10.3228731551119[/C][C]0.0152586102821331[/C][C]-0.430047057760226[/C][C]-1.91366749822315[/C][/ROW]
[ROW][C]49[/C][C]10.411[/C][C]10.2942365219112[/C][C]0.0146225919401837[/C][C]0.175339599888201[/C][C]-0.768054900182843[/C][/ROW]
[ROW][C]50[/C][C]9.511[/C][C]10.2920288871418[/C][C]0.0143814938328919[/C][C]-0.758603369680746[/C][C]-0.294033238808511[/C][/ROW]
[ROW][C]51[/C][C]10.402[/C][C]10.2539210823849[/C][C]0.0136006146599634[/C][C]0.217640024590396[/C][C]-0.912760057357238[/C][/ROW]
[ROW][C]52[/C][C]9.701[/C][C]10.2199388544998[/C][C]0.0128551596982026[/C][C]-0.456252344583077[/C][C]-0.82351506394424[/C][/ROW]
[ROW][C]53[/C][C]10.54[/C][C]10.2368602585868[/C][C]0.0129215206936001[/C][C]0.297803296402311[/C][C]0.0701789779402011[/C][/ROW]
[ROW][C]54[/C][C]10.112[/C][C]10.2272416179907[/C][C]0.0125460783776696[/C][C]-0.0856874764630684[/C][C]-0.388909784963529[/C][/ROW]
[ROW][C]55[/C][C]10.915[/C][C]10.3150408691588[/C][C]0.0137981679689141[/C][C]0.501128916912482[/C][C]1.30072142449968[/C][/ROW]
[ROW][C]56[/C][C]11.183[/C][C]10.431254126555[/C][C]0.0154678310562309[/C][C]0.616797301273182[/C][C]1.77561284754979[/C][/ROW]
[ROW][C]57[/C][C]10.384[/C][C]10.4213275003801[/C][C]0.0150686594822864[/C][C]-0.00372583921285353[/C][C]-0.441878884865934[/C][/ROW]
[ROW][C]58[/C][C]10.834[/C][C]10.4340176145795[/C][C]0.0150330589589415[/C][C]0.403143566019176[/C][C]-0.0415421102982172[/C][/ROW]
[ROW][C]59[/C][C]9.886[/C][C]10.4317069972562[/C][C]0.0147877419138621[/C][C]-0.522561024739936[/C][C]-0.303946992021462[/C][/ROW]
[ROW][C]60[/C][C]10.216[/C][C]10.4616932157659[/C][C]0.0149910490924513[/C][C]-0.266044163635058[/C][C]0.267070645235596[/C][/ROW]
[ROW][C]61[/C][C]10.943[/C][C]10.5181494922369[/C][C]0.0155230990720406[/C][C]0.369225975863527[/C][C]0.729655586561197[/C][/ROW]
[ROW][C]62[/C][C]9.867[/C][C]10.5493886427109[/C][C]0.0157221167674807[/C][C]-0.703463739161317[/C][C]0.276430728992788[/C][/ROW]
[ROW][C]63[/C][C]10.203[/C][C]10.4752105483055[/C][C]0.0145688699435745[/C][C]-0.151907956700221[/C][C]-1.57839772441336[/C][/ROW]
[ROW][C]64[/C][C]10.837[/C][C]10.5936061411938[/C][C]0.0159344603901666[/C][C]0.104812133641736[/C][C]1.81913824844548[/C][/ROW]
[ROW][C]65[/C][C]10.573[/C][C]10.5921665616523[/C][C]0.0157005986703439[/C][C]0.00398009754127546[/C][C]-0.303994953119957[/C][/ROW]
[ROW][C]66[/C][C]10.647[/C][C]10.6415994814089[/C][C]0.0161605224267335[/C][C]-0.0395145228649667[/C][C]0.590087109561325[/C][/ROW]
[ROW][C]67[/C][C]11.502[/C][C]10.7347149129627[/C][C]0.0172089821194915[/C][C]0.664739184730139[/C][C]1.34736691222468[/C][/ROW]
[ROW][C]68[/C][C]10.656[/C][C]10.6595108822779[/C][C]0.0159679364093401[/C][C]0.119855528505717[/C][C]-1.62072258870195[/C][/ROW]
[ROW][C]69[/C][C]10.866[/C][C]10.6803963806691[/C][C]0.0160322615011469[/C][C]0.17902308220629[/C][C]0.0864255845019666[/C][/ROW]
[ROW][C]70[/C][C]10.835[/C][C]10.656774979412[/C][C]0.0155314579475213[/C][C]0.231427802690694[/C][C]-0.698459897223181[/C][/ROW]
[ROW][C]71[/C][C]9.945[/C][C]10.6351041452543[/C][C]0.0150797617375863[/C][C]-0.640066837854304[/C][C]-0.656624372683265[/C][/ROW]
[ROW][C]72[/C][C]10.331[/C][C]10.6376576752644[/C][C]0.0149332571183332[/C][C]-0.289776685931933[/C][C]-0.221441162176421[/C][/ROW]
[ROW][C]73[/C][C]10.718[/C][C]10.6017434190628[/C][C]0.0143549257761365[/C][C]0.184857754549448[/C][C]-0.899666091475739[/C][/ROW]
[ROW][C]74[/C][C]9.462[/C][C]10.5260205506136[/C][C]0.0133432056316908[/C][C]-0.942483441113585[/C][C]-1.59376740793004[/C][/ROW]
[ROW][C]75[/C][C]10.579[/C][C]10.55904073347[/C][C]0.0135646677495032[/C][C]-0.00656929139189781[/C][C]0.347915434691131[/C][/ROW]
[ROW][C]76[/C][C]10.633[/C][C]10.5702242878133[/C][C]0.0135375862127626[/C][C]0.0659824559773204[/C][C]-0.042064790946943[/C][/ROW]
[ROW][C]77[/C][C]10.346[/C][C]10.5515318695593[/C][C]0.0131668518619567[/C][C]-0.162162767251075[/C][C]-0.569033146205613[/C][/ROW]
[ROW][C]78[/C][C]10.757[/C][C]10.5940439482601[/C][C]0.0135065291812581[/C][C]0.123478116848081[/C][C]0.518065669507745[/C][/ROW]
[ROW][C]79[/C][C]11.207[/C][C]10.5876525493821[/C][C]0.013276653392268[/C][C]0.64612826997795[/C][C]-0.351460810256383[/C][/ROW]
[ROW][C]80[/C][C]11.013[/C][C]10.634753402522[/C][C]0.0136631293059228[/C][C]0.332674322612097[/C][C]0.598029424747637[/C][/ROW]
[ROW][C]81[/C][C]11.015[/C][C]10.6746152501376[/C][C]0.0139567735298053[/C][C]0.305035495256469[/C][C]0.46379596005622[/C][/ROW]
[ROW][C]82[/C][C]10.765[/C][C]10.6614984951396[/C][C]0.0136608775991435[/C][C]0.140089604859237[/C][C]-0.479937306128604[/C][/ROW]
[ROW][C]83[/C][C]10.042[/C][C]10.6596311609356[/C][C]0.013495819622295[/C][C]-0.596613824671237[/C][C]-0.275621354469652[/C][/ROW]
[ROW][C]84[/C][C]10.661[/C][C]10.6969270967114[/C][C]0.0137422631743604[/C][C]-0.0681799995112097[/C][C]0.422869443064775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187541&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
tObservedLevelSlopeSeasonalStand. Residuals
19.6769.676000
28.6429.603967695992480.0037394895423648-0.635058359433444-3.47443271267423
39.4029.45401077342991-0.01831337970764450.0917052633369661-1.7839977791407
49.619.43894767543408-0.01788047047981530.1686843182694670.0319664407104806
59.2949.39464770528669-0.0209346464613445-0.0795135764902457-0.283132125202997
69.4489.38938852884792-0.019377461811760.04425487797773170.187641947747878
710.3199.58042412606209-0.001304010524922510.5236361233911542.75166179230744
89.5489.627878577306530.00236634682640294-0.1337931073460510.680043723035899
99.8019.676496327674380.005466457907320640.07039356868627880.6754774252295
109.5969.677485128304920.00519504145954117-0.0760304554521848-0.0675980843382872
118.9239.53814577187952-0.0028374757067737-0.433800968321019-2.23560178201297
129.7469.53267329017727-0.002973287942299660.21670642319818-0.0415040319391615
139.8299.53144970730544-0.002984065215540540.2947858055234680.0347006197747974
149.1259.5440510591881-0.00271303345401848-0.4404804092510160.271745824741238
159.7829.57494981318903-0.001453570764017240.1676437984273320.513030534567471
169.4419.52939855088511-0.00347671029563411-0.0401051136396316-0.640253557225453
179.1629.47664406780267-0.00582601190212476-0.260770145080189-0.718434981877873
189.9159.56351469535383-0.001536637780393490.2474010818898391.38630358411364
1910.4449.659368574089450.002702710304378730.671606300492031.49962559961438
2010.2099.81044376443880.008695219734197810.2210618851256472.34501331825596
219.9859.868643711164750.01053851608878190.05561506325712170.799334414619553
229.8429.878913153374220.0105293543427928-0.0365759965042006-0.00442061204912929
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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')