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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 computationSat, 24 Nov 2012 16:31:39 -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/24/t1353792743m5rrkh0v08ua6lk.htm/, Retrieved Mon, 29 Apr 2024 03:09:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=192527, Retrieved Mon, 29 Apr 2024 03:09:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
- RM D        [Structural Time Series Models] [] [2012-11-24 21:31:39] [0ce3a3cc7b36ec2616d0d876d7c7ef2d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.457
1.4718
1.4748
1.5527
1.5751
1.5557
1.5553
1.577
1.4975
1.437
1.3322
1.2732
1.3449
1.3239
1.2785
1.305
1.319
1.365
1.4016
1.4088
1.4268
1.4562
1.4816
1.4914
1.4614
1.4272
1.3686
1.3569
1.3406
1.2565
1.2209
1.277
1.2894
1.3067
1.3898
1.3661
1.322
1.336
1.3649
1.3999
1.4442
1.4349
1.4388
1.4264
1.4343
1.377
1.3706
1.3556
1.3179
1.2905
1.3224
1.3201
1.3162
1.2789
1.2526
1.2288
1.24
1.2856

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=192527&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=192527&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192527&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
11.29991.2999000
21.30741.307010000030420.000389999970546010.0003899999695825160.113824588275991
31.32421.323744621549150.0004553784508518530.0004553784508518530.436660603654864
41.35161.351037698455890.0005623015441054380.0005623015441054390.716986475594828
51.35111.350541897275910.0005581027240910810.00055810272409108-0.0282676761935586
61.34191.341380315000270.0005196849997296930.000519684999729693-0.259663599579548
71.37161.370965882401030.0006341175989732280.0006341175989732260.776495653625226
81.36221.361605078169960.0005949218300366540.000594921830036654-0.267012491652503
91.38961.388900778262680.0006992217373167850.0006992217373167830.713300920276821
101.42271.421875193860140.0008248061398585820.0008248061398585820.86221274062846
111.46841.467401930576210.0009980694237946730.0009980694237946721.19417670190628
121.4571.456049615455090.0009503845449104980.000950384544910497-0.329928290831618
131.47181.474233858145630.000221259830074057-0.002433858145627020.556237939947409
141.47481.474575818176460.0002241818087641130.0002241818235409150.00274334120988038
151.55271.552334845754330.0003651542456745630.0003651542456745592.06915806125182
161.57511.5746949275570.0004050724429992870.0004050724429992870.586973589043002
171.55571.555330741429870.0003692585701288140.000369258570128809-0.527576805336465
181.55531.554932129983190.0003678700168053120.000367870016805311-0.0204919039620929
191.5771.57659369371440.0004063062856034560.0004063062856034550.568257134910521
201.49751.497237410087230.0002625899127734250.000262589912773422-2.12859205406578
211.4371.436846499113510.0001535008864869030.000153500886486909-1.6186328874338
221.33221.33223458781776-3.45878177614303e-05-3.45878177614301e-05-2.79582325593262
231.27321.27334007155656-0.000140071556555917-0.000140071556555916-1.57076356687736
241.34491.34491178571926-1.17857192600127e-05-1.17857192600131e-051.91373117609304
251.32391.327524669494450.000329515403993621-0.00362466949444822-0.510875294005611
261.27851.27893035287514-0.00043035293905066-0.000430352875141546-1.18571499837174
271.3051.30539870740339-0.000398707403386623-0.0003987074033866290.717610879583461
281.3191.31938180751254-0.000381807512541413-0.0003818075125414110.383681424967551
291.3651.36532743259318-0.000327432593180287-0.0003274325931802841.2359338764337
301.40161.401884192041-0.000284192041000697-0.0002841920410006980.984004262063929
311.40881.40907543860026-0.000275438600261369-0.0002754386002613750.199431192427596
321.42681.42705408878941-0.00025408878940762-0.0002540887894076220.486985767479981
331.45621.45641948658642-0.000219486586416108-0.0002194865864161120.790193294845272
341.48161.48178962704577-0.000189627045770532-0.0001896270457705320.682683607098567
351.49141.49157799767817-0.000177997678170684-0.0001779976781706810.266194220330309
361.46141.46161267442409-0.000212674424094368-0.000212674424094369-0.79466931043553
371.42721.429367482099310.000197043818688604-0.00216748209931329-0.912175997360089
381.36861.36909434772111-0.000494347830797094-0.000494347721113301-1.50614399035251
391.35691.35740408340941-0.000504083409412514-0.000504083409412519-0.298641856717812
401.34061.34111779514223-0.000517795142227302-0.000517795142227304-0.420977165179637
411.25651.25709028621144-0.000590286211443915-0.000590286211443928-2.22755119751791
421.22091.22152062391762-0.000620623917622598-0.000620623917622599-0.933045010456818
431.2771.27757151515353-0.000571515153528945-0.0005715151535289511.51166374355889
441.28941.28996029411993-0.000560294119933747-0.000560294119933750.345704527765733
451.30671.30724485739246-0.000544857392463413-0.0005448573924634180.475995809402553
461.38981.39027262522031-0.000472625220314216-0.0004726252203142172.22922512925729
471.36611.36659266609539-0.000492666095389852-0.000492666095389849-0.619034671901758
481.3221.3225302586237-0.00053025862370105-0.000530258623701051-1.16218306804603
491.3361.32939570655247-0.000600390322510910.006604293447526490.207218023027775
501.36491.36517131026125-0.000271310351961002-0.0002713102612469960.919854110190372
511.39991.40014700207738-0.00024700207737642-0.0002470020773764250.940100266205888
521.44421.4444163223246-0.000216322324600395-0.0002163223246003941.1873292462828
531.43491.43512257399526-0.000222573995255684-0.000222573995255694-0.242110988903206
541.43881.43901973866245-0.00021973866245064-0.0002197386624506430.109880682568382
551.42641.42662810997589-0.000228109975888425-0.00022810997588843-0.324645657714
561.43431.4345225274829-0.000222527482903911-0.0002225274829039140.216642004567012
571.3771.37726170213711-0.00026170213711168-0.000261702137111674-1.52131073704159
581.37061.37086591221785-0.000265912217851919-0.00026591221785192-0.163606765219653
591.35561.35587601097552-0.000276010975519942-0.000276010975519941-0.39271424446009
601.31791.31820164384412-0.000301643844115872-0.000301643844115874-0.99747858461664
611.29051.28953289055889-8.79190501926321e-050.000967109441113496-0.787058251233449
621.32241.322242457053980.0001575428433437320.0001575429460176740.837390395757859
631.32011.31994386066460.0001561393353980280.000156139335398024-0.0655057338473819
641.31621.316046175812570.0001538241874301450.000153824187430146-0.10811629950424
651.27891.278767541370640.0001324586293556650.000132458629355651-0.998330973914385
661.25261.252482611187070.0001173888129322660.000117388812932263-0.704556798470277
671.22881.228696239328520.0001037606714793930.000103760671479388-0.63751775288016
681.241.239889920285770.0001100797142284850.0001100797142284850.29577019321982
691.28561.285464029608930.0001359703910730610.0001359703910730631.21253375092339

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 1.2999 & 1.2999 & 0 & 0 & 0 \tabularnewline
2 & 1.3074 & 1.30701000003042 & 0.00038999997054601 & 0.000389999969582516 & 0.113824588275991 \tabularnewline
3 & 1.3242 & 1.32374462154915 & 0.000455378450851853 & 0.000455378450851853 & 0.436660603654864 \tabularnewline
4 & 1.3516 & 1.35103769845589 & 0.000562301544105438 & 0.000562301544105439 & 0.716986475594828 \tabularnewline
5 & 1.3511 & 1.35054189727591 & 0.000558102724091081 & 0.00055810272409108 & -0.0282676761935586 \tabularnewline
6 & 1.3419 & 1.34138031500027 & 0.000519684999729693 & 0.000519684999729693 & -0.259663599579548 \tabularnewline
7 & 1.3716 & 1.37096588240103 & 0.000634117598973228 & 0.000634117598973226 & 0.776495653625226 \tabularnewline
8 & 1.3622 & 1.36160507816996 & 0.000594921830036654 & 0.000594921830036654 & -0.267012491652503 \tabularnewline
9 & 1.3896 & 1.38890077826268 & 0.000699221737316785 & 0.000699221737316783 & 0.713300920276821 \tabularnewline
10 & 1.4227 & 1.42187519386014 & 0.000824806139858582 & 0.000824806139858582 & 0.86221274062846 \tabularnewline
11 & 1.4684 & 1.46740193057621 & 0.000998069423794673 & 0.000998069423794672 & 1.19417670190628 \tabularnewline
12 & 1.457 & 1.45604961545509 & 0.000950384544910498 & 0.000950384544910497 & -0.329928290831618 \tabularnewline
13 & 1.4718 & 1.47423385814563 & 0.000221259830074057 & -0.00243385814562702 & 0.556237939947409 \tabularnewline
14 & 1.4748 & 1.47457581817646 & 0.000224181808764113 & 0.000224181823540915 & 0.00274334120988038 \tabularnewline
15 & 1.5527 & 1.55233484575433 & 0.000365154245674563 & 0.000365154245674559 & 2.06915806125182 \tabularnewline
16 & 1.5751 & 1.574694927557 & 0.000405072442999287 & 0.000405072442999287 & 0.586973589043002 \tabularnewline
17 & 1.5557 & 1.55533074142987 & 0.000369258570128814 & 0.000369258570128809 & -0.527576805336465 \tabularnewline
18 & 1.5553 & 1.55493212998319 & 0.000367870016805312 & 0.000367870016805311 & -0.0204919039620929 \tabularnewline
19 & 1.577 & 1.5765936937144 & 0.000406306285603456 & 0.000406306285603455 & 0.568257134910521 \tabularnewline
20 & 1.4975 & 1.49723741008723 & 0.000262589912773425 & 0.000262589912773422 & -2.12859205406578 \tabularnewline
21 & 1.437 & 1.43684649911351 & 0.000153500886486903 & 0.000153500886486909 & -1.6186328874338 \tabularnewline
22 & 1.3322 & 1.33223458781776 & -3.45878177614303e-05 & -3.45878177614301e-05 & -2.79582325593262 \tabularnewline
23 & 1.2732 & 1.27334007155656 & -0.000140071556555917 & -0.000140071556555916 & -1.57076356687736 \tabularnewline
24 & 1.3449 & 1.34491178571926 & -1.17857192600127e-05 & -1.17857192600131e-05 & 1.91373117609304 \tabularnewline
25 & 1.3239 & 1.32752466949445 & 0.000329515403993621 & -0.00362466949444822 & -0.510875294005611 \tabularnewline
26 & 1.2785 & 1.27893035287514 & -0.00043035293905066 & -0.000430352875141546 & -1.18571499837174 \tabularnewline
27 & 1.305 & 1.30539870740339 & -0.000398707403386623 & -0.000398707403386629 & 0.717610879583461 \tabularnewline
28 & 1.319 & 1.31938180751254 & -0.000381807512541413 & -0.000381807512541411 & 0.383681424967551 \tabularnewline
29 & 1.365 & 1.36532743259318 & -0.000327432593180287 & -0.000327432593180284 & 1.2359338764337 \tabularnewline
30 & 1.4016 & 1.401884192041 & -0.000284192041000697 & -0.000284192041000698 & 0.984004262063929 \tabularnewline
31 & 1.4088 & 1.40907543860026 & -0.000275438600261369 & -0.000275438600261375 & 0.199431192427596 \tabularnewline
32 & 1.4268 & 1.42705408878941 & -0.00025408878940762 & -0.000254088789407622 & 0.486985767479981 \tabularnewline
33 & 1.4562 & 1.45641948658642 & -0.000219486586416108 & -0.000219486586416112 & 0.790193294845272 \tabularnewline
34 & 1.4816 & 1.48178962704577 & -0.000189627045770532 & -0.000189627045770532 & 0.682683607098567 \tabularnewline
35 & 1.4914 & 1.49157799767817 & -0.000177997678170684 & -0.000177997678170681 & 0.266194220330309 \tabularnewline
36 & 1.4614 & 1.46161267442409 & -0.000212674424094368 & -0.000212674424094369 & -0.79466931043553 \tabularnewline
37 & 1.4272 & 1.42936748209931 & 0.000197043818688604 & -0.00216748209931329 & -0.912175997360089 \tabularnewline
38 & 1.3686 & 1.36909434772111 & -0.000494347830797094 & -0.000494347721113301 & -1.50614399035251 \tabularnewline
39 & 1.3569 & 1.35740408340941 & -0.000504083409412514 & -0.000504083409412519 & -0.298641856717812 \tabularnewline
40 & 1.3406 & 1.34111779514223 & -0.000517795142227302 & -0.000517795142227304 & -0.420977165179637 \tabularnewline
41 & 1.2565 & 1.25709028621144 & -0.000590286211443915 & -0.000590286211443928 & -2.22755119751791 \tabularnewline
42 & 1.2209 & 1.22152062391762 & -0.000620623917622598 & -0.000620623917622599 & -0.933045010456818 \tabularnewline
43 & 1.277 & 1.27757151515353 & -0.000571515153528945 & -0.000571515153528951 & 1.51166374355889 \tabularnewline
44 & 1.2894 & 1.28996029411993 & -0.000560294119933747 & -0.00056029411993375 & 0.345704527765733 \tabularnewline
45 & 1.3067 & 1.30724485739246 & -0.000544857392463413 & -0.000544857392463418 & 0.475995809402553 \tabularnewline
46 & 1.3898 & 1.39027262522031 & -0.000472625220314216 & -0.000472625220314217 & 2.22922512925729 \tabularnewline
47 & 1.3661 & 1.36659266609539 & -0.000492666095389852 & -0.000492666095389849 & -0.619034671901758 \tabularnewline
48 & 1.322 & 1.3225302586237 & -0.00053025862370105 & -0.000530258623701051 & -1.16218306804603 \tabularnewline
49 & 1.336 & 1.32939570655247 & -0.00060039032251091 & 0.00660429344752649 & 0.207218023027775 \tabularnewline
50 & 1.3649 & 1.36517131026125 & -0.000271310351961002 & -0.000271310261246996 & 0.919854110190372 \tabularnewline
51 & 1.3999 & 1.40014700207738 & -0.00024700207737642 & -0.000247002077376425 & 0.940100266205888 \tabularnewline
52 & 1.4442 & 1.4444163223246 & -0.000216322324600395 & -0.000216322324600394 & 1.1873292462828 \tabularnewline
53 & 1.4349 & 1.43512257399526 & -0.000222573995255684 & -0.000222573995255694 & -0.242110988903206 \tabularnewline
54 & 1.4388 & 1.43901973866245 & -0.00021973866245064 & -0.000219738662450643 & 0.109880682568382 \tabularnewline
55 & 1.4264 & 1.42662810997589 & -0.000228109975888425 & -0.00022810997588843 & -0.324645657714 \tabularnewline
56 & 1.4343 & 1.4345225274829 & -0.000222527482903911 & -0.000222527482903914 & 0.216642004567012 \tabularnewline
57 & 1.377 & 1.37726170213711 & -0.00026170213711168 & -0.000261702137111674 & -1.52131073704159 \tabularnewline
58 & 1.3706 & 1.37086591221785 & -0.000265912217851919 & -0.00026591221785192 & -0.163606765219653 \tabularnewline
59 & 1.3556 & 1.35587601097552 & -0.000276010975519942 & -0.000276010975519941 & -0.39271424446009 \tabularnewline
60 & 1.3179 & 1.31820164384412 & -0.000301643844115872 & -0.000301643844115874 & -0.99747858461664 \tabularnewline
61 & 1.2905 & 1.28953289055889 & -8.79190501926321e-05 & 0.000967109441113496 & -0.787058251233449 \tabularnewline
62 & 1.3224 & 1.32224245705398 & 0.000157542843343732 & 0.000157542946017674 & 0.837390395757859 \tabularnewline
63 & 1.3201 & 1.3199438606646 & 0.000156139335398028 & 0.000156139335398024 & -0.0655057338473819 \tabularnewline
64 & 1.3162 & 1.31604617581257 & 0.000153824187430145 & 0.000153824187430146 & -0.10811629950424 \tabularnewline
65 & 1.2789 & 1.27876754137064 & 0.000132458629355665 & 0.000132458629355651 & -0.998330973914385 \tabularnewline
66 & 1.2526 & 1.25248261118707 & 0.000117388812932266 & 0.000117388812932263 & -0.704556798470277 \tabularnewline
67 & 1.2288 & 1.22869623932852 & 0.000103760671479393 & 0.000103760671479388 & -0.63751775288016 \tabularnewline
68 & 1.24 & 1.23988992028577 & 0.000110079714228485 & 0.000110079714228485 & 0.29577019321982 \tabularnewline
69 & 1.2856 & 1.28546402960893 & 0.000135970391073061 & 0.000135970391073063 & 1.21253375092339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192527&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]1.2999[/C][C]1.2999[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]1.3074[/C][C]1.30701000003042[/C][C]0.00038999997054601[/C][C]0.000389999969582516[/C][C]0.113824588275991[/C][/ROW]
[ROW][C]3[/C][C]1.3242[/C][C]1.32374462154915[/C][C]0.000455378450851853[/C][C]0.000455378450851853[/C][C]0.436660603654864[/C][/ROW]
[ROW][C]4[/C][C]1.3516[/C][C]1.35103769845589[/C][C]0.000562301544105438[/C][C]0.000562301544105439[/C][C]0.716986475594828[/C][/ROW]
[ROW][C]5[/C][C]1.3511[/C][C]1.35054189727591[/C][C]0.000558102724091081[/C][C]0.00055810272409108[/C][C]-0.0282676761935586[/C][/ROW]
[ROW][C]6[/C][C]1.3419[/C][C]1.34138031500027[/C][C]0.000519684999729693[/C][C]0.000519684999729693[/C][C]-0.259663599579548[/C][/ROW]
[ROW][C]7[/C][C]1.3716[/C][C]1.37096588240103[/C][C]0.000634117598973228[/C][C]0.000634117598973226[/C][C]0.776495653625226[/C][/ROW]
[ROW][C]8[/C][C]1.3622[/C][C]1.36160507816996[/C][C]0.000594921830036654[/C][C]0.000594921830036654[/C][C]-0.267012491652503[/C][/ROW]
[ROW][C]9[/C][C]1.3896[/C][C]1.38890077826268[/C][C]0.000699221737316785[/C][C]0.000699221737316783[/C][C]0.713300920276821[/C][/ROW]
[ROW][C]10[/C][C]1.4227[/C][C]1.42187519386014[/C][C]0.000824806139858582[/C][C]0.000824806139858582[/C][C]0.86221274062846[/C][/ROW]
[ROW][C]11[/C][C]1.4684[/C][C]1.46740193057621[/C][C]0.000998069423794673[/C][C]0.000998069423794672[/C][C]1.19417670190628[/C][/ROW]
[ROW][C]12[/C][C]1.457[/C][C]1.45604961545509[/C][C]0.000950384544910498[/C][C]0.000950384544910497[/C][C]-0.329928290831618[/C][/ROW]
[ROW][C]13[/C][C]1.4718[/C][C]1.47423385814563[/C][C]0.000221259830074057[/C][C]-0.00243385814562702[/C][C]0.556237939947409[/C][/ROW]
[ROW][C]14[/C][C]1.4748[/C][C]1.47457581817646[/C][C]0.000224181808764113[/C][C]0.000224181823540915[/C][C]0.00274334120988038[/C][/ROW]
[ROW][C]15[/C][C]1.5527[/C][C]1.55233484575433[/C][C]0.000365154245674563[/C][C]0.000365154245674559[/C][C]2.06915806125182[/C][/ROW]
[ROW][C]16[/C][C]1.5751[/C][C]1.574694927557[/C][C]0.000405072442999287[/C][C]0.000405072442999287[/C][C]0.586973589043002[/C][/ROW]
[ROW][C]17[/C][C]1.5557[/C][C]1.55533074142987[/C][C]0.000369258570128814[/C][C]0.000369258570128809[/C][C]-0.527576805336465[/C][/ROW]
[ROW][C]18[/C][C]1.5553[/C][C]1.55493212998319[/C][C]0.000367870016805312[/C][C]0.000367870016805311[/C][C]-0.0204919039620929[/C][/ROW]
[ROW][C]19[/C][C]1.577[/C][C]1.5765936937144[/C][C]0.000406306285603456[/C][C]0.000406306285603455[/C][C]0.568257134910521[/C][/ROW]
[ROW][C]20[/C][C]1.4975[/C][C]1.49723741008723[/C][C]0.000262589912773425[/C][C]0.000262589912773422[/C][C]-2.12859205406578[/C][/ROW]
[ROW][C]21[/C][C]1.437[/C][C]1.43684649911351[/C][C]0.000153500886486903[/C][C]0.000153500886486909[/C][C]-1.6186328874338[/C][/ROW]
[ROW][C]22[/C][C]1.3322[/C][C]1.33223458781776[/C][C]-3.45878177614303e-05[/C][C]-3.45878177614301e-05[/C][C]-2.79582325593262[/C][/ROW]
[ROW][C]23[/C][C]1.2732[/C][C]1.27334007155656[/C][C]-0.000140071556555917[/C][C]-0.000140071556555916[/C][C]-1.57076356687736[/C][/ROW]
[ROW][C]24[/C][C]1.3449[/C][C]1.34491178571926[/C][C]-1.17857192600127e-05[/C][C]-1.17857192600131e-05[/C][C]1.91373117609304[/C][/ROW]
[ROW][C]25[/C][C]1.3239[/C][C]1.32752466949445[/C][C]0.000329515403993621[/C][C]-0.00362466949444822[/C][C]-0.510875294005611[/C][/ROW]
[ROW][C]26[/C][C]1.2785[/C][C]1.27893035287514[/C][C]-0.00043035293905066[/C][C]-0.000430352875141546[/C][C]-1.18571499837174[/C][/ROW]
[ROW][C]27[/C][C]1.305[/C][C]1.30539870740339[/C][C]-0.000398707403386623[/C][C]-0.000398707403386629[/C][C]0.717610879583461[/C][/ROW]
[ROW][C]28[/C][C]1.319[/C][C]1.31938180751254[/C][C]-0.000381807512541413[/C][C]-0.000381807512541411[/C][C]0.383681424967551[/C][/ROW]
[ROW][C]29[/C][C]1.365[/C][C]1.36532743259318[/C][C]-0.000327432593180287[/C][C]-0.000327432593180284[/C][C]1.2359338764337[/C][/ROW]
[ROW][C]30[/C][C]1.4016[/C][C]1.401884192041[/C][C]-0.000284192041000697[/C][C]-0.000284192041000698[/C][C]0.984004262063929[/C][/ROW]
[ROW][C]31[/C][C]1.4088[/C][C]1.40907543860026[/C][C]-0.000275438600261369[/C][C]-0.000275438600261375[/C][C]0.199431192427596[/C][/ROW]
[ROW][C]32[/C][C]1.4268[/C][C]1.42705408878941[/C][C]-0.00025408878940762[/C][C]-0.000254088789407622[/C][C]0.486985767479981[/C][/ROW]
[ROW][C]33[/C][C]1.4562[/C][C]1.45641948658642[/C][C]-0.000219486586416108[/C][C]-0.000219486586416112[/C][C]0.790193294845272[/C][/ROW]
[ROW][C]34[/C][C]1.4816[/C][C]1.48178962704577[/C][C]-0.000189627045770532[/C][C]-0.000189627045770532[/C][C]0.682683607098567[/C][/ROW]
[ROW][C]35[/C][C]1.4914[/C][C]1.49157799767817[/C][C]-0.000177997678170684[/C][C]-0.000177997678170681[/C][C]0.266194220330309[/C][/ROW]
[ROW][C]36[/C][C]1.4614[/C][C]1.46161267442409[/C][C]-0.000212674424094368[/C][C]-0.000212674424094369[/C][C]-0.79466931043553[/C][/ROW]
[ROW][C]37[/C][C]1.4272[/C][C]1.42936748209931[/C][C]0.000197043818688604[/C][C]-0.00216748209931329[/C][C]-0.912175997360089[/C][/ROW]
[ROW][C]38[/C][C]1.3686[/C][C]1.36909434772111[/C][C]-0.000494347830797094[/C][C]-0.000494347721113301[/C][C]-1.50614399035251[/C][/ROW]
[ROW][C]39[/C][C]1.3569[/C][C]1.35740408340941[/C][C]-0.000504083409412514[/C][C]-0.000504083409412519[/C][C]-0.298641856717812[/C][/ROW]
[ROW][C]40[/C][C]1.3406[/C][C]1.34111779514223[/C][C]-0.000517795142227302[/C][C]-0.000517795142227304[/C][C]-0.420977165179637[/C][/ROW]
[ROW][C]41[/C][C]1.2565[/C][C]1.25709028621144[/C][C]-0.000590286211443915[/C][C]-0.000590286211443928[/C][C]-2.22755119751791[/C][/ROW]
[ROW][C]42[/C][C]1.2209[/C][C]1.22152062391762[/C][C]-0.000620623917622598[/C][C]-0.000620623917622599[/C][C]-0.933045010456818[/C][/ROW]
[ROW][C]43[/C][C]1.277[/C][C]1.27757151515353[/C][C]-0.000571515153528945[/C][C]-0.000571515153528951[/C][C]1.51166374355889[/C][/ROW]
[ROW][C]44[/C][C]1.2894[/C][C]1.28996029411993[/C][C]-0.000560294119933747[/C][C]-0.00056029411993375[/C][C]0.345704527765733[/C][/ROW]
[ROW][C]45[/C][C]1.3067[/C][C]1.30724485739246[/C][C]-0.000544857392463413[/C][C]-0.000544857392463418[/C][C]0.475995809402553[/C][/ROW]
[ROW][C]46[/C][C]1.3898[/C][C]1.39027262522031[/C][C]-0.000472625220314216[/C][C]-0.000472625220314217[/C][C]2.22922512925729[/C][/ROW]
[ROW][C]47[/C][C]1.3661[/C][C]1.36659266609539[/C][C]-0.000492666095389852[/C][C]-0.000492666095389849[/C][C]-0.619034671901758[/C][/ROW]
[ROW][C]48[/C][C]1.322[/C][C]1.3225302586237[/C][C]-0.00053025862370105[/C][C]-0.000530258623701051[/C][C]-1.16218306804603[/C][/ROW]
[ROW][C]49[/C][C]1.336[/C][C]1.32939570655247[/C][C]-0.00060039032251091[/C][C]0.00660429344752649[/C][C]0.207218023027775[/C][/ROW]
[ROW][C]50[/C][C]1.3649[/C][C]1.36517131026125[/C][C]-0.000271310351961002[/C][C]-0.000271310261246996[/C][C]0.919854110190372[/C][/ROW]
[ROW][C]51[/C][C]1.3999[/C][C]1.40014700207738[/C][C]-0.00024700207737642[/C][C]-0.000247002077376425[/C][C]0.940100266205888[/C][/ROW]
[ROW][C]52[/C][C]1.4442[/C][C]1.4444163223246[/C][C]-0.000216322324600395[/C][C]-0.000216322324600394[/C][C]1.1873292462828[/C][/ROW]
[ROW][C]53[/C][C]1.4349[/C][C]1.43512257399526[/C][C]-0.000222573995255684[/C][C]-0.000222573995255694[/C][C]-0.242110988903206[/C][/ROW]
[ROW][C]54[/C][C]1.4388[/C][C]1.43901973866245[/C][C]-0.00021973866245064[/C][C]-0.000219738662450643[/C][C]0.109880682568382[/C][/ROW]
[ROW][C]55[/C][C]1.4264[/C][C]1.42662810997589[/C][C]-0.000228109975888425[/C][C]-0.00022810997588843[/C][C]-0.324645657714[/C][/ROW]
[ROW][C]56[/C][C]1.4343[/C][C]1.4345225274829[/C][C]-0.000222527482903911[/C][C]-0.000222527482903914[/C][C]0.216642004567012[/C][/ROW]
[ROW][C]57[/C][C]1.377[/C][C]1.37726170213711[/C][C]-0.00026170213711168[/C][C]-0.000261702137111674[/C][C]-1.52131073704159[/C][/ROW]
[ROW][C]58[/C][C]1.3706[/C][C]1.37086591221785[/C][C]-0.000265912217851919[/C][C]-0.00026591221785192[/C][C]-0.163606765219653[/C][/ROW]
[ROW][C]59[/C][C]1.3556[/C][C]1.35587601097552[/C][C]-0.000276010975519942[/C][C]-0.000276010975519941[/C][C]-0.39271424446009[/C][/ROW]
[ROW][C]60[/C][C]1.3179[/C][C]1.31820164384412[/C][C]-0.000301643844115872[/C][C]-0.000301643844115874[/C][C]-0.99747858461664[/C][/ROW]
[ROW][C]61[/C][C]1.2905[/C][C]1.28953289055889[/C][C]-8.79190501926321e-05[/C][C]0.000967109441113496[/C][C]-0.787058251233449[/C][/ROW]
[ROW][C]62[/C][C]1.3224[/C][C]1.32224245705398[/C][C]0.000157542843343732[/C][C]0.000157542946017674[/C][C]0.837390395757859[/C][/ROW]
[ROW][C]63[/C][C]1.3201[/C][C]1.3199438606646[/C][C]0.000156139335398028[/C][C]0.000156139335398024[/C][C]-0.0655057338473819[/C][/ROW]
[ROW][C]64[/C][C]1.3162[/C][C]1.31604617581257[/C][C]0.000153824187430145[/C][C]0.000153824187430146[/C][C]-0.10811629950424[/C][/ROW]
[ROW][C]65[/C][C]1.2789[/C][C]1.27876754137064[/C][C]0.000132458629355665[/C][C]0.000132458629355651[/C][C]-0.998330973914385[/C][/ROW]
[ROW][C]66[/C][C]1.2526[/C][C]1.25248261118707[/C][C]0.000117388812932266[/C][C]0.000117388812932263[/C][C]-0.704556798470277[/C][/ROW]
[ROW][C]67[/C][C]1.2288[/C][C]1.22869623932852[/C][C]0.000103760671479393[/C][C]0.000103760671479388[/C][C]-0.63751775288016[/C][/ROW]
[ROW][C]68[/C][C]1.24[/C][C]1.23988992028577[/C][C]0.000110079714228485[/C][C]0.000110079714228485[/C][C]0.29577019321982[/C][/ROW]
[ROW][C]69[/C][C]1.2856[/C][C]1.28546402960893[/C][C]0.000135970391073061[/C][C]0.000135970391073063[/C][C]1.21253375092339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192527&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192527&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
11.29991.2999000
21.30741.307010000030420.000389999970546010.0003899999695825160.113824588275991
31.32421.323744621549150.0004553784508518530.0004553784508518530.436660603654864
41.35161.351037698455890.0005623015441054380.0005623015441054390.716986475594828
51.35111.350541897275910.0005581027240910810.00055810272409108-0.0282676761935586
61.34191.341380315000270.0005196849997296930.000519684999729693-0.259663599579548
71.37161.370965882401030.0006341175989732280.0006341175989732260.776495653625226
81.36221.361605078169960.0005949218300366540.000594921830036654-0.267012491652503
91.38961.388900778262680.0006992217373167850.0006992217373167830.713300920276821
101.42271.421875193860140.0008248061398585820.0008248061398585820.86221274062846
111.46841.467401930576210.0009980694237946730.0009980694237946721.19417670190628
121.4571.456049615455090.0009503845449104980.000950384544910497-0.329928290831618
131.47181.474233858145630.000221259830074057-0.002433858145627020.556237939947409
141.47481.474575818176460.0002241818087641130.0002241818235409150.00274334120988038
151.55271.552334845754330.0003651542456745630.0003651542456745592.06915806125182
161.57511.5746949275570.0004050724429992870.0004050724429992870.586973589043002
171.55571.555330741429870.0003692585701288140.000369258570128809-0.527576805336465
181.55531.554932129983190.0003678700168053120.000367870016805311-0.0204919039620929
191.5771.57659369371440.0004063062856034560.0004063062856034550.568257134910521
201.49751.497237410087230.0002625899127734250.000262589912773422-2.12859205406578
211.4371.436846499113510.0001535008864869030.000153500886486909-1.6186328874338
221.33221.33223458781776-3.45878177614303e-05-3.45878177614301e-05-2.79582325593262
231.27321.27334007155656-0.000140071556555917-0.000140071556555916-1.57076356687736
241.34491.34491178571926-1.17857192600127e-05-1.17857192600131e-051.91373117609304
251.32391.327524669494450.000329515403993621-0.00362466949444822-0.510875294005611
261.27851.27893035287514-0.00043035293905066-0.000430352875141546-1.18571499837174
271.3051.30539870740339-0.000398707403386623-0.0003987074033866290.717610879583461
281.3191.31938180751254-0.000381807512541413-0.0003818075125414110.383681424967551
291.3651.36532743259318-0.000327432593180287-0.0003274325931802841.2359338764337
301.40161.401884192041-0.000284192041000697-0.0002841920410006980.984004262063929
311.40881.40907543860026-0.000275438600261369-0.0002754386002613750.199431192427596
321.42681.42705408878941-0.00025408878940762-0.0002540887894076220.486985767479981
331.45621.45641948658642-0.000219486586416108-0.0002194865864161120.790193294845272
341.48161.48178962704577-0.000189627045770532-0.0001896270457705320.682683607098567
351.49141.49157799767817-0.000177997678170684-0.0001779976781706810.266194220330309
361.46141.46161267442409-0.000212674424094368-0.000212674424094369-0.79466931043553
371.42721.429367482099310.000197043818688604-0.00216748209931329-0.912175997360089
381.36861.36909434772111-0.000494347830797094-0.000494347721113301-1.50614399035251
391.35691.35740408340941-0.000504083409412514-0.000504083409412519-0.298641856717812
401.34061.34111779514223-0.000517795142227302-0.000517795142227304-0.420977165179637
411.25651.25709028621144-0.000590286211443915-0.000590286211443928-2.22755119751791
421.22091.22152062391762-0.000620623917622598-0.000620623917622599-0.933045010456818
431.2771.27757151515353-0.000571515153528945-0.0005715151535289511.51166374355889
441.28941.28996029411993-0.000560294119933747-0.000560294119933750.345704527765733
451.30671.30724485739246-0.000544857392463413-0.0005448573924634180.475995809402553
461.38981.39027262522031-0.000472625220314216-0.0004726252203142172.22922512925729
471.36611.36659266609539-0.000492666095389852-0.000492666095389849-0.619034671901758
481.3221.3225302586237-0.00053025862370105-0.000530258623701051-1.16218306804603
491.3361.32939570655247-0.000600390322510910.006604293447526490.207218023027775
501.36491.36517131026125-0.000271310351961002-0.0002713102612469960.919854110190372
511.39991.40014700207738-0.00024700207737642-0.0002470020773764250.940100266205888
521.44421.4444163223246-0.000216322324600395-0.0002163223246003941.1873292462828
531.43491.43512257399526-0.000222573995255684-0.000222573995255694-0.242110988903206
541.43881.43901973866245-0.00021973866245064-0.0002197386624506430.109880682568382
551.42641.42662810997589-0.000228109975888425-0.00022810997588843-0.324645657714
561.43431.4345225274829-0.000222527482903911-0.0002225274829039140.216642004567012
571.3771.37726170213711-0.00026170213711168-0.000261702137111674-1.52131073704159
581.37061.37086591221785-0.000265912217851919-0.00026591221785192-0.163606765219653
591.35561.35587601097552-0.000276010975519942-0.000276010975519941-0.39271424446009
601.31791.31820164384412-0.000301643844115872-0.000301643844115874-0.99747858461664
611.29051.28953289055889-8.79190501926321e-050.000967109441113496-0.787058251233449
621.32241.322242457053980.0001575428433437320.0001575429460176740.837390395757859
631.32011.31994386066460.0001561393353980280.000156139335398024-0.0655057338473819
641.31621.316046175812570.0001538241874301450.000153824187430146-0.10811629950424
651.27891.278767541370640.0001324586293556650.000132458629355651-0.998330973914385
661.25261.252482611187070.0001173888129322660.000117388812932263-0.704556798470277
671.22881.228696239328520.0001037606714793930.000103760671479388-0.63751775288016
681.241.239889920285770.0001100797142284850.0001100797142284850.29577019321982
691.28561.285464029608930.0001359703910730610.0001359703910730631.21253375092339


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$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
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='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')