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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 computationWed, 29 Dec 2010 16:22:57 +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/2010/Dec/29/t12936396535ulimsjzv1iy152.htm/, Retrieved Fri, 03 May 2024 10:53:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116955, Retrieved Fri, 03 May 2024 10:53:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Structural Time Series Models] [] [2010-12-24 11:19:06] [055a14fb8042f7ec27c73c5dfc3bfa50]
-    D    [Structural Time Series Models] [Paper: Structural...] [2010-12-29 16:22:57] [4a884731c0d5b018eba30cab82c9416a] [Current]
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Dataseries X:
31245
30951
30872
30752
30967
30781
30681
31356
31434
31594
31949
32396
32441
32447
32288
32418
32346
32091
31855
31683
31615
31840
31536
31383
31638
31626
31720
31472
31372
31419
31341
31171
31036
30532
30666
30571
30173
30032
29874
30018
29911
29963
30050
29901
29544
29451
29293
29334
29389
29563




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116955&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116955&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116955&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 time1 seconds
R Server'Gwilym Jenkins' @ www.wessa.org







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
13124531245000
23095130966.2739415637-15.5442801599388-15.2739415637431-0.791661176826256
33087230887.5166084096-16.1346586769645-15.5166084096155-0.29892365905723
43075230767.9090426388-17.380907596485-15.9090426388181-0.48861711586687
53096730982.0438767587-13.9829549850008-15.04387675869471.09174463019894
63078130796.6733130974-16.9353257897189-15.6733130973929-0.807107610329334
73068130696.9712984209-18.5643540818563-15.9712984208925-0.389255466828759
83135631369.5378493448-3.33426269602627-13.53784934483123.24626914594959
93143431447.2593847371-1.36600264825519-13.25938473707210.380253557263629
103159431606.72146059022.88249691480855-12.72146059024340.75359423887647
113194931960.580922145912.8623013850883-11.58092214593091.64271996943008
123239632406.217236970325.9905886651772-10.21723697027922.02338682077191
133244132361.243222037826.305722557765679.7567779622374-0.398149163354623
143244732452.697054523629.5342130970008-5.697054523570420.258805926359441
153228832293.939576966523.1125477764634-5.93957696650549-0.876969086273123
163241832423.806975614926.9164976769195-5.806975614865730.496794993291035
173234632351.925147224423.2559089050994-5.92514722443949-0.459409099559962
183209132097.244829950412.5930008502601-6.24482995041355-1.29145369042109
193185531861.5191425292.76515580695383-6.51914252899029-1.15305278087372
203168331689.7041494154-4.33937976419046-6.70414941536826-0.810144006477588
213161531621.7687318731-6.99273965837496-6.76873187306778-0.294948002278496
223184031846.54341113152.8954429917442-6.543411131536771.07432379848715
233153631542.8285184522-10.4503339895168-6.82851845221873-1.42054592977705
243138331389.9550843462-16.7618423480564-6.95508434620576-0.659556110132069
253163831527.8345327213-11.4293162628538110.1654672787040.785401175030913
263162631634.2436891432-5.28026573408549-8.243689143225130.497025632650487
273172031728.197021138-0.702650629023177-8.197021137960540.458914510848177
283147231480.3078370393-12.2426509901965-8.30783703927386-1.14277732721684
293137231380.3453068556-16.3821604570421-8.3453068555836-0.405424961254062
303141931427.3195334722-13.3633544754091-8.319533472162640.292744987250647
313134131349.3445541952-16.4687894514474-8.34455419519239-0.298473926864508
323117131179.4011080844-23.902955353664-8.40110808439705-0.70882384263698
333103631044.440035665-29.3202906414276-8.44003566500355-0.512821616280683
343053230540.5981982787-52.6131252897033-8.59819827865321-2.19075626401384
353066630674.539087559-43.4038667268277-8.539087558982930.861136304245901
363057130579.5546202609-45.9631068661237-8.55462026087105-0.238061582436233
373017330136.4336583547-64.20975131951236.5663416453475-1.95087065774321
383003230035.7235296431-66.1318608577058-3.72352964305939-0.157954438992422
392987429877.7386827749-70.7431144549682-3.73868277487997-0.423742064582086
403001830021.7050470175-59.9278244707317-3.705047017548250.990414823373518
412991129914.7120475897-62.3057582247592-3.71204758971698-0.217083686027672
422996329966.6959091468-56.5156469474721-3.695909146797060.527107870954779
433005030053.6766755633-49.2280954675697-3.676675563319550.66176262275603
442990129904.6893662596-54.3055566941981-3.68936625955319-0.460029459230713
452954429547.7259048464-69.740394105798-3.72590484639961-1.39559295784481
462945129454.7285691163-70.9285469124179-3.7285691163369-0.107234838963537
472929329296.7380324213-75.3834673424578-3.7380324213163-0.401412269638809
482933429337.7260314656-69.4202663517712-3.726031465557020.536524188056835
492938929340.1757307954-65.848963775022548.82426920455780.347375103767396
502956329564.9375212838-50.615856627008-1.937521283812241.27568802192432

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 31245 & 31245 & 0 & 0 & 0 \tabularnewline
2 & 30951 & 30966.2739415637 & -15.5442801599388 & -15.2739415637431 & -0.791661176826256 \tabularnewline
3 & 30872 & 30887.5166084096 & -16.1346586769645 & -15.5166084096155 & -0.29892365905723 \tabularnewline
4 & 30752 & 30767.9090426388 & -17.380907596485 & -15.9090426388181 & -0.48861711586687 \tabularnewline
5 & 30967 & 30982.0438767587 & -13.9829549850008 & -15.0438767586947 & 1.09174463019894 \tabularnewline
6 & 30781 & 30796.6733130974 & -16.9353257897189 & -15.6733130973929 & -0.807107610329334 \tabularnewline
7 & 30681 & 30696.9712984209 & -18.5643540818563 & -15.9712984208925 & -0.389255466828759 \tabularnewline
8 & 31356 & 31369.5378493448 & -3.33426269602627 & -13.5378493448312 & 3.24626914594959 \tabularnewline
9 & 31434 & 31447.2593847371 & -1.36600264825519 & -13.2593847370721 & 0.380253557263629 \tabularnewline
10 & 31594 & 31606.7214605902 & 2.88249691480855 & -12.7214605902434 & 0.75359423887647 \tabularnewline
11 & 31949 & 31960.5809221459 & 12.8623013850883 & -11.5809221459309 & 1.64271996943008 \tabularnewline
12 & 32396 & 32406.2172369703 & 25.9905886651772 & -10.2172369702792 & 2.02338682077191 \tabularnewline
13 & 32441 & 32361.2432220378 & 26.3057225577656 & 79.7567779622374 & -0.398149163354623 \tabularnewline
14 & 32447 & 32452.6970545236 & 29.5342130970008 & -5.69705452357042 & 0.258805926359441 \tabularnewline
15 & 32288 & 32293.9395769665 & 23.1125477764634 & -5.93957696650549 & -0.876969086273123 \tabularnewline
16 & 32418 & 32423.8069756149 & 26.9164976769195 & -5.80697561486573 & 0.496794993291035 \tabularnewline
17 & 32346 & 32351.9251472244 & 23.2559089050994 & -5.92514722443949 & -0.459409099559962 \tabularnewline
18 & 32091 & 32097.2448299504 & 12.5930008502601 & -6.24482995041355 & -1.29145369042109 \tabularnewline
19 & 31855 & 31861.519142529 & 2.76515580695383 & -6.51914252899029 & -1.15305278087372 \tabularnewline
20 & 31683 & 31689.7041494154 & -4.33937976419046 & -6.70414941536826 & -0.810144006477588 \tabularnewline
21 & 31615 & 31621.7687318731 & -6.99273965837496 & -6.76873187306778 & -0.294948002278496 \tabularnewline
22 & 31840 & 31846.5434111315 & 2.8954429917442 & -6.54341113153677 & 1.07432379848715 \tabularnewline
23 & 31536 & 31542.8285184522 & -10.4503339895168 & -6.82851845221873 & -1.42054592977705 \tabularnewline
24 & 31383 & 31389.9550843462 & -16.7618423480564 & -6.95508434620576 & -0.659556110132069 \tabularnewline
25 & 31638 & 31527.8345327213 & -11.4293162628538 & 110.165467278704 & 0.785401175030913 \tabularnewline
26 & 31626 & 31634.2436891432 & -5.28026573408549 & -8.24368914322513 & 0.497025632650487 \tabularnewline
27 & 31720 & 31728.197021138 & -0.702650629023177 & -8.19702113796054 & 0.458914510848177 \tabularnewline
28 & 31472 & 31480.3078370393 & -12.2426509901965 & -8.30783703927386 & -1.14277732721684 \tabularnewline
29 & 31372 & 31380.3453068556 & -16.3821604570421 & -8.3453068555836 & -0.405424961254062 \tabularnewline
30 & 31419 & 31427.3195334722 & -13.3633544754091 & -8.31953347216264 & 0.292744987250647 \tabularnewline
31 & 31341 & 31349.3445541952 & -16.4687894514474 & -8.34455419519239 & -0.298473926864508 \tabularnewline
32 & 31171 & 31179.4011080844 & -23.902955353664 & -8.40110808439705 & -0.70882384263698 \tabularnewline
33 & 31036 & 31044.440035665 & -29.3202906414276 & -8.44003566500355 & -0.512821616280683 \tabularnewline
34 & 30532 & 30540.5981982787 & -52.6131252897033 & -8.59819827865321 & -2.19075626401384 \tabularnewline
35 & 30666 & 30674.539087559 & -43.4038667268277 & -8.53908755898293 & 0.861136304245901 \tabularnewline
36 & 30571 & 30579.5546202609 & -45.9631068661237 & -8.55462026087105 & -0.238061582436233 \tabularnewline
37 & 30173 & 30136.4336583547 & -64.209751319512 & 36.5663416453475 & -1.95087065774321 \tabularnewline
38 & 30032 & 30035.7235296431 & -66.1318608577058 & -3.72352964305939 & -0.157954438992422 \tabularnewline
39 & 29874 & 29877.7386827749 & -70.7431144549682 & -3.73868277487997 & -0.423742064582086 \tabularnewline
40 & 30018 & 30021.7050470175 & -59.9278244707317 & -3.70504701754825 & 0.990414823373518 \tabularnewline
41 & 29911 & 29914.7120475897 & -62.3057582247592 & -3.71204758971698 & -0.217083686027672 \tabularnewline
42 & 29963 & 29966.6959091468 & -56.5156469474721 & -3.69590914679706 & 0.527107870954779 \tabularnewline
43 & 30050 & 30053.6766755633 & -49.2280954675697 & -3.67667556331955 & 0.66176262275603 \tabularnewline
44 & 29901 & 29904.6893662596 & -54.3055566941981 & -3.68936625955319 & -0.460029459230713 \tabularnewline
45 & 29544 & 29547.7259048464 & -69.740394105798 & -3.72590484639961 & -1.39559295784481 \tabularnewline
46 & 29451 & 29454.7285691163 & -70.9285469124179 & -3.7285691163369 & -0.107234838963537 \tabularnewline
47 & 29293 & 29296.7380324213 & -75.3834673424578 & -3.7380324213163 & -0.401412269638809 \tabularnewline
48 & 29334 & 29337.7260314656 & -69.4202663517712 & -3.72603146555702 & 0.536524188056835 \tabularnewline
49 & 29389 & 29340.1757307954 & -65.8489637750225 & 48.8242692045578 & 0.347375103767396 \tabularnewline
50 & 29563 & 29564.9375212838 & -50.615856627008 & -1.93752128381224 & 1.27568802192432 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116955&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]31245[/C][C]31245[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]30951[/C][C]30966.2739415637[/C][C]-15.5442801599388[/C][C]-15.2739415637431[/C][C]-0.791661176826256[/C][/ROW]
[ROW][C]3[/C][C]30872[/C][C]30887.5166084096[/C][C]-16.1346586769645[/C][C]-15.5166084096155[/C][C]-0.29892365905723[/C][/ROW]
[ROW][C]4[/C][C]30752[/C][C]30767.9090426388[/C][C]-17.380907596485[/C][C]-15.9090426388181[/C][C]-0.48861711586687[/C][/ROW]
[ROW][C]5[/C][C]30967[/C][C]30982.0438767587[/C][C]-13.9829549850008[/C][C]-15.0438767586947[/C][C]1.09174463019894[/C][/ROW]
[ROW][C]6[/C][C]30781[/C][C]30796.6733130974[/C][C]-16.9353257897189[/C][C]-15.6733130973929[/C][C]-0.807107610329334[/C][/ROW]
[ROW][C]7[/C][C]30681[/C][C]30696.9712984209[/C][C]-18.5643540818563[/C][C]-15.9712984208925[/C][C]-0.389255466828759[/C][/ROW]
[ROW][C]8[/C][C]31356[/C][C]31369.5378493448[/C][C]-3.33426269602627[/C][C]-13.5378493448312[/C][C]3.24626914594959[/C][/ROW]
[ROW][C]9[/C][C]31434[/C][C]31447.2593847371[/C][C]-1.36600264825519[/C][C]-13.2593847370721[/C][C]0.380253557263629[/C][/ROW]
[ROW][C]10[/C][C]31594[/C][C]31606.7214605902[/C][C]2.88249691480855[/C][C]-12.7214605902434[/C][C]0.75359423887647[/C][/ROW]
[ROW][C]11[/C][C]31949[/C][C]31960.5809221459[/C][C]12.8623013850883[/C][C]-11.5809221459309[/C][C]1.64271996943008[/C][/ROW]
[ROW][C]12[/C][C]32396[/C][C]32406.2172369703[/C][C]25.9905886651772[/C][C]-10.2172369702792[/C][C]2.02338682077191[/C][/ROW]
[ROW][C]13[/C][C]32441[/C][C]32361.2432220378[/C][C]26.3057225577656[/C][C]79.7567779622374[/C][C]-0.398149163354623[/C][/ROW]
[ROW][C]14[/C][C]32447[/C][C]32452.6970545236[/C][C]29.5342130970008[/C][C]-5.69705452357042[/C][C]0.258805926359441[/C][/ROW]
[ROW][C]15[/C][C]32288[/C][C]32293.9395769665[/C][C]23.1125477764634[/C][C]-5.93957696650549[/C][C]-0.876969086273123[/C][/ROW]
[ROW][C]16[/C][C]32418[/C][C]32423.8069756149[/C][C]26.9164976769195[/C][C]-5.80697561486573[/C][C]0.496794993291035[/C][/ROW]
[ROW][C]17[/C][C]32346[/C][C]32351.9251472244[/C][C]23.2559089050994[/C][C]-5.92514722443949[/C][C]-0.459409099559962[/C][/ROW]
[ROW][C]18[/C][C]32091[/C][C]32097.2448299504[/C][C]12.5930008502601[/C][C]-6.24482995041355[/C][C]-1.29145369042109[/C][/ROW]
[ROW][C]19[/C][C]31855[/C][C]31861.519142529[/C][C]2.76515580695383[/C][C]-6.51914252899029[/C][C]-1.15305278087372[/C][/ROW]
[ROW][C]20[/C][C]31683[/C][C]31689.7041494154[/C][C]-4.33937976419046[/C][C]-6.70414941536826[/C][C]-0.810144006477588[/C][/ROW]
[ROW][C]21[/C][C]31615[/C][C]31621.7687318731[/C][C]-6.99273965837496[/C][C]-6.76873187306778[/C][C]-0.294948002278496[/C][/ROW]
[ROW][C]22[/C][C]31840[/C][C]31846.5434111315[/C][C]2.8954429917442[/C][C]-6.54341113153677[/C][C]1.07432379848715[/C][/ROW]
[ROW][C]23[/C][C]31536[/C][C]31542.8285184522[/C][C]-10.4503339895168[/C][C]-6.82851845221873[/C][C]-1.42054592977705[/C][/ROW]
[ROW][C]24[/C][C]31383[/C][C]31389.9550843462[/C][C]-16.7618423480564[/C][C]-6.95508434620576[/C][C]-0.659556110132069[/C][/ROW]
[ROW][C]25[/C][C]31638[/C][C]31527.8345327213[/C][C]-11.4293162628538[/C][C]110.165467278704[/C][C]0.785401175030913[/C][/ROW]
[ROW][C]26[/C][C]31626[/C][C]31634.2436891432[/C][C]-5.28026573408549[/C][C]-8.24368914322513[/C][C]0.497025632650487[/C][/ROW]
[ROW][C]27[/C][C]31720[/C][C]31728.197021138[/C][C]-0.702650629023177[/C][C]-8.19702113796054[/C][C]0.458914510848177[/C][/ROW]
[ROW][C]28[/C][C]31472[/C][C]31480.3078370393[/C][C]-12.2426509901965[/C][C]-8.30783703927386[/C][C]-1.14277732721684[/C][/ROW]
[ROW][C]29[/C][C]31372[/C][C]31380.3453068556[/C][C]-16.3821604570421[/C][C]-8.3453068555836[/C][C]-0.405424961254062[/C][/ROW]
[ROW][C]30[/C][C]31419[/C][C]31427.3195334722[/C][C]-13.3633544754091[/C][C]-8.31953347216264[/C][C]0.292744987250647[/C][/ROW]
[ROW][C]31[/C][C]31341[/C][C]31349.3445541952[/C][C]-16.4687894514474[/C][C]-8.34455419519239[/C][C]-0.298473926864508[/C][/ROW]
[ROW][C]32[/C][C]31171[/C][C]31179.4011080844[/C][C]-23.902955353664[/C][C]-8.40110808439705[/C][C]-0.70882384263698[/C][/ROW]
[ROW][C]33[/C][C]31036[/C][C]31044.440035665[/C][C]-29.3202906414276[/C][C]-8.44003566500355[/C][C]-0.512821616280683[/C][/ROW]
[ROW][C]34[/C][C]30532[/C][C]30540.5981982787[/C][C]-52.6131252897033[/C][C]-8.59819827865321[/C][C]-2.19075626401384[/C][/ROW]
[ROW][C]35[/C][C]30666[/C][C]30674.539087559[/C][C]-43.4038667268277[/C][C]-8.53908755898293[/C][C]0.861136304245901[/C][/ROW]
[ROW][C]36[/C][C]30571[/C][C]30579.5546202609[/C][C]-45.9631068661237[/C][C]-8.55462026087105[/C][C]-0.238061582436233[/C][/ROW]
[ROW][C]37[/C][C]30173[/C][C]30136.4336583547[/C][C]-64.209751319512[/C][C]36.5663416453475[/C][C]-1.95087065774321[/C][/ROW]
[ROW][C]38[/C][C]30032[/C][C]30035.7235296431[/C][C]-66.1318608577058[/C][C]-3.72352964305939[/C][C]-0.157954438992422[/C][/ROW]
[ROW][C]39[/C][C]29874[/C][C]29877.7386827749[/C][C]-70.7431144549682[/C][C]-3.73868277487997[/C][C]-0.423742064582086[/C][/ROW]
[ROW][C]40[/C][C]30018[/C][C]30021.7050470175[/C][C]-59.9278244707317[/C][C]-3.70504701754825[/C][C]0.990414823373518[/C][/ROW]
[ROW][C]41[/C][C]29911[/C][C]29914.7120475897[/C][C]-62.3057582247592[/C][C]-3.71204758971698[/C][C]-0.217083686027672[/C][/ROW]
[ROW][C]42[/C][C]29963[/C][C]29966.6959091468[/C][C]-56.5156469474721[/C][C]-3.69590914679706[/C][C]0.527107870954779[/C][/ROW]
[ROW][C]43[/C][C]30050[/C][C]30053.6766755633[/C][C]-49.2280954675697[/C][C]-3.67667556331955[/C][C]0.66176262275603[/C][/ROW]
[ROW][C]44[/C][C]29901[/C][C]29904.6893662596[/C][C]-54.3055566941981[/C][C]-3.68936625955319[/C][C]-0.460029459230713[/C][/ROW]
[ROW][C]45[/C][C]29544[/C][C]29547.7259048464[/C][C]-69.740394105798[/C][C]-3.72590484639961[/C][C]-1.39559295784481[/C][/ROW]
[ROW][C]46[/C][C]29451[/C][C]29454.7285691163[/C][C]-70.9285469124179[/C][C]-3.7285691163369[/C][C]-0.107234838963537[/C][/ROW]
[ROW][C]47[/C][C]29293[/C][C]29296.7380324213[/C][C]-75.3834673424578[/C][C]-3.7380324213163[/C][C]-0.401412269638809[/C][/ROW]
[ROW][C]48[/C][C]29334[/C][C]29337.7260314656[/C][C]-69.4202663517712[/C][C]-3.72603146555702[/C][C]0.536524188056835[/C][/ROW]
[ROW][C]49[/C][C]29389[/C][C]29340.1757307954[/C][C]-65.8489637750225[/C][C]48.8242692045578[/C][C]0.347375103767396[/C][/ROW]
[ROW][C]50[/C][C]29563[/C][C]29564.9375212838[/C][C]-50.615856627008[/C][C]-1.93752128381224[/C][C]1.27568802192432[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116955&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116955&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
13124531245000
23095130966.2739415637-15.5442801599388-15.2739415637431-0.791661176826256
33087230887.5166084096-16.1346586769645-15.5166084096155-0.29892365905723
43075230767.9090426388-17.380907596485-15.9090426388181-0.48861711586687
53096730982.0438767587-13.9829549850008-15.04387675869471.09174463019894
63078130796.6733130974-16.9353257897189-15.6733130973929-0.807107610329334
73068130696.9712984209-18.5643540818563-15.9712984208925-0.389255466828759
83135631369.5378493448-3.33426269602627-13.53784934483123.24626914594959
93143431447.2593847371-1.36600264825519-13.25938473707210.380253557263629
103159431606.72146059022.88249691480855-12.72146059024340.75359423887647
113194931960.580922145912.8623013850883-11.58092214593091.64271996943008
123239632406.217236970325.9905886651772-10.21723697027922.02338682077191
133244132361.243222037826.305722557765679.7567779622374-0.398149163354623
143244732452.697054523629.5342130970008-5.697054523570420.258805926359441
153228832293.939576966523.1125477764634-5.93957696650549-0.876969086273123
163241832423.806975614926.9164976769195-5.806975614865730.496794993291035
173234632351.925147224423.2559089050994-5.92514722443949-0.459409099559962
183209132097.244829950412.5930008502601-6.24482995041355-1.29145369042109
193185531861.5191425292.76515580695383-6.51914252899029-1.15305278087372
203168331689.7041494154-4.33937976419046-6.70414941536826-0.810144006477588
213161531621.7687318731-6.99273965837496-6.76873187306778-0.294948002278496
223184031846.54341113152.8954429917442-6.543411131536771.07432379848715
233153631542.8285184522-10.4503339895168-6.82851845221873-1.42054592977705
243138331389.9550843462-16.7618423480564-6.95508434620576-0.659556110132069
253163831527.8345327213-11.4293162628538110.1654672787040.785401175030913
263162631634.2436891432-5.28026573408549-8.243689143225130.497025632650487
273172031728.197021138-0.702650629023177-8.197021137960540.458914510848177
283147231480.3078370393-12.2426509901965-8.30783703927386-1.14277732721684
293137231380.3453068556-16.3821604570421-8.3453068555836-0.405424961254062
303141931427.3195334722-13.3633544754091-8.319533472162640.292744987250647
313134131349.3445541952-16.4687894514474-8.34455419519239-0.298473926864508
323117131179.4011080844-23.902955353664-8.40110808439705-0.70882384263698
333103631044.440035665-29.3202906414276-8.44003566500355-0.512821616280683
343053230540.5981982787-52.6131252897033-8.59819827865321-2.19075626401384
353066630674.539087559-43.4038667268277-8.539087558982930.861136304245901
363057130579.5546202609-45.9631068661237-8.55462026087105-0.238061582436233
373017330136.4336583547-64.20975131951236.5663416453475-1.95087065774321
383003230035.7235296431-66.1318608577058-3.72352964305939-0.157954438992422
392987429877.7386827749-70.7431144549682-3.73868277487997-0.423742064582086
403001830021.7050470175-59.9278244707317-3.705047017548250.990414823373518
412991129914.7120475897-62.3057582247592-3.71204758971698-0.217083686027672
422996329966.6959091468-56.5156469474721-3.695909146797060.527107870954779
433005030053.6766755633-49.2280954675697-3.676675563319550.66176262275603
442990129904.6893662596-54.3055566941981-3.68936625955319-0.460029459230713
452954429547.7259048464-69.740394105798-3.72590484639961-1.39559295784481
462945129454.7285691163-70.9285469124179-3.7285691163369-0.107234838963537
472929329296.7380324213-75.3834673424578-3.7380324213163-0.401412269638809
482933429337.7260314656-69.4202663517712-3.726031465557020.536524188056835
492938929340.1757307954-65.848963775022548.82426920455780.347375103767396
502956329564.9375212838-50.615856627008-1.937521283812241.27568802192432



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')