Free Statistics

of Irreproducible Research!

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 computationFri, 04 Dec 2009 07:23:59 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t1259936717hpkxtpzjimk4ulh.htm/, Retrieved Sun, 28 Apr 2024 13:28:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63600, Retrieved Sun, 28 Apr 2024 13:28:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Structural Time Series Models] [] [2009-11-27 15:02:30] [b98453cac15ba1066b407e146608df68]
-    D      [Structural Time Series Models] [WS 9 Structural T...] [2009-12-04 14:23:59] [eba9f01697e64705b70041e6f338cb22] [Current]
-    D        [Structural Time Series Models] [WS 9 Review 3 Str...] [2009-12-10 18:55:45] [83058a88a37d754675a5cd22dab372fc]
Feedback Forum

Post a new message
Dataseries X:
98,8
100,5
110,4
96,4
101,9
106,2
81
94,7
101
109,4
102,3
90,7
96,2
96,1
106
103,1
102
104,7
86
92,1
106,9
112,6
101,7
92
97,4
97
105,4
102,7
98,1
104,5
87,4
89,9
109,8
111,7
98,6
96,9
95,1
97
112,7
102,9
97,4
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
96
99,8
116,8
115,7
99,4
94,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63600&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63600&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63600&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
198.898.8000
2100.599.0098361764009-0.03919196494493011.490163823599110.388717178313888
3110.4103.5579386721950.2891175123964456.84206132780532.37894910697432
496.4102.9166161045240.204866863319226-6.51661610452434-0.453472455807471
5101.9102.4670317502710.148646019839951-0.567031750271342-0.389935500093396
6106.2103.3141541063810.1990167386170892.885845893619020.485265288551031
78198.1421630341768-0.107051973677707-17.1421630341768-4.03755497919976
894.795.2415616478735-0.232145392064929-0.541561647873479-2.17500001561392
910195.4144494351909-0.2173514459748065.585550564809140.320074983827219
10109.498.829318846847-0.10246554965938510.57068115315312.88736399319624
11102.3101.082184715780-0.03405458018410861.217815284220441.87555612160628
1290.799.5211029931645-0.0765164808777496-8.82110299316446-1.21573693447957
1396.298.4278335880762-0.0786365050015628-2.22783358807624-0.837114293790518
1496.197.6344558667332-0.0779097749925256-1.53445586673316-0.597327158208534
1510697.2148151878089-0.08170897635672558.78518481219112-0.271968943399785
16103.199.6618169891172-0.01882448958634353.438183010882791.88477326938139
17102100.6986164551630.01668708991826741.301383544836830.764909178644743
18104.7100.138930896851-0.004582686716128254.56106910314886-0.422243923205732
1986100.4261423593640.00592639577782337-14.42614235936440.219563317532909
2092.199.2041441317476-0.0341627032902864-7.10414413174765-0.947080104535874
21106.999.9994108213925-0.01078726888906246.900589178607490.650523709474136
22112.6100.9246747034240.011179872870973711.67532529657560.741231190687254
23101.7100.7420164872390.007513457368282280.957983512761186-0.154306910210952
2492100.4773575374090.00347865014955188-8.4773575374093-0.217427882668088
2597.4100.1993034460080.000152177320648185-2.79930344600771-0.225435315804073
269799.9893586502527-0.00221301989496133-2.98935865025267-0.167732327906410
27105.499.651326768601-0.006680468942725655.74867323139898-0.265059650259245
28102.799.5463226882764-0.008331143758389173.15367731172359-0.0764024285973884
2998.198.7266147144523-0.024716530736683-0.626614714452342-0.6233580183334
30104.598.7024140438546-0.02470494168734365.797585956145440.000395471388422841
3187.499.3706841150724-0.00862983931384387-11.97068411507230.534309673127569
3289.999.283120171661-0.0104047850297574-9.38312017166093-0.0614178309585382
33109.8100.2123339964730.009061797682844339.587666003526980.737438521284237
34111.7100.4108593267850.012545407469318811.28914067321500.149661901763741
3598.699.71589924770790.00123238558733513-1.11589924770786-0.561278537023017
3696.9100.6718935139540.0145715389641173-3.771893513954150.759306942950503
3795.1100.2771283882590.00937848982912856-5.17712838825894-0.325724349963536
389799.94658042597370.00518462919910609-2.94658042597369-0.270001948785785
39112.7101.3972657816720.023796481024138711.30273421832791.14338861161793
40102.9101.4691615657810.02446981324184111.430838434218950.0378481793485489
4197.4100.7839887910140.0136337196838558-3.38398879101382-0.556052023203621
42111.4101.8568060091540.03087580789336299.543193990845790.828606522996382
4387.4101.7697560446860.0288996685262079-14.3697560446857-0.0923682580025581
4496.8102.9506345834580.048045614227143-6.150634583457590.90515765807726
45114.1103.7625024627430.060223362990124610.33749753725740.602428981689017
46110.3102.9126041122120.04664775840926897.3873958877875-0.720272168885567
47103.9103.2469602820920.05061242712228860.653039717908380.228286603326934
48101.6103.8729532006170.0579596860053997-2.27295320061670.457284546526323
4994.6103.26984397760.0499844650346042-8.66984397760002-0.525669500923169
5095.9102.2873566038820.0378471829486033-6.38735660388211-0.820531912534926
51104.799.87837340793140.00890068473133824.82162659206855-1.94164489347105
52102.899.40901512170270.003075004834395613.39098487829731-0.378787462775978
5398.1100.0381013794860.0109906154563009-1.93810137948650.494996185223788
54113.9101.4541739495320.029328130090376512.44582605046761.11014924342745
5580.9100.7730683169390.0199016027302481-19.8730683169387-0.561470987021063
5695.7100.8171713531480.0202218476453798-5.117171353148110.0191492475154115
57113.2101.1739509955730.024579715518218712.02604900442720.266736234786609
58105.9100.6833208826830.01814888371954395.2166791173168-0.409016963290624
59108.8102.1219322817810.03510141187175046.678067718219071.12930723947157
60102.3102.8292891903370.0427747121393249-0.5292891903367520.534999421844736
6199103.7561831930880.0525091831587319-4.756183193088420.703946053253157
62100.7104.4660510323590.059591557389357-3.766051032358910.523373688636769
63115.5106.2464934753620.07802238167366289.25350652463781.369460830772
64100.7105.0498826921100.0642789463183618-4.3498826921101-1.01367015760388
65109.9106.3887118895830.07820309143017323.511288110416561.01297767969026
66114.6105.8280333521110.07113444051419598.77196664788895-0.507603384435839
6785.4105.589356044990.0676839168247103-20.1893560449899-0.246175581026117
68100.5105.6837690247530.0679807938960927-5.183769024752640.0212493259229752
69114.8105.2440763404350.06241408694737959.55592365956484-0.403900964636287
70116.5106.9669011159960.080235972686569.533098884004031.32213392324065
71112.9107.7746703249420.08784062008109595.125329675058390.579769434185688
72102107.1829981459590.080929299987709-5.18299814595898-0.541834657596631
73106108.0829999505450.0890638668738728-2.082999950545090.653363831570579
74105.3108.8927837056050.096099529042043-3.592783705604910.574983331025758
75118.8109.2362529563760.09849176828775129.563747043623980.197334193980319
76106.1109.8075916887910.103052877421846-3.707591688790770.377132033601843
77109.3108.9727465416740.09399076370445170.327253458326185-0.747902412160804
78117.2108.5537942481450.08902199113528148.64620575185526-0.408996736360124
7992.5109.4949635258610.097279416064863-16.99496352586090.679515249683659
80104.2110.0108019131170.101319218354531-5.810801913117460.333849764300692
81112.5108.9621248076630.09032054053098793.5378751923371-0.917612323072251
82122.4109.6600019217480.096051788401591512.73999807825240.485005688976279
83113.3109.6505116439250.09507285274807743.64948835607482-0.0842908545868984
84100108.8882172941430.0872611125754726-8.88821729414274-0.684995664189131
85110.7109.7100181277830.09384379291497240.9899818722173090.587025782419494
86112.8111.6482624606420.1101502535024441.151737539358111.47423888983122
87109.8109.6986857865730.09211565004811930.10131421342673-1.64645292240216
88117.3111.4708440302130.1067372864369535.829155969787381.34294879762472
89109.1111.5453438826230.106457692833247-2.44534388262266-0.0257687263146201
90115.9110.7384944748430.09855641802826945.1615055251569-0.73005761651245
9196110.9770323693690.0997636310885871-14.97703236936940.111904473912141
9299.8109.7105455150050.0880402166762467-9.91054551500455-1.09238868789963
93116.8110.2032822497170.0914866335741696.596717750282670.323649442445218
94115.7108.7234232106930.07823849546017696.97657678930742-1.25699249627229
9599.4105.2100533046810.0483135624866218-5.81005330468101-2.87387823368404
9694.3103.7664068061120.0360382604140943-9.46640680611158-1.19411146143459

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 98.8 & 98.8 & 0 & 0 & 0 \tabularnewline
2 & 100.5 & 99.0098361764009 & -0.0391919649449301 & 1.49016382359911 & 0.388717178313888 \tabularnewline
3 & 110.4 & 103.557938672195 & 0.289117512396445 & 6.8420613278053 & 2.37894910697432 \tabularnewline
4 & 96.4 & 102.916616104524 & 0.204866863319226 & -6.51661610452434 & -0.453472455807471 \tabularnewline
5 & 101.9 & 102.467031750271 & 0.148646019839951 & -0.567031750271342 & -0.389935500093396 \tabularnewline
6 & 106.2 & 103.314154106381 & 0.199016738617089 & 2.88584589361902 & 0.485265288551031 \tabularnewline
7 & 81 & 98.1421630341768 & -0.107051973677707 & -17.1421630341768 & -4.03755497919976 \tabularnewline
8 & 94.7 & 95.2415616478735 & -0.232145392064929 & -0.541561647873479 & -2.17500001561392 \tabularnewline
9 & 101 & 95.4144494351909 & -0.217351445974806 & 5.58555056480914 & 0.320074983827219 \tabularnewline
10 & 109.4 & 98.829318846847 & -0.102465549659385 & 10.5706811531531 & 2.88736399319624 \tabularnewline
11 & 102.3 & 101.082184715780 & -0.0340545801841086 & 1.21781528422044 & 1.87555612160628 \tabularnewline
12 & 90.7 & 99.5211029931645 & -0.0765164808777496 & -8.82110299316446 & -1.21573693447957 \tabularnewline
13 & 96.2 & 98.4278335880762 & -0.0786365050015628 & -2.22783358807624 & -0.837114293790518 \tabularnewline
14 & 96.1 & 97.6344558667332 & -0.0779097749925256 & -1.53445586673316 & -0.597327158208534 \tabularnewline
15 & 106 & 97.2148151878089 & -0.0817089763567255 & 8.78518481219112 & -0.271968943399785 \tabularnewline
16 & 103.1 & 99.6618169891172 & -0.0188244895863435 & 3.43818301088279 & 1.88477326938139 \tabularnewline
17 & 102 & 100.698616455163 & 0.0166870899182674 & 1.30138354483683 & 0.764909178644743 \tabularnewline
18 & 104.7 & 100.138930896851 & -0.00458268671612825 & 4.56106910314886 & -0.422243923205732 \tabularnewline
19 & 86 & 100.426142359364 & 0.00592639577782337 & -14.4261423593644 & 0.219563317532909 \tabularnewline
20 & 92.1 & 99.2041441317476 & -0.0341627032902864 & -7.10414413174765 & -0.947080104535874 \tabularnewline
21 & 106.9 & 99.9994108213925 & -0.0107872688890624 & 6.90058917860749 & 0.650523709474136 \tabularnewline
22 & 112.6 & 100.924674703424 & 0.0111798728709737 & 11.6753252965756 & 0.741231190687254 \tabularnewline
23 & 101.7 & 100.742016487239 & 0.00751345736828228 & 0.957983512761186 & -0.154306910210952 \tabularnewline
24 & 92 & 100.477357537409 & 0.00347865014955188 & -8.4773575374093 & -0.217427882668088 \tabularnewline
25 & 97.4 & 100.199303446008 & 0.000152177320648185 & -2.79930344600771 & -0.225435315804073 \tabularnewline
26 & 97 & 99.9893586502527 & -0.00221301989496133 & -2.98935865025267 & -0.167732327906410 \tabularnewline
27 & 105.4 & 99.651326768601 & -0.00668046894272565 & 5.74867323139898 & -0.265059650259245 \tabularnewline
28 & 102.7 & 99.5463226882764 & -0.00833114375838917 & 3.15367731172359 & -0.0764024285973884 \tabularnewline
29 & 98.1 & 98.7266147144523 & -0.024716530736683 & -0.626614714452342 & -0.6233580183334 \tabularnewline
30 & 104.5 & 98.7024140438546 & -0.0247049416873436 & 5.79758595614544 & 0.000395471388422841 \tabularnewline
31 & 87.4 & 99.3706841150724 & -0.00862983931384387 & -11.9706841150723 & 0.534309673127569 \tabularnewline
32 & 89.9 & 99.283120171661 & -0.0104047850297574 & -9.38312017166093 & -0.0614178309585382 \tabularnewline
33 & 109.8 & 100.212333996473 & 0.00906179768284433 & 9.58766600352698 & 0.737438521284237 \tabularnewline
34 & 111.7 & 100.410859326785 & 0.0125454074693188 & 11.2891406732150 & 0.149661901763741 \tabularnewline
35 & 98.6 & 99.7158992477079 & 0.00123238558733513 & -1.11589924770786 & -0.561278537023017 \tabularnewline
36 & 96.9 & 100.671893513954 & 0.0145715389641173 & -3.77189351395415 & 0.759306942950503 \tabularnewline
37 & 95.1 & 100.277128388259 & 0.00937848982912856 & -5.17712838825894 & -0.325724349963536 \tabularnewline
38 & 97 & 99.9465804259737 & 0.00518462919910609 & -2.94658042597369 & -0.270001948785785 \tabularnewline
39 & 112.7 & 101.397265781672 & 0.0237964810241387 & 11.3027342183279 & 1.14338861161793 \tabularnewline
40 & 102.9 & 101.469161565781 & 0.0244698132418411 & 1.43083843421895 & 0.0378481793485489 \tabularnewline
41 & 97.4 & 100.783988791014 & 0.0136337196838558 & -3.38398879101382 & -0.556052023203621 \tabularnewline
42 & 111.4 & 101.856806009154 & 0.0308758078933629 & 9.54319399084579 & 0.828606522996382 \tabularnewline
43 & 87.4 & 101.769756044686 & 0.0288996685262079 & -14.3697560446857 & -0.0923682580025581 \tabularnewline
44 & 96.8 & 102.950634583458 & 0.048045614227143 & -6.15063458345759 & 0.90515765807726 \tabularnewline
45 & 114.1 & 103.762502462743 & 0.0602233629901246 & 10.3374975372574 & 0.602428981689017 \tabularnewline
46 & 110.3 & 102.912604112212 & 0.0466477584092689 & 7.3873958877875 & -0.720272168885567 \tabularnewline
47 & 103.9 & 103.246960282092 & 0.0506124271222886 & 0.65303971790838 & 0.228286603326934 \tabularnewline
48 & 101.6 & 103.872953200617 & 0.0579596860053997 & -2.2729532006167 & 0.457284546526323 \tabularnewline
49 & 94.6 & 103.2698439776 & 0.0499844650346042 & -8.66984397760002 & -0.525669500923169 \tabularnewline
50 & 95.9 & 102.287356603882 & 0.0378471829486033 & -6.38735660388211 & -0.820531912534926 \tabularnewline
51 & 104.7 & 99.8783734079314 & 0.0089006847313382 & 4.82162659206855 & -1.94164489347105 \tabularnewline
52 & 102.8 & 99.4090151217027 & 0.00307500483439561 & 3.39098487829731 & -0.378787462775978 \tabularnewline
53 & 98.1 & 100.038101379486 & 0.0109906154563009 & -1.9381013794865 & 0.494996185223788 \tabularnewline
54 & 113.9 & 101.454173949532 & 0.0293281300903765 & 12.4458260504676 & 1.11014924342745 \tabularnewline
55 & 80.9 & 100.773068316939 & 0.0199016027302481 & -19.8730683169387 & -0.561470987021063 \tabularnewline
56 & 95.7 & 100.817171353148 & 0.0202218476453798 & -5.11717135314811 & 0.0191492475154115 \tabularnewline
57 & 113.2 & 101.173950995573 & 0.0245797155182187 & 12.0260490044272 & 0.266736234786609 \tabularnewline
58 & 105.9 & 100.683320882683 & 0.0181488837195439 & 5.2166791173168 & -0.409016963290624 \tabularnewline
59 & 108.8 & 102.121932281781 & 0.0351014118717504 & 6.67806771821907 & 1.12930723947157 \tabularnewline
60 & 102.3 & 102.829289190337 & 0.0427747121393249 & -0.529289190336752 & 0.534999421844736 \tabularnewline
61 & 99 & 103.756183193088 & 0.0525091831587319 & -4.75618319308842 & 0.703946053253157 \tabularnewline
62 & 100.7 & 104.466051032359 & 0.059591557389357 & -3.76605103235891 & 0.523373688636769 \tabularnewline
63 & 115.5 & 106.246493475362 & 0.0780223816736628 & 9.2535065246378 & 1.369460830772 \tabularnewline
64 & 100.7 & 105.049882692110 & 0.0642789463183618 & -4.3498826921101 & -1.01367015760388 \tabularnewline
65 & 109.9 & 106.388711889583 & 0.0782030914301732 & 3.51128811041656 & 1.01297767969026 \tabularnewline
66 & 114.6 & 105.828033352111 & 0.0711344405141959 & 8.77196664788895 & -0.507603384435839 \tabularnewline
67 & 85.4 & 105.58935604499 & 0.0676839168247103 & -20.1893560449899 & -0.246175581026117 \tabularnewline
68 & 100.5 & 105.683769024753 & 0.0679807938960927 & -5.18376902475264 & 0.0212493259229752 \tabularnewline
69 & 114.8 & 105.244076340435 & 0.0624140869473795 & 9.55592365956484 & -0.403900964636287 \tabularnewline
70 & 116.5 & 106.966901115996 & 0.08023597268656 & 9.53309888400403 & 1.32213392324065 \tabularnewline
71 & 112.9 & 107.774670324942 & 0.0878406200810959 & 5.12532967505839 & 0.579769434185688 \tabularnewline
72 & 102 & 107.182998145959 & 0.080929299987709 & -5.18299814595898 & -0.541834657596631 \tabularnewline
73 & 106 & 108.082999950545 & 0.0890638668738728 & -2.08299995054509 & 0.653363831570579 \tabularnewline
74 & 105.3 & 108.892783705605 & 0.096099529042043 & -3.59278370560491 & 0.574983331025758 \tabularnewline
75 & 118.8 & 109.236252956376 & 0.0984917682877512 & 9.56374704362398 & 0.197334193980319 \tabularnewline
76 & 106.1 & 109.807591688791 & 0.103052877421846 & -3.70759168879077 & 0.377132033601843 \tabularnewline
77 & 109.3 & 108.972746541674 & 0.0939907637044517 & 0.327253458326185 & -0.747902412160804 \tabularnewline
78 & 117.2 & 108.553794248145 & 0.0890219911352814 & 8.64620575185526 & -0.408996736360124 \tabularnewline
79 & 92.5 & 109.494963525861 & 0.097279416064863 & -16.9949635258609 & 0.679515249683659 \tabularnewline
80 & 104.2 & 110.010801913117 & 0.101319218354531 & -5.81080191311746 & 0.333849764300692 \tabularnewline
81 & 112.5 & 108.962124807663 & 0.0903205405309879 & 3.5378751923371 & -0.917612323072251 \tabularnewline
82 & 122.4 & 109.660001921748 & 0.0960517884015915 & 12.7399980782524 & 0.485005688976279 \tabularnewline
83 & 113.3 & 109.650511643925 & 0.0950728527480774 & 3.64948835607482 & -0.0842908545868984 \tabularnewline
84 & 100 & 108.888217294143 & 0.0872611125754726 & -8.88821729414274 & -0.684995664189131 \tabularnewline
85 & 110.7 & 109.710018127783 & 0.0938437929149724 & 0.989981872217309 & 0.587025782419494 \tabularnewline
86 & 112.8 & 111.648262460642 & 0.110150253502444 & 1.15173753935811 & 1.47423888983122 \tabularnewline
87 & 109.8 & 109.698685786573 & 0.0921156500481193 & 0.10131421342673 & -1.64645292240216 \tabularnewline
88 & 117.3 & 111.470844030213 & 0.106737286436953 & 5.82915596978738 & 1.34294879762472 \tabularnewline
89 & 109.1 & 111.545343882623 & 0.106457692833247 & -2.44534388262266 & -0.0257687263146201 \tabularnewline
90 & 115.9 & 110.738494474843 & 0.0985564180282694 & 5.1615055251569 & -0.73005761651245 \tabularnewline
91 & 96 & 110.977032369369 & 0.0997636310885871 & -14.9770323693694 & 0.111904473912141 \tabularnewline
92 & 99.8 & 109.710545515005 & 0.0880402166762467 & -9.91054551500455 & -1.09238868789963 \tabularnewline
93 & 116.8 & 110.203282249717 & 0.091486633574169 & 6.59671775028267 & 0.323649442445218 \tabularnewline
94 & 115.7 & 108.723423210693 & 0.0782384954601769 & 6.97657678930742 & -1.25699249627229 \tabularnewline
95 & 99.4 & 105.210053304681 & 0.0483135624866218 & -5.81005330468101 & -2.87387823368404 \tabularnewline
96 & 94.3 & 103.766406806112 & 0.0360382604140943 & -9.46640680611158 & -1.19411146143459 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63600&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]98.8[/C][C]98.8[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]100.5[/C][C]99.0098361764009[/C][C]-0.0391919649449301[/C][C]1.49016382359911[/C][C]0.388717178313888[/C][/ROW]
[ROW][C]3[/C][C]110.4[/C][C]103.557938672195[/C][C]0.289117512396445[/C][C]6.8420613278053[/C][C]2.37894910697432[/C][/ROW]
[ROW][C]4[/C][C]96.4[/C][C]102.916616104524[/C][C]0.204866863319226[/C][C]-6.51661610452434[/C][C]-0.453472455807471[/C][/ROW]
[ROW][C]5[/C][C]101.9[/C][C]102.467031750271[/C][C]0.148646019839951[/C][C]-0.567031750271342[/C][C]-0.389935500093396[/C][/ROW]
[ROW][C]6[/C][C]106.2[/C][C]103.314154106381[/C][C]0.199016738617089[/C][C]2.88584589361902[/C][C]0.485265288551031[/C][/ROW]
[ROW][C]7[/C][C]81[/C][C]98.1421630341768[/C][C]-0.107051973677707[/C][C]-17.1421630341768[/C][C]-4.03755497919976[/C][/ROW]
[ROW][C]8[/C][C]94.7[/C][C]95.2415616478735[/C][C]-0.232145392064929[/C][C]-0.541561647873479[/C][C]-2.17500001561392[/C][/ROW]
[ROW][C]9[/C][C]101[/C][C]95.4144494351909[/C][C]-0.217351445974806[/C][C]5.58555056480914[/C][C]0.320074983827219[/C][/ROW]
[ROW][C]10[/C][C]109.4[/C][C]98.829318846847[/C][C]-0.102465549659385[/C][C]10.5706811531531[/C][C]2.88736399319624[/C][/ROW]
[ROW][C]11[/C][C]102.3[/C][C]101.082184715780[/C][C]-0.0340545801841086[/C][C]1.21781528422044[/C][C]1.87555612160628[/C][/ROW]
[ROW][C]12[/C][C]90.7[/C][C]99.5211029931645[/C][C]-0.0765164808777496[/C][C]-8.82110299316446[/C][C]-1.21573693447957[/C][/ROW]
[ROW][C]13[/C][C]96.2[/C][C]98.4278335880762[/C][C]-0.0786365050015628[/C][C]-2.22783358807624[/C][C]-0.837114293790518[/C][/ROW]
[ROW][C]14[/C][C]96.1[/C][C]97.6344558667332[/C][C]-0.0779097749925256[/C][C]-1.53445586673316[/C][C]-0.597327158208534[/C][/ROW]
[ROW][C]15[/C][C]106[/C][C]97.2148151878089[/C][C]-0.0817089763567255[/C][C]8.78518481219112[/C][C]-0.271968943399785[/C][/ROW]
[ROW][C]16[/C][C]103.1[/C][C]99.6618169891172[/C][C]-0.0188244895863435[/C][C]3.43818301088279[/C][C]1.88477326938139[/C][/ROW]
[ROW][C]17[/C][C]102[/C][C]100.698616455163[/C][C]0.0166870899182674[/C][C]1.30138354483683[/C][C]0.764909178644743[/C][/ROW]
[ROW][C]18[/C][C]104.7[/C][C]100.138930896851[/C][C]-0.00458268671612825[/C][C]4.56106910314886[/C][C]-0.422243923205732[/C][/ROW]
[ROW][C]19[/C][C]86[/C][C]100.426142359364[/C][C]0.00592639577782337[/C][C]-14.4261423593644[/C][C]0.219563317532909[/C][/ROW]
[ROW][C]20[/C][C]92.1[/C][C]99.2041441317476[/C][C]-0.0341627032902864[/C][C]-7.10414413174765[/C][C]-0.947080104535874[/C][/ROW]
[ROW][C]21[/C][C]106.9[/C][C]99.9994108213925[/C][C]-0.0107872688890624[/C][C]6.90058917860749[/C][C]0.650523709474136[/C][/ROW]
[ROW][C]22[/C][C]112.6[/C][C]100.924674703424[/C][C]0.0111798728709737[/C][C]11.6753252965756[/C][C]0.741231190687254[/C][/ROW]
[ROW][C]23[/C][C]101.7[/C][C]100.742016487239[/C][C]0.00751345736828228[/C][C]0.957983512761186[/C][C]-0.154306910210952[/C][/ROW]
[ROW][C]24[/C][C]92[/C][C]100.477357537409[/C][C]0.00347865014955188[/C][C]-8.4773575374093[/C][C]-0.217427882668088[/C][/ROW]
[ROW][C]25[/C][C]97.4[/C][C]100.199303446008[/C][C]0.000152177320648185[/C][C]-2.79930344600771[/C][C]-0.225435315804073[/C][/ROW]
[ROW][C]26[/C][C]97[/C][C]99.9893586502527[/C][C]-0.00221301989496133[/C][C]-2.98935865025267[/C][C]-0.167732327906410[/C][/ROW]
[ROW][C]27[/C][C]105.4[/C][C]99.651326768601[/C][C]-0.00668046894272565[/C][C]5.74867323139898[/C][C]-0.265059650259245[/C][/ROW]
[ROW][C]28[/C][C]102.7[/C][C]99.5463226882764[/C][C]-0.00833114375838917[/C][C]3.15367731172359[/C][C]-0.0764024285973884[/C][/ROW]
[ROW][C]29[/C][C]98.1[/C][C]98.7266147144523[/C][C]-0.024716530736683[/C][C]-0.626614714452342[/C][C]-0.6233580183334[/C][/ROW]
[ROW][C]30[/C][C]104.5[/C][C]98.7024140438546[/C][C]-0.0247049416873436[/C][C]5.79758595614544[/C][C]0.000395471388422841[/C][/ROW]
[ROW][C]31[/C][C]87.4[/C][C]99.3706841150724[/C][C]-0.00862983931384387[/C][C]-11.9706841150723[/C][C]0.534309673127569[/C][/ROW]
[ROW][C]32[/C][C]89.9[/C][C]99.283120171661[/C][C]-0.0104047850297574[/C][C]-9.38312017166093[/C][C]-0.0614178309585382[/C][/ROW]
[ROW][C]33[/C][C]109.8[/C][C]100.212333996473[/C][C]0.00906179768284433[/C][C]9.58766600352698[/C][C]0.737438521284237[/C][/ROW]
[ROW][C]34[/C][C]111.7[/C][C]100.410859326785[/C][C]0.0125454074693188[/C][C]11.2891406732150[/C][C]0.149661901763741[/C][/ROW]
[ROW][C]35[/C][C]98.6[/C][C]99.7158992477079[/C][C]0.00123238558733513[/C][C]-1.11589924770786[/C][C]-0.561278537023017[/C][/ROW]
[ROW][C]36[/C][C]96.9[/C][C]100.671893513954[/C][C]0.0145715389641173[/C][C]-3.77189351395415[/C][C]0.759306942950503[/C][/ROW]
[ROW][C]37[/C][C]95.1[/C][C]100.277128388259[/C][C]0.00937848982912856[/C][C]-5.17712838825894[/C][C]-0.325724349963536[/C][/ROW]
[ROW][C]38[/C][C]97[/C][C]99.9465804259737[/C][C]0.00518462919910609[/C][C]-2.94658042597369[/C][C]-0.270001948785785[/C][/ROW]
[ROW][C]39[/C][C]112.7[/C][C]101.397265781672[/C][C]0.0237964810241387[/C][C]11.3027342183279[/C][C]1.14338861161793[/C][/ROW]
[ROW][C]40[/C][C]102.9[/C][C]101.469161565781[/C][C]0.0244698132418411[/C][C]1.43083843421895[/C][C]0.0378481793485489[/C][/ROW]
[ROW][C]41[/C][C]97.4[/C][C]100.783988791014[/C][C]0.0136337196838558[/C][C]-3.38398879101382[/C][C]-0.556052023203621[/C][/ROW]
[ROW][C]42[/C][C]111.4[/C][C]101.856806009154[/C][C]0.0308758078933629[/C][C]9.54319399084579[/C][C]0.828606522996382[/C][/ROW]
[ROW][C]43[/C][C]87.4[/C][C]101.769756044686[/C][C]0.0288996685262079[/C][C]-14.3697560446857[/C][C]-0.0923682580025581[/C][/ROW]
[ROW][C]44[/C][C]96.8[/C][C]102.950634583458[/C][C]0.048045614227143[/C][C]-6.15063458345759[/C][C]0.90515765807726[/C][/ROW]
[ROW][C]45[/C][C]114.1[/C][C]103.762502462743[/C][C]0.0602233629901246[/C][C]10.3374975372574[/C][C]0.602428981689017[/C][/ROW]
[ROW][C]46[/C][C]110.3[/C][C]102.912604112212[/C][C]0.0466477584092689[/C][C]7.3873958877875[/C][C]-0.720272168885567[/C][/ROW]
[ROW][C]47[/C][C]103.9[/C][C]103.246960282092[/C][C]0.0506124271222886[/C][C]0.65303971790838[/C][C]0.228286603326934[/C][/ROW]
[ROW][C]48[/C][C]101.6[/C][C]103.872953200617[/C][C]0.0579596860053997[/C][C]-2.2729532006167[/C][C]0.457284546526323[/C][/ROW]
[ROW][C]49[/C][C]94.6[/C][C]103.2698439776[/C][C]0.0499844650346042[/C][C]-8.66984397760002[/C][C]-0.525669500923169[/C][/ROW]
[ROW][C]50[/C][C]95.9[/C][C]102.287356603882[/C][C]0.0378471829486033[/C][C]-6.38735660388211[/C][C]-0.820531912534926[/C][/ROW]
[ROW][C]51[/C][C]104.7[/C][C]99.8783734079314[/C][C]0.0089006847313382[/C][C]4.82162659206855[/C][C]-1.94164489347105[/C][/ROW]
[ROW][C]52[/C][C]102.8[/C][C]99.4090151217027[/C][C]0.00307500483439561[/C][C]3.39098487829731[/C][C]-0.378787462775978[/C][/ROW]
[ROW][C]53[/C][C]98.1[/C][C]100.038101379486[/C][C]0.0109906154563009[/C][C]-1.9381013794865[/C][C]0.494996185223788[/C][/ROW]
[ROW][C]54[/C][C]113.9[/C][C]101.454173949532[/C][C]0.0293281300903765[/C][C]12.4458260504676[/C][C]1.11014924342745[/C][/ROW]
[ROW][C]55[/C][C]80.9[/C][C]100.773068316939[/C][C]0.0199016027302481[/C][C]-19.8730683169387[/C][C]-0.561470987021063[/C][/ROW]
[ROW][C]56[/C][C]95.7[/C][C]100.817171353148[/C][C]0.0202218476453798[/C][C]-5.11717135314811[/C][C]0.0191492475154115[/C][/ROW]
[ROW][C]57[/C][C]113.2[/C][C]101.173950995573[/C][C]0.0245797155182187[/C][C]12.0260490044272[/C][C]0.266736234786609[/C][/ROW]
[ROW][C]58[/C][C]105.9[/C][C]100.683320882683[/C][C]0.0181488837195439[/C][C]5.2166791173168[/C][C]-0.409016963290624[/C][/ROW]
[ROW][C]59[/C][C]108.8[/C][C]102.121932281781[/C][C]0.0351014118717504[/C][C]6.67806771821907[/C][C]1.12930723947157[/C][/ROW]
[ROW][C]60[/C][C]102.3[/C][C]102.829289190337[/C][C]0.0427747121393249[/C][C]-0.529289190336752[/C][C]0.534999421844736[/C][/ROW]
[ROW][C]61[/C][C]99[/C][C]103.756183193088[/C][C]0.0525091831587319[/C][C]-4.75618319308842[/C][C]0.703946053253157[/C][/ROW]
[ROW][C]62[/C][C]100.7[/C][C]104.466051032359[/C][C]0.059591557389357[/C][C]-3.76605103235891[/C][C]0.523373688636769[/C][/ROW]
[ROW][C]63[/C][C]115.5[/C][C]106.246493475362[/C][C]0.0780223816736628[/C][C]9.2535065246378[/C][C]1.369460830772[/C][/ROW]
[ROW][C]64[/C][C]100.7[/C][C]105.049882692110[/C][C]0.0642789463183618[/C][C]-4.3498826921101[/C][C]-1.01367015760388[/C][/ROW]
[ROW][C]65[/C][C]109.9[/C][C]106.388711889583[/C][C]0.0782030914301732[/C][C]3.51128811041656[/C][C]1.01297767969026[/C][/ROW]
[ROW][C]66[/C][C]114.6[/C][C]105.828033352111[/C][C]0.0711344405141959[/C][C]8.77196664788895[/C][C]-0.507603384435839[/C][/ROW]
[ROW][C]67[/C][C]85.4[/C][C]105.58935604499[/C][C]0.0676839168247103[/C][C]-20.1893560449899[/C][C]-0.246175581026117[/C][/ROW]
[ROW][C]68[/C][C]100.5[/C][C]105.683769024753[/C][C]0.0679807938960927[/C][C]-5.18376902475264[/C][C]0.0212493259229752[/C][/ROW]
[ROW][C]69[/C][C]114.8[/C][C]105.244076340435[/C][C]0.0624140869473795[/C][C]9.55592365956484[/C][C]-0.403900964636287[/C][/ROW]
[ROW][C]70[/C][C]116.5[/C][C]106.966901115996[/C][C]0.08023597268656[/C][C]9.53309888400403[/C][C]1.32213392324065[/C][/ROW]
[ROW][C]71[/C][C]112.9[/C][C]107.774670324942[/C][C]0.0878406200810959[/C][C]5.12532967505839[/C][C]0.579769434185688[/C][/ROW]
[ROW][C]72[/C][C]102[/C][C]107.182998145959[/C][C]0.080929299987709[/C][C]-5.18299814595898[/C][C]-0.541834657596631[/C][/ROW]
[ROW][C]73[/C][C]106[/C][C]108.082999950545[/C][C]0.0890638668738728[/C][C]-2.08299995054509[/C][C]0.653363831570579[/C][/ROW]
[ROW][C]74[/C][C]105.3[/C][C]108.892783705605[/C][C]0.096099529042043[/C][C]-3.59278370560491[/C][C]0.574983331025758[/C][/ROW]
[ROW][C]75[/C][C]118.8[/C][C]109.236252956376[/C][C]0.0984917682877512[/C][C]9.56374704362398[/C][C]0.197334193980319[/C][/ROW]
[ROW][C]76[/C][C]106.1[/C][C]109.807591688791[/C][C]0.103052877421846[/C][C]-3.70759168879077[/C][C]0.377132033601843[/C][/ROW]
[ROW][C]77[/C][C]109.3[/C][C]108.972746541674[/C][C]0.0939907637044517[/C][C]0.327253458326185[/C][C]-0.747902412160804[/C][/ROW]
[ROW][C]78[/C][C]117.2[/C][C]108.553794248145[/C][C]0.0890219911352814[/C][C]8.64620575185526[/C][C]-0.408996736360124[/C][/ROW]
[ROW][C]79[/C][C]92.5[/C][C]109.494963525861[/C][C]0.097279416064863[/C][C]-16.9949635258609[/C][C]0.679515249683659[/C][/ROW]
[ROW][C]80[/C][C]104.2[/C][C]110.010801913117[/C][C]0.101319218354531[/C][C]-5.81080191311746[/C][C]0.333849764300692[/C][/ROW]
[ROW][C]81[/C][C]112.5[/C][C]108.962124807663[/C][C]0.0903205405309879[/C][C]3.5378751923371[/C][C]-0.917612323072251[/C][/ROW]
[ROW][C]82[/C][C]122.4[/C][C]109.660001921748[/C][C]0.0960517884015915[/C][C]12.7399980782524[/C][C]0.485005688976279[/C][/ROW]
[ROW][C]83[/C][C]113.3[/C][C]109.650511643925[/C][C]0.0950728527480774[/C][C]3.64948835607482[/C][C]-0.0842908545868984[/C][/ROW]
[ROW][C]84[/C][C]100[/C][C]108.888217294143[/C][C]0.0872611125754726[/C][C]-8.88821729414274[/C][C]-0.684995664189131[/C][/ROW]
[ROW][C]85[/C][C]110.7[/C][C]109.710018127783[/C][C]0.0938437929149724[/C][C]0.989981872217309[/C][C]0.587025782419494[/C][/ROW]
[ROW][C]86[/C][C]112.8[/C][C]111.648262460642[/C][C]0.110150253502444[/C][C]1.15173753935811[/C][C]1.47423888983122[/C][/ROW]
[ROW][C]87[/C][C]109.8[/C][C]109.698685786573[/C][C]0.0921156500481193[/C][C]0.10131421342673[/C][C]-1.64645292240216[/C][/ROW]
[ROW][C]88[/C][C]117.3[/C][C]111.470844030213[/C][C]0.106737286436953[/C][C]5.82915596978738[/C][C]1.34294879762472[/C][/ROW]
[ROW][C]89[/C][C]109.1[/C][C]111.545343882623[/C][C]0.106457692833247[/C][C]-2.44534388262266[/C][C]-0.0257687263146201[/C][/ROW]
[ROW][C]90[/C][C]115.9[/C][C]110.738494474843[/C][C]0.0985564180282694[/C][C]5.1615055251569[/C][C]-0.73005761651245[/C][/ROW]
[ROW][C]91[/C][C]96[/C][C]110.977032369369[/C][C]0.0997636310885871[/C][C]-14.9770323693694[/C][C]0.111904473912141[/C][/ROW]
[ROW][C]92[/C][C]99.8[/C][C]109.710545515005[/C][C]0.0880402166762467[/C][C]-9.91054551500455[/C][C]-1.09238868789963[/C][/ROW]
[ROW][C]93[/C][C]116.8[/C][C]110.203282249717[/C][C]0.091486633574169[/C][C]6.59671775028267[/C][C]0.323649442445218[/C][/ROW]
[ROW][C]94[/C][C]115.7[/C][C]108.723423210693[/C][C]0.0782384954601769[/C][C]6.97657678930742[/C][C]-1.25699249627229[/C][/ROW]
[ROW][C]95[/C][C]99.4[/C][C]105.210053304681[/C][C]0.0483135624866218[/C][C]-5.81005330468101[/C][C]-2.87387823368404[/C][/ROW]
[ROW][C]96[/C][C]94.3[/C][C]103.766406806112[/C][C]0.0360382604140943[/C][C]-9.46640680611158[/C][C]-1.19411146143459[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63600&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63600&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
198.898.8000
2100.599.0098361764009-0.03919196494493011.490163823599110.388717178313888
3110.4103.5579386721950.2891175123964456.84206132780532.37894910697432
496.4102.9166161045240.204866863319226-6.51661610452434-0.453472455807471
5101.9102.4670317502710.148646019839951-0.567031750271342-0.389935500093396
6106.2103.3141541063810.1990167386170892.885845893619020.485265288551031
78198.1421630341768-0.107051973677707-17.1421630341768-4.03755497919976
894.795.2415616478735-0.232145392064929-0.541561647873479-2.17500001561392
910195.4144494351909-0.2173514459748065.585550564809140.320074983827219
10109.498.829318846847-0.10246554965938510.57068115315312.88736399319624
11102.3101.082184715780-0.03405458018410861.217815284220441.87555612160628
1290.799.5211029931645-0.0765164808777496-8.82110299316446-1.21573693447957
1396.298.4278335880762-0.0786365050015628-2.22783358807624-0.837114293790518
1496.197.6344558667332-0.0779097749925256-1.53445586673316-0.597327158208534
1510697.2148151878089-0.08170897635672558.78518481219112-0.271968943399785
16103.199.6618169891172-0.01882448958634353.438183010882791.88477326938139
17102100.6986164551630.01668708991826741.301383544836830.764909178644743
18104.7100.138930896851-0.004582686716128254.56106910314886-0.422243923205732
1986100.4261423593640.00592639577782337-14.42614235936440.219563317532909
2092.199.2041441317476-0.0341627032902864-7.10414413174765-0.947080104535874
21106.999.9994108213925-0.01078726888906246.900589178607490.650523709474136
22112.6100.9246747034240.011179872870973711.67532529657560.741231190687254
23101.7100.7420164872390.007513457368282280.957983512761186-0.154306910210952
2492100.4773575374090.00347865014955188-8.4773575374093-0.217427882668088
2597.4100.1993034460080.000152177320648185-2.79930344600771-0.225435315804073
269799.9893586502527-0.00221301989496133-2.98935865025267-0.167732327906410
27105.499.651326768601-0.006680468942725655.74867323139898-0.265059650259245
28102.799.5463226882764-0.008331143758389173.15367731172359-0.0764024285973884
2998.198.7266147144523-0.024716530736683-0.626614714452342-0.6233580183334
30104.598.7024140438546-0.02470494168734365.797585956145440.000395471388422841
3187.499.3706841150724-0.00862983931384387-11.97068411507230.534309673127569
3289.999.283120171661-0.0104047850297574-9.38312017166093-0.0614178309585382
33109.8100.2123339964730.009061797682844339.587666003526980.737438521284237
34111.7100.4108593267850.012545407469318811.28914067321500.149661901763741
3598.699.71589924770790.00123238558733513-1.11589924770786-0.561278537023017
3696.9100.6718935139540.0145715389641173-3.771893513954150.759306942950503
3795.1100.2771283882590.00937848982912856-5.17712838825894-0.325724349963536
389799.94658042597370.00518462919910609-2.94658042597369-0.270001948785785
39112.7101.3972657816720.023796481024138711.30273421832791.14338861161793
40102.9101.4691615657810.02446981324184111.430838434218950.0378481793485489
4197.4100.7839887910140.0136337196838558-3.38398879101382-0.556052023203621
42111.4101.8568060091540.03087580789336299.543193990845790.828606522996382
4387.4101.7697560446860.0288996685262079-14.3697560446857-0.0923682580025581
4496.8102.9506345834580.048045614227143-6.150634583457590.90515765807726
45114.1103.7625024627430.060223362990124610.33749753725740.602428981689017
46110.3102.9126041122120.04664775840926897.3873958877875-0.720272168885567
47103.9103.2469602820920.05061242712228860.653039717908380.228286603326934
48101.6103.8729532006170.0579596860053997-2.27295320061670.457284546526323
4994.6103.26984397760.0499844650346042-8.66984397760002-0.525669500923169
5095.9102.2873566038820.0378471829486033-6.38735660388211-0.820531912534926
51104.799.87837340793140.00890068473133824.82162659206855-1.94164489347105
52102.899.40901512170270.003075004834395613.39098487829731-0.378787462775978
5398.1100.0381013794860.0109906154563009-1.93810137948650.494996185223788
54113.9101.4541739495320.029328130090376512.44582605046761.11014924342745
5580.9100.7730683169390.0199016027302481-19.8730683169387-0.561470987021063
5695.7100.8171713531480.0202218476453798-5.117171353148110.0191492475154115
57113.2101.1739509955730.024579715518218712.02604900442720.266736234786609
58105.9100.6833208826830.01814888371954395.2166791173168-0.409016963290624
59108.8102.1219322817810.03510141187175046.678067718219071.12930723947157
60102.3102.8292891903370.0427747121393249-0.5292891903367520.534999421844736
6199103.7561831930880.0525091831587319-4.756183193088420.703946053253157
62100.7104.4660510323590.059591557389357-3.766051032358910.523373688636769
63115.5106.2464934753620.07802238167366289.25350652463781.369460830772
64100.7105.0498826921100.0642789463183618-4.3498826921101-1.01367015760388
65109.9106.3887118895830.07820309143017323.511288110416561.01297767969026
66114.6105.8280333521110.07113444051419598.77196664788895-0.507603384435839
6785.4105.589356044990.0676839168247103-20.1893560449899-0.246175581026117
68100.5105.6837690247530.0679807938960927-5.183769024752640.0212493259229752
69114.8105.2440763404350.06241408694737959.55592365956484-0.403900964636287
70116.5106.9669011159960.080235972686569.533098884004031.32213392324065
71112.9107.7746703249420.08784062008109595.125329675058390.579769434185688
72102107.1829981459590.080929299987709-5.18299814595898-0.541834657596631
73106108.0829999505450.0890638668738728-2.082999950545090.653363831570579
74105.3108.8927837056050.096099529042043-3.592783705604910.574983331025758
75118.8109.2362529563760.09849176828775129.563747043623980.197334193980319
76106.1109.8075916887910.103052877421846-3.707591688790770.377132033601843
77109.3108.9727465416740.09399076370445170.327253458326185-0.747902412160804
78117.2108.5537942481450.08902199113528148.64620575185526-0.408996736360124
7992.5109.4949635258610.097279416064863-16.99496352586090.679515249683659
80104.2110.0108019131170.101319218354531-5.810801913117460.333849764300692
81112.5108.9621248076630.09032054053098793.5378751923371-0.917612323072251
82122.4109.6600019217480.096051788401591512.73999807825240.485005688976279
83113.3109.6505116439250.09507285274807743.64948835607482-0.0842908545868984
84100108.8882172941430.0872611125754726-8.88821729414274-0.684995664189131
85110.7109.7100181277830.09384379291497240.9899818722173090.587025782419494
86112.8111.6482624606420.1101502535024441.151737539358111.47423888983122
87109.8109.6986857865730.09211565004811930.10131421342673-1.64645292240216
88117.3111.4708440302130.1067372864369535.829155969787381.34294879762472
89109.1111.5453438826230.106457692833247-2.44534388262266-0.0257687263146201
90115.9110.7384944748430.09855641802826945.1615055251569-0.73005761651245
9196110.9770323693690.0997636310885871-14.97703236936940.111904473912141
9299.8109.7105455150050.0880402166762467-9.91054551500455-1.09238868789963
93116.8110.2032822497170.0914866335741696.596717750282670.323649442445218
94115.7108.7234232106930.07823849546017696.97657678930742-1.25699249627229
9599.4105.2100533046810.0483135624866218-5.81005330468101-2.87387823368404
9694.3103.7664068061120.0360382604140943-9.46640680611158-1.19411146143459



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')