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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 computationTue, 21 Dec 2010 20:38:33 +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/21/t12929637857xh9x9qyvoeikax.htm/, Retrieved Sun, 19 May 2024 19:48:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113958, Retrieved Sun, 19 May 2024 19:48:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [Arima backwards s...] [2010-12-21 15:15:51] [ca50229b6b451ac8f5a30a9e3154d674]
- RMP     [Structural Time Series Models] [structural Time s...] [2010-12-21 20:38:33] [65e95fe5923d75db266bc83cb8a34c47] [Current]
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Dataseries X:
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745
19394
20148
20108
18584
18441
18391
19178
18079
18483
19644
19195
19650
20830
23595
22937
21814
21928
21777
21383
21467
22052
22680
24320
24977
25204




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=113958&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=113958&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113958&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
11057010570000
21029710311.4309338616-14.3300168867088-14.4309338616498-0.227169279244938
31063510645.4340167542-11.5503640960789-10.43401675416000.50969214536157
41087210882.9297069481-9.2485891206808-10.92970694810050.364039375874384
51029610313.5339426804-15.4524785552112-17.5339426803725-0.818027307141764
61038310394.8579236197-14.2153091466331-11.85792361973530.141200919554811
71043110444.0648802964-13.2992334631293-13.06488029639410.0924525028809954
81057410585.9057150308-10.8085959503998-11.90571503077830.225953065707245
91065310665.1256981962-9.22316568886463-12.12569819616620.131009033519912
101080510816.0338840354-6.163100360503-11.03388403539380.232827326833022
111087210883.4040078868-4.65198392042856-11.40400788680240.106828923057185
121062510638.8389634111-9.91323577423113-13.8389634111157-0.348271837000529
131040710383.9444843815-5.9631434738333323.0555156185204-0.426990202390501
141046310464.5467515216-2.36986939545989-1.546751521565810.106999428836634
151055610554.9953835900-0.072048875259331.004616410022210.134326064001681
161064610640.94815935652.110630895898685.051840643549020.124391474525599
171070210705.36639344123.76786453069574-3.366393441248390.0900414212268233
181135311343.397307376221.32496664450429.602692623799250.916030841199593
191134611347.814253130320.8397106088232-1.81425313026019-0.024405364334406
201145111448.192004034923.19880877491072.807995965145950.114744600080064
211196411957.533491019538.05687071781046.466508980492860.700968772022597
221257412566.953509453056.0043546394657.046490546962380.823450370086635
231303113024.375531909368.94260342355426.624468090656760.578282842290358
241381213802.364482884592.21532030840259.635517115495191.02080642946155
251454414461.0568846203104.00092394796982.9431153797040.893221118276242
261493114933.0239420776119.560091975791-2.023942077648740.48365443433101
271488614892.2272791964113.930974313189-6.22727919639597-0.230615695272288
281600515983.7698087912148.32056130291621.23019120875671.40503050421761
291706417065.8742390782181.728681083697-1.874239078173801.34170138404619
301516815199.0330663883107.400774340224-31.0330663883255-2.94264870076677
311605016031.8443997713134.05640944167018.15560022867141.04172979031148
321583915851.3175930065122.361800688473-12.3175930064887-0.451646175900321
331513715151.317298884291.4634489481066-14.3172988841658-1.18038819083854
341495414954.324214010380.51865767997-0.324214010258316-0.413951768417101
351564815641.1614438442103.7474232613706.838556155805070.869986214746308
361530515316.565274558987.281418367961-11.5652745589256-0.614268355669947
371557915532.78059147391.611017081251246.21940852699580.196265736264609
381634816328.1311469939121.77757098242519.86885300606360.949776244589926
391592815954.4988768729102.123000806226-26.4988768729438-0.710424099532503
401617116164.8033425708106.4002090239956.196657429203840.155042051538028
411593715906.829101336491.902039174062630.1708986636254-0.522184443462542
421571315755.077747261182.1573459744097-42.0777472610955-0.349143939918781
431559415574.184351191271.589049121550119.8156488087597-0.376898463657610
441568315676.392492504872.82432430523536.607507495237350.0438665386065906
451643816425.9249525618100.22926099031212.07504743822330.969397465199311
461703217032.4770064146120.807157673750-0.4770064146292170.725261131089244
471769617668.3593634435141.81891065486527.64063655646530.73780275508995
481774517757.4228852631139.668970186307-12.4228852630807-0.0755240816961078
491939419274.8688851192192.860438113673119.1311148807802.06047619153955
502014820115.825097015220.62397475477532.17490298499730.887884438663069
512010820157.2353552000213.205110021669-49.235355199975-0.256678521933197
521858418621.1449944282141.066501733468-37.1449944282249-2.50403529013489
531844118410.7790711907126.53932693743830.2209288093089-0.50307585419112
541839118433.8517844117122.254054256802-42.8517844117177-0.148110090241096
551917819146.8309120854146.75996799034431.16908791461020.845574925628327
561807918122.957079999798.1246066901327-43.957079999665-1.67560153872566
571848318471.6869124512108.55052330993011.31308754879230.35869412614005
581964419637.9152741721152.6111757020816.084725827854041.51384177085314
591919519188.5675517928127.4981383370566.43244820716244-0.861627992384058
601965019679.5089195119142.632334524159-29.50891951193310.519914012929075
612083020692.3644997046178.003795999333137.6355002954411.28769784418317
622359523511.8785745799290.65079585343583.12142542009163.65402350043202
632293722978.6376106425256.055656643196-41.6376106425308-1.17932711058717
642181421866.0010399569198.750238369558-52.0010399568686-1.95822450308203
652192821876.5489588988190.86365568668651.4510411011698-0.269277849997684
662177721835.8791519986181.153951520203-58.8791519985783-0.331283718039010
672138321328.7075398016152.27095946454554.2924601983522-0.984860485440262
682146721495.0157323517152.860291318174-28.01573235165050.0200842474512446
692205222048.9095535015169.7053294772113.090446498504170.573784967583753
702268022638.2738545643187.34170894831441.72614543574850.600441647326592
712432024266.3283297039247.92310241715753.6716702961342.06149034020675
722497725011.1175690590268.781202872275-34.11756905896370.710549527544314
732520425292.4391434107269.301659881545-88.43914341069360.0184252213719177

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 10570 & 10570 & 0 & 0 & 0 \tabularnewline
2 & 10297 & 10311.4309338616 & -14.3300168867088 & -14.4309338616498 & -0.227169279244938 \tabularnewline
3 & 10635 & 10645.4340167542 & -11.5503640960789 & -10.4340167541600 & 0.50969214536157 \tabularnewline
4 & 10872 & 10882.9297069481 & -9.2485891206808 & -10.9297069481005 & 0.364039375874384 \tabularnewline
5 & 10296 & 10313.5339426804 & -15.4524785552112 & -17.5339426803725 & -0.818027307141764 \tabularnewline
6 & 10383 & 10394.8579236197 & -14.2153091466331 & -11.8579236197353 & 0.141200919554811 \tabularnewline
7 & 10431 & 10444.0648802964 & -13.2992334631293 & -13.0648802963941 & 0.0924525028809954 \tabularnewline
8 & 10574 & 10585.9057150308 & -10.8085959503998 & -11.9057150307783 & 0.225953065707245 \tabularnewline
9 & 10653 & 10665.1256981962 & -9.22316568886463 & -12.1256981961662 & 0.131009033519912 \tabularnewline
10 & 10805 & 10816.0338840354 & -6.163100360503 & -11.0338840353938 & 0.232827326833022 \tabularnewline
11 & 10872 & 10883.4040078868 & -4.65198392042856 & -11.4040078868024 & 0.106828923057185 \tabularnewline
12 & 10625 & 10638.8389634111 & -9.91323577423113 & -13.8389634111157 & -0.348271837000529 \tabularnewline
13 & 10407 & 10383.9444843815 & -5.96314347383333 & 23.0555156185204 & -0.426990202390501 \tabularnewline
14 & 10463 & 10464.5467515216 & -2.36986939545989 & -1.54675152156581 & 0.106999428836634 \tabularnewline
15 & 10556 & 10554.9953835900 & -0.07204887525933 & 1.00461641002221 & 0.134326064001681 \tabularnewline
16 & 10646 & 10640.9481593565 & 2.11063089589868 & 5.05184064354902 & 0.124391474525599 \tabularnewline
17 & 10702 & 10705.3663934412 & 3.76786453069574 & -3.36639344124839 & 0.0900414212268233 \tabularnewline
18 & 11353 & 11343.3973073762 & 21.3249666445042 & 9.60269262379925 & 0.916030841199593 \tabularnewline
19 & 11346 & 11347.8142531303 & 20.8397106088232 & -1.81425313026019 & -0.024405364334406 \tabularnewline
20 & 11451 & 11448.1920040349 & 23.1988087749107 & 2.80799596514595 & 0.114744600080064 \tabularnewline
21 & 11964 & 11957.5334910195 & 38.0568707178104 & 6.46650898049286 & 0.700968772022597 \tabularnewline
22 & 12574 & 12566.9535094530 & 56.004354639465 & 7.04649054696238 & 0.823450370086635 \tabularnewline
23 & 13031 & 13024.3755319093 & 68.9426034235542 & 6.62446809065676 & 0.578282842290358 \tabularnewline
24 & 13812 & 13802.3644828845 & 92.2153203084025 & 9.63551711549519 & 1.02080642946155 \tabularnewline
25 & 14544 & 14461.0568846203 & 104.000923947969 & 82.943115379704 & 0.893221118276242 \tabularnewline
26 & 14931 & 14933.0239420776 & 119.560091975791 & -2.02394207764874 & 0.48365443433101 \tabularnewline
27 & 14886 & 14892.2272791964 & 113.930974313189 & -6.22727919639597 & -0.230615695272288 \tabularnewline
28 & 16005 & 15983.7698087912 & 148.320561302916 & 21.2301912087567 & 1.40503050421761 \tabularnewline
29 & 17064 & 17065.8742390782 & 181.728681083697 & -1.87423907817380 & 1.34170138404619 \tabularnewline
30 & 15168 & 15199.0330663883 & 107.400774340224 & -31.0330663883255 & -2.94264870076677 \tabularnewline
31 & 16050 & 16031.8443997713 & 134.056409441670 & 18.1556002286714 & 1.04172979031148 \tabularnewline
32 & 15839 & 15851.3175930065 & 122.361800688473 & -12.3175930064887 & -0.451646175900321 \tabularnewline
33 & 15137 & 15151.3172988842 & 91.4634489481066 & -14.3172988841658 & -1.18038819083854 \tabularnewline
34 & 14954 & 14954.3242140103 & 80.51865767997 & -0.324214010258316 & -0.413951768417101 \tabularnewline
35 & 15648 & 15641.1614438442 & 103.747423261370 & 6.83855615580507 & 0.869986214746308 \tabularnewline
36 & 15305 & 15316.5652745589 & 87.281418367961 & -11.5652745589256 & -0.614268355669947 \tabularnewline
37 & 15579 & 15532.780591473 & 91.6110170812512 & 46.2194085269958 & 0.196265736264609 \tabularnewline
38 & 16348 & 16328.1311469939 & 121.777570982425 & 19.8688530060636 & 0.949776244589926 \tabularnewline
39 & 15928 & 15954.4988768729 & 102.123000806226 & -26.4988768729438 & -0.710424099532503 \tabularnewline
40 & 16171 & 16164.8033425708 & 106.400209023995 & 6.19665742920384 & 0.155042051538028 \tabularnewline
41 & 15937 & 15906.8291013364 & 91.9020391740626 & 30.1708986636254 & -0.522184443462542 \tabularnewline
42 & 15713 & 15755.0777472611 & 82.1573459744097 & -42.0777472610955 & -0.349143939918781 \tabularnewline
43 & 15594 & 15574.1843511912 & 71.5890491215501 & 19.8156488087597 & -0.376898463657610 \tabularnewline
44 & 15683 & 15676.3924925048 & 72.8243243052353 & 6.60750749523735 & 0.0438665386065906 \tabularnewline
45 & 16438 & 16425.9249525618 & 100.229260990312 & 12.0750474382233 & 0.969397465199311 \tabularnewline
46 & 17032 & 17032.4770064146 & 120.807157673750 & -0.477006414629217 & 0.725261131089244 \tabularnewline
47 & 17696 & 17668.3593634435 & 141.818910654865 & 27.6406365564653 & 0.73780275508995 \tabularnewline
48 & 17745 & 17757.4228852631 & 139.668970186307 & -12.4228852630807 & -0.0755240816961078 \tabularnewline
49 & 19394 & 19274.8688851192 & 192.860438113673 & 119.131114880780 & 2.06047619153955 \tabularnewline
50 & 20148 & 20115.825097015 & 220.623974754775 & 32.1749029849973 & 0.887884438663069 \tabularnewline
51 & 20108 & 20157.2353552000 & 213.205110021669 & -49.235355199975 & -0.256678521933197 \tabularnewline
52 & 18584 & 18621.1449944282 & 141.066501733468 & -37.1449944282249 & -2.50403529013489 \tabularnewline
53 & 18441 & 18410.7790711907 & 126.539326937438 & 30.2209288093089 & -0.50307585419112 \tabularnewline
54 & 18391 & 18433.8517844117 & 122.254054256802 & -42.8517844117177 & -0.148110090241096 \tabularnewline
55 & 19178 & 19146.8309120854 & 146.759967990344 & 31.1690879146102 & 0.845574925628327 \tabularnewline
56 & 18079 & 18122.9570799997 & 98.1246066901327 & -43.957079999665 & -1.67560153872566 \tabularnewline
57 & 18483 & 18471.6869124512 & 108.550523309930 & 11.3130875487923 & 0.35869412614005 \tabularnewline
58 & 19644 & 19637.9152741721 & 152.611175702081 & 6.08472582785404 & 1.51384177085314 \tabularnewline
59 & 19195 & 19188.5675517928 & 127.498138337056 & 6.43244820716244 & -0.861627992384058 \tabularnewline
60 & 19650 & 19679.5089195119 & 142.632334524159 & -29.5089195119331 & 0.519914012929075 \tabularnewline
61 & 20830 & 20692.3644997046 & 178.003795999333 & 137.635500295441 & 1.28769784418317 \tabularnewline
62 & 23595 & 23511.8785745799 & 290.650795853435 & 83.1214254200916 & 3.65402350043202 \tabularnewline
63 & 22937 & 22978.6376106425 & 256.055656643196 & -41.6376106425308 & -1.17932711058717 \tabularnewline
64 & 21814 & 21866.0010399569 & 198.750238369558 & -52.0010399568686 & -1.95822450308203 \tabularnewline
65 & 21928 & 21876.5489588988 & 190.863655686686 & 51.4510411011698 & -0.269277849997684 \tabularnewline
66 & 21777 & 21835.8791519986 & 181.153951520203 & -58.8791519985783 & -0.331283718039010 \tabularnewline
67 & 21383 & 21328.7075398016 & 152.270959464545 & 54.2924601983522 & -0.984860485440262 \tabularnewline
68 & 21467 & 21495.0157323517 & 152.860291318174 & -28.0157323516505 & 0.0200842474512446 \tabularnewline
69 & 22052 & 22048.9095535015 & 169.705329477211 & 3.09044649850417 & 0.573784967583753 \tabularnewline
70 & 22680 & 22638.2738545643 & 187.341708948314 & 41.7261454357485 & 0.600441647326592 \tabularnewline
71 & 24320 & 24266.3283297039 & 247.923102417157 & 53.671670296134 & 2.06149034020675 \tabularnewline
72 & 24977 & 25011.1175690590 & 268.781202872275 & -34.1175690589637 & 0.710549527544314 \tabularnewline
73 & 25204 & 25292.4391434107 & 269.301659881545 & -88.4391434106936 & 0.0184252213719177 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113958&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]10570[/C][C]10570[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]10297[/C][C]10311.4309338616[/C][C]-14.3300168867088[/C][C]-14.4309338616498[/C][C]-0.227169279244938[/C][/ROW]
[ROW][C]3[/C][C]10635[/C][C]10645.4340167542[/C][C]-11.5503640960789[/C][C]-10.4340167541600[/C][C]0.50969214536157[/C][/ROW]
[ROW][C]4[/C][C]10872[/C][C]10882.9297069481[/C][C]-9.2485891206808[/C][C]-10.9297069481005[/C][C]0.364039375874384[/C][/ROW]
[ROW][C]5[/C][C]10296[/C][C]10313.5339426804[/C][C]-15.4524785552112[/C][C]-17.5339426803725[/C][C]-0.818027307141764[/C][/ROW]
[ROW][C]6[/C][C]10383[/C][C]10394.8579236197[/C][C]-14.2153091466331[/C][C]-11.8579236197353[/C][C]0.141200919554811[/C][/ROW]
[ROW][C]7[/C][C]10431[/C][C]10444.0648802964[/C][C]-13.2992334631293[/C][C]-13.0648802963941[/C][C]0.0924525028809954[/C][/ROW]
[ROW][C]8[/C][C]10574[/C][C]10585.9057150308[/C][C]-10.8085959503998[/C][C]-11.9057150307783[/C][C]0.225953065707245[/C][/ROW]
[ROW][C]9[/C][C]10653[/C][C]10665.1256981962[/C][C]-9.22316568886463[/C][C]-12.1256981961662[/C][C]0.131009033519912[/C][/ROW]
[ROW][C]10[/C][C]10805[/C][C]10816.0338840354[/C][C]-6.163100360503[/C][C]-11.0338840353938[/C][C]0.232827326833022[/C][/ROW]
[ROW][C]11[/C][C]10872[/C][C]10883.4040078868[/C][C]-4.65198392042856[/C][C]-11.4040078868024[/C][C]0.106828923057185[/C][/ROW]
[ROW][C]12[/C][C]10625[/C][C]10638.8389634111[/C][C]-9.91323577423113[/C][C]-13.8389634111157[/C][C]-0.348271837000529[/C][/ROW]
[ROW][C]13[/C][C]10407[/C][C]10383.9444843815[/C][C]-5.96314347383333[/C][C]23.0555156185204[/C][C]-0.426990202390501[/C][/ROW]
[ROW][C]14[/C][C]10463[/C][C]10464.5467515216[/C][C]-2.36986939545989[/C][C]-1.54675152156581[/C][C]0.106999428836634[/C][/ROW]
[ROW][C]15[/C][C]10556[/C][C]10554.9953835900[/C][C]-0.07204887525933[/C][C]1.00461641002221[/C][C]0.134326064001681[/C][/ROW]
[ROW][C]16[/C][C]10646[/C][C]10640.9481593565[/C][C]2.11063089589868[/C][C]5.05184064354902[/C][C]0.124391474525599[/C][/ROW]
[ROW][C]17[/C][C]10702[/C][C]10705.3663934412[/C][C]3.76786453069574[/C][C]-3.36639344124839[/C][C]0.0900414212268233[/C][/ROW]
[ROW][C]18[/C][C]11353[/C][C]11343.3973073762[/C][C]21.3249666445042[/C][C]9.60269262379925[/C][C]0.916030841199593[/C][/ROW]
[ROW][C]19[/C][C]11346[/C][C]11347.8142531303[/C][C]20.8397106088232[/C][C]-1.81425313026019[/C][C]-0.024405364334406[/C][/ROW]
[ROW][C]20[/C][C]11451[/C][C]11448.1920040349[/C][C]23.1988087749107[/C][C]2.80799596514595[/C][C]0.114744600080064[/C][/ROW]
[ROW][C]21[/C][C]11964[/C][C]11957.5334910195[/C][C]38.0568707178104[/C][C]6.46650898049286[/C][C]0.700968772022597[/C][/ROW]
[ROW][C]22[/C][C]12574[/C][C]12566.9535094530[/C][C]56.004354639465[/C][C]7.04649054696238[/C][C]0.823450370086635[/C][/ROW]
[ROW][C]23[/C][C]13031[/C][C]13024.3755319093[/C][C]68.9426034235542[/C][C]6.62446809065676[/C][C]0.578282842290358[/C][/ROW]
[ROW][C]24[/C][C]13812[/C][C]13802.3644828845[/C][C]92.2153203084025[/C][C]9.63551711549519[/C][C]1.02080642946155[/C][/ROW]
[ROW][C]25[/C][C]14544[/C][C]14461.0568846203[/C][C]104.000923947969[/C][C]82.943115379704[/C][C]0.893221118276242[/C][/ROW]
[ROW][C]26[/C][C]14931[/C][C]14933.0239420776[/C][C]119.560091975791[/C][C]-2.02394207764874[/C][C]0.48365443433101[/C][/ROW]
[ROW][C]27[/C][C]14886[/C][C]14892.2272791964[/C][C]113.930974313189[/C][C]-6.22727919639597[/C][C]-0.230615695272288[/C][/ROW]
[ROW][C]28[/C][C]16005[/C][C]15983.7698087912[/C][C]148.320561302916[/C][C]21.2301912087567[/C][C]1.40503050421761[/C][/ROW]
[ROW][C]29[/C][C]17064[/C][C]17065.8742390782[/C][C]181.728681083697[/C][C]-1.87423907817380[/C][C]1.34170138404619[/C][/ROW]
[ROW][C]30[/C][C]15168[/C][C]15199.0330663883[/C][C]107.400774340224[/C][C]-31.0330663883255[/C][C]-2.94264870076677[/C][/ROW]
[ROW][C]31[/C][C]16050[/C][C]16031.8443997713[/C][C]134.056409441670[/C][C]18.1556002286714[/C][C]1.04172979031148[/C][/ROW]
[ROW][C]32[/C][C]15839[/C][C]15851.3175930065[/C][C]122.361800688473[/C][C]-12.3175930064887[/C][C]-0.451646175900321[/C][/ROW]
[ROW][C]33[/C][C]15137[/C][C]15151.3172988842[/C][C]91.4634489481066[/C][C]-14.3172988841658[/C][C]-1.18038819083854[/C][/ROW]
[ROW][C]34[/C][C]14954[/C][C]14954.3242140103[/C][C]80.51865767997[/C][C]-0.324214010258316[/C][C]-0.413951768417101[/C][/ROW]
[ROW][C]35[/C][C]15648[/C][C]15641.1614438442[/C][C]103.747423261370[/C][C]6.83855615580507[/C][C]0.869986214746308[/C][/ROW]
[ROW][C]36[/C][C]15305[/C][C]15316.5652745589[/C][C]87.281418367961[/C][C]-11.5652745589256[/C][C]-0.614268355669947[/C][/ROW]
[ROW][C]37[/C][C]15579[/C][C]15532.780591473[/C][C]91.6110170812512[/C][C]46.2194085269958[/C][C]0.196265736264609[/C][/ROW]
[ROW][C]38[/C][C]16348[/C][C]16328.1311469939[/C][C]121.777570982425[/C][C]19.8688530060636[/C][C]0.949776244589926[/C][/ROW]
[ROW][C]39[/C][C]15928[/C][C]15954.4988768729[/C][C]102.123000806226[/C][C]-26.4988768729438[/C][C]-0.710424099532503[/C][/ROW]
[ROW][C]40[/C][C]16171[/C][C]16164.8033425708[/C][C]106.400209023995[/C][C]6.19665742920384[/C][C]0.155042051538028[/C][/ROW]
[ROW][C]41[/C][C]15937[/C][C]15906.8291013364[/C][C]91.9020391740626[/C][C]30.1708986636254[/C][C]-0.522184443462542[/C][/ROW]
[ROW][C]42[/C][C]15713[/C][C]15755.0777472611[/C][C]82.1573459744097[/C][C]-42.0777472610955[/C][C]-0.349143939918781[/C][/ROW]
[ROW][C]43[/C][C]15594[/C][C]15574.1843511912[/C][C]71.5890491215501[/C][C]19.8156488087597[/C][C]-0.376898463657610[/C][/ROW]
[ROW][C]44[/C][C]15683[/C][C]15676.3924925048[/C][C]72.8243243052353[/C][C]6.60750749523735[/C][C]0.0438665386065906[/C][/ROW]
[ROW][C]45[/C][C]16438[/C][C]16425.9249525618[/C][C]100.229260990312[/C][C]12.0750474382233[/C][C]0.969397465199311[/C][/ROW]
[ROW][C]46[/C][C]17032[/C][C]17032.4770064146[/C][C]120.807157673750[/C][C]-0.477006414629217[/C][C]0.725261131089244[/C][/ROW]
[ROW][C]47[/C][C]17696[/C][C]17668.3593634435[/C][C]141.818910654865[/C][C]27.6406365564653[/C][C]0.73780275508995[/C][/ROW]
[ROW][C]48[/C][C]17745[/C][C]17757.4228852631[/C][C]139.668970186307[/C][C]-12.4228852630807[/C][C]-0.0755240816961078[/C][/ROW]
[ROW][C]49[/C][C]19394[/C][C]19274.8688851192[/C][C]192.860438113673[/C][C]119.131114880780[/C][C]2.06047619153955[/C][/ROW]
[ROW][C]50[/C][C]20148[/C][C]20115.825097015[/C][C]220.623974754775[/C][C]32.1749029849973[/C][C]0.887884438663069[/C][/ROW]
[ROW][C]51[/C][C]20108[/C][C]20157.2353552000[/C][C]213.205110021669[/C][C]-49.235355199975[/C][C]-0.256678521933197[/C][/ROW]
[ROW][C]52[/C][C]18584[/C][C]18621.1449944282[/C][C]141.066501733468[/C][C]-37.1449944282249[/C][C]-2.50403529013489[/C][/ROW]
[ROW][C]53[/C][C]18441[/C][C]18410.7790711907[/C][C]126.539326937438[/C][C]30.2209288093089[/C][C]-0.50307585419112[/C][/ROW]
[ROW][C]54[/C][C]18391[/C][C]18433.8517844117[/C][C]122.254054256802[/C][C]-42.8517844117177[/C][C]-0.148110090241096[/C][/ROW]
[ROW][C]55[/C][C]19178[/C][C]19146.8309120854[/C][C]146.759967990344[/C][C]31.1690879146102[/C][C]0.845574925628327[/C][/ROW]
[ROW][C]56[/C][C]18079[/C][C]18122.9570799997[/C][C]98.1246066901327[/C][C]-43.957079999665[/C][C]-1.67560153872566[/C][/ROW]
[ROW][C]57[/C][C]18483[/C][C]18471.6869124512[/C][C]108.550523309930[/C][C]11.3130875487923[/C][C]0.35869412614005[/C][/ROW]
[ROW][C]58[/C][C]19644[/C][C]19637.9152741721[/C][C]152.611175702081[/C][C]6.08472582785404[/C][C]1.51384177085314[/C][/ROW]
[ROW][C]59[/C][C]19195[/C][C]19188.5675517928[/C][C]127.498138337056[/C][C]6.43244820716244[/C][C]-0.861627992384058[/C][/ROW]
[ROW][C]60[/C][C]19650[/C][C]19679.5089195119[/C][C]142.632334524159[/C][C]-29.5089195119331[/C][C]0.519914012929075[/C][/ROW]
[ROW][C]61[/C][C]20830[/C][C]20692.3644997046[/C][C]178.003795999333[/C][C]137.635500295441[/C][C]1.28769784418317[/C][/ROW]
[ROW][C]62[/C][C]23595[/C][C]23511.8785745799[/C][C]290.650795853435[/C][C]83.1214254200916[/C][C]3.65402350043202[/C][/ROW]
[ROW][C]63[/C][C]22937[/C][C]22978.6376106425[/C][C]256.055656643196[/C][C]-41.6376106425308[/C][C]-1.17932711058717[/C][/ROW]
[ROW][C]64[/C][C]21814[/C][C]21866.0010399569[/C][C]198.750238369558[/C][C]-52.0010399568686[/C][C]-1.95822450308203[/C][/ROW]
[ROW][C]65[/C][C]21928[/C][C]21876.5489588988[/C][C]190.863655686686[/C][C]51.4510411011698[/C][C]-0.269277849997684[/C][/ROW]
[ROW][C]66[/C][C]21777[/C][C]21835.8791519986[/C][C]181.153951520203[/C][C]-58.8791519985783[/C][C]-0.331283718039010[/C][/ROW]
[ROW][C]67[/C][C]21383[/C][C]21328.7075398016[/C][C]152.270959464545[/C][C]54.2924601983522[/C][C]-0.984860485440262[/C][/ROW]
[ROW][C]68[/C][C]21467[/C][C]21495.0157323517[/C][C]152.860291318174[/C][C]-28.0157323516505[/C][C]0.0200842474512446[/C][/ROW]
[ROW][C]69[/C][C]22052[/C][C]22048.9095535015[/C][C]169.705329477211[/C][C]3.09044649850417[/C][C]0.573784967583753[/C][/ROW]
[ROW][C]70[/C][C]22680[/C][C]22638.2738545643[/C][C]187.341708948314[/C][C]41.7261454357485[/C][C]0.600441647326592[/C][/ROW]
[ROW][C]71[/C][C]24320[/C][C]24266.3283297039[/C][C]247.923102417157[/C][C]53.671670296134[/C][C]2.06149034020675[/C][/ROW]
[ROW][C]72[/C][C]24977[/C][C]25011.1175690590[/C][C]268.781202872275[/C][C]-34.1175690589637[/C][C]0.710549527544314[/C][/ROW]
[ROW][C]73[/C][C]25204[/C][C]25292.4391434107[/C][C]269.301659881545[/C][C]-88.4391434106936[/C][C]0.0184252213719177[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113958&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113958&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
11057010570000
21029710311.4309338616-14.3300168867088-14.4309338616498-0.227169279244938
31063510645.4340167542-11.5503640960789-10.43401675416000.50969214536157
41087210882.9297069481-9.2485891206808-10.92970694810050.364039375874384
51029610313.5339426804-15.4524785552112-17.5339426803725-0.818027307141764
61038310394.8579236197-14.2153091466331-11.85792361973530.141200919554811
71043110444.0648802964-13.2992334631293-13.06488029639410.0924525028809954
81057410585.9057150308-10.8085959503998-11.90571503077830.225953065707245
91065310665.1256981962-9.22316568886463-12.12569819616620.131009033519912
101080510816.0338840354-6.163100360503-11.03388403539380.232827326833022
111087210883.4040078868-4.65198392042856-11.40400788680240.106828923057185
121062510638.8389634111-9.91323577423113-13.8389634111157-0.348271837000529
131040710383.9444843815-5.9631434738333323.0555156185204-0.426990202390501
141046310464.5467515216-2.36986939545989-1.546751521565810.106999428836634
151055610554.9953835900-0.072048875259331.004616410022210.134326064001681
161064610640.94815935652.110630895898685.051840643549020.124391474525599
171070210705.36639344123.76786453069574-3.366393441248390.0900414212268233
181135311343.397307376221.32496664450429.602692623799250.916030841199593
191134611347.814253130320.8397106088232-1.81425313026019-0.024405364334406
201145111448.192004034923.19880877491072.807995965145950.114744600080064
211196411957.533491019538.05687071781046.466508980492860.700968772022597
221257412566.953509453056.0043546394657.046490546962380.823450370086635
231303113024.375531909368.94260342355426.624468090656760.578282842290358
241381213802.364482884592.21532030840259.635517115495191.02080642946155
251454414461.0568846203104.00092394796982.9431153797040.893221118276242
261493114933.0239420776119.560091975791-2.023942077648740.48365443433101
271488614892.2272791964113.930974313189-6.22727919639597-0.230615695272288
281600515983.7698087912148.32056130291621.23019120875671.40503050421761
291706417065.8742390782181.728681083697-1.874239078173801.34170138404619
301516815199.0330663883107.400774340224-31.0330663883255-2.94264870076677
311605016031.8443997713134.05640944167018.15560022867141.04172979031148
321583915851.3175930065122.361800688473-12.3175930064887-0.451646175900321
331513715151.317298884291.4634489481066-14.3172988841658-1.18038819083854
341495414954.324214010380.51865767997-0.324214010258316-0.413951768417101
351564815641.1614438442103.7474232613706.838556155805070.869986214746308
361530515316.565274558987.281418367961-11.5652745589256-0.614268355669947
371557915532.78059147391.611017081251246.21940852699580.196265736264609
381634816328.1311469939121.77757098242519.86885300606360.949776244589926
391592815954.4988768729102.123000806226-26.4988768729438-0.710424099532503
401617116164.8033425708106.4002090239956.196657429203840.155042051538028
411593715906.829101336491.902039174062630.1708986636254-0.522184443462542
421571315755.077747261182.1573459744097-42.0777472610955-0.349143939918781
431559415574.184351191271.589049121550119.8156488087597-0.376898463657610
441568315676.392492504872.82432430523536.607507495237350.0438665386065906
451643816425.9249525618100.22926099031212.07504743822330.969397465199311
461703217032.4770064146120.807157673750-0.4770064146292170.725261131089244
471769617668.3593634435141.81891065486527.64063655646530.73780275508995
481774517757.4228852631139.668970186307-12.4228852630807-0.0755240816961078
491939419274.8688851192192.860438113673119.1311148807802.06047619153955
502014820115.825097015220.62397475477532.17490298499730.887884438663069
512010820157.2353552000213.205110021669-49.235355199975-0.256678521933197
521858418621.1449944282141.066501733468-37.1449944282249-2.50403529013489
531844118410.7790711907126.53932693743830.2209288093089-0.50307585419112
541839118433.8517844117122.254054256802-42.8517844117177-0.148110090241096
551917819146.8309120854146.75996799034431.16908791461020.845574925628327
561807918122.957079999798.1246066901327-43.957079999665-1.67560153872566
571848318471.6869124512108.55052330993011.31308754879230.35869412614005
581964419637.9152741721152.6111757020816.084725827854041.51384177085314
591919519188.5675517928127.4981383370566.43244820716244-0.861627992384058
601965019679.5089195119142.632334524159-29.50891951193310.519914012929075
612083020692.3644997046178.003795999333137.6355002954411.28769784418317
622359523511.8785745799290.65079585343583.12142542009163.65402350043202
632293722978.6376106425256.055656643196-41.6376106425308-1.17932711058717
642181421866.0010399569198.750238369558-52.0010399568686-1.95822450308203
652192821876.5489588988190.86365568668651.4510411011698-0.269277849997684
662177721835.8791519986181.153951520203-58.8791519985783-0.331283718039010
672138321328.7075398016152.27095946454554.2924601983522-0.984860485440262
682146721495.0157323517152.860291318174-28.01573235165050.0200842474512446
692205222048.9095535015169.7053294772113.090446498504170.573784967583753
702268022638.2738545643187.34170894831441.72614543574850.600441647326592
712432024266.3283297039247.92310241715753.6716702961342.06149034020675
722497725011.1175690590268.781202872275-34.11756905896370.710549527544314
732520425292.4391434107269.301659881545-88.43914341069360.0184252213719177



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')