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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationSun, 06 Dec 2009 12:44:42 -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/06/t1260128724pv1txpb3h20remo.htm/, Retrieved Sun, 05 May 2024 20:57:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64482, Retrieved Sun, 05 May 2024 20:57:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122
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] [WS9] [2009-12-06 19:44:42] [40cfc51151e9382b81a5fb0c269b074d] [Current]
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Dataseries X:
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881
293299




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64482&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]2 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=64482&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64482&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1286602286602000
2283042283653.978487577-193.757637766118-611.978487576924-0.512602058586361
3276687278740.990211037-626.91648573849-2053.99021103726-1.10434425180643
4277915277704.864198171-673.55551718559210.135801828790-0.101330739637021
5277128277273.640546886-640.785948258969-145.6405468858580.0584370187608226
6277103277214.827411661-551.988562908826-111.8274116612560.137775381399521
7275037275811.948393772-692.421269421379-774.948393772297-0.199101667700537
8270150271753.599507441-1275.95775947025-1603.59950744087-0.781314140029168
9267140267985.936032108-1721.42278317639-845.936032107815-0.575202190918298
10264993265328.515582245-1892.03633889931-335.515582244946-0.215266548845033
11287259280406.3589263741239.597535619586852.641073625963.8931729128653
12291186290440.1106591142875.28500374179745.889340885872.01424283726858
13292300291811.3900190012606.24837084285488.609980998629-0.372527026877422
14288186289098.6075505451618.16982635888-912.607550544624-1.16426911072216
15281477285178.999425359602.536601873665-3701.99942535885-1.19092457735949
16282656283206.224384905127.925516326566-550.224384904784-0.580264949079261
17280190281327.864600774-244.314731512342-1137.86460077385-0.452964131984537
18280408280367.008152864-377.43240381578940.9918471356168-0.160971815641822
19276836277424.781175635-853.839424952912-588.781175635382-0.575948862545888
20275216275496.58372056-1053.41932744088-280.583720559806-0.241500869741957
21274352274617.855766088-1020.95701995824-265.8557660879610.0393016841926683
22271311276030.215661518-568.683553263882-4719.215661518040.547625224235703
23289802282771.491607707788.9660761370447030.50839229351.64319917819594
24290726288213.5321325541650.382561782302512.467867446361.04636923700167
25292300289952.3119807751666.718039856192347.688019224490.0203784280270694
26278506281999.064691389-117.659049246313-3493.06469138926-2.15340139308426
27269826274836.563223571-1413.65069880534-5010.5632235706-1.54252059215159
28265861267760.870634804-2454.48893417320-1899.87063480361-1.26333867744152
29269034267809.600921741-1992.193840707731224.399078259360.562640557884551
30264176264112.236155732-2307.7632342798663.7638442678025-0.381999700049219
31255198257214.214674899-3157.17150710773-2016.21467489926-1.02625665260686
32253353253392.069538115-3280.18000254160-39.0695381152983-0.148704898086683
33246057248396.529836918-3597.46683497079-2339.5298369184-0.383840074575263
34235372243660.007073746-3808.10126249424-8288.00707374609-0.254844312051477
35258556248976.627828301-2122.705824813589579.372171699242.03989541260807
36260993255053.955971136-610.4699650815855939.044028864111.83962445629410
37254663251026.739372880-1241.295756003923636.26062712045-0.773380939517793
38250643250518.406034935-1105.81393404893124.5939650653880.163892018883985
39243422247728.116495114-1415.84137125016-4306.11649511423-0.371828651395445
40247105248640.464030903-988.115637813652-1535.464030902630.517745385301904
41248541247026.040000542-1103.448526477031514.95999945761-0.140257801685897
42245039244050.964668988-1448.79358272527988.035331012056-0.418794092280214
43237080239697.574284708-1984.906940721-2617.57428470779-0.648444263383376
44237085236437.658312311-2220.1657284884647.341687689025-0.284410628875452
45225554229952.287500718-3006.90280590260-4398.28750071783-0.95132373108318
46226839234617.804240254-1592.45202999503-7778.804240254071.71075555036107
47247934238924.679206512-505.9054165836619009.320793487991.31590710248393
48248333240707.601689204-84.5287031311757625.398310796420.512423869308125
49246969242740.200822058305.7245409595544228.799177941960.47562544061237
50245098244316.037711156539.957089869316781.9622888444380.283389732372138
51246263249456.1464426211386.20495140250-3193.146442621081.01866715220675
52255765255336.7120126022211.62675979135428.2879873977540.998333278051667
53264319260770.3616578642804.011659872183548.638342136410.719563361095417
54268347265434.1937287283146.489218633692912.806271271590.415612413075281
55273046272774.2237871663919.11985033031271.7762128338210.935383352977324
56273963273975.8789382593418.56586900893-12.8789382591303-0.605245222300388
57267430275523.3986993253074.09089325668-8093.3986993247-0.416427338040158
58271993280664.8429935173454.45798717111-8671.842993517230.460026571812748
59292710284483.8456402383521.48643465018226.154359761620.0812095325190694
60295881288632.0692575833636.734630811327248.930742417210.140042398042488
61293299290649.8679025383338.728748594212649.13209746249-0.362247822261644

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 286602 & 286602 & 0 & 0 & 0 \tabularnewline
2 & 283042 & 283653.978487577 & -193.757637766118 & -611.978487576924 & -0.512602058586361 \tabularnewline
3 & 276687 & 278740.990211037 & -626.91648573849 & -2053.99021103726 & -1.10434425180643 \tabularnewline
4 & 277915 & 277704.864198171 & -673.55551718559 & 210.135801828790 & -0.101330739637021 \tabularnewline
5 & 277128 & 277273.640546886 & -640.785948258969 & -145.640546885858 & 0.0584370187608226 \tabularnewline
6 & 277103 & 277214.827411661 & -551.988562908826 & -111.827411661256 & 0.137775381399521 \tabularnewline
7 & 275037 & 275811.948393772 & -692.421269421379 & -774.948393772297 & -0.199101667700537 \tabularnewline
8 & 270150 & 271753.599507441 & -1275.95775947025 & -1603.59950744087 & -0.781314140029168 \tabularnewline
9 & 267140 & 267985.936032108 & -1721.42278317639 & -845.936032107815 & -0.575202190918298 \tabularnewline
10 & 264993 & 265328.515582245 & -1892.03633889931 & -335.515582244946 & -0.215266548845033 \tabularnewline
11 & 287259 & 280406.358926374 & 1239.59753561958 & 6852.64107362596 & 3.8931729128653 \tabularnewline
12 & 291186 & 290440.110659114 & 2875.28500374179 & 745.88934088587 & 2.01424283726858 \tabularnewline
13 & 292300 & 291811.390019001 & 2606.24837084285 & 488.609980998629 & -0.372527026877422 \tabularnewline
14 & 288186 & 289098.607550545 & 1618.16982635888 & -912.607550544624 & -1.16426911072216 \tabularnewline
15 & 281477 & 285178.999425359 & 602.536601873665 & -3701.99942535885 & -1.19092457735949 \tabularnewline
16 & 282656 & 283206.224384905 & 127.925516326566 & -550.224384904784 & -0.580264949079261 \tabularnewline
17 & 280190 & 281327.864600774 & -244.314731512342 & -1137.86460077385 & -0.452964131984537 \tabularnewline
18 & 280408 & 280367.008152864 & -377.432403815789 & 40.9918471356168 & -0.160971815641822 \tabularnewline
19 & 276836 & 277424.781175635 & -853.839424952912 & -588.781175635382 & -0.575948862545888 \tabularnewline
20 & 275216 & 275496.58372056 & -1053.41932744088 & -280.583720559806 & -0.241500869741957 \tabularnewline
21 & 274352 & 274617.855766088 & -1020.95701995824 & -265.855766087961 & 0.0393016841926683 \tabularnewline
22 & 271311 & 276030.215661518 & -568.683553263882 & -4719.21566151804 & 0.547625224235703 \tabularnewline
23 & 289802 & 282771.491607707 & 788.966076137044 & 7030.5083922935 & 1.64319917819594 \tabularnewline
24 & 290726 & 288213.532132554 & 1650.38256178230 & 2512.46786744636 & 1.04636923700167 \tabularnewline
25 & 292300 & 289952.311980775 & 1666.71803985619 & 2347.68801922449 & 0.0203784280270694 \tabularnewline
26 & 278506 & 281999.064691389 & -117.659049246313 & -3493.06469138926 & -2.15340139308426 \tabularnewline
27 & 269826 & 274836.563223571 & -1413.65069880534 & -5010.5632235706 & -1.54252059215159 \tabularnewline
28 & 265861 & 267760.870634804 & -2454.48893417320 & -1899.87063480361 & -1.26333867744152 \tabularnewline
29 & 269034 & 267809.600921741 & -1992.19384070773 & 1224.39907825936 & 0.562640557884551 \tabularnewline
30 & 264176 & 264112.236155732 & -2307.76323427986 & 63.7638442678025 & -0.381999700049219 \tabularnewline
31 & 255198 & 257214.214674899 & -3157.17150710773 & -2016.21467489926 & -1.02625665260686 \tabularnewline
32 & 253353 & 253392.069538115 & -3280.18000254160 & -39.0695381152983 & -0.148704898086683 \tabularnewline
33 & 246057 & 248396.529836918 & -3597.46683497079 & -2339.5298369184 & -0.383840074575263 \tabularnewline
34 & 235372 & 243660.007073746 & -3808.10126249424 & -8288.00707374609 & -0.254844312051477 \tabularnewline
35 & 258556 & 248976.627828301 & -2122.70582481358 & 9579.37217169924 & 2.03989541260807 \tabularnewline
36 & 260993 & 255053.955971136 & -610.469965081585 & 5939.04402886411 & 1.83962445629410 \tabularnewline
37 & 254663 & 251026.739372880 & -1241.29575600392 & 3636.26062712045 & -0.773380939517793 \tabularnewline
38 & 250643 & 250518.406034935 & -1105.81393404893 & 124.593965065388 & 0.163892018883985 \tabularnewline
39 & 243422 & 247728.116495114 & -1415.84137125016 & -4306.11649511423 & -0.371828651395445 \tabularnewline
40 & 247105 & 248640.464030903 & -988.115637813652 & -1535.46403090263 & 0.517745385301904 \tabularnewline
41 & 248541 & 247026.040000542 & -1103.44852647703 & 1514.95999945761 & -0.140257801685897 \tabularnewline
42 & 245039 & 244050.964668988 & -1448.79358272527 & 988.035331012056 & -0.418794092280214 \tabularnewline
43 & 237080 & 239697.574284708 & -1984.906940721 & -2617.57428470779 & -0.648444263383376 \tabularnewline
44 & 237085 & 236437.658312311 & -2220.1657284884 & 647.341687689025 & -0.284410628875452 \tabularnewline
45 & 225554 & 229952.287500718 & -3006.90280590260 & -4398.28750071783 & -0.95132373108318 \tabularnewline
46 & 226839 & 234617.804240254 & -1592.45202999503 & -7778.80424025407 & 1.71075555036107 \tabularnewline
47 & 247934 & 238924.679206512 & -505.905416583661 & 9009.32079348799 & 1.31590710248393 \tabularnewline
48 & 248333 & 240707.601689204 & -84.528703131175 & 7625.39831079642 & 0.512423869308125 \tabularnewline
49 & 246969 & 242740.200822058 & 305.724540959554 & 4228.79917794196 & 0.47562544061237 \tabularnewline
50 & 245098 & 244316.037711156 & 539.957089869316 & 781.962288844438 & 0.283389732372138 \tabularnewline
51 & 246263 & 249456.146442621 & 1386.20495140250 & -3193.14644262108 & 1.01866715220675 \tabularnewline
52 & 255765 & 255336.712012602 & 2211.62675979135 & 428.287987397754 & 0.998333278051667 \tabularnewline
53 & 264319 & 260770.361657864 & 2804.01165987218 & 3548.63834213641 & 0.719563361095417 \tabularnewline
54 & 268347 & 265434.193728728 & 3146.48921863369 & 2912.80627127159 & 0.415612413075281 \tabularnewline
55 & 273046 & 272774.223787166 & 3919.11985033031 & 271.776212833821 & 0.935383352977324 \tabularnewline
56 & 273963 & 273975.878938259 & 3418.56586900893 & -12.8789382591303 & -0.605245222300388 \tabularnewline
57 & 267430 & 275523.398699325 & 3074.09089325668 & -8093.3986993247 & -0.416427338040158 \tabularnewline
58 & 271993 & 280664.842993517 & 3454.45798717111 & -8671.84299351723 & 0.460026571812748 \tabularnewline
59 & 292710 & 284483.845640238 & 3521.4864346501 & 8226.15435976162 & 0.0812095325190694 \tabularnewline
60 & 295881 & 288632.069257583 & 3636.73463081132 & 7248.93074241721 & 0.140042398042488 \tabularnewline
61 & 293299 & 290649.867902538 & 3338.72874859421 & 2649.13209746249 & -0.362247822261644 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64482&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]286602[/C][C]286602[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]283042[/C][C]283653.978487577[/C][C]-193.757637766118[/C][C]-611.978487576924[/C][C]-0.512602058586361[/C][/ROW]
[ROW][C]3[/C][C]276687[/C][C]278740.990211037[/C][C]-626.91648573849[/C][C]-2053.99021103726[/C][C]-1.10434425180643[/C][/ROW]
[ROW][C]4[/C][C]277915[/C][C]277704.864198171[/C][C]-673.55551718559[/C][C]210.135801828790[/C][C]-0.101330739637021[/C][/ROW]
[ROW][C]5[/C][C]277128[/C][C]277273.640546886[/C][C]-640.785948258969[/C][C]-145.640546885858[/C][C]0.0584370187608226[/C][/ROW]
[ROW][C]6[/C][C]277103[/C][C]277214.827411661[/C][C]-551.988562908826[/C][C]-111.827411661256[/C][C]0.137775381399521[/C][/ROW]
[ROW][C]7[/C][C]275037[/C][C]275811.948393772[/C][C]-692.421269421379[/C][C]-774.948393772297[/C][C]-0.199101667700537[/C][/ROW]
[ROW][C]8[/C][C]270150[/C][C]271753.599507441[/C][C]-1275.95775947025[/C][C]-1603.59950744087[/C][C]-0.781314140029168[/C][/ROW]
[ROW][C]9[/C][C]267140[/C][C]267985.936032108[/C][C]-1721.42278317639[/C][C]-845.936032107815[/C][C]-0.575202190918298[/C][/ROW]
[ROW][C]10[/C][C]264993[/C][C]265328.515582245[/C][C]-1892.03633889931[/C][C]-335.515582244946[/C][C]-0.215266548845033[/C][/ROW]
[ROW][C]11[/C][C]287259[/C][C]280406.358926374[/C][C]1239.59753561958[/C][C]6852.64107362596[/C][C]3.8931729128653[/C][/ROW]
[ROW][C]12[/C][C]291186[/C][C]290440.110659114[/C][C]2875.28500374179[/C][C]745.88934088587[/C][C]2.01424283726858[/C][/ROW]
[ROW][C]13[/C][C]292300[/C][C]291811.390019001[/C][C]2606.24837084285[/C][C]488.609980998629[/C][C]-0.372527026877422[/C][/ROW]
[ROW][C]14[/C][C]288186[/C][C]289098.607550545[/C][C]1618.16982635888[/C][C]-912.607550544624[/C][C]-1.16426911072216[/C][/ROW]
[ROW][C]15[/C][C]281477[/C][C]285178.999425359[/C][C]602.536601873665[/C][C]-3701.99942535885[/C][C]-1.19092457735949[/C][/ROW]
[ROW][C]16[/C][C]282656[/C][C]283206.224384905[/C][C]127.925516326566[/C][C]-550.224384904784[/C][C]-0.580264949079261[/C][/ROW]
[ROW][C]17[/C][C]280190[/C][C]281327.864600774[/C][C]-244.314731512342[/C][C]-1137.86460077385[/C][C]-0.452964131984537[/C][/ROW]
[ROW][C]18[/C][C]280408[/C][C]280367.008152864[/C][C]-377.432403815789[/C][C]40.9918471356168[/C][C]-0.160971815641822[/C][/ROW]
[ROW][C]19[/C][C]276836[/C][C]277424.781175635[/C][C]-853.839424952912[/C][C]-588.781175635382[/C][C]-0.575948862545888[/C][/ROW]
[ROW][C]20[/C][C]275216[/C][C]275496.58372056[/C][C]-1053.41932744088[/C][C]-280.583720559806[/C][C]-0.241500869741957[/C][/ROW]
[ROW][C]21[/C][C]274352[/C][C]274617.855766088[/C][C]-1020.95701995824[/C][C]-265.855766087961[/C][C]0.0393016841926683[/C][/ROW]
[ROW][C]22[/C][C]271311[/C][C]276030.215661518[/C][C]-568.683553263882[/C][C]-4719.21566151804[/C][C]0.547625224235703[/C][/ROW]
[ROW][C]23[/C][C]289802[/C][C]282771.491607707[/C][C]788.966076137044[/C][C]7030.5083922935[/C][C]1.64319917819594[/C][/ROW]
[ROW][C]24[/C][C]290726[/C][C]288213.532132554[/C][C]1650.38256178230[/C][C]2512.46786744636[/C][C]1.04636923700167[/C][/ROW]
[ROW][C]25[/C][C]292300[/C][C]289952.311980775[/C][C]1666.71803985619[/C][C]2347.68801922449[/C][C]0.0203784280270694[/C][/ROW]
[ROW][C]26[/C][C]278506[/C][C]281999.064691389[/C][C]-117.659049246313[/C][C]-3493.06469138926[/C][C]-2.15340139308426[/C][/ROW]
[ROW][C]27[/C][C]269826[/C][C]274836.563223571[/C][C]-1413.65069880534[/C][C]-5010.5632235706[/C][C]-1.54252059215159[/C][/ROW]
[ROW][C]28[/C][C]265861[/C][C]267760.870634804[/C][C]-2454.48893417320[/C][C]-1899.87063480361[/C][C]-1.26333867744152[/C][/ROW]
[ROW][C]29[/C][C]269034[/C][C]267809.600921741[/C][C]-1992.19384070773[/C][C]1224.39907825936[/C][C]0.562640557884551[/C][/ROW]
[ROW][C]30[/C][C]264176[/C][C]264112.236155732[/C][C]-2307.76323427986[/C][C]63.7638442678025[/C][C]-0.381999700049219[/C][/ROW]
[ROW][C]31[/C][C]255198[/C][C]257214.214674899[/C][C]-3157.17150710773[/C][C]-2016.21467489926[/C][C]-1.02625665260686[/C][/ROW]
[ROW][C]32[/C][C]253353[/C][C]253392.069538115[/C][C]-3280.18000254160[/C][C]-39.0695381152983[/C][C]-0.148704898086683[/C][/ROW]
[ROW][C]33[/C][C]246057[/C][C]248396.529836918[/C][C]-3597.46683497079[/C][C]-2339.5298369184[/C][C]-0.383840074575263[/C][/ROW]
[ROW][C]34[/C][C]235372[/C][C]243660.007073746[/C][C]-3808.10126249424[/C][C]-8288.00707374609[/C][C]-0.254844312051477[/C][/ROW]
[ROW][C]35[/C][C]258556[/C][C]248976.627828301[/C][C]-2122.70582481358[/C][C]9579.37217169924[/C][C]2.03989541260807[/C][/ROW]
[ROW][C]36[/C][C]260993[/C][C]255053.955971136[/C][C]-610.469965081585[/C][C]5939.04402886411[/C][C]1.83962445629410[/C][/ROW]
[ROW][C]37[/C][C]254663[/C][C]251026.739372880[/C][C]-1241.29575600392[/C][C]3636.26062712045[/C][C]-0.773380939517793[/C][/ROW]
[ROW][C]38[/C][C]250643[/C][C]250518.406034935[/C][C]-1105.81393404893[/C][C]124.593965065388[/C][C]0.163892018883985[/C][/ROW]
[ROW][C]39[/C][C]243422[/C][C]247728.116495114[/C][C]-1415.84137125016[/C][C]-4306.11649511423[/C][C]-0.371828651395445[/C][/ROW]
[ROW][C]40[/C][C]247105[/C][C]248640.464030903[/C][C]-988.115637813652[/C][C]-1535.46403090263[/C][C]0.517745385301904[/C][/ROW]
[ROW][C]41[/C][C]248541[/C][C]247026.040000542[/C][C]-1103.44852647703[/C][C]1514.95999945761[/C][C]-0.140257801685897[/C][/ROW]
[ROW][C]42[/C][C]245039[/C][C]244050.964668988[/C][C]-1448.79358272527[/C][C]988.035331012056[/C][C]-0.418794092280214[/C][/ROW]
[ROW][C]43[/C][C]237080[/C][C]239697.574284708[/C][C]-1984.906940721[/C][C]-2617.57428470779[/C][C]-0.648444263383376[/C][/ROW]
[ROW][C]44[/C][C]237085[/C][C]236437.658312311[/C][C]-2220.1657284884[/C][C]647.341687689025[/C][C]-0.284410628875452[/C][/ROW]
[ROW][C]45[/C][C]225554[/C][C]229952.287500718[/C][C]-3006.90280590260[/C][C]-4398.28750071783[/C][C]-0.95132373108318[/C][/ROW]
[ROW][C]46[/C][C]226839[/C][C]234617.804240254[/C][C]-1592.45202999503[/C][C]-7778.80424025407[/C][C]1.71075555036107[/C][/ROW]
[ROW][C]47[/C][C]247934[/C][C]238924.679206512[/C][C]-505.905416583661[/C][C]9009.32079348799[/C][C]1.31590710248393[/C][/ROW]
[ROW][C]48[/C][C]248333[/C][C]240707.601689204[/C][C]-84.528703131175[/C][C]7625.39831079642[/C][C]0.512423869308125[/C][/ROW]
[ROW][C]49[/C][C]246969[/C][C]242740.200822058[/C][C]305.724540959554[/C][C]4228.79917794196[/C][C]0.47562544061237[/C][/ROW]
[ROW][C]50[/C][C]245098[/C][C]244316.037711156[/C][C]539.957089869316[/C][C]781.962288844438[/C][C]0.283389732372138[/C][/ROW]
[ROW][C]51[/C][C]246263[/C][C]249456.146442621[/C][C]1386.20495140250[/C][C]-3193.14644262108[/C][C]1.01866715220675[/C][/ROW]
[ROW][C]52[/C][C]255765[/C][C]255336.712012602[/C][C]2211.62675979135[/C][C]428.287987397754[/C][C]0.998333278051667[/C][/ROW]
[ROW][C]53[/C][C]264319[/C][C]260770.361657864[/C][C]2804.01165987218[/C][C]3548.63834213641[/C][C]0.719563361095417[/C][/ROW]
[ROW][C]54[/C][C]268347[/C][C]265434.193728728[/C][C]3146.48921863369[/C][C]2912.80627127159[/C][C]0.415612413075281[/C][/ROW]
[ROW][C]55[/C][C]273046[/C][C]272774.223787166[/C][C]3919.11985033031[/C][C]271.776212833821[/C][C]0.935383352977324[/C][/ROW]
[ROW][C]56[/C][C]273963[/C][C]273975.878938259[/C][C]3418.56586900893[/C][C]-12.8789382591303[/C][C]-0.605245222300388[/C][/ROW]
[ROW][C]57[/C][C]267430[/C][C]275523.398699325[/C][C]3074.09089325668[/C][C]-8093.3986993247[/C][C]-0.416427338040158[/C][/ROW]
[ROW][C]58[/C][C]271993[/C][C]280664.842993517[/C][C]3454.45798717111[/C][C]-8671.84299351723[/C][C]0.460026571812748[/C][/ROW]
[ROW][C]59[/C][C]292710[/C][C]284483.845640238[/C][C]3521.4864346501[/C][C]8226.15435976162[/C][C]0.0812095325190694[/C][/ROW]
[ROW][C]60[/C][C]295881[/C][C]288632.069257583[/C][C]3636.73463081132[/C][C]7248.93074241721[/C][C]0.140042398042488[/C][/ROW]
[ROW][C]61[/C][C]293299[/C][C]290649.867902538[/C][C]3338.72874859421[/C][C]2649.13209746249[/C][C]-0.362247822261644[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64482&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64482&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
1286602286602000
2283042283653.978487577-193.757637766118-611.978487576924-0.512602058586361
3276687278740.990211037-626.91648573849-2053.99021103726-1.10434425180643
4277915277704.864198171-673.55551718559210.135801828790-0.101330739637021
5277128277273.640546886-640.785948258969-145.6405468858580.0584370187608226
6277103277214.827411661-551.988562908826-111.8274116612560.137775381399521
7275037275811.948393772-692.421269421379-774.948393772297-0.199101667700537
8270150271753.599507441-1275.95775947025-1603.59950744087-0.781314140029168
9267140267985.936032108-1721.42278317639-845.936032107815-0.575202190918298
10264993265328.515582245-1892.03633889931-335.515582244946-0.215266548845033
11287259280406.3589263741239.597535619586852.641073625963.8931729128653
12291186290440.1106591142875.28500374179745.889340885872.01424283726858
13292300291811.3900190012606.24837084285488.609980998629-0.372527026877422
14288186289098.6075505451618.16982635888-912.607550544624-1.16426911072216
15281477285178.999425359602.536601873665-3701.99942535885-1.19092457735949
16282656283206.224384905127.925516326566-550.224384904784-0.580264949079261
17280190281327.864600774-244.314731512342-1137.86460077385-0.452964131984537
18280408280367.008152864-377.43240381578940.9918471356168-0.160971815641822
19276836277424.781175635-853.839424952912-588.781175635382-0.575948862545888
20275216275496.58372056-1053.41932744088-280.583720559806-0.241500869741957
21274352274617.855766088-1020.95701995824-265.8557660879610.0393016841926683
22271311276030.215661518-568.683553263882-4719.215661518040.547625224235703
23289802282771.491607707788.9660761370447030.50839229351.64319917819594
24290726288213.5321325541650.382561782302512.467867446361.04636923700167
25292300289952.3119807751666.718039856192347.688019224490.0203784280270694
26278506281999.064691389-117.659049246313-3493.06469138926-2.15340139308426
27269826274836.563223571-1413.65069880534-5010.5632235706-1.54252059215159
28265861267760.870634804-2454.48893417320-1899.87063480361-1.26333867744152
29269034267809.600921741-1992.193840707731224.399078259360.562640557884551
30264176264112.236155732-2307.7632342798663.7638442678025-0.381999700049219
31255198257214.214674899-3157.17150710773-2016.21467489926-1.02625665260686
32253353253392.069538115-3280.18000254160-39.0695381152983-0.148704898086683
33246057248396.529836918-3597.46683497079-2339.5298369184-0.383840074575263
34235372243660.007073746-3808.10126249424-8288.00707374609-0.254844312051477
35258556248976.627828301-2122.705824813589579.372171699242.03989541260807
36260993255053.955971136-610.4699650815855939.044028864111.83962445629410
37254663251026.739372880-1241.295756003923636.26062712045-0.773380939517793
38250643250518.406034935-1105.81393404893124.5939650653880.163892018883985
39243422247728.116495114-1415.84137125016-4306.11649511423-0.371828651395445
40247105248640.464030903-988.115637813652-1535.464030902630.517745385301904
41248541247026.040000542-1103.448526477031514.95999945761-0.140257801685897
42245039244050.964668988-1448.79358272527988.035331012056-0.418794092280214
43237080239697.574284708-1984.906940721-2617.57428470779-0.648444263383376
44237085236437.658312311-2220.1657284884647.341687689025-0.284410628875452
45225554229952.287500718-3006.90280590260-4398.28750071783-0.95132373108318
46226839234617.804240254-1592.45202999503-7778.804240254071.71075555036107
47247934238924.679206512-505.9054165836619009.320793487991.31590710248393
48248333240707.601689204-84.5287031311757625.398310796420.512423869308125
49246969242740.200822058305.7245409595544228.799177941960.47562544061237
50245098244316.037711156539.957089869316781.9622888444380.283389732372138
51246263249456.1464426211386.20495140250-3193.146442621081.01866715220675
52255765255336.7120126022211.62675979135428.2879873977540.998333278051667
53264319260770.3616578642804.011659872183548.638342136410.719563361095417
54268347265434.1937287283146.489218633692912.806271271590.415612413075281
55273046272774.2237871663919.11985033031271.7762128338210.935383352977324
56273963273975.8789382593418.56586900893-12.8789382591303-0.605245222300388
57267430275523.3986993253074.09089325668-8093.3986993247-0.416427338040158
58271993280664.8429935173454.45798717111-8671.842993517230.460026571812748
59292710284483.8456402383521.48643465018226.154359761620.0812095325190694
60295881288632.0692575833636.734630811327248.930742417210.140042398042488
61293299290649.8679025383338.728748594212649.13209746249-0.362247822261644



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')