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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 computationWed, 02 Dec 2009 14:48:13 -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/02/t12597905434m8sc32a2xgf2js.htm/, Retrieved Sun, 28 Apr 2024 05:57:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62603, Retrieved Sun, 28 Apr 2024 05:57:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
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(2)] [2009-12-02 21:48:13] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataseries X:
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186412
189226
191563
188906
186005
195309
223532
226899
214126




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=62603&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=62603&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62603&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
1216234216234000
2213587214477.181578230-1830.38714480497-890.18157823028-0.39479893349566
3209465209827.776322188-3680.183873355-362.776322187599-0.33994872187352
4204045204418.526126059-4877.81228434098-373.526126059336-0.224145044258044
5200237199912.724765473-4623.02694404524324.2752345265760.0447853618394943
6203666201577.920789916-375.5222130585052088.079210083870.754017126473183
7241476231683.74818366320286.08194321279792.251816337443.67433989511235
8260307260697.08433500726211.6813865841-390.084335006971.05224332628533
9243324255302.8589815834750.96165544077-11978.8589815831-3.81108721658072
10244460245969.507346691-4810.34385832014-1509.50734669066-1.69798373655502
11233575234448.121881445-9365.40693011369-873.121881445027-0.808911182158405
12237217233621.72911782-3569.825000217873595.270882179871.02920968741838
13235243234448.999317957-594.937579165195794.0006820430060.530187414592767
14230354231487.733683511-2202.77240311391-1133.73368351057-0.290158593620246
15227184226389.049191915-4111.79879594066794.950808084671-0.336336347303463
16221678220112.165410824-5523.987200581811565.83458917626-0.254681916560283
17217142217319.207638779-3722.61739222962-177.2076387785390.321211514433398
18219452225574.0737385684118.63235016086-6122.073738567771.38708366320003
19256446246288.85601264214948.57351128610157.14398735851.92374910746258
20265845258827.95498047913373.18624631377017.04501952103-0.279940690474034
21248624259837.7629183145281.72057677067-11213.7629183136-1.43681442840166
22241114246096.84742379-7168.52294247772-4982.84742379007-2.21108948209455
23229245233605.498697259-10650.5840068462-4360.49869725849-0.618383956824398
24231805227827.192949423-7467.02543547793977.807050577030.565603424674838
25219277218543.624534856-8654.23149439876733.37546514395-0.211501834754061
26219313215992.168336011-4660.449573681183320.831663989320.71039202623335
27212610210179.950654399-5407.540799784172430.04934560058-0.132288676925589
28214771210854.180975122-1481.966390475483916.819024878440.700184460883853
29211142214841.0252232562066.75062721389-3699.025223255680.632709485648814
30211457223122.9406838996096.0388137432-11665.94068389930.714353567549834
31240048230441.9568304426886.251562942359606.043169558020.140188518068640
32240636231564.3891061163161.077870520519071.61089388379-0.661749836521446
33230580234650.3840577073112.49731290947-4070.38405770683-0.00862787527067449
34208795218734.187169042-9202.46609052241-9939.18716904172-2.18694549691350
35197922204202.905219426-12649.5276759828-6280.90521942641-0.6121891033156
36194596190122.423514331-13574.7295112674473.5764856685-0.164426694542214
37194581190251.101893247-4707.744281960864329.898106752751.57733900903130
38185686182988.429579636-6360.541822852072697.57042036405-0.293491191252335
39178106176859.121284027-6211.613176204131246.878715972600.0264108176182695
40172608170764.884649402-6136.189652638541843.115350598470.0134191535255904
41167302171497.339101412-1710.96625017192-4195.339101412200.78787019449899
42168053178477.2914906453891.65135072021-10424.29149064530.994589206368886
43202300190018.1068497338812.9156805698312281.89315026660.87303164596816
44202388195001.0899908676350.434887120917386.91000913265-0.437232023869609
45182516184852.724262001-4263.76325082504-2336.72426200113-1.88509875979197
46173476180114.036656314-4569.38692897991-6638.03665631371-0.0542776617268997
47166444173617.799436375-5809.12872835949-7173.79943637479-0.220209075636228
48171297170483.167250836-4088.2521850003813.8327491640850.305824936134334
49169701164676.579226762-5194.545355098175024.42077323782-0.196622435415268
50164182160119.692223411-4784.272326634964062.307776588600.0728281882559792
51161914158822.518977709-2546.590723858173091.481022290630.397062001356254
52159612159426.398381158-527.463891824144185.6016188421210.358942433469935
53151001159375.049523596-221.861061375823-8374.049523596150.0543642486848535
54158114168868.9993127826019.4993300538-10754.99931278181.10855163258835
55186530173678.9210731255243.3241558322612851.0789268747-0.137731493842675
56187069175021.2557753172742.3721201044912047.7442246825-0.443955593424929
57174330176604.2024867301999.03500934169-2274.20248672969-0.132007690850250
58169362176282.125291881510.600391879073-6920.12529188148-0.264371078849236
59166827175188.700349993-518.085727951854-8361.70034999336-0.182749363677611
60178037175800.558907678206.7832872250792236.441092321940.128806519531542
61186412180014.0728645912778.024523775366397.927135408550.456780487556198
62189226185377.1191041394435.708153362543848.880895861470.294238190255126
63191563189375.1948387264155.572410894372187.80516127351-0.0497219247628187
64188906190385.5143802672143.79154419358-1479.51438026679-0.357512665973949
65186005196606.2228903394754.09175784515-10601.22289033890.464137381115021
66195309204886.2727074397013.35614700393-9577.272707439050.401351579474383
67223532210211.2930338495932.2149956461913320.7069661513-0.191894445648607
68226899214691.9192096235003.5364751445912207.0807903768-0.164841281353842
69214126216343.3880230122859.71232736978-2217.38802301183-0.380687409990829

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 216234 & 216234 & 0 & 0 & 0 \tabularnewline
2 & 213587 & 214477.181578230 & -1830.38714480497 & -890.18157823028 & -0.39479893349566 \tabularnewline
3 & 209465 & 209827.776322188 & -3680.183873355 & -362.776322187599 & -0.33994872187352 \tabularnewline
4 & 204045 & 204418.526126059 & -4877.81228434098 & -373.526126059336 & -0.224145044258044 \tabularnewline
5 & 200237 & 199912.724765473 & -4623.02694404524 & 324.275234526576 & 0.0447853618394943 \tabularnewline
6 & 203666 & 201577.920789916 & -375.522213058505 & 2088.07921008387 & 0.754017126473183 \tabularnewline
7 & 241476 & 231683.748183663 & 20286.0819432127 & 9792.25181633744 & 3.67433989511235 \tabularnewline
8 & 260307 & 260697.084335007 & 26211.6813865841 & -390.08433500697 & 1.05224332628533 \tabularnewline
9 & 243324 & 255302.858981583 & 4750.96165544077 & -11978.8589815831 & -3.81108721658072 \tabularnewline
10 & 244460 & 245969.507346691 & -4810.34385832014 & -1509.50734669066 & -1.69798373655502 \tabularnewline
11 & 233575 & 234448.121881445 & -9365.40693011369 & -873.121881445027 & -0.808911182158405 \tabularnewline
12 & 237217 & 233621.72911782 & -3569.82500021787 & 3595.27088217987 & 1.02920968741838 \tabularnewline
13 & 235243 & 234448.999317957 & -594.937579165195 & 794.000682043006 & 0.530187414592767 \tabularnewline
14 & 230354 & 231487.733683511 & -2202.77240311391 & -1133.73368351057 & -0.290158593620246 \tabularnewline
15 & 227184 & 226389.049191915 & -4111.79879594066 & 794.950808084671 & -0.336336347303463 \tabularnewline
16 & 221678 & 220112.165410824 & -5523.98720058181 & 1565.83458917626 & -0.254681916560283 \tabularnewline
17 & 217142 & 217319.207638779 & -3722.61739222962 & -177.207638778539 & 0.321211514433398 \tabularnewline
18 & 219452 & 225574.073738568 & 4118.63235016086 & -6122.07373856777 & 1.38708366320003 \tabularnewline
19 & 256446 & 246288.856012642 & 14948.573511286 & 10157.1439873585 & 1.92374910746258 \tabularnewline
20 & 265845 & 258827.954980479 & 13373.1862463137 & 7017.04501952103 & -0.279940690474034 \tabularnewline
21 & 248624 & 259837.762918314 & 5281.72057677067 & -11213.7629183136 & -1.43681442840166 \tabularnewline
22 & 241114 & 246096.84742379 & -7168.52294247772 & -4982.84742379007 & -2.21108948209455 \tabularnewline
23 & 229245 & 233605.498697259 & -10650.5840068462 & -4360.49869725849 & -0.618383956824398 \tabularnewline
24 & 231805 & 227827.192949423 & -7467.0254354779 & 3977.80705057703 & 0.565603424674838 \tabularnewline
25 & 219277 & 218543.624534856 & -8654.23149439876 & 733.37546514395 & -0.211501834754061 \tabularnewline
26 & 219313 & 215992.168336011 & -4660.44957368118 & 3320.83166398932 & 0.71039202623335 \tabularnewline
27 & 212610 & 210179.950654399 & -5407.54079978417 & 2430.04934560058 & -0.132288676925589 \tabularnewline
28 & 214771 & 210854.180975122 & -1481.96639047548 & 3916.81902487844 & 0.700184460883853 \tabularnewline
29 & 211142 & 214841.025223256 & 2066.75062721389 & -3699.02522325568 & 0.632709485648814 \tabularnewline
30 & 211457 & 223122.940683899 & 6096.0388137432 & -11665.9406838993 & 0.714353567549834 \tabularnewline
31 & 240048 & 230441.956830442 & 6886.25156294235 & 9606.04316955802 & 0.140188518068640 \tabularnewline
32 & 240636 & 231564.389106116 & 3161.07787052051 & 9071.61089388379 & -0.661749836521446 \tabularnewline
33 & 230580 & 234650.384057707 & 3112.49731290947 & -4070.38405770683 & -0.00862787527067449 \tabularnewline
34 & 208795 & 218734.187169042 & -9202.46609052241 & -9939.18716904172 & -2.18694549691350 \tabularnewline
35 & 197922 & 204202.905219426 & -12649.5276759828 & -6280.90521942641 & -0.6121891033156 \tabularnewline
36 & 194596 & 190122.423514331 & -13574.729511267 & 4473.5764856685 & -0.164426694542214 \tabularnewline
37 & 194581 & 190251.101893247 & -4707.74428196086 & 4329.89810675275 & 1.57733900903130 \tabularnewline
38 & 185686 & 182988.429579636 & -6360.54182285207 & 2697.57042036405 & -0.293491191252335 \tabularnewline
39 & 178106 & 176859.121284027 & -6211.61317620413 & 1246.87871597260 & 0.0264108176182695 \tabularnewline
40 & 172608 & 170764.884649402 & -6136.18965263854 & 1843.11535059847 & 0.0134191535255904 \tabularnewline
41 & 167302 & 171497.339101412 & -1710.96625017192 & -4195.33910141220 & 0.78787019449899 \tabularnewline
42 & 168053 & 178477.291490645 & 3891.65135072021 & -10424.2914906453 & 0.994589206368886 \tabularnewline
43 & 202300 & 190018.106849733 & 8812.91568056983 & 12281.8931502666 & 0.87303164596816 \tabularnewline
44 & 202388 & 195001.089990867 & 6350.43488712091 & 7386.91000913265 & -0.437232023869609 \tabularnewline
45 & 182516 & 184852.724262001 & -4263.76325082504 & -2336.72426200113 & -1.88509875979197 \tabularnewline
46 & 173476 & 180114.036656314 & -4569.38692897991 & -6638.03665631371 & -0.0542776617268997 \tabularnewline
47 & 166444 & 173617.799436375 & -5809.12872835949 & -7173.79943637479 & -0.220209075636228 \tabularnewline
48 & 171297 & 170483.167250836 & -4088.2521850003 & 813.832749164085 & 0.305824936134334 \tabularnewline
49 & 169701 & 164676.579226762 & -5194.54535509817 & 5024.42077323782 & -0.196622435415268 \tabularnewline
50 & 164182 & 160119.692223411 & -4784.27232663496 & 4062.30777658860 & 0.0728281882559792 \tabularnewline
51 & 161914 & 158822.518977709 & -2546.59072385817 & 3091.48102229063 & 0.397062001356254 \tabularnewline
52 & 159612 & 159426.398381158 & -527.463891824144 & 185.601618842121 & 0.358942433469935 \tabularnewline
53 & 151001 & 159375.049523596 & -221.861061375823 & -8374.04952359615 & 0.0543642486848535 \tabularnewline
54 & 158114 & 168868.999312782 & 6019.4993300538 & -10754.9993127818 & 1.10855163258835 \tabularnewline
55 & 186530 & 173678.921073125 & 5243.32415583226 & 12851.0789268747 & -0.137731493842675 \tabularnewline
56 & 187069 & 175021.255775317 & 2742.37212010449 & 12047.7442246825 & -0.443955593424929 \tabularnewline
57 & 174330 & 176604.202486730 & 1999.03500934169 & -2274.20248672969 & -0.132007690850250 \tabularnewline
58 & 169362 & 176282.125291881 & 510.600391879073 & -6920.12529188148 & -0.264371078849236 \tabularnewline
59 & 166827 & 175188.700349993 & -518.085727951854 & -8361.70034999336 & -0.182749363677611 \tabularnewline
60 & 178037 & 175800.558907678 & 206.783287225079 & 2236.44109232194 & 0.128806519531542 \tabularnewline
61 & 186412 & 180014.072864591 & 2778.02452377536 & 6397.92713540855 & 0.456780487556198 \tabularnewline
62 & 189226 & 185377.119104139 & 4435.70815336254 & 3848.88089586147 & 0.294238190255126 \tabularnewline
63 & 191563 & 189375.194838726 & 4155.57241089437 & 2187.80516127351 & -0.0497219247628187 \tabularnewline
64 & 188906 & 190385.514380267 & 2143.79154419358 & -1479.51438026679 & -0.357512665973949 \tabularnewline
65 & 186005 & 196606.222890339 & 4754.09175784515 & -10601.2228903389 & 0.464137381115021 \tabularnewline
66 & 195309 & 204886.272707439 & 7013.35614700393 & -9577.27270743905 & 0.401351579474383 \tabularnewline
67 & 223532 & 210211.293033849 & 5932.21499564619 & 13320.7069661513 & -0.191894445648607 \tabularnewline
68 & 226899 & 214691.919209623 & 5003.53647514459 & 12207.0807903768 & -0.164841281353842 \tabularnewline
69 & 214126 & 216343.388023012 & 2859.71232736978 & -2217.38802301183 & -0.380687409990829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62603&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]216234[/C][C]216234[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]213587[/C][C]214477.181578230[/C][C]-1830.38714480497[/C][C]-890.18157823028[/C][C]-0.39479893349566[/C][/ROW]
[ROW][C]3[/C][C]209465[/C][C]209827.776322188[/C][C]-3680.183873355[/C][C]-362.776322187599[/C][C]-0.33994872187352[/C][/ROW]
[ROW][C]4[/C][C]204045[/C][C]204418.526126059[/C][C]-4877.81228434098[/C][C]-373.526126059336[/C][C]-0.224145044258044[/C][/ROW]
[ROW][C]5[/C][C]200237[/C][C]199912.724765473[/C][C]-4623.02694404524[/C][C]324.275234526576[/C][C]0.0447853618394943[/C][/ROW]
[ROW][C]6[/C][C]203666[/C][C]201577.920789916[/C][C]-375.522213058505[/C][C]2088.07921008387[/C][C]0.754017126473183[/C][/ROW]
[ROW][C]7[/C][C]241476[/C][C]231683.748183663[/C][C]20286.0819432127[/C][C]9792.25181633744[/C][C]3.67433989511235[/C][/ROW]
[ROW][C]8[/C][C]260307[/C][C]260697.084335007[/C][C]26211.6813865841[/C][C]-390.08433500697[/C][C]1.05224332628533[/C][/ROW]
[ROW][C]9[/C][C]243324[/C][C]255302.858981583[/C][C]4750.96165544077[/C][C]-11978.8589815831[/C][C]-3.81108721658072[/C][/ROW]
[ROW][C]10[/C][C]244460[/C][C]245969.507346691[/C][C]-4810.34385832014[/C][C]-1509.50734669066[/C][C]-1.69798373655502[/C][/ROW]
[ROW][C]11[/C][C]233575[/C][C]234448.121881445[/C][C]-9365.40693011369[/C][C]-873.121881445027[/C][C]-0.808911182158405[/C][/ROW]
[ROW][C]12[/C][C]237217[/C][C]233621.72911782[/C][C]-3569.82500021787[/C][C]3595.27088217987[/C][C]1.02920968741838[/C][/ROW]
[ROW][C]13[/C][C]235243[/C][C]234448.999317957[/C][C]-594.937579165195[/C][C]794.000682043006[/C][C]0.530187414592767[/C][/ROW]
[ROW][C]14[/C][C]230354[/C][C]231487.733683511[/C][C]-2202.77240311391[/C][C]-1133.73368351057[/C][C]-0.290158593620246[/C][/ROW]
[ROW][C]15[/C][C]227184[/C][C]226389.049191915[/C][C]-4111.79879594066[/C][C]794.950808084671[/C][C]-0.336336347303463[/C][/ROW]
[ROW][C]16[/C][C]221678[/C][C]220112.165410824[/C][C]-5523.98720058181[/C][C]1565.83458917626[/C][C]-0.254681916560283[/C][/ROW]
[ROW][C]17[/C][C]217142[/C][C]217319.207638779[/C][C]-3722.61739222962[/C][C]-177.207638778539[/C][C]0.321211514433398[/C][/ROW]
[ROW][C]18[/C][C]219452[/C][C]225574.073738568[/C][C]4118.63235016086[/C][C]-6122.07373856777[/C][C]1.38708366320003[/C][/ROW]
[ROW][C]19[/C][C]256446[/C][C]246288.856012642[/C][C]14948.573511286[/C][C]10157.1439873585[/C][C]1.92374910746258[/C][/ROW]
[ROW][C]20[/C][C]265845[/C][C]258827.954980479[/C][C]13373.1862463137[/C][C]7017.04501952103[/C][C]-0.279940690474034[/C][/ROW]
[ROW][C]21[/C][C]248624[/C][C]259837.762918314[/C][C]5281.72057677067[/C][C]-11213.7629183136[/C][C]-1.43681442840166[/C][/ROW]
[ROW][C]22[/C][C]241114[/C][C]246096.84742379[/C][C]-7168.52294247772[/C][C]-4982.84742379007[/C][C]-2.21108948209455[/C][/ROW]
[ROW][C]23[/C][C]229245[/C][C]233605.498697259[/C][C]-10650.5840068462[/C][C]-4360.49869725849[/C][C]-0.618383956824398[/C][/ROW]
[ROW][C]24[/C][C]231805[/C][C]227827.192949423[/C][C]-7467.0254354779[/C][C]3977.80705057703[/C][C]0.565603424674838[/C][/ROW]
[ROW][C]25[/C][C]219277[/C][C]218543.624534856[/C][C]-8654.23149439876[/C][C]733.37546514395[/C][C]-0.211501834754061[/C][/ROW]
[ROW][C]26[/C][C]219313[/C][C]215992.168336011[/C][C]-4660.44957368118[/C][C]3320.83166398932[/C][C]0.71039202623335[/C][/ROW]
[ROW][C]27[/C][C]212610[/C][C]210179.950654399[/C][C]-5407.54079978417[/C][C]2430.04934560058[/C][C]-0.132288676925589[/C][/ROW]
[ROW][C]28[/C][C]214771[/C][C]210854.180975122[/C][C]-1481.96639047548[/C][C]3916.81902487844[/C][C]0.700184460883853[/C][/ROW]
[ROW][C]29[/C][C]211142[/C][C]214841.025223256[/C][C]2066.75062721389[/C][C]-3699.02522325568[/C][C]0.632709485648814[/C][/ROW]
[ROW][C]30[/C][C]211457[/C][C]223122.940683899[/C][C]6096.0388137432[/C][C]-11665.9406838993[/C][C]0.714353567549834[/C][/ROW]
[ROW][C]31[/C][C]240048[/C][C]230441.956830442[/C][C]6886.25156294235[/C][C]9606.04316955802[/C][C]0.140188518068640[/C][/ROW]
[ROW][C]32[/C][C]240636[/C][C]231564.389106116[/C][C]3161.07787052051[/C][C]9071.61089388379[/C][C]-0.661749836521446[/C][/ROW]
[ROW][C]33[/C][C]230580[/C][C]234650.384057707[/C][C]3112.49731290947[/C][C]-4070.38405770683[/C][C]-0.00862787527067449[/C][/ROW]
[ROW][C]34[/C][C]208795[/C][C]218734.187169042[/C][C]-9202.46609052241[/C][C]-9939.18716904172[/C][C]-2.18694549691350[/C][/ROW]
[ROW][C]35[/C][C]197922[/C][C]204202.905219426[/C][C]-12649.5276759828[/C][C]-6280.90521942641[/C][C]-0.6121891033156[/C][/ROW]
[ROW][C]36[/C][C]194596[/C][C]190122.423514331[/C][C]-13574.729511267[/C][C]4473.5764856685[/C][C]-0.164426694542214[/C][/ROW]
[ROW][C]37[/C][C]194581[/C][C]190251.101893247[/C][C]-4707.74428196086[/C][C]4329.89810675275[/C][C]1.57733900903130[/C][/ROW]
[ROW][C]38[/C][C]185686[/C][C]182988.429579636[/C][C]-6360.54182285207[/C][C]2697.57042036405[/C][C]-0.293491191252335[/C][/ROW]
[ROW][C]39[/C][C]178106[/C][C]176859.121284027[/C][C]-6211.61317620413[/C][C]1246.87871597260[/C][C]0.0264108176182695[/C][/ROW]
[ROW][C]40[/C][C]172608[/C][C]170764.884649402[/C][C]-6136.18965263854[/C][C]1843.11535059847[/C][C]0.0134191535255904[/C][/ROW]
[ROW][C]41[/C][C]167302[/C][C]171497.339101412[/C][C]-1710.96625017192[/C][C]-4195.33910141220[/C][C]0.78787019449899[/C][/ROW]
[ROW][C]42[/C][C]168053[/C][C]178477.291490645[/C][C]3891.65135072021[/C][C]-10424.2914906453[/C][C]0.994589206368886[/C][/ROW]
[ROW][C]43[/C][C]202300[/C][C]190018.106849733[/C][C]8812.91568056983[/C][C]12281.8931502666[/C][C]0.87303164596816[/C][/ROW]
[ROW][C]44[/C][C]202388[/C][C]195001.089990867[/C][C]6350.43488712091[/C][C]7386.91000913265[/C][C]-0.437232023869609[/C][/ROW]
[ROW][C]45[/C][C]182516[/C][C]184852.724262001[/C][C]-4263.76325082504[/C][C]-2336.72426200113[/C][C]-1.88509875979197[/C][/ROW]
[ROW][C]46[/C][C]173476[/C][C]180114.036656314[/C][C]-4569.38692897991[/C][C]-6638.03665631371[/C][C]-0.0542776617268997[/C][/ROW]
[ROW][C]47[/C][C]166444[/C][C]173617.799436375[/C][C]-5809.12872835949[/C][C]-7173.79943637479[/C][C]-0.220209075636228[/C][/ROW]
[ROW][C]48[/C][C]171297[/C][C]170483.167250836[/C][C]-4088.2521850003[/C][C]813.832749164085[/C][C]0.305824936134334[/C][/ROW]
[ROW][C]49[/C][C]169701[/C][C]164676.579226762[/C][C]-5194.54535509817[/C][C]5024.42077323782[/C][C]-0.196622435415268[/C][/ROW]
[ROW][C]50[/C][C]164182[/C][C]160119.692223411[/C][C]-4784.27232663496[/C][C]4062.30777658860[/C][C]0.0728281882559792[/C][/ROW]
[ROW][C]51[/C][C]161914[/C][C]158822.518977709[/C][C]-2546.59072385817[/C][C]3091.48102229063[/C][C]0.397062001356254[/C][/ROW]
[ROW][C]52[/C][C]159612[/C][C]159426.398381158[/C][C]-527.463891824144[/C][C]185.601618842121[/C][C]0.358942433469935[/C][/ROW]
[ROW][C]53[/C][C]151001[/C][C]159375.049523596[/C][C]-221.861061375823[/C][C]-8374.04952359615[/C][C]0.0543642486848535[/C][/ROW]
[ROW][C]54[/C][C]158114[/C][C]168868.999312782[/C][C]6019.4993300538[/C][C]-10754.9993127818[/C][C]1.10855163258835[/C][/ROW]
[ROW][C]55[/C][C]186530[/C][C]173678.921073125[/C][C]5243.32415583226[/C][C]12851.0789268747[/C][C]-0.137731493842675[/C][/ROW]
[ROW][C]56[/C][C]187069[/C][C]175021.255775317[/C][C]2742.37212010449[/C][C]12047.7442246825[/C][C]-0.443955593424929[/C][/ROW]
[ROW][C]57[/C][C]174330[/C][C]176604.202486730[/C][C]1999.03500934169[/C][C]-2274.20248672969[/C][C]-0.132007690850250[/C][/ROW]
[ROW][C]58[/C][C]169362[/C][C]176282.125291881[/C][C]510.600391879073[/C][C]-6920.12529188148[/C][C]-0.264371078849236[/C][/ROW]
[ROW][C]59[/C][C]166827[/C][C]175188.700349993[/C][C]-518.085727951854[/C][C]-8361.70034999336[/C][C]-0.182749363677611[/C][/ROW]
[ROW][C]60[/C][C]178037[/C][C]175800.558907678[/C][C]206.783287225079[/C][C]2236.44109232194[/C][C]0.128806519531542[/C][/ROW]
[ROW][C]61[/C][C]186412[/C][C]180014.072864591[/C][C]2778.02452377536[/C][C]6397.92713540855[/C][C]0.456780487556198[/C][/ROW]
[ROW][C]62[/C][C]189226[/C][C]185377.119104139[/C][C]4435.70815336254[/C][C]3848.88089586147[/C][C]0.294238190255126[/C][/ROW]
[ROW][C]63[/C][C]191563[/C][C]189375.194838726[/C][C]4155.57241089437[/C][C]2187.80516127351[/C][C]-0.0497219247628187[/C][/ROW]
[ROW][C]64[/C][C]188906[/C][C]190385.514380267[/C][C]2143.79154419358[/C][C]-1479.51438026679[/C][C]-0.357512665973949[/C][/ROW]
[ROW][C]65[/C][C]186005[/C][C]196606.222890339[/C][C]4754.09175784515[/C][C]-10601.2228903389[/C][C]0.464137381115021[/C][/ROW]
[ROW][C]66[/C][C]195309[/C][C]204886.272707439[/C][C]7013.35614700393[/C][C]-9577.27270743905[/C][C]0.401351579474383[/C][/ROW]
[ROW][C]67[/C][C]223532[/C][C]210211.293033849[/C][C]5932.21499564619[/C][C]13320.7069661513[/C][C]-0.191894445648607[/C][/ROW]
[ROW][C]68[/C][C]226899[/C][C]214691.919209623[/C][C]5003.53647514459[/C][C]12207.0807903768[/C][C]-0.164841281353842[/C][/ROW]
[ROW][C]69[/C][C]214126[/C][C]216343.388023012[/C][C]2859.71232736978[/C][C]-2217.38802301183[/C][C]-0.380687409990829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62603&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62603&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
1216234216234000
2213587214477.181578230-1830.38714480497-890.18157823028-0.39479893349566
3209465209827.776322188-3680.183873355-362.776322187599-0.33994872187352
4204045204418.526126059-4877.81228434098-373.526126059336-0.224145044258044
5200237199912.724765473-4623.02694404524324.2752345265760.0447853618394943
6203666201577.920789916-375.5222130585052088.079210083870.754017126473183
7241476231683.74818366320286.08194321279792.251816337443.67433989511235
8260307260697.08433500726211.6813865841-390.084335006971.05224332628533
9243324255302.8589815834750.96165544077-11978.8589815831-3.81108721658072
10244460245969.507346691-4810.34385832014-1509.50734669066-1.69798373655502
11233575234448.121881445-9365.40693011369-873.121881445027-0.808911182158405
12237217233621.72911782-3569.825000217873595.270882179871.02920968741838
13235243234448.999317957-594.937579165195794.0006820430060.530187414592767
14230354231487.733683511-2202.77240311391-1133.73368351057-0.290158593620246
15227184226389.049191915-4111.79879594066794.950808084671-0.336336347303463
16221678220112.165410824-5523.987200581811565.83458917626-0.254681916560283
17217142217319.207638779-3722.61739222962-177.2076387785390.321211514433398
18219452225574.0737385684118.63235016086-6122.073738567771.38708366320003
19256446246288.85601264214948.57351128610157.14398735851.92374910746258
20265845258827.95498047913373.18624631377017.04501952103-0.279940690474034
21248624259837.7629183145281.72057677067-11213.7629183136-1.43681442840166
22241114246096.84742379-7168.52294247772-4982.84742379007-2.21108948209455
23229245233605.498697259-10650.5840068462-4360.49869725849-0.618383956824398
24231805227827.192949423-7467.02543547793977.807050577030.565603424674838
25219277218543.624534856-8654.23149439876733.37546514395-0.211501834754061
26219313215992.168336011-4660.449573681183320.831663989320.71039202623335
27212610210179.950654399-5407.540799784172430.04934560058-0.132288676925589
28214771210854.180975122-1481.966390475483916.819024878440.700184460883853
29211142214841.0252232562066.75062721389-3699.025223255680.632709485648814
30211457223122.9406838996096.0388137432-11665.94068389930.714353567549834
31240048230441.9568304426886.251562942359606.043169558020.140188518068640
32240636231564.3891061163161.077870520519071.61089388379-0.661749836521446
33230580234650.3840577073112.49731290947-4070.38405770683-0.00862787527067449
34208795218734.187169042-9202.46609052241-9939.18716904172-2.18694549691350
35197922204202.905219426-12649.5276759828-6280.90521942641-0.6121891033156
36194596190122.423514331-13574.7295112674473.5764856685-0.164426694542214
37194581190251.101893247-4707.744281960864329.898106752751.57733900903130
38185686182988.429579636-6360.541822852072697.57042036405-0.293491191252335
39178106176859.121284027-6211.613176204131246.878715972600.0264108176182695
40172608170764.884649402-6136.189652638541843.115350598470.0134191535255904
41167302171497.339101412-1710.96625017192-4195.339101412200.78787019449899
42168053178477.2914906453891.65135072021-10424.29149064530.994589206368886
43202300190018.1068497338812.9156805698312281.89315026660.87303164596816
44202388195001.0899908676350.434887120917386.91000913265-0.437232023869609
45182516184852.724262001-4263.76325082504-2336.72426200113-1.88509875979197
46173476180114.036656314-4569.38692897991-6638.03665631371-0.0542776617268997
47166444173617.799436375-5809.12872835949-7173.79943637479-0.220209075636228
48171297170483.167250836-4088.2521850003813.8327491640850.305824936134334
49169701164676.579226762-5194.545355098175024.42077323782-0.196622435415268
50164182160119.692223411-4784.272326634964062.307776588600.0728281882559792
51161914158822.518977709-2546.590723858173091.481022290630.397062001356254
52159612159426.398381158-527.463891824144185.6016188421210.358942433469935
53151001159375.049523596-221.861061375823-8374.049523596150.0543642486848535
54158114168868.9993127826019.4993300538-10754.99931278181.10855163258835
55186530173678.9210731255243.3241558322612851.0789268747-0.137731493842675
56187069175021.2557753172742.3721201044912047.7442246825-0.443955593424929
57174330176604.2024867301999.03500934169-2274.20248672969-0.132007690850250
58169362176282.125291881510.600391879073-6920.12529188148-0.264371078849236
59166827175188.700349993-518.085727951854-8361.70034999336-0.182749363677611
60178037175800.558907678206.7832872250792236.441092321940.128806519531542
61186412180014.0728645912778.024523775366397.927135408550.456780487556198
62189226185377.1191041394435.708153362543848.880895861470.294238190255126
63191563189375.1948387264155.572410894372187.80516127351-0.0497219247628187
64188906190385.5143802672143.79154419358-1479.51438026679-0.357512665973949
65186005196606.2228903394754.09175784515-10601.22289033890.464137381115021
66195309204886.2727074397013.35614700393-9577.272707439050.401351579474383
67223532210211.2930338495932.2149956461913320.7069661513-0.191894445648607
68226899214691.9192096235003.5364751445912207.0807903768-0.164841281353842
69214126216343.3880230122859.71232736978-2217.38802301183-0.380687409990829



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')