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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 computationFri, 04 Dec 2009 09:57:36 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t1259945985evxh8y9k85cdr8g.htm/, Retrieved Sun, 28 Apr 2024 16:42:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63903, Retrieved Sun, 28 Apr 2024 16:42:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
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]
-   PD      [Structural Time Series Models] [Workshop 9: Struc...] [2009-12-04 16:57:36] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
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Dataseries X:
267413
267366
264777
258863
254844
254868
277267
285351
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 time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63903&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63903&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63903&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1267413267413000
2267366267384.357654688-30.1595068318717-18.3576546875851-0.0120573306031779
3264777265475.763074761-1230.64730462337-698.763074761267-0.387207780916152
4258863260376.173861343-3814.08699359233-1513.17386134343-0.872939958251469
5254844254967.296867130-4876.39017440018-123.296867129658-0.332923013120594
6254868253450.915489083-2679.709509652431417.084510916890.693250988131664
7277267270270.99146744710102.88450484356996.008532553124.05104096080793
8285351285788.00352167813660.7770413176-437.0035216783141.12545651843299
9286602290736.2763746377934.00112730939-4134.27637463657-1.81127216020215
10283042286687.50076563959.2377145686369-3645.50076563855-2.49085226920937
11276687278491.420276328-5364.70454217156-1804.42027632774-1.71558560645971
12277915275926.488391431-3525.347509766141988.511608568970.581783458681778
13277128275888.618919733-1242.353913331001239.381080267340.724897532317247
14277103276119.640050427-273.442006580221983.3599495725230.311502990853579
15275037274310.546622751-1256.50466219448726.453377248726-0.308218470510597
16270150270425.803219630-2914.36198059900-275.803219630438-0.531896063830159
17267140267870.660803246-2684.87710598065-730.6608032457810.073090659271585
18264993269620.758930962131.330768791653-4627.7589309620.886951137946173
19287259279812.7234712866487.89198089447446.2765287142.00973341430148
20291186289067.0859777568238.786706765812118.914022243630.554283770795183
21292300293757.1653613275989.62411900662-1457.16536132667-0.711398811597042
22288186291683.116036667878.090627124425-3497.11603666658-1.61678482966945
23281477286133.284538209-3194.37722816267-4656.28453820917-1.28817389796142
24282656281944.939650254-3823.35446379716711.060349745754-0.199045423403195
25280190279026.569949849-3250.517923530971163.430050150730.181769936433091
26280408277630.461624367-2075.112102747652777.538375632980.372419943967702
27276836274670.010576067-2631.760328782412165.98942393288-0.175527054931249
28275216273993.861055428-1409.302150858151222.138944572480.388059482722576
29274352275843.892322561638.320053464804-1491.892322560890.650790183526992
30271311279467.5535938812514.41172645266-8156.553593881060.592726949539441
31289802283709.1462796413595.881421130606092.853720358820.341553139415206
32290726287633.876589383801.700849683633092.12341061980.0651105199350271
33292300290947.5296940553495.882923609391352.47030594478-0.0967453124667064
34278506283703.845381414-3236.44053030738-5197.8453814141-2.12942823619126
35269826275263.654781419-6497.21044619752-5437.65478141853-1.03149128100706
36265861266174.582475066-8120.73639557832-313.58247506571-0.513937878309871
37269034265211.732959609-3633.506841428213822.26704039091.42162440072165
38264176261286.649501754-3816.256187899962889.35049824554-0.057799338075365
39255198254427.318593741-5715.73511057414770.681406259409-0.59991216601527
40253353251794.842969670-3796.222819009011558.157030329660.608055454268744
41246057248859.105094192-3259.28166814887-2802.105094192000.170316022397996
42235372245091.625017296-3576.77771057387-9719.62501729559-0.100435874232346
43258556250185.4333219111830.321698257038370.566678088981.70823975157416
44260993256661.4737560674724.160348943144331.526243932920.914941079265525
45254663252630.03949029-731.5612023612682032.96050971022-1.72577205456562
46250643252529.07339128-338.486833767182-1886.073391280140.124346023835854
47243422249524.259015868-2000.44577866795-6102.25901586832-0.525848546663348
48247105249320.305104821-880.464671722156-2215.305104820840.354524958695860
49248541245548.325514164-2684.147853189962992.67448583648-0.570929765356757
50245039241221.400684498-3708.244072420443817.5993155022-0.323773745385182
51237080237068.307936376-3984.8620986799511.6920636239260-0.0874174362504562
52237085234614.621625068-3034.091093589492470.378374932340.300987728283051
53225554229476.274529091-4342.42688382378-3922.27452909119-0.414592290697748
54226839236099.6374835972483.23188002607-9260.637483597212.16002895079982
55247934240991.1856218123980.98269792656942.814378187790.47338301735257
56248333242009.1403779452140.454089949916323.85962205526-0.581806500273487
57246969244702.5223032962483.811885865492266.477696704260.108596769884744
58245098246686.3577524782173.28267813475-1588.35775247784-0.0982459658341283
59246263251949.6085416434092.8627024764-5686.608541642950.607477935434488
60255765256802.8263408554565.41443157929-1037.826340854820.149570211298826
61264319260744.5128461864177.647279257643574.48715381359-0.122688892520152
62268347264204.2049600623731.629711250954142.79503993849-0.140999503967521
63273046271478.8996529595928.851749972481567.100347040790.694566262438454
64273963273042.3584569853224.03588936383920.641543015415-0.856043335704996
65267430275607.5010215472815.42548075274-8177.50102154707-0.129417363409643
66271993281017.3006589914425.81672752953-9024.300658990910.509664428701021
67292710284951.6844451514120.903374296937758.31555484861-0.096399711316369
68295881289357.087379764297.232248283576523.912620239770.0557380803996539
69293299291689.9137150153080.480998435331609.08628498541-0.384794295264137

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 267413 & 267413 & 0 & 0 & 0 \tabularnewline
2 & 267366 & 267384.357654688 & -30.1595068318717 & -18.3576546875851 & -0.0120573306031779 \tabularnewline
3 & 264777 & 265475.763074761 & -1230.64730462337 & -698.763074761267 & -0.387207780916152 \tabularnewline
4 & 258863 & 260376.173861343 & -3814.08699359233 & -1513.17386134343 & -0.872939958251469 \tabularnewline
5 & 254844 & 254967.296867130 & -4876.39017440018 & -123.296867129658 & -0.332923013120594 \tabularnewline
6 & 254868 & 253450.915489083 & -2679.70950965243 & 1417.08451091689 & 0.693250988131664 \tabularnewline
7 & 277267 & 270270.991467447 & 10102.8845048435 & 6996.00853255312 & 4.05104096080793 \tabularnewline
8 & 285351 & 285788.003521678 & 13660.7770413176 & -437.003521678314 & 1.12545651843299 \tabularnewline
9 & 286602 & 290736.276374637 & 7934.00112730939 & -4134.27637463657 & -1.81127216020215 \tabularnewline
10 & 283042 & 286687.500765639 & 59.2377145686369 & -3645.50076563855 & -2.49085226920937 \tabularnewline
11 & 276687 & 278491.420276328 & -5364.70454217156 & -1804.42027632774 & -1.71558560645971 \tabularnewline
12 & 277915 & 275926.488391431 & -3525.34750976614 & 1988.51160856897 & 0.581783458681778 \tabularnewline
13 & 277128 & 275888.618919733 & -1242.35391333100 & 1239.38108026734 & 0.724897532317247 \tabularnewline
14 & 277103 & 276119.640050427 & -273.442006580221 & 983.359949572523 & 0.311502990853579 \tabularnewline
15 & 275037 & 274310.546622751 & -1256.50466219448 & 726.453377248726 & -0.308218470510597 \tabularnewline
16 & 270150 & 270425.803219630 & -2914.36198059900 & -275.803219630438 & -0.531896063830159 \tabularnewline
17 & 267140 & 267870.660803246 & -2684.87710598065 & -730.660803245781 & 0.073090659271585 \tabularnewline
18 & 264993 & 269620.758930962 & 131.330768791653 & -4627.758930962 & 0.886951137946173 \tabularnewline
19 & 287259 & 279812.723471286 & 6487.8919808944 & 7446.276528714 & 2.00973341430148 \tabularnewline
20 & 291186 & 289067.085977756 & 8238.78670676581 & 2118.91402224363 & 0.554283770795183 \tabularnewline
21 & 292300 & 293757.165361327 & 5989.62411900662 & -1457.16536132667 & -0.711398811597042 \tabularnewline
22 & 288186 & 291683.116036667 & 878.090627124425 & -3497.11603666658 & -1.61678482966945 \tabularnewline
23 & 281477 & 286133.284538209 & -3194.37722816267 & -4656.28453820917 & -1.28817389796142 \tabularnewline
24 & 282656 & 281944.939650254 & -3823.35446379716 & 711.060349745754 & -0.199045423403195 \tabularnewline
25 & 280190 & 279026.569949849 & -3250.51792353097 & 1163.43005015073 & 0.181769936433091 \tabularnewline
26 & 280408 & 277630.461624367 & -2075.11210274765 & 2777.53837563298 & 0.372419943967702 \tabularnewline
27 & 276836 & 274670.010576067 & -2631.76032878241 & 2165.98942393288 & -0.175527054931249 \tabularnewline
28 & 275216 & 273993.861055428 & -1409.30215085815 & 1222.13894457248 & 0.388059482722576 \tabularnewline
29 & 274352 & 275843.892322561 & 638.320053464804 & -1491.89232256089 & 0.650790183526992 \tabularnewline
30 & 271311 & 279467.553593881 & 2514.41172645266 & -8156.55359388106 & 0.592726949539441 \tabularnewline
31 & 289802 & 283709.146279641 & 3595.88142113060 & 6092.85372035882 & 0.341553139415206 \tabularnewline
32 & 290726 & 287633.87658938 & 3801.70084968363 & 3092.1234106198 & 0.0651105199350271 \tabularnewline
33 & 292300 & 290947.529694055 & 3495.88292360939 & 1352.47030594478 & -0.0967453124667064 \tabularnewline
34 & 278506 & 283703.845381414 & -3236.44053030738 & -5197.8453814141 & -2.12942823619126 \tabularnewline
35 & 269826 & 275263.654781419 & -6497.21044619752 & -5437.65478141853 & -1.03149128100706 \tabularnewline
36 & 265861 & 266174.582475066 & -8120.73639557832 & -313.58247506571 & -0.513937878309871 \tabularnewline
37 & 269034 & 265211.732959609 & -3633.50684142821 & 3822.2670403909 & 1.42162440072165 \tabularnewline
38 & 264176 & 261286.649501754 & -3816.25618789996 & 2889.35049824554 & -0.057799338075365 \tabularnewline
39 & 255198 & 254427.318593741 & -5715.73511057414 & 770.681406259409 & -0.59991216601527 \tabularnewline
40 & 253353 & 251794.842969670 & -3796.22281900901 & 1558.15703032966 & 0.608055454268744 \tabularnewline
41 & 246057 & 248859.105094192 & -3259.28166814887 & -2802.10509419200 & 0.170316022397996 \tabularnewline
42 & 235372 & 245091.625017296 & -3576.77771057387 & -9719.62501729559 & -0.100435874232346 \tabularnewline
43 & 258556 & 250185.433321911 & 1830.32169825703 & 8370.56667808898 & 1.70823975157416 \tabularnewline
44 & 260993 & 256661.473756067 & 4724.16034894314 & 4331.52624393292 & 0.914941079265525 \tabularnewline
45 & 254663 & 252630.03949029 & -731.561202361268 & 2032.96050971022 & -1.72577205456562 \tabularnewline
46 & 250643 & 252529.07339128 & -338.486833767182 & -1886.07339128014 & 0.124346023835854 \tabularnewline
47 & 243422 & 249524.259015868 & -2000.44577866795 & -6102.25901586832 & -0.525848546663348 \tabularnewline
48 & 247105 & 249320.305104821 & -880.464671722156 & -2215.30510482084 & 0.354524958695860 \tabularnewline
49 & 248541 & 245548.325514164 & -2684.14785318996 & 2992.67448583648 & -0.570929765356757 \tabularnewline
50 & 245039 & 241221.400684498 & -3708.24407242044 & 3817.5993155022 & -0.323773745385182 \tabularnewline
51 & 237080 & 237068.307936376 & -3984.86209867995 & 11.6920636239260 & -0.0874174362504562 \tabularnewline
52 & 237085 & 234614.621625068 & -3034.09109358949 & 2470.37837493234 & 0.300987728283051 \tabularnewline
53 & 225554 & 229476.274529091 & -4342.42688382378 & -3922.27452909119 & -0.414592290697748 \tabularnewline
54 & 226839 & 236099.637483597 & 2483.23188002607 & -9260.63748359721 & 2.16002895079982 \tabularnewline
55 & 247934 & 240991.185621812 & 3980.9826979265 & 6942.81437818779 & 0.47338301735257 \tabularnewline
56 & 248333 & 242009.140377945 & 2140.45408994991 & 6323.85962205526 & -0.581806500273487 \tabularnewline
57 & 246969 & 244702.522303296 & 2483.81188586549 & 2266.47769670426 & 0.108596769884744 \tabularnewline
58 & 245098 & 246686.357752478 & 2173.28267813475 & -1588.35775247784 & -0.0982459658341283 \tabularnewline
59 & 246263 & 251949.608541643 & 4092.8627024764 & -5686.60854164295 & 0.607477935434488 \tabularnewline
60 & 255765 & 256802.826340855 & 4565.41443157929 & -1037.82634085482 & 0.149570211298826 \tabularnewline
61 & 264319 & 260744.512846186 & 4177.64727925764 & 3574.48715381359 & -0.122688892520152 \tabularnewline
62 & 268347 & 264204.204960062 & 3731.62971125095 & 4142.79503993849 & -0.140999503967521 \tabularnewline
63 & 273046 & 271478.899652959 & 5928.85174997248 & 1567.10034704079 & 0.694566262438454 \tabularnewline
64 & 273963 & 273042.358456985 & 3224.03588936383 & 920.641543015415 & -0.856043335704996 \tabularnewline
65 & 267430 & 275607.501021547 & 2815.42548075274 & -8177.50102154707 & -0.129417363409643 \tabularnewline
66 & 271993 & 281017.300658991 & 4425.81672752953 & -9024.30065899091 & 0.509664428701021 \tabularnewline
67 & 292710 & 284951.684445151 & 4120.90337429693 & 7758.31555484861 & -0.096399711316369 \tabularnewline
68 & 295881 & 289357.08737976 & 4297.23224828357 & 6523.91262023977 & 0.0557380803996539 \tabularnewline
69 & 293299 & 291689.913715015 & 3080.48099843533 & 1609.08628498541 & -0.384794295264137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63903&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]267413[/C][C]267413[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]267366[/C][C]267384.357654688[/C][C]-30.1595068318717[/C][C]-18.3576546875851[/C][C]-0.0120573306031779[/C][/ROW]
[ROW][C]3[/C][C]264777[/C][C]265475.763074761[/C][C]-1230.64730462337[/C][C]-698.763074761267[/C][C]-0.387207780916152[/C][/ROW]
[ROW][C]4[/C][C]258863[/C][C]260376.173861343[/C][C]-3814.08699359233[/C][C]-1513.17386134343[/C][C]-0.872939958251469[/C][/ROW]
[ROW][C]5[/C][C]254844[/C][C]254967.296867130[/C][C]-4876.39017440018[/C][C]-123.296867129658[/C][C]-0.332923013120594[/C][/ROW]
[ROW][C]6[/C][C]254868[/C][C]253450.915489083[/C][C]-2679.70950965243[/C][C]1417.08451091689[/C][C]0.693250988131664[/C][/ROW]
[ROW][C]7[/C][C]277267[/C][C]270270.991467447[/C][C]10102.8845048435[/C][C]6996.00853255312[/C][C]4.05104096080793[/C][/ROW]
[ROW][C]8[/C][C]285351[/C][C]285788.003521678[/C][C]13660.7770413176[/C][C]-437.003521678314[/C][C]1.12545651843299[/C][/ROW]
[ROW][C]9[/C][C]286602[/C][C]290736.276374637[/C][C]7934.00112730939[/C][C]-4134.27637463657[/C][C]-1.81127216020215[/C][/ROW]
[ROW][C]10[/C][C]283042[/C][C]286687.500765639[/C][C]59.2377145686369[/C][C]-3645.50076563855[/C][C]-2.49085226920937[/C][/ROW]
[ROW][C]11[/C][C]276687[/C][C]278491.420276328[/C][C]-5364.70454217156[/C][C]-1804.42027632774[/C][C]-1.71558560645971[/C][/ROW]
[ROW][C]12[/C][C]277915[/C][C]275926.488391431[/C][C]-3525.34750976614[/C][C]1988.51160856897[/C][C]0.581783458681778[/C][/ROW]
[ROW][C]13[/C][C]277128[/C][C]275888.618919733[/C][C]-1242.35391333100[/C][C]1239.38108026734[/C][C]0.724897532317247[/C][/ROW]
[ROW][C]14[/C][C]277103[/C][C]276119.640050427[/C][C]-273.442006580221[/C][C]983.359949572523[/C][C]0.311502990853579[/C][/ROW]
[ROW][C]15[/C][C]275037[/C][C]274310.546622751[/C][C]-1256.50466219448[/C][C]726.453377248726[/C][C]-0.308218470510597[/C][/ROW]
[ROW][C]16[/C][C]270150[/C][C]270425.803219630[/C][C]-2914.36198059900[/C][C]-275.803219630438[/C][C]-0.531896063830159[/C][/ROW]
[ROW][C]17[/C][C]267140[/C][C]267870.660803246[/C][C]-2684.87710598065[/C][C]-730.660803245781[/C][C]0.073090659271585[/C][/ROW]
[ROW][C]18[/C][C]264993[/C][C]269620.758930962[/C][C]131.330768791653[/C][C]-4627.758930962[/C][C]0.886951137946173[/C][/ROW]
[ROW][C]19[/C][C]287259[/C][C]279812.723471286[/C][C]6487.8919808944[/C][C]7446.276528714[/C][C]2.00973341430148[/C][/ROW]
[ROW][C]20[/C][C]291186[/C][C]289067.085977756[/C][C]8238.78670676581[/C][C]2118.91402224363[/C][C]0.554283770795183[/C][/ROW]
[ROW][C]21[/C][C]292300[/C][C]293757.165361327[/C][C]5989.62411900662[/C][C]-1457.16536132667[/C][C]-0.711398811597042[/C][/ROW]
[ROW][C]22[/C][C]288186[/C][C]291683.116036667[/C][C]878.090627124425[/C][C]-3497.11603666658[/C][C]-1.61678482966945[/C][/ROW]
[ROW][C]23[/C][C]281477[/C][C]286133.284538209[/C][C]-3194.37722816267[/C][C]-4656.28453820917[/C][C]-1.28817389796142[/C][/ROW]
[ROW][C]24[/C][C]282656[/C][C]281944.939650254[/C][C]-3823.35446379716[/C][C]711.060349745754[/C][C]-0.199045423403195[/C][/ROW]
[ROW][C]25[/C][C]280190[/C][C]279026.569949849[/C][C]-3250.51792353097[/C][C]1163.43005015073[/C][C]0.181769936433091[/C][/ROW]
[ROW][C]26[/C][C]280408[/C][C]277630.461624367[/C][C]-2075.11210274765[/C][C]2777.53837563298[/C][C]0.372419943967702[/C][/ROW]
[ROW][C]27[/C][C]276836[/C][C]274670.010576067[/C][C]-2631.76032878241[/C][C]2165.98942393288[/C][C]-0.175527054931249[/C][/ROW]
[ROW][C]28[/C][C]275216[/C][C]273993.861055428[/C][C]-1409.30215085815[/C][C]1222.13894457248[/C][C]0.388059482722576[/C][/ROW]
[ROW][C]29[/C][C]274352[/C][C]275843.892322561[/C][C]638.320053464804[/C][C]-1491.89232256089[/C][C]0.650790183526992[/C][/ROW]
[ROW][C]30[/C][C]271311[/C][C]279467.553593881[/C][C]2514.41172645266[/C][C]-8156.55359388106[/C][C]0.592726949539441[/C][/ROW]
[ROW][C]31[/C][C]289802[/C][C]283709.146279641[/C][C]3595.88142113060[/C][C]6092.85372035882[/C][C]0.341553139415206[/C][/ROW]
[ROW][C]32[/C][C]290726[/C][C]287633.87658938[/C][C]3801.70084968363[/C][C]3092.1234106198[/C][C]0.0651105199350271[/C][/ROW]
[ROW][C]33[/C][C]292300[/C][C]290947.529694055[/C][C]3495.88292360939[/C][C]1352.47030594478[/C][C]-0.0967453124667064[/C][/ROW]
[ROW][C]34[/C][C]278506[/C][C]283703.845381414[/C][C]-3236.44053030738[/C][C]-5197.8453814141[/C][C]-2.12942823619126[/C][/ROW]
[ROW][C]35[/C][C]269826[/C][C]275263.654781419[/C][C]-6497.21044619752[/C][C]-5437.65478141853[/C][C]-1.03149128100706[/C][/ROW]
[ROW][C]36[/C][C]265861[/C][C]266174.582475066[/C][C]-8120.73639557832[/C][C]-313.58247506571[/C][C]-0.513937878309871[/C][/ROW]
[ROW][C]37[/C][C]269034[/C][C]265211.732959609[/C][C]-3633.50684142821[/C][C]3822.2670403909[/C][C]1.42162440072165[/C][/ROW]
[ROW][C]38[/C][C]264176[/C][C]261286.649501754[/C][C]-3816.25618789996[/C][C]2889.35049824554[/C][C]-0.057799338075365[/C][/ROW]
[ROW][C]39[/C][C]255198[/C][C]254427.318593741[/C][C]-5715.73511057414[/C][C]770.681406259409[/C][C]-0.59991216601527[/C][/ROW]
[ROW][C]40[/C][C]253353[/C][C]251794.842969670[/C][C]-3796.22281900901[/C][C]1558.15703032966[/C][C]0.608055454268744[/C][/ROW]
[ROW][C]41[/C][C]246057[/C][C]248859.105094192[/C][C]-3259.28166814887[/C][C]-2802.10509419200[/C][C]0.170316022397996[/C][/ROW]
[ROW][C]42[/C][C]235372[/C][C]245091.625017296[/C][C]-3576.77771057387[/C][C]-9719.62501729559[/C][C]-0.100435874232346[/C][/ROW]
[ROW][C]43[/C][C]258556[/C][C]250185.433321911[/C][C]1830.32169825703[/C][C]8370.56667808898[/C][C]1.70823975157416[/C][/ROW]
[ROW][C]44[/C][C]260993[/C][C]256661.473756067[/C][C]4724.16034894314[/C][C]4331.52624393292[/C][C]0.914941079265525[/C][/ROW]
[ROW][C]45[/C][C]254663[/C][C]252630.03949029[/C][C]-731.561202361268[/C][C]2032.96050971022[/C][C]-1.72577205456562[/C][/ROW]
[ROW][C]46[/C][C]250643[/C][C]252529.07339128[/C][C]-338.486833767182[/C][C]-1886.07339128014[/C][C]0.124346023835854[/C][/ROW]
[ROW][C]47[/C][C]243422[/C][C]249524.259015868[/C][C]-2000.44577866795[/C][C]-6102.25901586832[/C][C]-0.525848546663348[/C][/ROW]
[ROW][C]48[/C][C]247105[/C][C]249320.305104821[/C][C]-880.464671722156[/C][C]-2215.30510482084[/C][C]0.354524958695860[/C][/ROW]
[ROW][C]49[/C][C]248541[/C][C]245548.325514164[/C][C]-2684.14785318996[/C][C]2992.67448583648[/C][C]-0.570929765356757[/C][/ROW]
[ROW][C]50[/C][C]245039[/C][C]241221.400684498[/C][C]-3708.24407242044[/C][C]3817.5993155022[/C][C]-0.323773745385182[/C][/ROW]
[ROW][C]51[/C][C]237080[/C][C]237068.307936376[/C][C]-3984.86209867995[/C][C]11.6920636239260[/C][C]-0.0874174362504562[/C][/ROW]
[ROW][C]52[/C][C]237085[/C][C]234614.621625068[/C][C]-3034.09109358949[/C][C]2470.37837493234[/C][C]0.300987728283051[/C][/ROW]
[ROW][C]53[/C][C]225554[/C][C]229476.274529091[/C][C]-4342.42688382378[/C][C]-3922.27452909119[/C][C]-0.414592290697748[/C][/ROW]
[ROW][C]54[/C][C]226839[/C][C]236099.637483597[/C][C]2483.23188002607[/C][C]-9260.63748359721[/C][C]2.16002895079982[/C][/ROW]
[ROW][C]55[/C][C]247934[/C][C]240991.185621812[/C][C]3980.9826979265[/C][C]6942.81437818779[/C][C]0.47338301735257[/C][/ROW]
[ROW][C]56[/C][C]248333[/C][C]242009.140377945[/C][C]2140.45408994991[/C][C]6323.85962205526[/C][C]-0.581806500273487[/C][/ROW]
[ROW][C]57[/C][C]246969[/C][C]244702.522303296[/C][C]2483.81188586549[/C][C]2266.47769670426[/C][C]0.108596769884744[/C][/ROW]
[ROW][C]58[/C][C]245098[/C][C]246686.357752478[/C][C]2173.28267813475[/C][C]-1588.35775247784[/C][C]-0.0982459658341283[/C][/ROW]
[ROW][C]59[/C][C]246263[/C][C]251949.608541643[/C][C]4092.8627024764[/C][C]-5686.60854164295[/C][C]0.607477935434488[/C][/ROW]
[ROW][C]60[/C][C]255765[/C][C]256802.826340855[/C][C]4565.41443157929[/C][C]-1037.82634085482[/C][C]0.149570211298826[/C][/ROW]
[ROW][C]61[/C][C]264319[/C][C]260744.512846186[/C][C]4177.64727925764[/C][C]3574.48715381359[/C][C]-0.122688892520152[/C][/ROW]
[ROW][C]62[/C][C]268347[/C][C]264204.204960062[/C][C]3731.62971125095[/C][C]4142.79503993849[/C][C]-0.140999503967521[/C][/ROW]
[ROW][C]63[/C][C]273046[/C][C]271478.899652959[/C][C]5928.85174997248[/C][C]1567.10034704079[/C][C]0.694566262438454[/C][/ROW]
[ROW][C]64[/C][C]273963[/C][C]273042.358456985[/C][C]3224.03588936383[/C][C]920.641543015415[/C][C]-0.856043335704996[/C][/ROW]
[ROW][C]65[/C][C]267430[/C][C]275607.501021547[/C][C]2815.42548075274[/C][C]-8177.50102154707[/C][C]-0.129417363409643[/C][/ROW]
[ROW][C]66[/C][C]271993[/C][C]281017.300658991[/C][C]4425.81672752953[/C][C]-9024.30065899091[/C][C]0.509664428701021[/C][/ROW]
[ROW][C]67[/C][C]292710[/C][C]284951.684445151[/C][C]4120.90337429693[/C][C]7758.31555484861[/C][C]-0.096399711316369[/C][/ROW]
[ROW][C]68[/C][C]295881[/C][C]289357.08737976[/C][C]4297.23224828357[/C][C]6523.91262023977[/C][C]0.0557380803996539[/C][/ROW]
[ROW][C]69[/C][C]293299[/C][C]291689.913715015[/C][C]3080.48099843533[/C][C]1609.08628498541[/C][C]-0.384794295264137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63903&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63903&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
1267413267413000
2267366267384.357654688-30.1595068318717-18.3576546875851-0.0120573306031779
3264777265475.763074761-1230.64730462337-698.763074761267-0.387207780916152
4258863260376.173861343-3814.08699359233-1513.17386134343-0.872939958251469
5254844254967.296867130-4876.39017440018-123.296867129658-0.332923013120594
6254868253450.915489083-2679.709509652431417.084510916890.693250988131664
7277267270270.99146744710102.88450484356996.008532553124.05104096080793
8285351285788.00352167813660.7770413176-437.0035216783141.12545651843299
9286602290736.2763746377934.00112730939-4134.27637463657-1.81127216020215
10283042286687.50076563959.2377145686369-3645.50076563855-2.49085226920937
11276687278491.420276328-5364.70454217156-1804.42027632774-1.71558560645971
12277915275926.488391431-3525.347509766141988.511608568970.581783458681778
13277128275888.618919733-1242.353913331001239.381080267340.724897532317247
14277103276119.640050427-273.442006580221983.3599495725230.311502990853579
15275037274310.546622751-1256.50466219448726.453377248726-0.308218470510597
16270150270425.803219630-2914.36198059900-275.803219630438-0.531896063830159
17267140267870.660803246-2684.87710598065-730.6608032457810.073090659271585
18264993269620.758930962131.330768791653-4627.7589309620.886951137946173
19287259279812.7234712866487.89198089447446.2765287142.00973341430148
20291186289067.0859777568238.786706765812118.914022243630.554283770795183
21292300293757.1653613275989.62411900662-1457.16536132667-0.711398811597042
22288186291683.116036667878.090627124425-3497.11603666658-1.61678482966945
23281477286133.284538209-3194.37722816267-4656.28453820917-1.28817389796142
24282656281944.939650254-3823.35446379716711.060349745754-0.199045423403195
25280190279026.569949849-3250.517923530971163.430050150730.181769936433091
26280408277630.461624367-2075.112102747652777.538375632980.372419943967702
27276836274670.010576067-2631.760328782412165.98942393288-0.175527054931249
28275216273993.861055428-1409.302150858151222.138944572480.388059482722576
29274352275843.892322561638.320053464804-1491.892322560890.650790183526992
30271311279467.5535938812514.41172645266-8156.553593881060.592726949539441
31289802283709.1462796413595.881421130606092.853720358820.341553139415206
32290726287633.876589383801.700849683633092.12341061980.0651105199350271
33292300290947.5296940553495.882923609391352.47030594478-0.0967453124667064
34278506283703.845381414-3236.44053030738-5197.8453814141-2.12942823619126
35269826275263.654781419-6497.21044619752-5437.65478141853-1.03149128100706
36265861266174.582475066-8120.73639557832-313.58247506571-0.513937878309871
37269034265211.732959609-3633.506841428213822.26704039091.42162440072165
38264176261286.649501754-3816.256187899962889.35049824554-0.057799338075365
39255198254427.318593741-5715.73511057414770.681406259409-0.59991216601527
40253353251794.842969670-3796.222819009011558.157030329660.608055454268744
41246057248859.105094192-3259.28166814887-2802.105094192000.170316022397996
42235372245091.625017296-3576.77771057387-9719.62501729559-0.100435874232346
43258556250185.4333219111830.321698257038370.566678088981.70823975157416
44260993256661.4737560674724.160348943144331.526243932920.914941079265525
45254663252630.03949029-731.5612023612682032.96050971022-1.72577205456562
46250643252529.07339128-338.486833767182-1886.073391280140.124346023835854
47243422249524.259015868-2000.44577866795-6102.25901586832-0.525848546663348
48247105249320.305104821-880.464671722156-2215.305104820840.354524958695860
49248541245548.325514164-2684.147853189962992.67448583648-0.570929765356757
50245039241221.400684498-3708.244072420443817.5993155022-0.323773745385182
51237080237068.307936376-3984.8620986799511.6920636239260-0.0874174362504562
52237085234614.621625068-3034.091093589492470.378374932340.300987728283051
53225554229476.274529091-4342.42688382378-3922.27452909119-0.414592290697748
54226839236099.6374835972483.23188002607-9260.637483597212.16002895079982
55247934240991.1856218123980.98269792656942.814378187790.47338301735257
56248333242009.1403779452140.454089949916323.85962205526-0.581806500273487
57246969244702.5223032962483.811885865492266.477696704260.108596769884744
58245098246686.3577524782173.28267813475-1588.35775247784-0.0982459658341283
59246263251949.6085416434092.8627024764-5686.608541642950.607477935434488
60255765256802.8263408554565.41443157929-1037.826340854820.149570211298826
61264319260744.5128461864177.647279257643574.48715381359-0.122688892520152
62268347264204.2049600623731.629711250954142.79503993849-0.140999503967521
63273046271478.8996529595928.851749972481567.100347040790.694566262438454
64273963273042.3584569853224.03588936383920.641543015415-0.856043335704996
65267430275607.5010215472815.42548075274-8177.50102154707-0.129417363409643
66271993281017.3006589914425.81672752953-9024.300658990910.509664428701021
67292710284951.6844451514120.903374296937758.31555484861-0.096399711316369
68295881289357.087379764297.232248283576523.912620239770.0557380803996539
69293299291689.9137150153080.480998435331609.08628498541-0.384794295264137



Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
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')