Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationFri, 04 Dec 2009 05:25:21 -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/t12599295669pe316r4bwcd34g.htm/, Retrieved Sun, 28 Apr 2024 13:54:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63398, Retrieved Sun, 28 Apr 2024 13:54:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
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] [] [2009-12-04 12:25:21] [54f12ba6dfaf5b88c7c2745223d9c32f] [Current]
Feedback Forum

Post a new message
Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63398&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]3 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=63398&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63398&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
12036620366000
22278221193.6675851375958.9347181758261588.332414862530.997276983536058
31916920924.4843277242237.385385001715-1755.48432772419-0.437492457784884
41380716727.0517507557-2218.62355168664-2920.05175075572-1.73937110654325
52974323291.22899239252908.048171644946451.771007607473.32856330234781
62559127164.67867106603456.87449877651-1573.678671065970.342895434537874
72909629875.38734796313038.29426951669-779.387347963149-0.265218197482212
82648228863.1183195991756.640596866757-2381.11831959906-1.45026658659479
92240524643.7348440921-2055.24970013090-2238.73484409214-1.78290175841877
102704424815.3412892653-796.2870847985382228.658710734660.79788885643197
111797020594.9333592384-2731.72090378324-2624.93335923837-1.22685550331592
121873018041.7786043577-2630.82113190869688.2213956422960.0639589718187483
131968417941.3226596808-1209.029720840241742.677340319160.905671678121439
141978516976.2896379384-1071.192042822202808.710362061630.0888683917718068
151847917684.2722047980-79.0737090463728794.7277952020440.623777469104689
161069817853.985761065756.0249926095691-7155.985761065680.0858650176625413
173195623170.37347510622935.283018402998785.62652489381.85693005783753
182950629557.83912707134837.45981268984-51.83912707125551.20767469639308
193450634023.32146648794634.14817202373482.678533512138-0.128233395283186
202716531726.0347443636861.489801120861-4561.03474436356-2.38993447130127
212673629994.2967587512-552.503505558864-3258.29675875124-0.89706647400581
222369123175.8384658944-3974.65822862368515.161534105587-2.16959438384515
231815719624.5008052785-3743.49813450407-1467.500805278520.146545424076826
241732816921.9628292914-3175.53144022084406.0371707086490.360368606101136
251820515390.1210921186-2278.083326066942814.878907881380.57058953523941
262099516664.0275548978-335.9523741649514330.972445102161.23324769979221
271738217277.0723363253180.334664438083104.927663674720.326236378340560
28936719047.40811859761038.85127371424-9680.408118597620.544118254525539
293112423112.60016834022674.763424626858011.399831659841.04324384771461
302655126437.69816216573027.88550077186113.3018378342840.224605054653344
313065127996.16867660812230.958202097272654.83132339190-0.504303814073434
322585929000.19205396281567.90792866891-3141.19205396277-0.419449319291681
332510027138.4299432095-283.372743220674-2038.42994320953-1.17310080388471
342577825487.9281381442-1021.70396643237290.071861855767-0.468241959680586
352041822909.0547076613-1863.04916896555-2491.05470766127-0.533785528846109
361868819652.4171276587-2616.40031000041-964.417127658702-0.478219081961303
372042418145.9972831992-2015.791836675702278.002716800820.381239880619699
382477619263.6610800866-320.6801168345975512.338919913411.07411934126550
391981420470.2232877218502.928463061592-656.2232877217510.521086914453038
401273823113.37567280511653.24787540263-10375.37567280510.729162304600828
413156624521.75659827331521.580621980787044.24340172667-0.0837175067358104
423011128220.23263407072695.134362069321890.767365929290.745879219348724
433001928457.99849036071369.969586043141561.00150963933-0.839814572746483
443193431875.25249192132471.5540716714558.7475080787360.697118496416605
452582629872.174829828168.7404363168002-4046.17482982809-1.52170871095426
462683526574.1301062608-1738.24410910148260.8698937392-1.14590188775832
472020522653.0960196170-2910.44967679836-2448.09601961695-0.74404159149443
481778919330.2173855243-3132.16343074005-1541.21738552429-0.140755866161784
492052018392.0812694051-1951.852789843192127.918730594900.74870643142129
502251817551.1059180449-1354.679343648514966.89408195510.378241476645152
511557216924.2473486072-964.332482578171-1352.24734860720.247097371033234
521150919977.68135683581186.26399857658-8468.68135683581.3633303884715
532544720501.4710065703831.5444725689554945.52899342968-0.225304814152327
542409021504.4456840479923.4941328490332585.554315952090.0584038432930896
552778625317.58634528702474.253251731952468.413654713040.983207468070805
562619525493.74295112981242.73860389668701.25704887024-0.779676939134254
572051623839.9217403962-306.431655162060-3323.92174039622-0.98100859084074
582275921787.7739812756-1239.25411424985971.226018724396-0.591467686998088
591902820893.5151327091-1054.81738691758-1865.515132709110.117072143999097
601697119615.3722642040-1174.34133904716-2644.37226420395-0.0758740948010906
612003618351.9763427279-1222.030462859021684.02365727214-0.0302428817436366

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 20366 & 20366 & 0 & 0 & 0 \tabularnewline
2 & 22782 & 21193.6675851375 & 958.934718175826 & 1588.33241486253 & 0.997276983536058 \tabularnewline
3 & 19169 & 20924.4843277242 & 237.385385001715 & -1755.48432772419 & -0.437492457784884 \tabularnewline
4 & 13807 & 16727.0517507557 & -2218.62355168664 & -2920.05175075572 & -1.73937110654325 \tabularnewline
5 & 29743 & 23291.2289923925 & 2908.04817164494 & 6451.77100760747 & 3.32856330234781 \tabularnewline
6 & 25591 & 27164.6786710660 & 3456.87449877651 & -1573.67867106597 & 0.342895434537874 \tabularnewline
7 & 29096 & 29875.3873479631 & 3038.29426951669 & -779.387347963149 & -0.265218197482212 \tabularnewline
8 & 26482 & 28863.1183195991 & 756.640596866757 & -2381.11831959906 & -1.45026658659479 \tabularnewline
9 & 22405 & 24643.7348440921 & -2055.24970013090 & -2238.73484409214 & -1.78290175841877 \tabularnewline
10 & 27044 & 24815.3412892653 & -796.287084798538 & 2228.65871073466 & 0.79788885643197 \tabularnewline
11 & 17970 & 20594.9333592384 & -2731.72090378324 & -2624.93335923837 & -1.22685550331592 \tabularnewline
12 & 18730 & 18041.7786043577 & -2630.82113190869 & 688.221395642296 & 0.0639589718187483 \tabularnewline
13 & 19684 & 17941.3226596808 & -1209.02972084024 & 1742.67734031916 & 0.905671678121439 \tabularnewline
14 & 19785 & 16976.2896379384 & -1071.19204282220 & 2808.71036206163 & 0.0888683917718068 \tabularnewline
15 & 18479 & 17684.2722047980 & -79.0737090463728 & 794.727795202044 & 0.623777469104689 \tabularnewline
16 & 10698 & 17853.9857610657 & 56.0249926095691 & -7155.98576106568 & 0.0858650176625413 \tabularnewline
17 & 31956 & 23170.3734751062 & 2935.28301840299 & 8785.6265248938 & 1.85693005783753 \tabularnewline
18 & 29506 & 29557.8391270713 & 4837.45981268984 & -51.8391270712555 & 1.20767469639308 \tabularnewline
19 & 34506 & 34023.3214664879 & 4634.14817202373 & 482.678533512138 & -0.128233395283186 \tabularnewline
20 & 27165 & 31726.0347443636 & 861.489801120861 & -4561.03474436356 & -2.38993447130127 \tabularnewline
21 & 26736 & 29994.2967587512 & -552.503505558864 & -3258.29675875124 & -0.89706647400581 \tabularnewline
22 & 23691 & 23175.8384658944 & -3974.65822862368 & 515.161534105587 & -2.16959438384515 \tabularnewline
23 & 18157 & 19624.5008052785 & -3743.49813450407 & -1467.50080527852 & 0.146545424076826 \tabularnewline
24 & 17328 & 16921.9628292914 & -3175.53144022084 & 406.037170708649 & 0.360368606101136 \tabularnewline
25 & 18205 & 15390.1210921186 & -2278.08332606694 & 2814.87890788138 & 0.57058953523941 \tabularnewline
26 & 20995 & 16664.0275548978 & -335.952374164951 & 4330.97244510216 & 1.23324769979221 \tabularnewline
27 & 17382 & 17277.0723363253 & 180.334664438083 & 104.92766367472 & 0.326236378340560 \tabularnewline
28 & 9367 & 19047.4081185976 & 1038.85127371424 & -9680.40811859762 & 0.544118254525539 \tabularnewline
29 & 31124 & 23112.6001683402 & 2674.76342462685 & 8011.39983165984 & 1.04324384771461 \tabularnewline
30 & 26551 & 26437.6981621657 & 3027.88550077186 & 113.301837834284 & 0.224605054653344 \tabularnewline
31 & 30651 & 27996.1686766081 & 2230.95820209727 & 2654.83132339190 & -0.504303814073434 \tabularnewline
32 & 25859 & 29000.1920539628 & 1567.90792866891 & -3141.19205396277 & -0.419449319291681 \tabularnewline
33 & 25100 & 27138.4299432095 & -283.372743220674 & -2038.42994320953 & -1.17310080388471 \tabularnewline
34 & 25778 & 25487.9281381442 & -1021.70396643237 & 290.071861855767 & -0.468241959680586 \tabularnewline
35 & 20418 & 22909.0547076613 & -1863.04916896555 & -2491.05470766127 & -0.533785528846109 \tabularnewline
36 & 18688 & 19652.4171276587 & -2616.40031000041 & -964.417127658702 & -0.478219081961303 \tabularnewline
37 & 20424 & 18145.9972831992 & -2015.79183667570 & 2278.00271680082 & 0.381239880619699 \tabularnewline
38 & 24776 & 19263.6610800866 & -320.680116834597 & 5512.33891991341 & 1.07411934126550 \tabularnewline
39 & 19814 & 20470.2232877218 & 502.928463061592 & -656.223287721751 & 0.521086914453038 \tabularnewline
40 & 12738 & 23113.3756728051 & 1653.24787540263 & -10375.3756728051 & 0.729162304600828 \tabularnewline
41 & 31566 & 24521.7565982733 & 1521.58062198078 & 7044.24340172667 & -0.0837175067358104 \tabularnewline
42 & 30111 & 28220.2326340707 & 2695.13436206932 & 1890.76736592929 & 0.745879219348724 \tabularnewline
43 & 30019 & 28457.9984903607 & 1369.96958604314 & 1561.00150963933 & -0.839814572746483 \tabularnewline
44 & 31934 & 31875.2524919213 & 2471.55407167145 & 58.747508078736 & 0.697118496416605 \tabularnewline
45 & 25826 & 29872.1748298281 & 68.7404363168002 & -4046.17482982809 & -1.52170871095426 \tabularnewline
46 & 26835 & 26574.1301062608 & -1738.24410910148 & 260.8698937392 & -1.14590188775832 \tabularnewline
47 & 20205 & 22653.0960196170 & -2910.44967679836 & -2448.09601961695 & -0.74404159149443 \tabularnewline
48 & 17789 & 19330.2173855243 & -3132.16343074005 & -1541.21738552429 & -0.140755866161784 \tabularnewline
49 & 20520 & 18392.0812694051 & -1951.85278984319 & 2127.91873059490 & 0.74870643142129 \tabularnewline
50 & 22518 & 17551.1059180449 & -1354.67934364851 & 4966.8940819551 & 0.378241476645152 \tabularnewline
51 & 15572 & 16924.2473486072 & -964.332482578171 & -1352.2473486072 & 0.247097371033234 \tabularnewline
52 & 11509 & 19977.6813568358 & 1186.26399857658 & -8468.6813568358 & 1.3633303884715 \tabularnewline
53 & 25447 & 20501.4710065703 & 831.544472568955 & 4945.52899342968 & -0.225304814152327 \tabularnewline
54 & 24090 & 21504.4456840479 & 923.494132849033 & 2585.55431595209 & 0.0584038432930896 \tabularnewline
55 & 27786 & 25317.5863452870 & 2474.25325173195 & 2468.41365471304 & 0.983207468070805 \tabularnewline
56 & 26195 & 25493.7429511298 & 1242.73860389668 & 701.25704887024 & -0.779676939134254 \tabularnewline
57 & 20516 & 23839.9217403962 & -306.431655162060 & -3323.92174039622 & -0.98100859084074 \tabularnewline
58 & 22759 & 21787.7739812756 & -1239.25411424985 & 971.226018724396 & -0.591467686998088 \tabularnewline
59 & 19028 & 20893.5151327091 & -1054.81738691758 & -1865.51513270911 & 0.117072143999097 \tabularnewline
60 & 16971 & 19615.3722642040 & -1174.34133904716 & -2644.37226420395 & -0.0758740948010906 \tabularnewline
61 & 20036 & 18351.9763427279 & -1222.03046285902 & 1684.02365727214 & -0.0302428817436366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63398&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]20366[/C][C]20366[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]22782[/C][C]21193.6675851375[/C][C]958.934718175826[/C][C]1588.33241486253[/C][C]0.997276983536058[/C][/ROW]
[ROW][C]3[/C][C]19169[/C][C]20924.4843277242[/C][C]237.385385001715[/C][C]-1755.48432772419[/C][C]-0.437492457784884[/C][/ROW]
[ROW][C]4[/C][C]13807[/C][C]16727.0517507557[/C][C]-2218.62355168664[/C][C]-2920.05175075572[/C][C]-1.73937110654325[/C][/ROW]
[ROW][C]5[/C][C]29743[/C][C]23291.2289923925[/C][C]2908.04817164494[/C][C]6451.77100760747[/C][C]3.32856330234781[/C][/ROW]
[ROW][C]6[/C][C]25591[/C][C]27164.6786710660[/C][C]3456.87449877651[/C][C]-1573.67867106597[/C][C]0.342895434537874[/C][/ROW]
[ROW][C]7[/C][C]29096[/C][C]29875.3873479631[/C][C]3038.29426951669[/C][C]-779.387347963149[/C][C]-0.265218197482212[/C][/ROW]
[ROW][C]8[/C][C]26482[/C][C]28863.1183195991[/C][C]756.640596866757[/C][C]-2381.11831959906[/C][C]-1.45026658659479[/C][/ROW]
[ROW][C]9[/C][C]22405[/C][C]24643.7348440921[/C][C]-2055.24970013090[/C][C]-2238.73484409214[/C][C]-1.78290175841877[/C][/ROW]
[ROW][C]10[/C][C]27044[/C][C]24815.3412892653[/C][C]-796.287084798538[/C][C]2228.65871073466[/C][C]0.79788885643197[/C][/ROW]
[ROW][C]11[/C][C]17970[/C][C]20594.9333592384[/C][C]-2731.72090378324[/C][C]-2624.93335923837[/C][C]-1.22685550331592[/C][/ROW]
[ROW][C]12[/C][C]18730[/C][C]18041.7786043577[/C][C]-2630.82113190869[/C][C]688.221395642296[/C][C]0.0639589718187483[/C][/ROW]
[ROW][C]13[/C][C]19684[/C][C]17941.3226596808[/C][C]-1209.02972084024[/C][C]1742.67734031916[/C][C]0.905671678121439[/C][/ROW]
[ROW][C]14[/C][C]19785[/C][C]16976.2896379384[/C][C]-1071.19204282220[/C][C]2808.71036206163[/C][C]0.0888683917718068[/C][/ROW]
[ROW][C]15[/C][C]18479[/C][C]17684.2722047980[/C][C]-79.0737090463728[/C][C]794.727795202044[/C][C]0.623777469104689[/C][/ROW]
[ROW][C]16[/C][C]10698[/C][C]17853.9857610657[/C][C]56.0249926095691[/C][C]-7155.98576106568[/C][C]0.0858650176625413[/C][/ROW]
[ROW][C]17[/C][C]31956[/C][C]23170.3734751062[/C][C]2935.28301840299[/C][C]8785.6265248938[/C][C]1.85693005783753[/C][/ROW]
[ROW][C]18[/C][C]29506[/C][C]29557.8391270713[/C][C]4837.45981268984[/C][C]-51.8391270712555[/C][C]1.20767469639308[/C][/ROW]
[ROW][C]19[/C][C]34506[/C][C]34023.3214664879[/C][C]4634.14817202373[/C][C]482.678533512138[/C][C]-0.128233395283186[/C][/ROW]
[ROW][C]20[/C][C]27165[/C][C]31726.0347443636[/C][C]861.489801120861[/C][C]-4561.03474436356[/C][C]-2.38993447130127[/C][/ROW]
[ROW][C]21[/C][C]26736[/C][C]29994.2967587512[/C][C]-552.503505558864[/C][C]-3258.29675875124[/C][C]-0.89706647400581[/C][/ROW]
[ROW][C]22[/C][C]23691[/C][C]23175.8384658944[/C][C]-3974.65822862368[/C][C]515.161534105587[/C][C]-2.16959438384515[/C][/ROW]
[ROW][C]23[/C][C]18157[/C][C]19624.5008052785[/C][C]-3743.49813450407[/C][C]-1467.50080527852[/C][C]0.146545424076826[/C][/ROW]
[ROW][C]24[/C][C]17328[/C][C]16921.9628292914[/C][C]-3175.53144022084[/C][C]406.037170708649[/C][C]0.360368606101136[/C][/ROW]
[ROW][C]25[/C][C]18205[/C][C]15390.1210921186[/C][C]-2278.08332606694[/C][C]2814.87890788138[/C][C]0.57058953523941[/C][/ROW]
[ROW][C]26[/C][C]20995[/C][C]16664.0275548978[/C][C]-335.952374164951[/C][C]4330.97244510216[/C][C]1.23324769979221[/C][/ROW]
[ROW][C]27[/C][C]17382[/C][C]17277.0723363253[/C][C]180.334664438083[/C][C]104.92766367472[/C][C]0.326236378340560[/C][/ROW]
[ROW][C]28[/C][C]9367[/C][C]19047.4081185976[/C][C]1038.85127371424[/C][C]-9680.40811859762[/C][C]0.544118254525539[/C][/ROW]
[ROW][C]29[/C][C]31124[/C][C]23112.6001683402[/C][C]2674.76342462685[/C][C]8011.39983165984[/C][C]1.04324384771461[/C][/ROW]
[ROW][C]30[/C][C]26551[/C][C]26437.6981621657[/C][C]3027.88550077186[/C][C]113.301837834284[/C][C]0.224605054653344[/C][/ROW]
[ROW][C]31[/C][C]30651[/C][C]27996.1686766081[/C][C]2230.95820209727[/C][C]2654.83132339190[/C][C]-0.504303814073434[/C][/ROW]
[ROW][C]32[/C][C]25859[/C][C]29000.1920539628[/C][C]1567.90792866891[/C][C]-3141.19205396277[/C][C]-0.419449319291681[/C][/ROW]
[ROW][C]33[/C][C]25100[/C][C]27138.4299432095[/C][C]-283.372743220674[/C][C]-2038.42994320953[/C][C]-1.17310080388471[/C][/ROW]
[ROW][C]34[/C][C]25778[/C][C]25487.9281381442[/C][C]-1021.70396643237[/C][C]290.071861855767[/C][C]-0.468241959680586[/C][/ROW]
[ROW][C]35[/C][C]20418[/C][C]22909.0547076613[/C][C]-1863.04916896555[/C][C]-2491.05470766127[/C][C]-0.533785528846109[/C][/ROW]
[ROW][C]36[/C][C]18688[/C][C]19652.4171276587[/C][C]-2616.40031000041[/C][C]-964.417127658702[/C][C]-0.478219081961303[/C][/ROW]
[ROW][C]37[/C][C]20424[/C][C]18145.9972831992[/C][C]-2015.79183667570[/C][C]2278.00271680082[/C][C]0.381239880619699[/C][/ROW]
[ROW][C]38[/C][C]24776[/C][C]19263.6610800866[/C][C]-320.680116834597[/C][C]5512.33891991341[/C][C]1.07411934126550[/C][/ROW]
[ROW][C]39[/C][C]19814[/C][C]20470.2232877218[/C][C]502.928463061592[/C][C]-656.223287721751[/C][C]0.521086914453038[/C][/ROW]
[ROW][C]40[/C][C]12738[/C][C]23113.3756728051[/C][C]1653.24787540263[/C][C]-10375.3756728051[/C][C]0.729162304600828[/C][/ROW]
[ROW][C]41[/C][C]31566[/C][C]24521.7565982733[/C][C]1521.58062198078[/C][C]7044.24340172667[/C][C]-0.0837175067358104[/C][/ROW]
[ROW][C]42[/C][C]30111[/C][C]28220.2326340707[/C][C]2695.13436206932[/C][C]1890.76736592929[/C][C]0.745879219348724[/C][/ROW]
[ROW][C]43[/C][C]30019[/C][C]28457.9984903607[/C][C]1369.96958604314[/C][C]1561.00150963933[/C][C]-0.839814572746483[/C][/ROW]
[ROW][C]44[/C][C]31934[/C][C]31875.2524919213[/C][C]2471.55407167145[/C][C]58.747508078736[/C][C]0.697118496416605[/C][/ROW]
[ROW][C]45[/C][C]25826[/C][C]29872.1748298281[/C][C]68.7404363168002[/C][C]-4046.17482982809[/C][C]-1.52170871095426[/C][/ROW]
[ROW][C]46[/C][C]26835[/C][C]26574.1301062608[/C][C]-1738.24410910148[/C][C]260.8698937392[/C][C]-1.14590188775832[/C][/ROW]
[ROW][C]47[/C][C]20205[/C][C]22653.0960196170[/C][C]-2910.44967679836[/C][C]-2448.09601961695[/C][C]-0.74404159149443[/C][/ROW]
[ROW][C]48[/C][C]17789[/C][C]19330.2173855243[/C][C]-3132.16343074005[/C][C]-1541.21738552429[/C][C]-0.140755866161784[/C][/ROW]
[ROW][C]49[/C][C]20520[/C][C]18392.0812694051[/C][C]-1951.85278984319[/C][C]2127.91873059490[/C][C]0.74870643142129[/C][/ROW]
[ROW][C]50[/C][C]22518[/C][C]17551.1059180449[/C][C]-1354.67934364851[/C][C]4966.8940819551[/C][C]0.378241476645152[/C][/ROW]
[ROW][C]51[/C][C]15572[/C][C]16924.2473486072[/C][C]-964.332482578171[/C][C]-1352.2473486072[/C][C]0.247097371033234[/C][/ROW]
[ROW][C]52[/C][C]11509[/C][C]19977.6813568358[/C][C]1186.26399857658[/C][C]-8468.6813568358[/C][C]1.3633303884715[/C][/ROW]
[ROW][C]53[/C][C]25447[/C][C]20501.4710065703[/C][C]831.544472568955[/C][C]4945.52899342968[/C][C]-0.225304814152327[/C][/ROW]
[ROW][C]54[/C][C]24090[/C][C]21504.4456840479[/C][C]923.494132849033[/C][C]2585.55431595209[/C][C]0.0584038432930896[/C][/ROW]
[ROW][C]55[/C][C]27786[/C][C]25317.5863452870[/C][C]2474.25325173195[/C][C]2468.41365471304[/C][C]0.983207468070805[/C][/ROW]
[ROW][C]56[/C][C]26195[/C][C]25493.7429511298[/C][C]1242.73860389668[/C][C]701.25704887024[/C][C]-0.779676939134254[/C][/ROW]
[ROW][C]57[/C][C]20516[/C][C]23839.9217403962[/C][C]-306.431655162060[/C][C]-3323.92174039622[/C][C]-0.98100859084074[/C][/ROW]
[ROW][C]58[/C][C]22759[/C][C]21787.7739812756[/C][C]-1239.25411424985[/C][C]971.226018724396[/C][C]-0.591467686998088[/C][/ROW]
[ROW][C]59[/C][C]19028[/C][C]20893.5151327091[/C][C]-1054.81738691758[/C][C]-1865.51513270911[/C][C]0.117072143999097[/C][/ROW]
[ROW][C]60[/C][C]16971[/C][C]19615.3722642040[/C][C]-1174.34133904716[/C][C]-2644.37226420395[/C][C]-0.0758740948010906[/C][/ROW]
[ROW][C]61[/C][C]20036[/C][C]18351.9763427279[/C][C]-1222.03046285902[/C][C]1684.02365727214[/C][C]-0.0302428817436366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63398&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63398&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
12036620366000
22278221193.6675851375958.9347181758261588.332414862530.997276983536058
31916920924.4843277242237.385385001715-1755.48432772419-0.437492457784884
41380716727.0517507557-2218.62355168664-2920.05175075572-1.73937110654325
52974323291.22899239252908.048171644946451.771007607473.32856330234781
62559127164.67867106603456.87449877651-1573.678671065970.342895434537874
72909629875.38734796313038.29426951669-779.387347963149-0.265218197482212
82648228863.1183195991756.640596866757-2381.11831959906-1.45026658659479
92240524643.7348440921-2055.24970013090-2238.73484409214-1.78290175841877
102704424815.3412892653-796.2870847985382228.658710734660.79788885643197
111797020594.9333592384-2731.72090378324-2624.93335923837-1.22685550331592
121873018041.7786043577-2630.82113190869688.2213956422960.0639589718187483
131968417941.3226596808-1209.029720840241742.677340319160.905671678121439
141978516976.2896379384-1071.192042822202808.710362061630.0888683917718068
151847917684.2722047980-79.0737090463728794.7277952020440.623777469104689
161069817853.985761065756.0249926095691-7155.985761065680.0858650176625413
173195623170.37347510622935.283018402998785.62652489381.85693005783753
182950629557.83912707134837.45981268984-51.83912707125551.20767469639308
193450634023.32146648794634.14817202373482.678533512138-0.128233395283186
202716531726.0347443636861.489801120861-4561.03474436356-2.38993447130127
212673629994.2967587512-552.503505558864-3258.29675875124-0.89706647400581
222369123175.8384658944-3974.65822862368515.161534105587-2.16959438384515
231815719624.5008052785-3743.49813450407-1467.500805278520.146545424076826
241732816921.9628292914-3175.53144022084406.0371707086490.360368606101136
251820515390.1210921186-2278.083326066942814.878907881380.57058953523941
262099516664.0275548978-335.9523741649514330.972445102161.23324769979221
271738217277.0723363253180.334664438083104.927663674720.326236378340560
28936719047.40811859761038.85127371424-9680.408118597620.544118254525539
293112423112.60016834022674.763424626858011.399831659841.04324384771461
302655126437.69816216573027.88550077186113.3018378342840.224605054653344
313065127996.16867660812230.958202097272654.83132339190-0.504303814073434
322585929000.19205396281567.90792866891-3141.19205396277-0.419449319291681
332510027138.4299432095-283.372743220674-2038.42994320953-1.17310080388471
342577825487.9281381442-1021.70396643237290.071861855767-0.468241959680586
352041822909.0547076613-1863.04916896555-2491.05470766127-0.533785528846109
361868819652.4171276587-2616.40031000041-964.417127658702-0.478219081961303
372042418145.9972831992-2015.791836675702278.002716800820.381239880619699
382477619263.6610800866-320.6801168345975512.338919913411.07411934126550
391981420470.2232877218502.928463061592-656.2232877217510.521086914453038
401273823113.37567280511653.24787540263-10375.37567280510.729162304600828
413156624521.75659827331521.580621980787044.24340172667-0.0837175067358104
423011128220.23263407072695.134362069321890.767365929290.745879219348724
433001928457.99849036071369.969586043141561.00150963933-0.839814572746483
443193431875.25249192132471.5540716714558.7475080787360.697118496416605
452582629872.174829828168.7404363168002-4046.17482982809-1.52170871095426
462683526574.1301062608-1738.24410910148260.8698937392-1.14590188775832
472020522653.0960196170-2910.44967679836-2448.09601961695-0.74404159149443
481778919330.2173855243-3132.16343074005-1541.21738552429-0.140755866161784
492052018392.0812694051-1951.852789843192127.918730594900.74870643142129
502251817551.1059180449-1354.679343648514966.89408195510.378241476645152
511557216924.2473486072-964.332482578171-1352.24734860720.247097371033234
521150919977.68135683581186.26399857658-8468.68135683581.3633303884715
532544720501.4710065703831.5444725689554945.52899342968-0.225304814152327
542409021504.4456840479923.4941328490332585.554315952090.0584038432930896
552778625317.58634528702474.253251731952468.413654713040.983207468070805
562619525493.74295112981242.73860389668701.25704887024-0.779676939134254
572051623839.9217403962-306.431655162060-3323.92174039622-0.98100859084074
582275921787.7739812756-1239.25411424985971.226018724396-0.591467686998088
591902820893.5151327091-1054.81738691758-1865.515132709110.117072143999097
601697119615.3722642040-1174.34133904716-2644.37226420395-0.0758740948010906
612003618351.9763427279-1222.030462859021684.02365727214-0.0302428817436366



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')