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Description of Statistical Computation

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, 29 Nov 2013 06:36:20 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/29/t13857250571cf6i14zp53us9l.htm/, Retrieved Mon, 06 May 2024 02:57:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229491, Retrieved Mon, 06 May 2024 02:57:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
- RM D        [Structural Time Series Models] [ws9 2] [2013-11-29 11:36:20] [d36997adcafcba0a4d18dd87f1a174ea] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 6 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229491&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229491&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229491&T=0

As an alternative you can also use a QR Code:  
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 time6 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1655362655362000
2873127804406.270817217154723.66978983968720.72918278260.792697781381092
311078971106300.63779134252402.5236210351596.362208664860.434957337700437
415559641514241.73456645361658.41568155741722.26543354540.490125218997499
516711591734860.34846504263973.661425898-63701.3484650378-0.4137976512751
614933081606381.34091051-4624.90867438636-113073.340910512-1.14966330893201
729577962589589.23105702673905.400680125368206.7689429822.9071334293725
826386912870691.93282971403718.86963183-232000.932829711-1.156156489603
913056691764653.85288982-634755.495959943-458984.852889824-4.44410988509648
1012804961125357.48640317-637878.215997435155138.513596834-0.0133636849287866
11921900813555.87986142-413672.625339348108344.120138580.959470784762586
12867888776975.148360408-154394.44315846290912.85163959161.10956307070096
13652586674263.043043139-118967.081855769-21677.04304313930.152133840402312
14913831817118.29669425661258.581966796796712.7033057440.783697784636652
1511085441100837.19712946209625.3725114367706.802870541030.630196214247842
1615558271402058.78520992270175.012413362153768.2147900770.263216866455932
1716992831685824.30765519279252.43313927613458.69234481150.0389643055351252
1815094582025952.93802306319595.258616362-516494.938023060.172020783859019
1932689752693984.92648707549922.935127363574990.0735129340.98611830013804
2024250162455590.5361482927803.9183219634-30574.5361482875-2.23553728269171
2113127031887240.74216706-367364.789501795-574537.742167058-1.69095075768284
2213654981322291.48774066-498337.76161889943206.5122593431-0.560523218644924
23934453883149.573812276-459116.92083427851303.42618772430.167847623405376
24775019614397.04662381-333135.170265809160621.953376190.539354990094884
25651142633505.356688571-99975.501269869617636.64331142951.00094352126735
26843192752375.11801008845074.412135745490816.88198991190.6217171636256
2711467661071980.14154407225370.48677726974785.85845592970.769405262111056
2816526011471062.66649293338941.272520412181538.3335070680.488287356746175
2914659061626318.1993766218206.615191827-160412.1993766-0.518534295030964
3016527342205887.05137829455393.024148022-553153.0513782891.01320209478391
3129223342258299.17734342191716.792067189664034.822656582-1.12747130480507
3227028052485325.18804676214831.173991222217479.8119532370.0989511868742471
3314589562139065.60150261-152861.885198379-680109.601502615-1.57359274744334
3414103631487508.58643397-479723.84503753-77145.5864339687-1.39878280234894
351019279985788.825884229-494133.65495961533490.1741157709-0.0616691419540275
36936574774886.570752386-308681.244405212161687.4292476140.794213859235905
37708917691302.904882645-161180.41114095417614.09511735540.63231491233377
38885295800990.64804691416266.164983703584304.35195308610.759309259060842
3910996631017114.005189146601.33908951982548.99481099780.557010142400845
4015762201322724.97615491250074.738472876253495.0238450850.443697340161415
4114878701748618.92954501364798.302453669-260748.9295450090.492143384389582
4214886352010215.70543903297435.3879405-521580.705439027-0.288124877486228
4328825302267215.03927286271094.349146423615314.960727136-0.11261605032918
4426770262324713.86848311132015.680678739352312.131516894-0.595133412995484
4514043982019831.92800518-152644.41689516-615433.928005179-1.2182865283996
4613443701491863.08348701-397249.206794858-147493.083487009-1.0468117072174
47936865991231.037080863-464609.891976463-54366.0370808627-0.28832009637793
48872705704400.339659038-348773.930269055168304.6603409620.496064585440203
49628151609708.893548849-183123.02846567218442.10645115120.70949258400527
50953712811251.90205585867500.5593414442142460.0979441421.07209030828603
5111603841091172.37080161205525.39409199269211.62919839060.590213658372561
5214006181248644.17487991174338.290689294151973.825120092-0.13361239250685
5316615111797784.55866388417973.358489318-136273.5586638831.0443518080831
5414953472109124.00099398348610.228705982-613777.000993983-0.296843977876798
5529187862296705.37529593243985.537437644622080.624704068-0.447395909886792
5627756772327785.78882779105763.616428471447891.21117221-0.591320956704601
5714070261999944.5843604-175778.823392583-592918.584360396-1.20487951667266
5813701991527005.29415834-368766.836205007-156806.294158337-0.825997988266398
599645261068224.38310689-427227.539281329-103698.383106894-0.250262249222115
60850851726189.274199237-371883.920261523124661.7258007630.236982799847482
61683118681906.495439164-158988.6635106241211.504560835760.911420825009972
62847224711405.302368401-36586.6819110019135818.6976315990.523566375076595
631073256929423.343106478128451.265808722143832.6568935220.705916124914252
6415143261412776.704785358337.189783297101549.2952150010.98450813997098
6515037341684675.44722847302288.604468051-180941.447228469-0.240149735808021
6615077122069108.47664058355589.320011833-561396.476640580.228154245919783
6728656982249922.90292182242260.613351824615775.097078177-0.484722179522536
6827881282252724.5292228187120.401559368535403.47077719-0.663634965792908
6913915961969764.57136546-152592.210370312-578168.571365458-1.0257973777395
7013663781535961.71044508-334761.549854313-169583.710445079-0.779759949949857
719462951084296.50475239-410508.113412565-138001.504752389-0.324294377837851
72859626782388.239886654-340116.39757633677237.76011334560.301390835179339

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 655362 & 655362 & 0 & 0 & 0 \tabularnewline
2 & 873127 & 804406.270817217 & 154723.669789839 & 68720.7291827826 & 0.792697781381092 \tabularnewline
3 & 1107897 & 1106300.63779134 & 252402.523621035 & 1596.36220866486 & 0.434957337700437 \tabularnewline
4 & 1555964 & 1514241.73456645 & 361658.415681557 & 41722.2654335454 & 0.490125218997499 \tabularnewline
5 & 1671159 & 1734860.34846504 & 263973.661425898 & -63701.3484650378 & -0.4137976512751 \tabularnewline
6 & 1493308 & 1606381.34091051 & -4624.90867438636 & -113073.340910512 & -1.14966330893201 \tabularnewline
7 & 2957796 & 2589589.23105702 & 673905.400680125 & 368206.768942982 & 2.9071334293725 \tabularnewline
8 & 2638691 & 2870691.93282971 & 403718.86963183 & -232000.932829711 & -1.156156489603 \tabularnewline
9 & 1305669 & 1764653.85288982 & -634755.495959943 & -458984.852889824 & -4.44410988509648 \tabularnewline
10 & 1280496 & 1125357.48640317 & -637878.215997435 & 155138.513596834 & -0.0133636849287866 \tabularnewline
11 & 921900 & 813555.87986142 & -413672.625339348 & 108344.12013858 & 0.959470784762586 \tabularnewline
12 & 867888 & 776975.148360408 & -154394.443158462 & 90912.8516395916 & 1.10956307070096 \tabularnewline
13 & 652586 & 674263.043043139 & -118967.081855769 & -21677.0430431393 & 0.152133840402312 \tabularnewline
14 & 913831 & 817118.296694256 & 61258.5819667967 & 96712.703305744 & 0.783697784636652 \tabularnewline
15 & 1108544 & 1100837.19712946 & 209625.372511436 & 7706.80287054103 & 0.630196214247842 \tabularnewline
16 & 1555827 & 1402058.78520992 & 270175.012413362 & 153768.214790077 & 0.263216866455932 \tabularnewline
17 & 1699283 & 1685824.30765519 & 279252.433139276 & 13458.6923448115 & 0.0389643055351252 \tabularnewline
18 & 1509458 & 2025952.93802306 & 319595.258616362 & -516494.93802306 & 0.172020783859019 \tabularnewline
19 & 3268975 & 2693984.92648707 & 549922.935127363 & 574990.073512934 & 0.98611830013804 \tabularnewline
20 & 2425016 & 2455590.53614829 & 27803.9183219634 & -30574.5361482875 & -2.23553728269171 \tabularnewline
21 & 1312703 & 1887240.74216706 & -367364.789501795 & -574537.742167058 & -1.69095075768284 \tabularnewline
22 & 1365498 & 1322291.48774066 & -498337.761618899 & 43206.5122593431 & -0.560523218644924 \tabularnewline
23 & 934453 & 883149.573812276 & -459116.920834278 & 51303.4261877243 & 0.167847623405376 \tabularnewline
24 & 775019 & 614397.04662381 & -333135.170265809 & 160621.95337619 & 0.539354990094884 \tabularnewline
25 & 651142 & 633505.356688571 & -99975.5012698696 & 17636.6433114295 & 1.00094352126735 \tabularnewline
26 & 843192 & 752375.118010088 & 45074.4121357454 & 90816.8819899119 & 0.6217171636256 \tabularnewline
27 & 1146766 & 1071980.14154407 & 225370.486777269 & 74785.8584559297 & 0.769405262111056 \tabularnewline
28 & 1652601 & 1471062.66649293 & 338941.272520412 & 181538.333507068 & 0.488287356746175 \tabularnewline
29 & 1465906 & 1626318.1993766 & 218206.615191827 & -160412.1993766 & -0.518534295030964 \tabularnewline
30 & 1652734 & 2205887.05137829 & 455393.024148022 & -553153.051378289 & 1.01320209478391 \tabularnewline
31 & 2922334 & 2258299.17734342 & 191716.792067189 & 664034.822656582 & -1.12747130480507 \tabularnewline
32 & 2702805 & 2485325.18804676 & 214831.173991222 & 217479.811953237 & 0.0989511868742471 \tabularnewline
33 & 1458956 & 2139065.60150261 & -152861.885198379 & -680109.601502615 & -1.57359274744334 \tabularnewline
34 & 1410363 & 1487508.58643397 & -479723.84503753 & -77145.5864339687 & -1.39878280234894 \tabularnewline
35 & 1019279 & 985788.825884229 & -494133.654959615 & 33490.1741157709 & -0.0616691419540275 \tabularnewline
36 & 936574 & 774886.570752386 & -308681.244405212 & 161687.429247614 & 0.794213859235905 \tabularnewline
37 & 708917 & 691302.904882645 & -161180.411140954 & 17614.0951173554 & 0.63231491233377 \tabularnewline
38 & 885295 & 800990.648046914 & 16266.1649837035 & 84304.3519530861 & 0.759309259060842 \tabularnewline
39 & 1099663 & 1017114.005189 & 146601.339089519 & 82548.9948109978 & 0.557010142400845 \tabularnewline
40 & 1576220 & 1322724.97615491 & 250074.738472876 & 253495.023845085 & 0.443697340161415 \tabularnewline
41 & 1487870 & 1748618.92954501 & 364798.302453669 & -260748.929545009 & 0.492143384389582 \tabularnewline
42 & 1488635 & 2010215.70543903 & 297435.3879405 & -521580.705439027 & -0.288124877486228 \tabularnewline
43 & 2882530 & 2267215.03927286 & 271094.349146423 & 615314.960727136 & -0.11261605032918 \tabularnewline
44 & 2677026 & 2324713.86848311 & 132015.680678739 & 352312.131516894 & -0.595133412995484 \tabularnewline
45 & 1404398 & 2019831.92800518 & -152644.41689516 & -615433.928005179 & -1.2182865283996 \tabularnewline
46 & 1344370 & 1491863.08348701 & -397249.206794858 & -147493.083487009 & -1.0468117072174 \tabularnewline
47 & 936865 & 991231.037080863 & -464609.891976463 & -54366.0370808627 & -0.28832009637793 \tabularnewline
48 & 872705 & 704400.339659038 & -348773.930269055 & 168304.660340962 & 0.496064585440203 \tabularnewline
49 & 628151 & 609708.893548849 & -183123.028465672 & 18442.1064511512 & 0.70949258400527 \tabularnewline
50 & 953712 & 811251.902055858 & 67500.5593414442 & 142460.097944142 & 1.07209030828603 \tabularnewline
51 & 1160384 & 1091172.37080161 & 205525.394091992 & 69211.6291983906 & 0.590213658372561 \tabularnewline
52 & 1400618 & 1248644.17487991 & 174338.290689294 & 151973.825120092 & -0.13361239250685 \tabularnewline
53 & 1661511 & 1797784.55866388 & 417973.358489318 & -136273.558663883 & 1.0443518080831 \tabularnewline
54 & 1495347 & 2109124.00099398 & 348610.228705982 & -613777.000993983 & -0.296843977876798 \tabularnewline
55 & 2918786 & 2296705.37529593 & 243985.537437644 & 622080.624704068 & -0.447395909886792 \tabularnewline
56 & 2775677 & 2327785.78882779 & 105763.616428471 & 447891.21117221 & -0.591320956704601 \tabularnewline
57 & 1407026 & 1999944.5843604 & -175778.823392583 & -592918.584360396 & -1.20487951667266 \tabularnewline
58 & 1370199 & 1527005.29415834 & -368766.836205007 & -156806.294158337 & -0.825997988266398 \tabularnewline
59 & 964526 & 1068224.38310689 & -427227.539281329 & -103698.383106894 & -0.250262249222115 \tabularnewline
60 & 850851 & 726189.274199237 & -371883.920261523 & 124661.725800763 & 0.236982799847482 \tabularnewline
61 & 683118 & 681906.495439164 & -158988.663510624 & 1211.50456083576 & 0.911420825009972 \tabularnewline
62 & 847224 & 711405.302368401 & -36586.6819110019 & 135818.697631599 & 0.523566375076595 \tabularnewline
63 & 1073256 & 929423.343106478 & 128451.265808722 & 143832.656893522 & 0.705916124914252 \tabularnewline
64 & 1514326 & 1412776.704785 & 358337.189783297 & 101549.295215001 & 0.98450813997098 \tabularnewline
65 & 1503734 & 1684675.44722847 & 302288.604468051 & -180941.447228469 & -0.240149735808021 \tabularnewline
66 & 1507712 & 2069108.47664058 & 355589.320011833 & -561396.47664058 & 0.228154245919783 \tabularnewline
67 & 2865698 & 2249922.90292182 & 242260.613351824 & 615775.097078177 & -0.484722179522536 \tabularnewline
68 & 2788128 & 2252724.52922281 & 87120.401559368 & 535403.47077719 & -0.663634965792908 \tabularnewline
69 & 1391596 & 1969764.57136546 & -152592.210370312 & -578168.571365458 & -1.0257973777395 \tabularnewline
70 & 1366378 & 1535961.71044508 & -334761.549854313 & -169583.710445079 & -0.779759949949857 \tabularnewline
71 & 946295 & 1084296.50475239 & -410508.113412565 & -138001.504752389 & -0.324294377837851 \tabularnewline
72 & 859626 & 782388.239886654 & -340116.397576336 & 77237.7601133456 & 0.301390835179339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229491&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]655362[/C][C]655362[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]873127[/C][C]804406.270817217[/C][C]154723.669789839[/C][C]68720.7291827826[/C][C]0.792697781381092[/C][/ROW]
[ROW][C]3[/C][C]1107897[/C][C]1106300.63779134[/C][C]252402.523621035[/C][C]1596.36220866486[/C][C]0.434957337700437[/C][/ROW]
[ROW][C]4[/C][C]1555964[/C][C]1514241.73456645[/C][C]361658.415681557[/C][C]41722.2654335454[/C][C]0.490125218997499[/C][/ROW]
[ROW][C]5[/C][C]1671159[/C][C]1734860.34846504[/C][C]263973.661425898[/C][C]-63701.3484650378[/C][C]-0.4137976512751[/C][/ROW]
[ROW][C]6[/C][C]1493308[/C][C]1606381.34091051[/C][C]-4624.90867438636[/C][C]-113073.340910512[/C][C]-1.14966330893201[/C][/ROW]
[ROW][C]7[/C][C]2957796[/C][C]2589589.23105702[/C][C]673905.400680125[/C][C]368206.768942982[/C][C]2.9071334293725[/C][/ROW]
[ROW][C]8[/C][C]2638691[/C][C]2870691.93282971[/C][C]403718.86963183[/C][C]-232000.932829711[/C][C]-1.156156489603[/C][/ROW]
[ROW][C]9[/C][C]1305669[/C][C]1764653.85288982[/C][C]-634755.495959943[/C][C]-458984.852889824[/C][C]-4.44410988509648[/C][/ROW]
[ROW][C]10[/C][C]1280496[/C][C]1125357.48640317[/C][C]-637878.215997435[/C][C]155138.513596834[/C][C]-0.0133636849287866[/C][/ROW]
[ROW][C]11[/C][C]921900[/C][C]813555.87986142[/C][C]-413672.625339348[/C][C]108344.12013858[/C][C]0.959470784762586[/C][/ROW]
[ROW][C]12[/C][C]867888[/C][C]776975.148360408[/C][C]-154394.443158462[/C][C]90912.8516395916[/C][C]1.10956307070096[/C][/ROW]
[ROW][C]13[/C][C]652586[/C][C]674263.043043139[/C][C]-118967.081855769[/C][C]-21677.0430431393[/C][C]0.152133840402312[/C][/ROW]
[ROW][C]14[/C][C]913831[/C][C]817118.296694256[/C][C]61258.5819667967[/C][C]96712.703305744[/C][C]0.783697784636652[/C][/ROW]
[ROW][C]15[/C][C]1108544[/C][C]1100837.19712946[/C][C]209625.372511436[/C][C]7706.80287054103[/C][C]0.630196214247842[/C][/ROW]
[ROW][C]16[/C][C]1555827[/C][C]1402058.78520992[/C][C]270175.012413362[/C][C]153768.214790077[/C][C]0.263216866455932[/C][/ROW]
[ROW][C]17[/C][C]1699283[/C][C]1685824.30765519[/C][C]279252.433139276[/C][C]13458.6923448115[/C][C]0.0389643055351252[/C][/ROW]
[ROW][C]18[/C][C]1509458[/C][C]2025952.93802306[/C][C]319595.258616362[/C][C]-516494.93802306[/C][C]0.172020783859019[/C][/ROW]
[ROW][C]19[/C][C]3268975[/C][C]2693984.92648707[/C][C]549922.935127363[/C][C]574990.073512934[/C][C]0.98611830013804[/C][/ROW]
[ROW][C]20[/C][C]2425016[/C][C]2455590.53614829[/C][C]27803.9183219634[/C][C]-30574.5361482875[/C][C]-2.23553728269171[/C][/ROW]
[ROW][C]21[/C][C]1312703[/C][C]1887240.74216706[/C][C]-367364.789501795[/C][C]-574537.742167058[/C][C]-1.69095075768284[/C][/ROW]
[ROW][C]22[/C][C]1365498[/C][C]1322291.48774066[/C][C]-498337.761618899[/C][C]43206.5122593431[/C][C]-0.560523218644924[/C][/ROW]
[ROW][C]23[/C][C]934453[/C][C]883149.573812276[/C][C]-459116.920834278[/C][C]51303.4261877243[/C][C]0.167847623405376[/C][/ROW]
[ROW][C]24[/C][C]775019[/C][C]614397.04662381[/C][C]-333135.170265809[/C][C]160621.95337619[/C][C]0.539354990094884[/C][/ROW]
[ROW][C]25[/C][C]651142[/C][C]633505.356688571[/C][C]-99975.5012698696[/C][C]17636.6433114295[/C][C]1.00094352126735[/C][/ROW]
[ROW][C]26[/C][C]843192[/C][C]752375.118010088[/C][C]45074.4121357454[/C][C]90816.8819899119[/C][C]0.6217171636256[/C][/ROW]
[ROW][C]27[/C][C]1146766[/C][C]1071980.14154407[/C][C]225370.486777269[/C][C]74785.8584559297[/C][C]0.769405262111056[/C][/ROW]
[ROW][C]28[/C][C]1652601[/C][C]1471062.66649293[/C][C]338941.272520412[/C][C]181538.333507068[/C][C]0.488287356746175[/C][/ROW]
[ROW][C]29[/C][C]1465906[/C][C]1626318.1993766[/C][C]218206.615191827[/C][C]-160412.1993766[/C][C]-0.518534295030964[/C][/ROW]
[ROW][C]30[/C][C]1652734[/C][C]2205887.05137829[/C][C]455393.024148022[/C][C]-553153.051378289[/C][C]1.01320209478391[/C][/ROW]
[ROW][C]31[/C][C]2922334[/C][C]2258299.17734342[/C][C]191716.792067189[/C][C]664034.822656582[/C][C]-1.12747130480507[/C][/ROW]
[ROW][C]32[/C][C]2702805[/C][C]2485325.18804676[/C][C]214831.173991222[/C][C]217479.811953237[/C][C]0.0989511868742471[/C][/ROW]
[ROW][C]33[/C][C]1458956[/C][C]2139065.60150261[/C][C]-152861.885198379[/C][C]-680109.601502615[/C][C]-1.57359274744334[/C][/ROW]
[ROW][C]34[/C][C]1410363[/C][C]1487508.58643397[/C][C]-479723.84503753[/C][C]-77145.5864339687[/C][C]-1.39878280234894[/C][/ROW]
[ROW][C]35[/C][C]1019279[/C][C]985788.825884229[/C][C]-494133.654959615[/C][C]33490.1741157709[/C][C]-0.0616691419540275[/C][/ROW]
[ROW][C]36[/C][C]936574[/C][C]774886.570752386[/C][C]-308681.244405212[/C][C]161687.429247614[/C][C]0.794213859235905[/C][/ROW]
[ROW][C]37[/C][C]708917[/C][C]691302.904882645[/C][C]-161180.411140954[/C][C]17614.0951173554[/C][C]0.63231491233377[/C][/ROW]
[ROW][C]38[/C][C]885295[/C][C]800990.648046914[/C][C]16266.1649837035[/C][C]84304.3519530861[/C][C]0.759309259060842[/C][/ROW]
[ROW][C]39[/C][C]1099663[/C][C]1017114.005189[/C][C]146601.339089519[/C][C]82548.9948109978[/C][C]0.557010142400845[/C][/ROW]
[ROW][C]40[/C][C]1576220[/C][C]1322724.97615491[/C][C]250074.738472876[/C][C]253495.023845085[/C][C]0.443697340161415[/C][/ROW]
[ROW][C]41[/C][C]1487870[/C][C]1748618.92954501[/C][C]364798.302453669[/C][C]-260748.929545009[/C][C]0.492143384389582[/C][/ROW]
[ROW][C]42[/C][C]1488635[/C][C]2010215.70543903[/C][C]297435.3879405[/C][C]-521580.705439027[/C][C]-0.288124877486228[/C][/ROW]
[ROW][C]43[/C][C]2882530[/C][C]2267215.03927286[/C][C]271094.349146423[/C][C]615314.960727136[/C][C]-0.11261605032918[/C][/ROW]
[ROW][C]44[/C][C]2677026[/C][C]2324713.86848311[/C][C]132015.680678739[/C][C]352312.131516894[/C][C]-0.595133412995484[/C][/ROW]
[ROW][C]45[/C][C]1404398[/C][C]2019831.92800518[/C][C]-152644.41689516[/C][C]-615433.928005179[/C][C]-1.2182865283996[/C][/ROW]
[ROW][C]46[/C][C]1344370[/C][C]1491863.08348701[/C][C]-397249.206794858[/C][C]-147493.083487009[/C][C]-1.0468117072174[/C][/ROW]
[ROW][C]47[/C][C]936865[/C][C]991231.037080863[/C][C]-464609.891976463[/C][C]-54366.0370808627[/C][C]-0.28832009637793[/C][/ROW]
[ROW][C]48[/C][C]872705[/C][C]704400.339659038[/C][C]-348773.930269055[/C][C]168304.660340962[/C][C]0.496064585440203[/C][/ROW]
[ROW][C]49[/C][C]628151[/C][C]609708.893548849[/C][C]-183123.028465672[/C][C]18442.1064511512[/C][C]0.70949258400527[/C][/ROW]
[ROW][C]50[/C][C]953712[/C][C]811251.902055858[/C][C]67500.5593414442[/C][C]142460.097944142[/C][C]1.07209030828603[/C][/ROW]
[ROW][C]51[/C][C]1160384[/C][C]1091172.37080161[/C][C]205525.394091992[/C][C]69211.6291983906[/C][C]0.590213658372561[/C][/ROW]
[ROW][C]52[/C][C]1400618[/C][C]1248644.17487991[/C][C]174338.290689294[/C][C]151973.825120092[/C][C]-0.13361239250685[/C][/ROW]
[ROW][C]53[/C][C]1661511[/C][C]1797784.55866388[/C][C]417973.358489318[/C][C]-136273.558663883[/C][C]1.0443518080831[/C][/ROW]
[ROW][C]54[/C][C]1495347[/C][C]2109124.00099398[/C][C]348610.228705982[/C][C]-613777.000993983[/C][C]-0.296843977876798[/C][/ROW]
[ROW][C]55[/C][C]2918786[/C][C]2296705.37529593[/C][C]243985.537437644[/C][C]622080.624704068[/C][C]-0.447395909886792[/C][/ROW]
[ROW][C]56[/C][C]2775677[/C][C]2327785.78882779[/C][C]105763.616428471[/C][C]447891.21117221[/C][C]-0.591320956704601[/C][/ROW]
[ROW][C]57[/C][C]1407026[/C][C]1999944.5843604[/C][C]-175778.823392583[/C][C]-592918.584360396[/C][C]-1.20487951667266[/C][/ROW]
[ROW][C]58[/C][C]1370199[/C][C]1527005.29415834[/C][C]-368766.836205007[/C][C]-156806.294158337[/C][C]-0.825997988266398[/C][/ROW]
[ROW][C]59[/C][C]964526[/C][C]1068224.38310689[/C][C]-427227.539281329[/C][C]-103698.383106894[/C][C]-0.250262249222115[/C][/ROW]
[ROW][C]60[/C][C]850851[/C][C]726189.274199237[/C][C]-371883.920261523[/C][C]124661.725800763[/C][C]0.236982799847482[/C][/ROW]
[ROW][C]61[/C][C]683118[/C][C]681906.495439164[/C][C]-158988.663510624[/C][C]1211.50456083576[/C][C]0.911420825009972[/C][/ROW]
[ROW][C]62[/C][C]847224[/C][C]711405.302368401[/C][C]-36586.6819110019[/C][C]135818.697631599[/C][C]0.523566375076595[/C][/ROW]
[ROW][C]63[/C][C]1073256[/C][C]929423.343106478[/C][C]128451.265808722[/C][C]143832.656893522[/C][C]0.705916124914252[/C][/ROW]
[ROW][C]64[/C][C]1514326[/C][C]1412776.704785[/C][C]358337.189783297[/C][C]101549.295215001[/C][C]0.98450813997098[/C][/ROW]
[ROW][C]65[/C][C]1503734[/C][C]1684675.44722847[/C][C]302288.604468051[/C][C]-180941.447228469[/C][C]-0.240149735808021[/C][/ROW]
[ROW][C]66[/C][C]1507712[/C][C]2069108.47664058[/C][C]355589.320011833[/C][C]-561396.47664058[/C][C]0.228154245919783[/C][/ROW]
[ROW][C]67[/C][C]2865698[/C][C]2249922.90292182[/C][C]242260.613351824[/C][C]615775.097078177[/C][C]-0.484722179522536[/C][/ROW]
[ROW][C]68[/C][C]2788128[/C][C]2252724.52922281[/C][C]87120.401559368[/C][C]535403.47077719[/C][C]-0.663634965792908[/C][/ROW]
[ROW][C]69[/C][C]1391596[/C][C]1969764.57136546[/C][C]-152592.210370312[/C][C]-578168.571365458[/C][C]-1.0257973777395[/C][/ROW]
[ROW][C]70[/C][C]1366378[/C][C]1535961.71044508[/C][C]-334761.549854313[/C][C]-169583.710445079[/C][C]-0.779759949949857[/C][/ROW]
[ROW][C]71[/C][C]946295[/C][C]1084296.50475239[/C][C]-410508.113412565[/C][C]-138001.504752389[/C][C]-0.324294377837851[/C][/ROW]
[ROW][C]72[/C][C]859626[/C][C]782388.239886654[/C][C]-340116.397576336[/C][C]77237.7601133456[/C][C]0.301390835179339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229491&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229491&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1655362655362000
2873127804406.270817217154723.66978983968720.72918278260.792697781381092
311078971106300.63779134252402.5236210351596.362208664860.434957337700437
415559641514241.73456645361658.41568155741722.26543354540.490125218997499
516711591734860.34846504263973.661425898-63701.3484650378-0.4137976512751
614933081606381.34091051-4624.90867438636-113073.340910512-1.14966330893201
729577962589589.23105702673905.400680125368206.7689429822.9071334293725
826386912870691.93282971403718.86963183-232000.932829711-1.156156489603
913056691764653.85288982-634755.495959943-458984.852889824-4.44410988509648
1012804961125357.48640317-637878.215997435155138.513596834-0.0133636849287866
11921900813555.87986142-413672.625339348108344.120138580.959470784762586
12867888776975.148360408-154394.44315846290912.85163959161.10956307070096
13652586674263.043043139-118967.081855769-21677.04304313930.152133840402312
14913831817118.29669425661258.581966796796712.7033057440.783697784636652
1511085441100837.19712946209625.3725114367706.802870541030.630196214247842
1615558271402058.78520992270175.012413362153768.2147900770.263216866455932
1716992831685824.30765519279252.43313927613458.69234481150.0389643055351252
1815094582025952.93802306319595.258616362-516494.938023060.172020783859019
1932689752693984.92648707549922.935127363574990.0735129340.98611830013804
2024250162455590.5361482927803.9183219634-30574.5361482875-2.23553728269171
2113127031887240.74216706-367364.789501795-574537.742167058-1.69095075768284
2213654981322291.48774066-498337.76161889943206.5122593431-0.560523218644924
23934453883149.573812276-459116.92083427851303.42618772430.167847623405376
24775019614397.04662381-333135.170265809160621.953376190.539354990094884
25651142633505.356688571-99975.501269869617636.64331142951.00094352126735
26843192752375.11801008845074.412135745490816.88198991190.6217171636256
2711467661071980.14154407225370.48677726974785.85845592970.769405262111056
2816526011471062.66649293338941.272520412181538.3335070680.488287356746175
2914659061626318.1993766218206.615191827-160412.1993766-0.518534295030964
3016527342205887.05137829455393.024148022-553153.0513782891.01320209478391
3129223342258299.17734342191716.792067189664034.822656582-1.12747130480507
3227028052485325.18804676214831.173991222217479.8119532370.0989511868742471
3314589562139065.60150261-152861.885198379-680109.601502615-1.57359274744334
3414103631487508.58643397-479723.84503753-77145.5864339687-1.39878280234894
351019279985788.825884229-494133.65495961533490.1741157709-0.0616691419540275
36936574774886.570752386-308681.244405212161687.4292476140.794213859235905
37708917691302.904882645-161180.41114095417614.09511735540.63231491233377
38885295800990.64804691416266.164983703584304.35195308610.759309259060842
3910996631017114.005189146601.33908951982548.99481099780.557010142400845
4015762201322724.97615491250074.738472876253495.0238450850.443697340161415
4114878701748618.92954501364798.302453669-260748.9295450090.492143384389582
4214886352010215.70543903297435.3879405-521580.705439027-0.288124877486228
4328825302267215.03927286271094.349146423615314.960727136-0.11261605032918
4426770262324713.86848311132015.680678739352312.131516894-0.595133412995484
4514043982019831.92800518-152644.41689516-615433.928005179-1.2182865283996
4613443701491863.08348701-397249.206794858-147493.083487009-1.0468117072174
47936865991231.037080863-464609.891976463-54366.0370808627-0.28832009637793
48872705704400.339659038-348773.930269055168304.6603409620.496064585440203
49628151609708.893548849-183123.02846567218442.10645115120.70949258400527
50953712811251.90205585867500.5593414442142460.0979441421.07209030828603
5111603841091172.37080161205525.39409199269211.62919839060.590213658372561
5214006181248644.17487991174338.290689294151973.825120092-0.13361239250685
5316615111797784.55866388417973.358489318-136273.5586638831.0443518080831
5414953472109124.00099398348610.228705982-613777.000993983-0.296843977876798
5529187862296705.37529593243985.537437644622080.624704068-0.447395909886792
5627756772327785.78882779105763.616428471447891.21117221-0.591320956704601
5714070261999944.5843604-175778.823392583-592918.584360396-1.20487951667266
5813701991527005.29415834-368766.836205007-156806.294158337-0.825997988266398
599645261068224.38310689-427227.539281329-103698.383106894-0.250262249222115
60850851726189.274199237-371883.920261523124661.7258007630.236982799847482
61683118681906.495439164-158988.6635106241211.504560835760.911420825009972
62847224711405.302368401-36586.6819110019135818.6976315990.523566375076595
631073256929423.343106478128451.265808722143832.6568935220.705916124914252
6415143261412776.704785358337.189783297101549.2952150010.98450813997098
6515037341684675.44722847302288.604468051-180941.447228469-0.240149735808021
6615077122069108.47664058355589.320011833-561396.476640580.228154245919783
6728656982249922.90292182242260.613351824615775.097078177-0.484722179522536
6827881282252724.5292228187120.401559368535403.47077719-0.663634965792908
6913915961969764.57136546-152592.210370312-578168.571365458-1.0257973777395
7013663781535961.71044508-334761.549854313-169583.710445079-0.779759949949857
719462951084296.50475239-410508.113412565-138001.504752389-0.324294377837851
72859626782388.239886654-340116.39757633677237.76011334560.301390835179339


Figures (Output of Computation)

Input Parameters & R Code

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$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
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='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')