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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, 10 Dec 2010 13:55:58 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/10/t1291989418nbs8cv00xl53l48.htm/, Retrieved Mon, 29 Apr 2024 12:26:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107688, Retrieved Mon, 29 Apr 2024 12:26:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact239

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]
-  M D      [Structural Time Series Models] [WS5] [2010-12-07 13:51:52] [fa854ea294f510d944d2dbf77761bfce]
-             [Structural Time Series Models] [ws5q5] [2010-12-08 19:32:28] [df61ce38492c371f14c407a12b3bb2eb]
-                 [Structural Time Series Models] [WSvraag5] [2010-12-10 13:55:58] [a35bd1e3fb5b4b301d5250bc2f7eb297] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13328
12873
14000
13477
14237
13674
13529
14058
12975
14326
14008
16193
14483
14011
15057
14884
15414
14440
14900
15074
14442
15307
14938
17193
15528
14765
15838
15723
16150
15486
15986
15983
15692
16490
15686
18897
16316
15636
17163
16534
16518
16375
16290
16352
15943
16362
16393
19051
16747
16320
17910
16961
17480
17049
16879
17473
16998
17307
17418
20169
17871
17226
19062
17804
19100
18522
18060
18869
18127
18871
18890
21263
19547
18450
20254
19240
20216
19420
19415
20018
18652
19978
19509
21971

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107688&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107688&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107688&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11332813328000
21287313200.60943725763.82152215418458-327.60943725757-1.30910910455104
31400013460.252713378221.9988103836074539.7472866218031.31766718817925
41347713535.986936847526.2778514725775-58.98693684750910.3119018951803
51423713789.380687607442.1621864062807447.6193123926241.58143678363955
61367413834.078546832842.304813576799-160.0785468327980.0192401175127454
71352913756.194174572836.7695778352094-227.194174572758-0.93687477922123
81405813824.108092922638.0413651349866233.8919070773720.243932780905403
91297513582.498439751627.0308655431981-607.498439751644-2.18563522321182
101432613729.747079441631.8415148666767596.2529205584470.935635145334216
111400813869.995006720536.3416212726261138.0049932794520.83989232790268
121619314657.751026420568.75452352292061535.248973579515.79778333316117
131448314940.968016369973.3764539119965-457.9680163698851.70441853624671
141401114973.304688225872.3101107570872-962.304688225774-0.329014378964596
151505714910.203527235866.739967786076146.796472764226-1.01366319307546
161488414966.765965331066.2089827983878-82.7659653309797-0.0721838684600287
171541414983.384596991863.3965754736545430.615403008248-0.352180429765533
181444014841.901262787951.7595341466996-401.901262787872-1.49386554764302
191490014877.572056401550.877898261684422.4279435984515-0.119893630636551
201507414855.282627259147.0432538657153218.717372740914-0.550703589224719
211444214996.138440519651.7709122935584-554.13844051960.707320665841406
221530715086.873875396653.6729327269379220.1261246033810.29317698821905
231493815227.867554008157.8168114646312-289.8675540080740.655223717116413
241719315465.187877777766.11861283523581727.812122222261.34613900460798
251552815699.356854263273.7849643858837-171.3568542632051.26383314497992
261476515768.896899981473.5864325978395-1003.89689998135-0.0318767913317064
271583815770.225099242470.022796617075967.7749007576431-0.53598968203871
281572315767.794008326466.2585553298344-44.794008326355-0.529666835606198
291615015725.549782990460.4284412968454424.450217009605-0.78914526021634
301548615780.155127015460.111468623206-294.155127015362-0.0425722754290249
311598615877.228637281662.1175757953697108.7713627184400.272499822725137
321598315928.547771348761.538676227111454.4522286513501-0.0800430636830513
331569216100.19146046367.3471799287255-408.1914604630150.816985506429388
341649016281.835561045773.2823838806303208.1644389542550.846804441462566
351568616325.100987659171.7432917911031-639.100987659145-0.222069430077944
361889716660.862017433585.18305080291852236.137982566501.95350170875901
371631616722.820466924284.000666347788-406.820466924182-0.172016459264779
381563616713.57660316279.2163022303728-1077.57660316201-0.690270569590547
391716316831.775272491081.242312767349331.2247275089730.287597218590611
401653416796.035807653275.0806559430563-262.035807653178-0.859203182183173
411651816595.763214220760.4294612260057-77.763214220708-2.01772361813529
421637516599.69346808957.407487084985-224.693468089016-0.414444134280058
431629016513.574055976749.7272941782886-223.574055976672-1.05580442807704
441635216484.458833482245.5216189412185-132.458833482220-0.581264011985356
451594316491.132400767643.4599349205430-548.132400767599-0.286540543738518
461636216429.665483083937.9219342010331-67.6654830839178-0.773357579733872
471639316668.180540711348.4616659078146-275.1805407113431.47741432595823
481905116787.462605731452.17348804589522263.537394268620.521644691090645
491674716927.772285837456.792677707048-180.7722858374190.649525131657709
501632017113.104170935863.5441761274461-793.1041709357860.947301688069572
511791017270.620728813968.4977148282845639.379271186090.691872668321675
521696117247.86541415963.6692206290222-286.865414158987-0.67085706019038
531748017325.068027142264.387494933109154.9319728577680.0993994143963147
541704917312.027770090460.2709331837657-263.027770090449-0.568790491786287
551687917242.323303609553.3581514597171-363.323303609512-0.955697068414683
561747317351.463417588556.3226004544241121.5365824114670.410502924565005
571699817478.671949963160.0840640137906-480.6719499631010.521762688225939
581730717568.384236594361.6535247190075-261.3842365942740.21801502975952
591741817693.238968756664.9964281204076-275.2389687566170.464906342198786
602016917860.159205893170.38270722124312308.84079410690.749748252953783
611787118029.545304558675.6140177325728-158.5453045586060.728434546245092
621722618110.440178205875.8932174272593-884.440178205750.0388587135122467
631906218234.470092425878.4407947006641827.5299075741540.354115600480104
641780418242.099181142574.6889953333371-438.099181142517-0.5206638162686
651910018466.823152610982.6455779130433633.176847389151.10276967932766
661852218650.022396045187.9810633800512-128.0223960450760.739082059332285
671806018689.525478585385.4083722329187-629.525478585296-0.356426798586708
681886918776.595620915185.496544124584692.40437908485570.0122216771278885
691812718804.520574680982.4431636156105-677.520574680931-0.423455696205232
701887118980.913044849487.4232641499781-109.9130448494240.690945687987493
711889019161.226321572392.3448685963206-271.2263215723370.683059514657614
722126319208.340009443589.94911582569272054.65999055652-0.332598175819422
731954719420.026166671296.3966483906145126.9738333288210.895250386793068
741845019505.233220722295.8039317238105-1055.23322072221-0.0822934402494889
752025419548.793369715693.0357655513966705.206630284366-0.384200720802587
761924019679.905850945595.0539453246925-439.9058509455030.279969699295708
772021619740.469860158493.2253639804314475.530139841585-0.253560638247648
781942019722.554141454487.3318635868154-302.554141454413-0.817063950179949
791941519854.625964114589.7044383627577-439.6259641145130.328941624394363
802001819957.113073549590.382276765725860.88692645049660.0939926577936619
811865219856.404442617680.250344656764-1204.40444261761-1.40517312873333
821997819952.881292408281.11056421088725.11870759180290.119315648765566
831950919964.528345092577.428629017943-455.52834509247-0.510744834039157
842197120006.573393243675.55330645478591964.42660675644-0.260161365412173

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 13328 & 13328 & 0 & 0 & 0 \tabularnewline
2 & 12873 & 13200.6094372576 & 3.82152215418458 & -327.60943725757 & -1.30910910455104 \tabularnewline
3 & 14000 & 13460.2527133782 & 21.9988103836074 & 539.747286621803 & 1.31766718817925 \tabularnewline
4 & 13477 & 13535.9869368475 & 26.2778514725775 & -58.9869368475091 & 0.3119018951803 \tabularnewline
5 & 14237 & 13789.3806876074 & 42.1621864062807 & 447.619312392624 & 1.58143678363955 \tabularnewline
6 & 13674 & 13834.0785468328 & 42.304813576799 & -160.078546832798 & 0.0192401175127454 \tabularnewline
7 & 13529 & 13756.1941745728 & 36.7695778352094 & -227.194174572758 & -0.93687477922123 \tabularnewline
8 & 14058 & 13824.1080929226 & 38.0413651349866 & 233.891907077372 & 0.243932780905403 \tabularnewline
9 & 12975 & 13582.4984397516 & 27.0308655431981 & -607.498439751644 & -2.18563522321182 \tabularnewline
10 & 14326 & 13729.7470794416 & 31.8415148666767 & 596.252920558447 & 0.935635145334216 \tabularnewline
11 & 14008 & 13869.9950067205 & 36.3416212726261 & 138.004993279452 & 0.83989232790268 \tabularnewline
12 & 16193 & 14657.7510264205 & 68.7545235229206 & 1535.24897357951 & 5.79778333316117 \tabularnewline
13 & 14483 & 14940.9680163699 & 73.3764539119965 & -457.968016369885 & 1.70441853624671 \tabularnewline
14 & 14011 & 14973.3046882258 & 72.3101107570872 & -962.304688225774 & -0.329014378964596 \tabularnewline
15 & 15057 & 14910.2035272358 & 66.739967786076 & 146.796472764226 & -1.01366319307546 \tabularnewline
16 & 14884 & 14966.7659653310 & 66.2089827983878 & -82.7659653309797 & -0.0721838684600287 \tabularnewline
17 & 15414 & 14983.3845969918 & 63.3965754736545 & 430.615403008248 & -0.352180429765533 \tabularnewline
18 & 14440 & 14841.9012627879 & 51.7595341466996 & -401.901262787872 & -1.49386554764302 \tabularnewline
19 & 14900 & 14877.5720564015 & 50.8778982616844 & 22.4279435984515 & -0.119893630636551 \tabularnewline
20 & 15074 & 14855.2826272591 & 47.0432538657153 & 218.717372740914 & -0.550703589224719 \tabularnewline
21 & 14442 & 14996.1384405196 & 51.7709122935584 & -554.1384405196 & 0.707320665841406 \tabularnewline
22 & 15307 & 15086.8738753966 & 53.6729327269379 & 220.126124603381 & 0.29317698821905 \tabularnewline
23 & 14938 & 15227.8675540081 & 57.8168114646312 & -289.867554008074 & 0.655223717116413 \tabularnewline
24 & 17193 & 15465.1878777777 & 66.1186128352358 & 1727.81212222226 & 1.34613900460798 \tabularnewline
25 & 15528 & 15699.3568542632 & 73.7849643858837 & -171.356854263205 & 1.26383314497992 \tabularnewline
26 & 14765 & 15768.8968999814 & 73.5864325978395 & -1003.89689998135 & -0.0318767913317064 \tabularnewline
27 & 15838 & 15770.2250992424 & 70.0227966170759 & 67.7749007576431 & -0.53598968203871 \tabularnewline
28 & 15723 & 15767.7940083264 & 66.2585553298344 & -44.794008326355 & -0.529666835606198 \tabularnewline
29 & 16150 & 15725.5497829904 & 60.4284412968454 & 424.450217009605 & -0.78914526021634 \tabularnewline
30 & 15486 & 15780.1551270154 & 60.111468623206 & -294.155127015362 & -0.0425722754290249 \tabularnewline
31 & 15986 & 15877.2286372816 & 62.1175757953697 & 108.771362718440 & 0.272499822725137 \tabularnewline
32 & 15983 & 15928.5477713487 & 61.5386762271114 & 54.4522286513501 & -0.0800430636830513 \tabularnewline
33 & 15692 & 16100.191460463 & 67.3471799287255 & -408.191460463015 & 0.816985506429388 \tabularnewline
34 & 16490 & 16281.8355610457 & 73.2823838806303 & 208.164438954255 & 0.846804441462566 \tabularnewline
35 & 15686 & 16325.1009876591 & 71.7432917911031 & -639.100987659145 & -0.222069430077944 \tabularnewline
36 & 18897 & 16660.8620174335 & 85.1830508029185 & 2236.13798256650 & 1.95350170875901 \tabularnewline
37 & 16316 & 16722.8204669242 & 84.000666347788 & -406.820466924182 & -0.172016459264779 \tabularnewline
38 & 15636 & 16713.576603162 & 79.2163022303728 & -1077.57660316201 & -0.690270569590547 \tabularnewline
39 & 17163 & 16831.7752724910 & 81.242312767349 & 331.224727508973 & 0.287597218590611 \tabularnewline
40 & 16534 & 16796.0358076532 & 75.0806559430563 & -262.035807653178 & -0.859203182183173 \tabularnewline
41 & 16518 & 16595.7632142207 & 60.4294612260057 & -77.763214220708 & -2.01772361813529 \tabularnewline
42 & 16375 & 16599.693468089 & 57.407487084985 & -224.693468089016 & -0.414444134280058 \tabularnewline
43 & 16290 & 16513.5740559767 & 49.7272941782886 & -223.574055976672 & -1.05580442807704 \tabularnewline
44 & 16352 & 16484.4588334822 & 45.5216189412185 & -132.458833482220 & -0.581264011985356 \tabularnewline
45 & 15943 & 16491.1324007676 & 43.4599349205430 & -548.132400767599 & -0.286540543738518 \tabularnewline
46 & 16362 & 16429.6654830839 & 37.9219342010331 & -67.6654830839178 & -0.773357579733872 \tabularnewline
47 & 16393 & 16668.1805407113 & 48.4616659078146 & -275.180540711343 & 1.47741432595823 \tabularnewline
48 & 19051 & 16787.4626057314 & 52.1734880458952 & 2263.53739426862 & 0.521644691090645 \tabularnewline
49 & 16747 & 16927.7722858374 & 56.792677707048 & -180.772285837419 & 0.649525131657709 \tabularnewline
50 & 16320 & 17113.1041709358 & 63.5441761274461 & -793.104170935786 & 0.947301688069572 \tabularnewline
51 & 17910 & 17270.6207288139 & 68.4977148282845 & 639.37927118609 & 0.691872668321675 \tabularnewline
52 & 16961 & 17247.865414159 & 63.6692206290222 & -286.865414158987 & -0.67085706019038 \tabularnewline
53 & 17480 & 17325.0680271422 & 64.387494933109 & 154.931972857768 & 0.0993994143963147 \tabularnewline
54 & 17049 & 17312.0277700904 & 60.2709331837657 & -263.027770090449 & -0.568790491786287 \tabularnewline
55 & 16879 & 17242.3233036095 & 53.3581514597171 & -363.323303609512 & -0.955697068414683 \tabularnewline
56 & 17473 & 17351.4634175885 & 56.3226004544241 & 121.536582411467 & 0.410502924565005 \tabularnewline
57 & 16998 & 17478.6719499631 & 60.0840640137906 & -480.671949963101 & 0.521762688225939 \tabularnewline
58 & 17307 & 17568.3842365943 & 61.6535247190075 & -261.384236594274 & 0.21801502975952 \tabularnewline
59 & 17418 & 17693.2389687566 & 64.9964281204076 & -275.238968756617 & 0.464906342198786 \tabularnewline
60 & 20169 & 17860.1592058931 & 70.3827072212431 & 2308.8407941069 & 0.749748252953783 \tabularnewline
61 & 17871 & 18029.5453045586 & 75.6140177325728 & -158.545304558606 & 0.728434546245092 \tabularnewline
62 & 17226 & 18110.4401782058 & 75.8932174272593 & -884.44017820575 & 0.0388587135122467 \tabularnewline
63 & 19062 & 18234.4700924258 & 78.4407947006641 & 827.529907574154 & 0.354115600480104 \tabularnewline
64 & 17804 & 18242.0991811425 & 74.6889953333371 & -438.099181142517 & -0.5206638162686 \tabularnewline
65 & 19100 & 18466.8231526109 & 82.6455779130433 & 633.17684738915 & 1.10276967932766 \tabularnewline
66 & 18522 & 18650.0223960451 & 87.9810633800512 & -128.022396045076 & 0.739082059332285 \tabularnewline
67 & 18060 & 18689.5254785853 & 85.4083722329187 & -629.525478585296 & -0.356426798586708 \tabularnewline
68 & 18869 & 18776.5956209151 & 85.4965441245846 & 92.4043790848557 & 0.0122216771278885 \tabularnewline
69 & 18127 & 18804.5205746809 & 82.4431636156105 & -677.520574680931 & -0.423455696205232 \tabularnewline
70 & 18871 & 18980.9130448494 & 87.4232641499781 & -109.913044849424 & 0.690945687987493 \tabularnewline
71 & 18890 & 19161.2263215723 & 92.3448685963206 & -271.226321572337 & 0.683059514657614 \tabularnewline
72 & 21263 & 19208.3400094435 & 89.9491158256927 & 2054.65999055652 & -0.332598175819422 \tabularnewline
73 & 19547 & 19420.0261666712 & 96.3966483906145 & 126.973833328821 & 0.895250386793068 \tabularnewline
74 & 18450 & 19505.2332207222 & 95.8039317238105 & -1055.23322072221 & -0.0822934402494889 \tabularnewline
75 & 20254 & 19548.7933697156 & 93.0357655513966 & 705.206630284366 & -0.384200720802587 \tabularnewline
76 & 19240 & 19679.9058509455 & 95.0539453246925 & -439.905850945503 & 0.279969699295708 \tabularnewline
77 & 20216 & 19740.4698601584 & 93.2253639804314 & 475.530139841585 & -0.253560638247648 \tabularnewline
78 & 19420 & 19722.5541414544 & 87.3318635868154 & -302.554141454413 & -0.817063950179949 \tabularnewline
79 & 19415 & 19854.6259641145 & 89.7044383627577 & -439.625964114513 & 0.328941624394363 \tabularnewline
80 & 20018 & 19957.1130735495 & 90.3822767657258 & 60.8869264504966 & 0.0939926577936619 \tabularnewline
81 & 18652 & 19856.4044426176 & 80.250344656764 & -1204.40444261761 & -1.40517312873333 \tabularnewline
82 & 19978 & 19952.8812924082 & 81.110564210887 & 25.1187075918029 & 0.119315648765566 \tabularnewline
83 & 19509 & 19964.5283450925 & 77.428629017943 & -455.52834509247 & -0.510744834039157 \tabularnewline
84 & 21971 & 20006.5733932436 & 75.5533064547859 & 1964.42660675644 & -0.260161365412173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107688&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]13328[/C][C]13328[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]12873[/C][C]13200.6094372576[/C][C]3.82152215418458[/C][C]-327.60943725757[/C][C]-1.30910910455104[/C][/ROW]
[ROW][C]3[/C][C]14000[/C][C]13460.2527133782[/C][C]21.9988103836074[/C][C]539.747286621803[/C][C]1.31766718817925[/C][/ROW]
[ROW][C]4[/C][C]13477[/C][C]13535.9869368475[/C][C]26.2778514725775[/C][C]-58.9869368475091[/C][C]0.3119018951803[/C][/ROW]
[ROW][C]5[/C][C]14237[/C][C]13789.3806876074[/C][C]42.1621864062807[/C][C]447.619312392624[/C][C]1.58143678363955[/C][/ROW]
[ROW][C]6[/C][C]13674[/C][C]13834.0785468328[/C][C]42.304813576799[/C][C]-160.078546832798[/C][C]0.0192401175127454[/C][/ROW]
[ROW][C]7[/C][C]13529[/C][C]13756.1941745728[/C][C]36.7695778352094[/C][C]-227.194174572758[/C][C]-0.93687477922123[/C][/ROW]
[ROW][C]8[/C][C]14058[/C][C]13824.1080929226[/C][C]38.0413651349866[/C][C]233.891907077372[/C][C]0.243932780905403[/C][/ROW]
[ROW][C]9[/C][C]12975[/C][C]13582.4984397516[/C][C]27.0308655431981[/C][C]-607.498439751644[/C][C]-2.18563522321182[/C][/ROW]
[ROW][C]10[/C][C]14326[/C][C]13729.7470794416[/C][C]31.8415148666767[/C][C]596.252920558447[/C][C]0.935635145334216[/C][/ROW]
[ROW][C]11[/C][C]14008[/C][C]13869.9950067205[/C][C]36.3416212726261[/C][C]138.004993279452[/C][C]0.83989232790268[/C][/ROW]
[ROW][C]12[/C][C]16193[/C][C]14657.7510264205[/C][C]68.7545235229206[/C][C]1535.24897357951[/C][C]5.79778333316117[/C][/ROW]
[ROW][C]13[/C][C]14483[/C][C]14940.9680163699[/C][C]73.3764539119965[/C][C]-457.968016369885[/C][C]1.70441853624671[/C][/ROW]
[ROW][C]14[/C][C]14011[/C][C]14973.3046882258[/C][C]72.3101107570872[/C][C]-962.304688225774[/C][C]-0.329014378964596[/C][/ROW]
[ROW][C]15[/C][C]15057[/C][C]14910.2035272358[/C][C]66.739967786076[/C][C]146.796472764226[/C][C]-1.01366319307546[/C][/ROW]
[ROW][C]16[/C][C]14884[/C][C]14966.7659653310[/C][C]66.2089827983878[/C][C]-82.7659653309797[/C][C]-0.0721838684600287[/C][/ROW]
[ROW][C]17[/C][C]15414[/C][C]14983.3845969918[/C][C]63.3965754736545[/C][C]430.615403008248[/C][C]-0.352180429765533[/C][/ROW]
[ROW][C]18[/C][C]14440[/C][C]14841.9012627879[/C][C]51.7595341466996[/C][C]-401.901262787872[/C][C]-1.49386554764302[/C][/ROW]
[ROW][C]19[/C][C]14900[/C][C]14877.5720564015[/C][C]50.8778982616844[/C][C]22.4279435984515[/C][C]-0.119893630636551[/C][/ROW]
[ROW][C]20[/C][C]15074[/C][C]14855.2826272591[/C][C]47.0432538657153[/C][C]218.717372740914[/C][C]-0.550703589224719[/C][/ROW]
[ROW][C]21[/C][C]14442[/C][C]14996.1384405196[/C][C]51.7709122935584[/C][C]-554.1384405196[/C][C]0.707320665841406[/C][/ROW]
[ROW][C]22[/C][C]15307[/C][C]15086.8738753966[/C][C]53.6729327269379[/C][C]220.126124603381[/C][C]0.29317698821905[/C][/ROW]
[ROW][C]23[/C][C]14938[/C][C]15227.8675540081[/C][C]57.8168114646312[/C][C]-289.867554008074[/C][C]0.655223717116413[/C][/ROW]
[ROW][C]24[/C][C]17193[/C][C]15465.1878777777[/C][C]66.1186128352358[/C][C]1727.81212222226[/C][C]1.34613900460798[/C][/ROW]
[ROW][C]25[/C][C]15528[/C][C]15699.3568542632[/C][C]73.7849643858837[/C][C]-171.356854263205[/C][C]1.26383314497992[/C][/ROW]
[ROW][C]26[/C][C]14765[/C][C]15768.8968999814[/C][C]73.5864325978395[/C][C]-1003.89689998135[/C][C]-0.0318767913317064[/C][/ROW]
[ROW][C]27[/C][C]15838[/C][C]15770.2250992424[/C][C]70.0227966170759[/C][C]67.7749007576431[/C][C]-0.53598968203871[/C][/ROW]
[ROW][C]28[/C][C]15723[/C][C]15767.7940083264[/C][C]66.2585553298344[/C][C]-44.794008326355[/C][C]-0.529666835606198[/C][/ROW]
[ROW][C]29[/C][C]16150[/C][C]15725.5497829904[/C][C]60.4284412968454[/C][C]424.450217009605[/C][C]-0.78914526021634[/C][/ROW]
[ROW][C]30[/C][C]15486[/C][C]15780.1551270154[/C][C]60.111468623206[/C][C]-294.155127015362[/C][C]-0.0425722754290249[/C][/ROW]
[ROW][C]31[/C][C]15986[/C][C]15877.2286372816[/C][C]62.1175757953697[/C][C]108.771362718440[/C][C]0.272499822725137[/C][/ROW]
[ROW][C]32[/C][C]15983[/C][C]15928.5477713487[/C][C]61.5386762271114[/C][C]54.4522286513501[/C][C]-0.0800430636830513[/C][/ROW]
[ROW][C]33[/C][C]15692[/C][C]16100.191460463[/C][C]67.3471799287255[/C][C]-408.191460463015[/C][C]0.816985506429388[/C][/ROW]
[ROW][C]34[/C][C]16490[/C][C]16281.8355610457[/C][C]73.2823838806303[/C][C]208.164438954255[/C][C]0.846804441462566[/C][/ROW]
[ROW][C]35[/C][C]15686[/C][C]16325.1009876591[/C][C]71.7432917911031[/C][C]-639.100987659145[/C][C]-0.222069430077944[/C][/ROW]
[ROW][C]36[/C][C]18897[/C][C]16660.8620174335[/C][C]85.1830508029185[/C][C]2236.13798256650[/C][C]1.95350170875901[/C][/ROW]
[ROW][C]37[/C][C]16316[/C][C]16722.8204669242[/C][C]84.000666347788[/C][C]-406.820466924182[/C][C]-0.172016459264779[/C][/ROW]
[ROW][C]38[/C][C]15636[/C][C]16713.576603162[/C][C]79.2163022303728[/C][C]-1077.57660316201[/C][C]-0.690270569590547[/C][/ROW]
[ROW][C]39[/C][C]17163[/C][C]16831.7752724910[/C][C]81.242312767349[/C][C]331.224727508973[/C][C]0.287597218590611[/C][/ROW]
[ROW][C]40[/C][C]16534[/C][C]16796.0358076532[/C][C]75.0806559430563[/C][C]-262.035807653178[/C][C]-0.859203182183173[/C][/ROW]
[ROW][C]41[/C][C]16518[/C][C]16595.7632142207[/C][C]60.4294612260057[/C][C]-77.763214220708[/C][C]-2.01772361813529[/C][/ROW]
[ROW][C]42[/C][C]16375[/C][C]16599.693468089[/C][C]57.407487084985[/C][C]-224.693468089016[/C][C]-0.414444134280058[/C][/ROW]
[ROW][C]43[/C][C]16290[/C][C]16513.5740559767[/C][C]49.7272941782886[/C][C]-223.574055976672[/C][C]-1.05580442807704[/C][/ROW]
[ROW][C]44[/C][C]16352[/C][C]16484.4588334822[/C][C]45.5216189412185[/C][C]-132.458833482220[/C][C]-0.581264011985356[/C][/ROW]
[ROW][C]45[/C][C]15943[/C][C]16491.1324007676[/C][C]43.4599349205430[/C][C]-548.132400767599[/C][C]-0.286540543738518[/C][/ROW]
[ROW][C]46[/C][C]16362[/C][C]16429.6654830839[/C][C]37.9219342010331[/C][C]-67.6654830839178[/C][C]-0.773357579733872[/C][/ROW]
[ROW][C]47[/C][C]16393[/C][C]16668.1805407113[/C][C]48.4616659078146[/C][C]-275.180540711343[/C][C]1.47741432595823[/C][/ROW]
[ROW][C]48[/C][C]19051[/C][C]16787.4626057314[/C][C]52.1734880458952[/C][C]2263.53739426862[/C][C]0.521644691090645[/C][/ROW]
[ROW][C]49[/C][C]16747[/C][C]16927.7722858374[/C][C]56.792677707048[/C][C]-180.772285837419[/C][C]0.649525131657709[/C][/ROW]
[ROW][C]50[/C][C]16320[/C][C]17113.1041709358[/C][C]63.5441761274461[/C][C]-793.104170935786[/C][C]0.947301688069572[/C][/ROW]
[ROW][C]51[/C][C]17910[/C][C]17270.6207288139[/C][C]68.4977148282845[/C][C]639.37927118609[/C][C]0.691872668321675[/C][/ROW]
[ROW][C]52[/C][C]16961[/C][C]17247.865414159[/C][C]63.6692206290222[/C][C]-286.865414158987[/C][C]-0.67085706019038[/C][/ROW]
[ROW][C]53[/C][C]17480[/C][C]17325.0680271422[/C][C]64.387494933109[/C][C]154.931972857768[/C][C]0.0993994143963147[/C][/ROW]
[ROW][C]54[/C][C]17049[/C][C]17312.0277700904[/C][C]60.2709331837657[/C][C]-263.027770090449[/C][C]-0.568790491786287[/C][/ROW]
[ROW][C]55[/C][C]16879[/C][C]17242.3233036095[/C][C]53.3581514597171[/C][C]-363.323303609512[/C][C]-0.955697068414683[/C][/ROW]
[ROW][C]56[/C][C]17473[/C][C]17351.4634175885[/C][C]56.3226004544241[/C][C]121.536582411467[/C][C]0.410502924565005[/C][/ROW]
[ROW][C]57[/C][C]16998[/C][C]17478.6719499631[/C][C]60.0840640137906[/C][C]-480.671949963101[/C][C]0.521762688225939[/C][/ROW]
[ROW][C]58[/C][C]17307[/C][C]17568.3842365943[/C][C]61.6535247190075[/C][C]-261.384236594274[/C][C]0.21801502975952[/C][/ROW]
[ROW][C]59[/C][C]17418[/C][C]17693.2389687566[/C][C]64.9964281204076[/C][C]-275.238968756617[/C][C]0.464906342198786[/C][/ROW]
[ROW][C]60[/C][C]20169[/C][C]17860.1592058931[/C][C]70.3827072212431[/C][C]2308.8407941069[/C][C]0.749748252953783[/C][/ROW]
[ROW][C]61[/C][C]17871[/C][C]18029.5453045586[/C][C]75.6140177325728[/C][C]-158.545304558606[/C][C]0.728434546245092[/C][/ROW]
[ROW][C]62[/C][C]17226[/C][C]18110.4401782058[/C][C]75.8932174272593[/C][C]-884.44017820575[/C][C]0.0388587135122467[/C][/ROW]
[ROW][C]63[/C][C]19062[/C][C]18234.4700924258[/C][C]78.4407947006641[/C][C]827.529907574154[/C][C]0.354115600480104[/C][/ROW]
[ROW][C]64[/C][C]17804[/C][C]18242.0991811425[/C][C]74.6889953333371[/C][C]-438.099181142517[/C][C]-0.5206638162686[/C][/ROW]
[ROW][C]65[/C][C]19100[/C][C]18466.8231526109[/C][C]82.6455779130433[/C][C]633.17684738915[/C][C]1.10276967932766[/C][/ROW]
[ROW][C]66[/C][C]18522[/C][C]18650.0223960451[/C][C]87.9810633800512[/C][C]-128.022396045076[/C][C]0.739082059332285[/C][/ROW]
[ROW][C]67[/C][C]18060[/C][C]18689.5254785853[/C][C]85.4083722329187[/C][C]-629.525478585296[/C][C]-0.356426798586708[/C][/ROW]
[ROW][C]68[/C][C]18869[/C][C]18776.5956209151[/C][C]85.4965441245846[/C][C]92.4043790848557[/C][C]0.0122216771278885[/C][/ROW]
[ROW][C]69[/C][C]18127[/C][C]18804.5205746809[/C][C]82.4431636156105[/C][C]-677.520574680931[/C][C]-0.423455696205232[/C][/ROW]
[ROW][C]70[/C][C]18871[/C][C]18980.9130448494[/C][C]87.4232641499781[/C][C]-109.913044849424[/C][C]0.690945687987493[/C][/ROW]
[ROW][C]71[/C][C]18890[/C][C]19161.2263215723[/C][C]92.3448685963206[/C][C]-271.226321572337[/C][C]0.683059514657614[/C][/ROW]
[ROW][C]72[/C][C]21263[/C][C]19208.3400094435[/C][C]89.9491158256927[/C][C]2054.65999055652[/C][C]-0.332598175819422[/C][/ROW]
[ROW][C]73[/C][C]19547[/C][C]19420.0261666712[/C][C]96.3966483906145[/C][C]126.973833328821[/C][C]0.895250386793068[/C][/ROW]
[ROW][C]74[/C][C]18450[/C][C]19505.2332207222[/C][C]95.8039317238105[/C][C]-1055.23322072221[/C][C]-0.0822934402494889[/C][/ROW]
[ROW][C]75[/C][C]20254[/C][C]19548.7933697156[/C][C]93.0357655513966[/C][C]705.206630284366[/C][C]-0.384200720802587[/C][/ROW]
[ROW][C]76[/C][C]19240[/C][C]19679.9058509455[/C][C]95.0539453246925[/C][C]-439.905850945503[/C][C]0.279969699295708[/C][/ROW]
[ROW][C]77[/C][C]20216[/C][C]19740.4698601584[/C][C]93.2253639804314[/C][C]475.530139841585[/C][C]-0.253560638247648[/C][/ROW]
[ROW][C]78[/C][C]19420[/C][C]19722.5541414544[/C][C]87.3318635868154[/C][C]-302.554141454413[/C][C]-0.817063950179949[/C][/ROW]
[ROW][C]79[/C][C]19415[/C][C]19854.6259641145[/C][C]89.7044383627577[/C][C]-439.625964114513[/C][C]0.328941624394363[/C][/ROW]
[ROW][C]80[/C][C]20018[/C][C]19957.1130735495[/C][C]90.3822767657258[/C][C]60.8869264504966[/C][C]0.0939926577936619[/C][/ROW]
[ROW][C]81[/C][C]18652[/C][C]19856.4044426176[/C][C]80.250344656764[/C][C]-1204.40444261761[/C][C]-1.40517312873333[/C][/ROW]
[ROW][C]82[/C][C]19978[/C][C]19952.8812924082[/C][C]81.110564210887[/C][C]25.1187075918029[/C][C]0.119315648765566[/C][/ROW]
[ROW][C]83[/C][C]19509[/C][C]19964.5283450925[/C][C]77.428629017943[/C][C]-455.52834509247[/C][C]-0.510744834039157[/C][/ROW]
[ROW][C]84[/C][C]21971[/C][C]20006.5733932436[/C][C]75.5533064547859[/C][C]1964.42660675644[/C][C]-0.260161365412173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107688&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107688&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
11332813328000
21287313200.60943725763.82152215418458-327.60943725757-1.30910910455104
31400013460.252713378221.9988103836074539.7472866218031.31766718817925
41347713535.986936847526.2778514725775-58.98693684750910.3119018951803
51423713789.380687607442.1621864062807447.6193123926241.58143678363955
61367413834.078546832842.304813576799-160.0785468327980.0192401175127454
71352913756.194174572836.7695778352094-227.194174572758-0.93687477922123
81405813824.108092922638.0413651349866233.8919070773720.243932780905403
91297513582.498439751627.0308655431981-607.498439751644-2.18563522321182
101432613729.747079441631.8415148666767596.2529205584470.935635145334216
111400813869.995006720536.3416212726261138.0049932794520.83989232790268
121619314657.751026420568.75452352292061535.248973579515.79778333316117
131448314940.968016369973.3764539119965-457.9680163698851.70441853624671
141401114973.304688225872.3101107570872-962.304688225774-0.329014378964596
151505714910.203527235866.739967786076146.796472764226-1.01366319307546
161488414966.765965331066.2089827983878-82.7659653309797-0.0721838684600287
171541414983.384596991863.3965754736545430.615403008248-0.352180429765533
181444014841.901262787951.7595341466996-401.901262787872-1.49386554764302
191490014877.572056401550.877898261684422.4279435984515-0.119893630636551
201507414855.282627259147.0432538657153218.717372740914-0.550703589224719
211444214996.138440519651.7709122935584-554.13844051960.707320665841406
221530715086.873875396653.6729327269379220.1261246033810.29317698821905
231493815227.867554008157.8168114646312-289.8675540080740.655223717116413
241719315465.187877777766.11861283523581727.812122222261.34613900460798
251552815699.356854263273.7849643858837-171.3568542632051.26383314497992
261476515768.896899981473.5864325978395-1003.89689998135-0.0318767913317064
271583815770.225099242470.022796617075967.7749007576431-0.53598968203871
281572315767.794008326466.2585553298344-44.794008326355-0.529666835606198
291615015725.549782990460.4284412968454424.450217009605-0.78914526021634
301548615780.155127015460.111468623206-294.155127015362-0.0425722754290249
311598615877.228637281662.1175757953697108.7713627184400.272499822725137
321598315928.547771348761.538676227111454.4522286513501-0.0800430636830513
331569216100.19146046367.3471799287255-408.1914604630150.816985506429388
341649016281.835561045773.2823838806303208.1644389542550.846804441462566
351568616325.100987659171.7432917911031-639.100987659145-0.222069430077944
361889716660.862017433585.18305080291852236.137982566501.95350170875901
371631616722.820466924284.000666347788-406.820466924182-0.172016459264779
381563616713.57660316279.2163022303728-1077.57660316201-0.690270569590547
391716316831.775272491081.242312767349331.2247275089730.287597218590611
401653416796.035807653275.0806559430563-262.035807653178-0.859203182183173
411651816595.763214220760.4294612260057-77.763214220708-2.01772361813529
421637516599.69346808957.407487084985-224.693468089016-0.414444134280058
431629016513.574055976749.7272941782886-223.574055976672-1.05580442807704
441635216484.458833482245.5216189412185-132.458833482220-0.581264011985356
451594316491.132400767643.4599349205430-548.132400767599-0.286540543738518
461636216429.665483083937.9219342010331-67.6654830839178-0.773357579733872
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Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')