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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 computationThu, 13 Dec 2012 06:55:44 -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/2012/Dec/13/t1355399762yyunpjlrjv2r0t0.htm/, Retrieved Sun, 28 Apr 2024 22:55:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199156, Retrieved Sun, 28 Apr 2024 22:55:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

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] [Deel: STSM] [2012-12-13 11:55:44] [f988ca26b10d35edf58465884f70a009] [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 time5 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199156&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199156&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199156&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 time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11332813328000
21287313200.60962398193.82153144452669-327.609623981897-1.30910987071981
31400013460.252680486121.9988245017758539.7473195138841.31766722495341
41347713535.986923896726.2778743429412-58.98692389668910.311902089354995
51423713789.380669811942.162266105722447.6193301881161.58143730484835
61367413834.078594357242.3048934237142-160.0785943572140.0192400152934595
71352913756.194248921336.7695964292128-227.194248921304-0.936875366433657
81405813824.108148288438.0414004936403233.8918517116360.2439324857269
91297513582.498393921827.0307080074523-607.498393921793-2.18563591932464
101432613729.746989923831.8414508160075596.2530100761510.935635744398642
111400813869.994958927136.34164807476138.0050410729160.839892793994035
121619314657.751439426968.75520506890051535.248560573155.79778367420672
131448314940.968724046173.3773688856586-457.9687240460691.70441394890217
141401114973.305464155572.3109559091014-962.305464155451-0.329020905473217
151505714910.20422134866.7406339803371146.795778652028-1.0136695735579
161488414966.766576051166.2096005385596-82.766576051059-0.0721891529657442
171541414983.385155101663.3971124474737430.614844898437-0.352185026007329
181444014841.901719563951.759856817248-401.901719563874-1.49386934689329
191490014877.572507991850.878188261213122.4274920081985-0.119895985779129
201507414855.283055979447.0434564549557218.716944020602-0.550705437135385
211444214996.1390022651.7712074561959-554.1390022599970.707319370754378
221530715086.874491134253.673257910205220.1255088658470.293174817589811
231493815227.868189567957.8172199390118-289.8681895678720.655220582876502
241719315465.18854774566.11921357162791727.811452255041.34613444850409
251552815699.357549433473.7857412914154-171.3575494333561.26382724031705
261476515768.897500254873.5871636587702-1003.89750025478-0.0318833028520451
271583815770.22558611970.023403858070667.7744138810036-0.535995445382637
281572315767.794416412166.2590497762195-44.7944164121311-0.529671417573312
291615015725.55013810360.428796881512424.449861897001-0.789148624610837
301548615780.155541794460.1118023747269-294.155541794421-0.0425744042741396
311598615877.229179800462.1179348420207108.7708201995510.272498060749683
321598315928.548400236261.539009746611854.4515997637581-0.0800450045473509
331569216100.192240231267.3476185737285-408.1922402312230.816983235586892
341649016281.83645833973.2829286966797208.1635416610230.846801035866773
351568616325.101768706371.7437696253494-639.101768706257-0.22207404222866
361889716660.862905804485.18380550913752236.137094195621.9534965495236
371631616722.821186249984.0013479153592-406.821186249865-0.172023099503823
381563616713.577098073479.2168336365953-1077.57709807335-0.690276530194596
391716316831.775704574381.2428556262029331.224295425750.287592548695499
401653416796.036136921175.0810413731387-262.036136921077-0.859207121563809
411651816595.763339446160.4295321398447-77.7633394461416-2.0177261009118
421637516599.693545201257.4074944227417-224.693545201208-0.414444627151398
431629016513.574043399449.7271513998338-223.574043399373-1.05580413949883
441635216484.458763729245.5214004998715-132.458763729166-0.581262800499785
451594316491.132283939343.4596854976379-548.132283939343-0.286538977905852
461636216429.665225803337.9215806764241-67.6652258033373-0.773355926909379
471639316668.18040797848.4615500582029-275.1804079780131.47741619172089
481905116787.462494955752.17345498588962263.537505044260.521645125342458
491674716927.772216285156.7927426547764-180.7722162850660.649524975671401
501632017113.104199885963.5443793766792-793.1041998858550.947300948414592
511791017270.620858352568.4980115177112639.3791416475450.69187121811033
521696117247.865520649863.6694055181696-286.865520649841-0.670858755156991
531748017325.068196930364.387687293961154.9318030697360.0993984253574095
541704917312.027935730860.2710359663591-263.027935730802-0.568791385336734
551687917242.323397472753.3581123888634-363.323397472748-0.955697416482515
561747317351.463573184756.3226237715685121.5364268153330.410503256727105
571699817478.672195451360.0841637128221-480.6721954512970.52176264608561
581730717568.384518019861.6536516719484-261.3845180198430.218014334097787
591741817693.239264597164.9966147934322-275.2392645970980.464905026736286
602016917860.159534666870.3829919968462308.84046533320.749746336702257
611787118029.545668016575.6143925259649-158.545668016510.728431951259421
621722618110.440502126575.89357581055-884.4405021265150.0388556250502212
631906218234.470426607878.4411845774433827.529573392230.354112683608188
641780418242.099462520174.6892886411142-438.099462520128-0.520666553506449
651910018466.823586271282.6460180413301633.1764137287671.10276755193253
661852218650.023003123887.9815924889895-128.0230031237850.739079367833474
671806018689.526129030785.4088258900366-629.526129030696-0.356430015846306
681886918776.596293282785.496976577741392.40370671732520.0122184896605663
691812718804.521176396682.4435102460089-677.521176396598-0.423458969600661
701887118980.91367562887.4236906699088-109.9136756280440.690942650567986
711889019161.226986265592.3453701354828-271.2269862654580.68305593088137
722126319208.340573870989.94953877263892054.65942612915-0.332602261746061
731954719420.026758055496.3971761350063126.9732419445580.895246564622811
741845019505.23376195695.8044173027641-1055.23376195603-0.0822976071641925
752025419548.793827428893.0361670993899705.206172571227-0.384204519783857
761924019679.906313815195.0543650686325-439.9063138151470.279966504492501
772021619740.470284473993.2257239640508475.529715526084-0.253563754270562
781942019722.554462630787.3320848555325-302.554462630712-0.817066538903295
791941519854.626320773289.7046957134652-439.6263207731650.328939929482861
802001819957.113463740290.382535373894360.88653625984140.0939909178015415
811865219856.404664839880.2503842979406-1204.40466483976-1.40517485279381
821997819952.881458947881.110615484782325.11854105218240.119314827562374
831950919964.528388657577.4285995720264-455.528388657524-0.510745599513183
842197120006.573338933475.55323695194481964.42666106661-0.260161605777078

\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 & 13200.6096239819 & 3.82153144452669 & -327.609623981897 & -1.30910987071981 \tabularnewline
3 & 14000 & 13460.2526804861 & 21.9988245017758 & 539.747319513884 & 1.31766722495341 \tabularnewline
4 & 13477 & 13535.9869238967 & 26.2778743429412 & -58.9869238966891 & 0.311902089354995 \tabularnewline
5 & 14237 & 13789.3806698119 & 42.162266105722 & 447.619330188116 & 1.58143730484835 \tabularnewline
6 & 13674 & 13834.0785943572 & 42.3048934237142 & -160.078594357214 & 0.0192400152934595 \tabularnewline
7 & 13529 & 13756.1942489213 & 36.7695964292128 & -227.194248921304 & -0.936875366433657 \tabularnewline
8 & 14058 & 13824.1081482884 & 38.0414004936403 & 233.891851711636 & 0.2439324857269 \tabularnewline
9 & 12975 & 13582.4983939218 & 27.0307080074523 & -607.498393921793 & -2.18563591932464 \tabularnewline
10 & 14326 & 13729.7469899238 & 31.8414508160075 & 596.253010076151 & 0.935635744398642 \tabularnewline
11 & 14008 & 13869.9949589271 & 36.34164807476 & 138.005041072916 & 0.839892793994035 \tabularnewline
12 & 16193 & 14657.7514394269 & 68.7552050689005 & 1535.24856057315 & 5.79778367420672 \tabularnewline
13 & 14483 & 14940.9687240461 & 73.3773688856586 & -457.968724046069 & 1.70441394890217 \tabularnewline
14 & 14011 & 14973.3054641555 & 72.3109559091014 & -962.305464155451 & -0.329020905473217 \tabularnewline
15 & 15057 & 14910.204221348 & 66.7406339803371 & 146.795778652028 & -1.0136695735579 \tabularnewline
16 & 14884 & 14966.7665760511 & 66.2096005385596 & -82.766576051059 & -0.0721891529657442 \tabularnewline
17 & 15414 & 14983.3851551016 & 63.3971124474737 & 430.614844898437 & -0.352185026007329 \tabularnewline
18 & 14440 & 14841.9017195639 & 51.759856817248 & -401.901719563874 & -1.49386934689329 \tabularnewline
19 & 14900 & 14877.5725079918 & 50.8781882612131 & 22.4274920081985 & -0.119895985779129 \tabularnewline
20 & 15074 & 14855.2830559794 & 47.0434564549557 & 218.716944020602 & -0.550705437135385 \tabularnewline
21 & 14442 & 14996.13900226 & 51.7712074561959 & -554.139002259997 & 0.707319370754378 \tabularnewline
22 & 15307 & 15086.8744911342 & 53.673257910205 & 220.125508865847 & 0.293174817589811 \tabularnewline
23 & 14938 & 15227.8681895679 & 57.8172199390118 & -289.868189567872 & 0.655220582876502 \tabularnewline
24 & 17193 & 15465.188547745 & 66.1192135716279 & 1727.81145225504 & 1.34613444850409 \tabularnewline
25 & 15528 & 15699.3575494334 & 73.7857412914154 & -171.357549433356 & 1.26382724031705 \tabularnewline
26 & 14765 & 15768.8975002548 & 73.5871636587702 & -1003.89750025478 & -0.0318833028520451 \tabularnewline
27 & 15838 & 15770.225586119 & 70.0234038580706 & 67.7744138810036 & -0.535995445382637 \tabularnewline
28 & 15723 & 15767.7944164121 & 66.2590497762195 & -44.7944164121311 & -0.529671417573312 \tabularnewline
29 & 16150 & 15725.550138103 & 60.428796881512 & 424.449861897001 & -0.789148624610837 \tabularnewline
30 & 15486 & 15780.1555417944 & 60.1118023747269 & -294.155541794421 & -0.0425744042741396 \tabularnewline
31 & 15986 & 15877.2291798004 & 62.1179348420207 & 108.770820199551 & 0.272498060749683 \tabularnewline
32 & 15983 & 15928.5484002362 & 61.5390097466118 & 54.4515997637581 & -0.0800450045473509 \tabularnewline
33 & 15692 & 16100.1922402312 & 67.3476185737285 & -408.192240231223 & 0.816983235586892 \tabularnewline
34 & 16490 & 16281.836458339 & 73.2829286966797 & 208.163541661023 & 0.846801035866773 \tabularnewline
35 & 15686 & 16325.1017687063 & 71.7437696253494 & -639.101768706257 & -0.22207404222866 \tabularnewline
36 & 18897 & 16660.8629058044 & 85.1838055091375 & 2236.13709419562 & 1.9534965495236 \tabularnewline
37 & 16316 & 16722.8211862499 & 84.0013479153592 & -406.821186249865 & -0.172023099503823 \tabularnewline
38 & 15636 & 16713.5770980734 & 79.2168336365953 & -1077.57709807335 & -0.690276530194596 \tabularnewline
39 & 17163 & 16831.7757045743 & 81.2428556262029 & 331.22429542575 & 0.287592548695499 \tabularnewline
40 & 16534 & 16796.0361369211 & 75.0810413731387 & -262.036136921077 & -0.859207121563809 \tabularnewline
41 & 16518 & 16595.7633394461 & 60.4295321398447 & -77.7633394461416 & -2.0177261009118 \tabularnewline
42 & 16375 & 16599.6935452012 & 57.4074944227417 & -224.693545201208 & -0.414444627151398 \tabularnewline
43 & 16290 & 16513.5740433994 & 49.7271513998338 & -223.574043399373 & -1.05580413949883 \tabularnewline
44 & 16352 & 16484.4587637292 & 45.5214004998715 & -132.458763729166 & -0.581262800499785 \tabularnewline
45 & 15943 & 16491.1322839393 & 43.4596854976379 & -548.132283939343 & -0.286538977905852 \tabularnewline
46 & 16362 & 16429.6652258033 & 37.9215806764241 & -67.6652258033373 & -0.773355926909379 \tabularnewline
47 & 16393 & 16668.180407978 & 48.4615500582029 & -275.180407978013 & 1.47741619172089 \tabularnewline
48 & 19051 & 16787.4624949557 & 52.1734549858896 & 2263.53750504426 & 0.521645125342458 \tabularnewline
49 & 16747 & 16927.7722162851 & 56.7927426547764 & -180.772216285066 & 0.649524975671401 \tabularnewline
50 & 16320 & 17113.1041998859 & 63.5443793766792 & -793.104199885855 & 0.947300948414592 \tabularnewline
51 & 17910 & 17270.6208583525 & 68.4980115177112 & 639.379141647545 & 0.69187121811033 \tabularnewline
52 & 16961 & 17247.8655206498 & 63.6694055181696 & -286.865520649841 & -0.670858755156991 \tabularnewline
53 & 17480 & 17325.0681969303 & 64.387687293961 & 154.931803069736 & 0.0993984253574095 \tabularnewline
54 & 17049 & 17312.0279357308 & 60.2710359663591 & -263.027935730802 & -0.568791385336734 \tabularnewline
55 & 16879 & 17242.3233974727 & 53.3581123888634 & -363.323397472748 & -0.955697416482515 \tabularnewline
56 & 17473 & 17351.4635731847 & 56.3226237715685 & 121.536426815333 & 0.410503256727105 \tabularnewline
57 & 16998 & 17478.6721954513 & 60.0841637128221 & -480.672195451297 & 0.52176264608561 \tabularnewline
58 & 17307 & 17568.3845180198 & 61.6536516719484 & -261.384518019843 & 0.218014334097787 \tabularnewline
59 & 17418 & 17693.2392645971 & 64.9966147934322 & -275.239264597098 & 0.464905026736286 \tabularnewline
60 & 20169 & 17860.1595346668 & 70.382991996846 & 2308.8404653332 & 0.749746336702257 \tabularnewline
61 & 17871 & 18029.5456680165 & 75.6143925259649 & -158.54566801651 & 0.728431951259421 \tabularnewline
62 & 17226 & 18110.4405021265 & 75.89357581055 & -884.440502126515 & 0.0388556250502212 \tabularnewline
63 & 19062 & 18234.4704266078 & 78.4411845774433 & 827.52957339223 & 0.354112683608188 \tabularnewline
64 & 17804 & 18242.0994625201 & 74.6892886411142 & -438.099462520128 & -0.520666553506449 \tabularnewline
65 & 19100 & 18466.8235862712 & 82.6460180413301 & 633.176413728767 & 1.10276755193253 \tabularnewline
66 & 18522 & 18650.0230031238 & 87.9815924889895 & -128.023003123785 & 0.739079367833474 \tabularnewline
67 & 18060 & 18689.5261290307 & 85.4088258900366 & -629.526129030696 & -0.356430015846306 \tabularnewline
68 & 18869 & 18776.5962932827 & 85.4969765777413 & 92.4037067173252 & 0.0122184896605663 \tabularnewline
69 & 18127 & 18804.5211763966 & 82.4435102460089 & -677.521176396598 & -0.423458969600661 \tabularnewline
70 & 18871 & 18980.913675628 & 87.4236906699088 & -109.913675628044 & 0.690942650567986 \tabularnewline
71 & 18890 & 19161.2269862655 & 92.3453701354828 & -271.226986265458 & 0.68305593088137 \tabularnewline
72 & 21263 & 19208.3405738709 & 89.9495387726389 & 2054.65942612915 & -0.332602261746061 \tabularnewline
73 & 19547 & 19420.0267580554 & 96.3971761350063 & 126.973241944558 & 0.895246564622811 \tabularnewline
74 & 18450 & 19505.233761956 & 95.8044173027641 & -1055.23376195603 & -0.0822976071641925 \tabularnewline
75 & 20254 & 19548.7938274288 & 93.0361670993899 & 705.206172571227 & -0.384204519783857 \tabularnewline
76 & 19240 & 19679.9063138151 & 95.0543650686325 & -439.906313815147 & 0.279966504492501 \tabularnewline
77 & 20216 & 19740.4702844739 & 93.2257239640508 & 475.529715526084 & -0.253563754270562 \tabularnewline
78 & 19420 & 19722.5544626307 & 87.3320848555325 & -302.554462630712 & -0.817066538903295 \tabularnewline
79 & 19415 & 19854.6263207732 & 89.7046957134652 & -439.626320773165 & 0.328939929482861 \tabularnewline
80 & 20018 & 19957.1134637402 & 90.3825353738943 & 60.8865362598414 & 0.0939909178015415 \tabularnewline
81 & 18652 & 19856.4046648398 & 80.2503842979406 & -1204.40466483976 & -1.40517485279381 \tabularnewline
82 & 19978 & 19952.8814589478 & 81.1106154847823 & 25.1185410521824 & 0.119314827562374 \tabularnewline
83 & 19509 & 19964.5283886575 & 77.4285995720264 & -455.528388657524 & -0.510745599513183 \tabularnewline
84 & 21971 & 20006.5733389334 & 75.5532369519448 & 1964.42666106661 & -0.260161605777078 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199156&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]13200.6096239819[/C][C]3.82153144452669[/C][C]-327.609623981897[/C][C]-1.30910987071981[/C][/ROW]
[ROW][C]3[/C][C]14000[/C][C]13460.2526804861[/C][C]21.9988245017758[/C][C]539.747319513884[/C][C]1.31766722495341[/C][/ROW]
[ROW][C]4[/C][C]13477[/C][C]13535.9869238967[/C][C]26.2778743429412[/C][C]-58.9869238966891[/C][C]0.311902089354995[/C][/ROW]
[ROW][C]5[/C][C]14237[/C][C]13789.3806698119[/C][C]42.162266105722[/C][C]447.619330188116[/C][C]1.58143730484835[/C][/ROW]
[ROW][C]6[/C][C]13674[/C][C]13834.0785943572[/C][C]42.3048934237142[/C][C]-160.078594357214[/C][C]0.0192400152934595[/C][/ROW]
[ROW][C]7[/C][C]13529[/C][C]13756.1942489213[/C][C]36.7695964292128[/C][C]-227.194248921304[/C][C]-0.936875366433657[/C][/ROW]
[ROW][C]8[/C][C]14058[/C][C]13824.1081482884[/C][C]38.0414004936403[/C][C]233.891851711636[/C][C]0.2439324857269[/C][/ROW]
[ROW][C]9[/C][C]12975[/C][C]13582.4983939218[/C][C]27.0307080074523[/C][C]-607.498393921793[/C][C]-2.18563591932464[/C][/ROW]
[ROW][C]10[/C][C]14326[/C][C]13729.7469899238[/C][C]31.8414508160075[/C][C]596.253010076151[/C][C]0.935635744398642[/C][/ROW]
[ROW][C]11[/C][C]14008[/C][C]13869.9949589271[/C][C]36.34164807476[/C][C]138.005041072916[/C][C]0.839892793994035[/C][/ROW]
[ROW][C]12[/C][C]16193[/C][C]14657.7514394269[/C][C]68.7552050689005[/C][C]1535.24856057315[/C][C]5.79778367420672[/C][/ROW]
[ROW][C]13[/C][C]14483[/C][C]14940.9687240461[/C][C]73.3773688856586[/C][C]-457.968724046069[/C][C]1.70441394890217[/C][/ROW]
[ROW][C]14[/C][C]14011[/C][C]14973.3054641555[/C][C]72.3109559091014[/C][C]-962.305464155451[/C][C]-0.329020905473217[/C][/ROW]
[ROW][C]15[/C][C]15057[/C][C]14910.204221348[/C][C]66.7406339803371[/C][C]146.795778652028[/C][C]-1.0136695735579[/C][/ROW]
[ROW][C]16[/C][C]14884[/C][C]14966.7665760511[/C][C]66.2096005385596[/C][C]-82.766576051059[/C][C]-0.0721891529657442[/C][/ROW]
[ROW][C]17[/C][C]15414[/C][C]14983.3851551016[/C][C]63.3971124474737[/C][C]430.614844898437[/C][C]-0.352185026007329[/C][/ROW]
[ROW][C]18[/C][C]14440[/C][C]14841.9017195639[/C][C]51.759856817248[/C][C]-401.901719563874[/C][C]-1.49386934689329[/C][/ROW]
[ROW][C]19[/C][C]14900[/C][C]14877.5725079918[/C][C]50.8781882612131[/C][C]22.4274920081985[/C][C]-0.119895985779129[/C][/ROW]
[ROW][C]20[/C][C]15074[/C][C]14855.2830559794[/C][C]47.0434564549557[/C][C]218.716944020602[/C][C]-0.550705437135385[/C][/ROW]
[ROW][C]21[/C][C]14442[/C][C]14996.13900226[/C][C]51.7712074561959[/C][C]-554.139002259997[/C][C]0.707319370754378[/C][/ROW]
[ROW][C]22[/C][C]15307[/C][C]15086.8744911342[/C][C]53.673257910205[/C][C]220.125508865847[/C][C]0.293174817589811[/C][/ROW]
[ROW][C]23[/C][C]14938[/C][C]15227.8681895679[/C][C]57.8172199390118[/C][C]-289.868189567872[/C][C]0.655220582876502[/C][/ROW]
[ROW][C]24[/C][C]17193[/C][C]15465.188547745[/C][C]66.1192135716279[/C][C]1727.81145225504[/C][C]1.34613444850409[/C][/ROW]
[ROW][C]25[/C][C]15528[/C][C]15699.3575494334[/C][C]73.7857412914154[/C][C]-171.357549433356[/C][C]1.26382724031705[/C][/ROW]
[ROW][C]26[/C][C]14765[/C][C]15768.8975002548[/C][C]73.5871636587702[/C][C]-1003.89750025478[/C][C]-0.0318833028520451[/C][/ROW]
[ROW][C]27[/C][C]15838[/C][C]15770.225586119[/C][C]70.0234038580706[/C][C]67.7744138810036[/C][C]-0.535995445382637[/C][/ROW]
[ROW][C]28[/C][C]15723[/C][C]15767.7944164121[/C][C]66.2590497762195[/C][C]-44.7944164121311[/C][C]-0.529671417573312[/C][/ROW]
[ROW][C]29[/C][C]16150[/C][C]15725.550138103[/C][C]60.428796881512[/C][C]424.449861897001[/C][C]-0.789148624610837[/C][/ROW]
[ROW][C]30[/C][C]15486[/C][C]15780.1555417944[/C][C]60.1118023747269[/C][C]-294.155541794421[/C][C]-0.0425744042741396[/C][/ROW]
[ROW][C]31[/C][C]15986[/C][C]15877.2291798004[/C][C]62.1179348420207[/C][C]108.770820199551[/C][C]0.272498060749683[/C][/ROW]
[ROW][C]32[/C][C]15983[/C][C]15928.5484002362[/C][C]61.5390097466118[/C][C]54.4515997637581[/C][C]-0.0800450045473509[/C][/ROW]
[ROW][C]33[/C][C]15692[/C][C]16100.1922402312[/C][C]67.3476185737285[/C][C]-408.192240231223[/C][C]0.816983235586892[/C][/ROW]
[ROW][C]34[/C][C]16490[/C][C]16281.836458339[/C][C]73.2829286966797[/C][C]208.163541661023[/C][C]0.846801035866773[/C][/ROW]
[ROW][C]35[/C][C]15686[/C][C]16325.1017687063[/C][C]71.7437696253494[/C][C]-639.101768706257[/C][C]-0.22207404222866[/C][/ROW]
[ROW][C]36[/C][C]18897[/C][C]16660.8629058044[/C][C]85.1838055091375[/C][C]2236.13709419562[/C][C]1.9534965495236[/C][/ROW]
[ROW][C]37[/C][C]16316[/C][C]16722.8211862499[/C][C]84.0013479153592[/C][C]-406.821186249865[/C][C]-0.172023099503823[/C][/ROW]
[ROW][C]38[/C][C]15636[/C][C]16713.5770980734[/C][C]79.2168336365953[/C][C]-1077.57709807335[/C][C]-0.690276530194596[/C][/ROW]
[ROW][C]39[/C][C]17163[/C][C]16831.7757045743[/C][C]81.2428556262029[/C][C]331.22429542575[/C][C]0.287592548695499[/C][/ROW]
[ROW][C]40[/C][C]16534[/C][C]16796.0361369211[/C][C]75.0810413731387[/C][C]-262.036136921077[/C][C]-0.859207121563809[/C][/ROW]
[ROW][C]41[/C][C]16518[/C][C]16595.7633394461[/C][C]60.4295321398447[/C][C]-77.7633394461416[/C][C]-2.0177261009118[/C][/ROW]
[ROW][C]42[/C][C]16375[/C][C]16599.6935452012[/C][C]57.4074944227417[/C][C]-224.693545201208[/C][C]-0.414444627151398[/C][/ROW]
[ROW][C]43[/C][C]16290[/C][C]16513.5740433994[/C][C]49.7271513998338[/C][C]-223.574043399373[/C][C]-1.05580413949883[/C][/ROW]
[ROW][C]44[/C][C]16352[/C][C]16484.4587637292[/C][C]45.5214004998715[/C][C]-132.458763729166[/C][C]-0.581262800499785[/C][/ROW]
[ROW][C]45[/C][C]15943[/C][C]16491.1322839393[/C][C]43.4596854976379[/C][C]-548.132283939343[/C][C]-0.286538977905852[/C][/ROW]
[ROW][C]46[/C][C]16362[/C][C]16429.6652258033[/C][C]37.9215806764241[/C][C]-67.6652258033373[/C][C]-0.773355926909379[/C][/ROW]
[ROW][C]47[/C][C]16393[/C][C]16668.180407978[/C][C]48.4615500582029[/C][C]-275.180407978013[/C][C]1.47741619172089[/C][/ROW]
[ROW][C]48[/C][C]19051[/C][C]16787.4624949557[/C][C]52.1734549858896[/C][C]2263.53750504426[/C][C]0.521645125342458[/C][/ROW]
[ROW][C]49[/C][C]16747[/C][C]16927.7722162851[/C][C]56.7927426547764[/C][C]-180.772216285066[/C][C]0.649524975671401[/C][/ROW]
[ROW][C]50[/C][C]16320[/C][C]17113.1041998859[/C][C]63.5443793766792[/C][C]-793.104199885855[/C][C]0.947300948414592[/C][/ROW]
[ROW][C]51[/C][C]17910[/C][C]17270.6208583525[/C][C]68.4980115177112[/C][C]639.379141647545[/C][C]0.69187121811033[/C][/ROW]
[ROW][C]52[/C][C]16961[/C][C]17247.8655206498[/C][C]63.6694055181696[/C][C]-286.865520649841[/C][C]-0.670858755156991[/C][/ROW]
[ROW][C]53[/C][C]17480[/C][C]17325.0681969303[/C][C]64.387687293961[/C][C]154.931803069736[/C][C]0.0993984253574095[/C][/ROW]
[ROW][C]54[/C][C]17049[/C][C]17312.0279357308[/C][C]60.2710359663591[/C][C]-263.027935730802[/C][C]-0.568791385336734[/C][/ROW]
[ROW][C]55[/C][C]16879[/C][C]17242.3233974727[/C][C]53.3581123888634[/C][C]-363.323397472748[/C][C]-0.955697416482515[/C][/ROW]
[ROW][C]56[/C][C]17473[/C][C]17351.4635731847[/C][C]56.3226237715685[/C][C]121.536426815333[/C][C]0.410503256727105[/C][/ROW]
[ROW][C]57[/C][C]16998[/C][C]17478.6721954513[/C][C]60.0841637128221[/C][C]-480.672195451297[/C][C]0.52176264608561[/C][/ROW]
[ROW][C]58[/C][C]17307[/C][C]17568.3845180198[/C][C]61.6536516719484[/C][C]-261.384518019843[/C][C]0.218014334097787[/C][/ROW]
[ROW][C]59[/C][C]17418[/C][C]17693.2392645971[/C][C]64.9966147934322[/C][C]-275.239264597098[/C][C]0.464905026736286[/C][/ROW]
[ROW][C]60[/C][C]20169[/C][C]17860.1595346668[/C][C]70.382991996846[/C][C]2308.8404653332[/C][C]0.749746336702257[/C][/ROW]
[ROW][C]61[/C][C]17871[/C][C]18029.5456680165[/C][C]75.6143925259649[/C][C]-158.54566801651[/C][C]0.728431951259421[/C][/ROW]
[ROW][C]62[/C][C]17226[/C][C]18110.4405021265[/C][C]75.89357581055[/C][C]-884.440502126515[/C][C]0.0388556250502212[/C][/ROW]
[ROW][C]63[/C][C]19062[/C][C]18234.4704266078[/C][C]78.4411845774433[/C][C]827.52957339223[/C][C]0.354112683608188[/C][/ROW]
[ROW][C]64[/C][C]17804[/C][C]18242.0994625201[/C][C]74.6892886411142[/C][C]-438.099462520128[/C][C]-0.520666553506449[/C][/ROW]
[ROW][C]65[/C][C]19100[/C][C]18466.8235862712[/C][C]82.6460180413301[/C][C]633.176413728767[/C][C]1.10276755193253[/C][/ROW]
[ROW][C]66[/C][C]18522[/C][C]18650.0230031238[/C][C]87.9815924889895[/C][C]-128.023003123785[/C][C]0.739079367833474[/C][/ROW]
[ROW][C]67[/C][C]18060[/C][C]18689.5261290307[/C][C]85.4088258900366[/C][C]-629.526129030696[/C][C]-0.356430015846306[/C][/ROW]
[ROW][C]68[/C][C]18869[/C][C]18776.5962932827[/C][C]85.4969765777413[/C][C]92.4037067173252[/C][C]0.0122184896605663[/C][/ROW]
[ROW][C]69[/C][C]18127[/C][C]18804.5211763966[/C][C]82.4435102460089[/C][C]-677.521176396598[/C][C]-0.423458969600661[/C][/ROW]
[ROW][C]70[/C][C]18871[/C][C]18980.913675628[/C][C]87.4236906699088[/C][C]-109.913675628044[/C][C]0.690942650567986[/C][/ROW]
[ROW][C]71[/C][C]18890[/C][C]19161.2269862655[/C][C]92.3453701354828[/C][C]-271.226986265458[/C][C]0.68305593088137[/C][/ROW]
[ROW][C]72[/C][C]21263[/C][C]19208.3405738709[/C][C]89.9495387726389[/C][C]2054.65942612915[/C][C]-0.332602261746061[/C][/ROW]
[ROW][C]73[/C][C]19547[/C][C]19420.0267580554[/C][C]96.3971761350063[/C][C]126.973241944558[/C][C]0.895246564622811[/C][/ROW]
[ROW][C]74[/C][C]18450[/C][C]19505.233761956[/C][C]95.8044173027641[/C][C]-1055.23376195603[/C][C]-0.0822976071641925[/C][/ROW]
[ROW][C]75[/C][C]20254[/C][C]19548.7938274288[/C][C]93.0361670993899[/C][C]705.206172571227[/C][C]-0.384204519783857[/C][/ROW]
[ROW][C]76[/C][C]19240[/C][C]19679.9063138151[/C][C]95.0543650686325[/C][C]-439.906313815147[/C][C]0.279966504492501[/C][/ROW]
[ROW][C]77[/C][C]20216[/C][C]19740.4702844739[/C][C]93.2257239640508[/C][C]475.529715526084[/C][C]-0.253563754270562[/C][/ROW]
[ROW][C]78[/C][C]19420[/C][C]19722.5544626307[/C][C]87.3320848555325[/C][C]-302.554462630712[/C][C]-0.817066538903295[/C][/ROW]
[ROW][C]79[/C][C]19415[/C][C]19854.6263207732[/C][C]89.7046957134652[/C][C]-439.626320773165[/C][C]0.328939929482861[/C][/ROW]
[ROW][C]80[/C][C]20018[/C][C]19957.1134637402[/C][C]90.3825353738943[/C][C]60.8865362598414[/C][C]0.0939909178015415[/C][/ROW]
[ROW][C]81[/C][C]18652[/C][C]19856.4046648398[/C][C]80.2503842979406[/C][C]-1204.40466483976[/C][C]-1.40517485279381[/C][/ROW]
[ROW][C]82[/C][C]19978[/C][C]19952.8814589478[/C][C]81.1106154847823[/C][C]25.1185410521824[/C][C]0.119314827562374[/C][/ROW]
[ROW][C]83[/C][C]19509[/C][C]19964.5283886575[/C][C]77.4285995720264[/C][C]-455.528388657524[/C][C]-0.510745599513183[/C][/ROW]
[ROW][C]84[/C][C]21971[/C][C]20006.5733389334[/C][C]75.5532369519448[/C][C]1964.42666106661[/C][C]-0.260161605777078[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199156&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199156&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
21287313200.60962398193.82153144452669-327.609623981897-1.30910987071981
31400013460.252680486121.9988245017758539.7473195138841.31766722495341
41347713535.986923896726.2778743429412-58.98692389668910.311902089354995
51423713789.380669811942.162266105722447.6193301881161.58143730484835
61367413834.078594357242.3048934237142-160.0785943572140.0192400152934595
71352913756.194248921336.7695964292128-227.194248921304-0.936875366433657
81405813824.108148288438.0414004936403233.8918517116360.2439324857269
91297513582.498393921827.0307080074523-607.498393921793-2.18563591932464
101432613729.746989923831.8414508160075596.2530100761510.935635744398642
111400813869.994958927136.34164807476138.0050410729160.839892793994035
121619314657.751439426968.75520506890051535.248560573155.79778367420672
131448314940.968724046173.3773688856586-457.9687240460691.70441394890217
141401114973.305464155572.3109559091014-962.305464155451-0.329020905473217
151505714910.20422134866.7406339803371146.795778652028-1.0136695735579
161488414966.766576051166.2096005385596-82.766576051059-0.0721891529657442
171541414983.385155101663.3971124474737430.614844898437-0.352185026007329
181444014841.901719563951.759856817248-401.901719563874-1.49386934689329
191490014877.572507991850.878188261213122.4274920081985-0.119895985779129
201507414855.283055979447.0434564549557218.716944020602-0.550705437135385
211444214996.1390022651.7712074561959-554.1390022599970.707319370754378
221530715086.874491134253.673257910205220.1255088658470.293174817589811
231493815227.868189567957.8172199390118-289.8681895678720.655220582876502
241719315465.18854774566.11921357162791727.811452255041.34613444850409
251552815699.357549433473.7857412914154-171.3575494333561.26382724031705
261476515768.897500254873.5871636587702-1003.89750025478-0.0318833028520451
271583815770.22558611970.023403858070667.7744138810036-0.535995445382637
281572315767.794416412166.2590497762195-44.7944164121311-0.529671417573312
291615015725.55013810360.428796881512424.449861897001-0.789148624610837
301548615780.155541794460.1118023747269-294.155541794421-0.0425744042741396
311598615877.229179800462.1179348420207108.7708201995510.272498060749683
321598315928.548400236261.539009746611854.4515997637581-0.0800450045473509
331569216100.192240231267.3476185737285-408.1922402312230.816983235586892
341649016281.83645833973.2829286966797208.1635416610230.846801035866773
351568616325.101768706371.7437696253494-639.101768706257-0.22207404222866
361889716660.862905804485.18380550913752236.137094195621.9534965495236
371631616722.821186249984.0013479153592-406.821186249865-0.172023099503823
381563616713.577098073479.2168336365953-1077.57709807335-0.690276530194596
391716316831.775704574381.2428556262029331.224295425750.287592548695499
401653416796.036136921175.0810413731387-262.036136921077-0.859207121563809
411651816595.763339446160.4295321398447-77.7633394461416-2.0177261009118
421637516599.693545201257.4074944227417-224.693545201208-0.414444627151398
431629016513.574043399449.7271513998338-223.574043399373-1.05580413949883
441635216484.458763729245.5214004998715-132.458763729166-0.581262800499785
451594316491.132283939343.4596854976379-548.132283939343-0.286538977905852
461636216429.665225803337.9215806764241-67.6652258033373-0.773355926909379
471639316668.18040797848.4615500582029-275.1804079780131.47741619172089
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761924019679.906313815195.0543650686325-439.9063138151470.279966504492501
772021619740.470284473993.2257239640508475.529715526084-0.253563754270562
781942019722.554462630787.3320848555325-302.554462630712-0.817066538903295
791941519854.626320773289.7046957134652-439.6263207731650.328939929482861
802001819957.113463740290.382535373894360.88653625984140.0939909178015415
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821997819952.881458947881.110615484782325.11854105218240.119314827562374
831950919964.528388657577.4285995720264-455.528388657524-0.510745599513183
842197120006.573338933475.55323695194481964.42666106661-0.260161605777078


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')