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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Thu, 01 Dec 2011 09:49:49 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/01/t1322751334p5n6094d8bqhaow.htm/, Retrieved Fri, 19 Apr 2024 15:24:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=149761, Retrieved Fri, 19 Apr 2024 15:24:49 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

161

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [(Partial) Autocorrelation Function] [WS8 - ACF2] [2011-12-01 13:01:36] [d3c56829b3e69baec30b0d469b5d7237]
- RMP   [Spectral Analysis] [WS9 - spectral an...] [2011-12-01 13:18:10] [d3c56829b3e69baec30b0d469b5d7237]
- RMP       [ARIMA Backward Selection] [WS9 - ARIMA] [2011-12-01 14:49:49] [90397ad74249faf9640e6aa26282b307] [Current]
- R PD        [ARIMA Backward Selection] [] [2011-12-08 21:29:22] [5c12c14850e1dddd68cd7e26a7cf987c] 
- R PD        [ARIMA Backward Selection] [] [2011-12-08 21:29:22] [5c12c14850e1dddd68cd7e26a7cf987c] 
- R PD        [ARIMA Backward Selection] [] [2011-12-08 21:43:46] [5c12c14850e1dddd68cd7e26a7cf987c] 
-   P           [ARIMA Backward Selection] [WS9 - Overnachtin...] [2011-12-12 21:47:33] [2628f630b839c9d14ba9c3627ab0414a] 
- RMPD        [Kendall tau Correlation Matrix] [workshop 10 pears...] [2011-12-09 19:24:31] [aa7c7608f809e956d7797134ec926e04] 
- R             [Kendall tau Correlation Matrix] [] [2012-12-11 11:53:26] [3ba5358ad212dca7c498c7fc6d6ebde5] 

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149761&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]4 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=149761&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149761&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ma1	sma1
Estimates ( 1 )	0.4619	0.1882	-0.3768	-0.721
(p-val)	(0.0077 )	(0.0044 )	(0.0306 )	(0 )
Estimates ( 2 )	0.1094	0.2417	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(0 )
Estimates ( 3 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 4 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ma1 & sma1 \tabularnewline
Estimates ( 1 ) & 0.4619 & 0.1882 & -0.3768 & -0.721 \tabularnewline
(p-val) & (0.0077 ) & (0.0044 ) & (0.0306 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.1094 & 0.2417 & 0 & -0.724 \tabularnewline
(p-val) & (0.0348 ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 3 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149761&T=1

[TABLE]
[ROW][C]ARIMA Parameter Estimation and Backward Selection[/C][/ROW]
[ROW][C]Iteration[/C][C]ar1[/C][C]ar2[/C][C]ma1[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]0.4619[/C][C]0.1882[/C][C]-0.3768[/C][C]-0.721[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0077 )[/C][C](0.0044 )[/C][C](0.0306 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.1094[/C][C]0.2417[/C][C]0[/C][C]-0.724[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0348 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149761&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149761&T=1

As an alternative you can also use a QR Code:

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

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ma1	sma1
Estimates ( 1 )	0.4619	0.1882	-0.3768	-0.721
(p-val)	(0.0077 )	(0.0044 )	(0.0306 )	(0 )
Estimates ( 2 )	0.1094	0.2417	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(0 )
Estimates ( 3 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 4 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.0447135975563754
-0.0688510773371363
0.199758860044668
0.36923771854977
1.52891008582121
-0.362461383728246
0.456332846551667
-0.580190970124052
-0.364333252566302
1.27450372562042
-1.35440590228669
-0.363598697892761
0.165785245479883
-0.850601443381676
-0.559434617578944
-0.731897929685193
-0.402813851620158
-0.0477724393926766
-0.776849659719344
-0.839353538148865
0.708971127756123
-0.699689662443406
0.895086298870522
-0.0956342525971721
-1.57974818082311
-1.09723588083731
0.417039933755797
0.0439997586358202
0.167496311961932
0.365238293646528
-0.251725164421644
0.318837141008799
0.865734156897206
0.124189179989358
0.0903329557718262
-1.20515699966855
-0.183214650334194
-0.0632739917527146
-0.348733259666055
0.593474101120229
0.492799630370638
-0.314844128424003
0.100870213882383
0.573039262465596
-0.494356778318471
-0.421225791561678
-0.119085783643399
-0.11701280593626
0.520332372628229
-0.993117055676768
0.337983590246786
0.853117145061822
-0.457610017301283
-0.413607276948185
-0.0766437063370465
0.306427995917046
0.875079154540586
0.46863723308168
0.823142611378267
0.915708764413595
1.20366939825228
0.416221221675754
0.273455917532051
-0.224500131058835
-0.243846205053668
-1.10646962222807
-0.0326091552420104
0.549057328741296
0.103171731616491
-0.884283826308935
-0.333679106856095
-0.414771400310296
-0.335151159773555
-0.445011430699749
-0.0128575803428709
0.519556851467222
-0.696980776543239
-0.0498598988496553
-0.514252271806842
0.583668608805387
-0.33331912268081
0.662837243255079
0.0561917843531383
-0.0411524988783707
-0.853189729429448
-0.11309147244877
0.734507297070408
-0.506413554077716
1.0234265491194
0.411021441055682
-0.600246450481634
-0.99896682505811
-0.252766410112452
0.252299554016176
1.00571064234172
0.010224691390479
-0.537293110285251
-0.563639188482655
-0.275112654692135
0.307454959289824
0.64264543457022
0.633466901617811
-0.703923160578168
-0.161817893587373
0.360736549247296
0.511094850147124
0.835857699547514
0.189891890381882
0.722949814938076
1.18106818342907
0.164913912888807
0.0100164911171993
-0.502761819772201
-0.318345596277904
0.134347356689117
-0.168654846277167
-1.04340733884281
-0.178322272031546
-0.957227809693615
0.690930423786887
-0.395368903395507
-0.311809593233093
-0.415378679943547
-1.11444294807947
0.0777377628864085
0.626822820272136
0.105795346797318
0.325709217207496
0.154354363564152
0.598011483866889
0.0114304215592837
-0.884708349666059
-0.452863222883427
-0.758032195821606
1.41250623844311
-0.340443068695051
-0.272356294025885
1.07383377974078
-0.341684612404454
0.288713147933651
-0.570178375885347
0.920864593251684
0.0990618268165434
0.823573065885147
-0.0609090710142616
0.332837290159821
-0.497230844234429
-0.274357415417183
0.0211320082408941
0.156660836239269
-0.28069499902652
-0.422116334194435
-0.21695256857078
-0.182930098018099
-0.698085770741611
-0.0555192211993102
-0.227526605773121
-0.395395304251476
0.087790467737873
0.150835186621549
0.824188996848891
-0.699442819319935
-0.480703403915358
1.06253285111481
-0.201920243239259
-0.54300264574833
0.549311529872812
-0.291324700943185
0.330625072619694
0.482571357488207
-0.808521163363471
-0.0584059785953535
0.291289144182766
0.335777311933669
-0.360563116352467
-0.383946671904132
0.151464454186652
0.186525703326074
0.279324129308393
-0.549542473924301
-0.074331853752277
-0.260815504403362
-0.00535042548481961
0.220801673145021
-0.502188957981608
1.11771421800838
-1.13397643087592
0.310238693574404
0.176860486013815
0.0813948596781497
-0.71142532810663
0.0913318659258747
-0.304666277073196
0.531762512745846
-0.609982159625018
0.522866801270252
-0.277808945514797
0.636558928294153
-0.531300722660161
-0.191649864014867
-0.0507802803048712
-0.0853233865282239
-0.234326630288585
-0.426080253238712
-0.266141479586712
-0.449391879042413
0.552249716174346
0.313444850558047
0.667294122915503
0.415519847646124
-0.453800040799769
-0.173880805582889
-0.145531265853721
0.184780483120188
-0.372914392116789
0.207246918874904
-0.0896899167839434
-0.00469030893368804
-0.0300931074983437
0.0294783225813145
-0.32225068851016
1.52890778100781
0.237391405125333
-0.544594142793075
0.581191327643956
0.330668950462775
-0.986825042304288
-0.754572167065651
-0.344428453269353
0.759526019377999
-0.260033467860636
-0.467803398970105
-0.0940196335824325
1.6886280636037
0.115040234642084
-0.889880337073422
0.0676016731864127
-0.117202655567668
-0.209507138626528
-0.38241050632908
0.0910559714101356
0.0417472951304564
0.256954005992646
0.389318399853475
-0.384469281428512
0.458532146600365
0.604655485126501
-0.17724828416432
0.709930417259947
-0.30339437692803
-0.95385300629152
-0.0482991207836124
0.991525874424292
0.825956138926677
0.284996452574077
0.139735055722216
-0.144410003517006
0.166306724001155
0.530924856146391
0.0237506509885344
0.353800139209895
-0.0112804039785091
0.499744150914677
0.121930578700587
-0.114215564175415
-0.504280760192632
-0.0904212266656877
-0.243343898134012
-0.125828499555998
-0.400377279177997
0.604748668457267
0.332080861381028
-0.350557375504458
-0.48856167669871
0.295154745994051
-0.0565870548862424
0.00478840221845962
-0.371090500023273
0.158928092206783
-0.216648970939356
-0.224067997219291
-0.282626423263178
0.264514943631371
0.157522198279435
-0.151106223822044
-0.128481389806176
-0.848383716102376
-0.0795563831878318
-0.107817655685065
0.328071235241063
-0.154768162708847
0.165799027192829
-0.247712618997008
-0.178864229114114
0.0510925314736864
-0.0018931710165511
0.275780381046859
-0.658673635496858
0.601320874032054
0.310561088202804
0.558385654117761
-0.106050297172753
-0.461152113053405
-0.205809007023439
0.392378615834678
0.190088475528501
0.332604768811689
-0.160478794581049
0.876919262320868
0.0698071133104919
0.824301473679013
0.811798314285586
1.76116716988745
-0.560099459451128
0.15742846038906
-0.271266441076903
0.0298150089006276
-1.16844648059996
-0.0760071758948753
0.0762442180067965
-0.213133096648745
0.0554242325054169
-0.545106021668063
-0.0970187825674411
-0.414561793489955
-0.3541642272954
-0.247488453879097
-0.0173177706182127
-0.401574770741385
0.302548944571315
0.590591902273397
0.350161203024818
-0.574360264097611
0.0527131229411632
0.110062420831778
-0.218477278123741
-0.671792342940494
0.443222996035537
-0.272979855535611
-0.823082143797428
0.046480262185613
0.266124407078502
-0.400171439089707
0.443833900250728
-0.312784943982657
0.0242214757972601
-0.13072888053403
-0.915920746463421
0.146465384764294
-0.285944693672895
0.31685027587315
-0.223099239196909
0.301762330419675
-0.618747380878247
0.84544589076605
-0.330790135656626
-0.0371750233168321
-0.226828455001578
-0.0121392875472843
0.516891082298516

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0447135975563754 \tabularnewline
-0.0688510773371363 \tabularnewline
0.199758860044668 \tabularnewline
0.36923771854977 \tabularnewline
1.52891008582121 \tabularnewline
-0.362461383728246 \tabularnewline
0.456332846551667 \tabularnewline
-0.580190970124052 \tabularnewline
-0.364333252566302 \tabularnewline
1.27450372562042 \tabularnewline
-1.35440590228669 \tabularnewline
-0.363598697892761 \tabularnewline
0.165785245479883 \tabularnewline
-0.850601443381676 \tabularnewline
-0.559434617578944 \tabularnewline
-0.731897929685193 \tabularnewline
-0.402813851620158 \tabularnewline
-0.0477724393926766 \tabularnewline
-0.776849659719344 \tabularnewline
-0.839353538148865 \tabularnewline
0.708971127756123 \tabularnewline
-0.699689662443406 \tabularnewline
0.895086298870522 \tabularnewline
-0.0956342525971721 \tabularnewline
-1.57974818082311 \tabularnewline
-1.09723588083731 \tabularnewline
0.417039933755797 \tabularnewline
0.0439997586358202 \tabularnewline
0.167496311961932 \tabularnewline
0.365238293646528 \tabularnewline
-0.251725164421644 \tabularnewline
0.318837141008799 \tabularnewline
0.865734156897206 \tabularnewline
0.124189179989358 \tabularnewline
0.0903329557718262 \tabularnewline
-1.20515699966855 \tabularnewline
-0.183214650334194 \tabularnewline
-0.0632739917527146 \tabularnewline
-0.348733259666055 \tabularnewline
0.593474101120229 \tabularnewline
0.492799630370638 \tabularnewline
-0.314844128424003 \tabularnewline
0.100870213882383 \tabularnewline
0.573039262465596 \tabularnewline
-0.494356778318471 \tabularnewline
-0.421225791561678 \tabularnewline
-0.119085783643399 \tabularnewline
-0.11701280593626 \tabularnewline
0.520332372628229 \tabularnewline
-0.993117055676768 \tabularnewline
0.337983590246786 \tabularnewline
0.853117145061822 \tabularnewline
-0.457610017301283 \tabularnewline
-0.413607276948185 \tabularnewline
-0.0766437063370465 \tabularnewline
0.306427995917046 \tabularnewline
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\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149761&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0447135975563754[/C][/ROW]
[ROW][C]-0.0688510773371363[/C][/ROW]
[ROW][C]0.199758860044668[/C][/ROW]
[ROW][C]0.36923771854977[/C][/ROW]
[ROW][C]1.52891008582121[/C][/ROW]
[ROW][C]-0.362461383728246[/C][/ROW]
[ROW][C]0.456332846551667[/C][/ROW]
[ROW][C]-0.580190970124052[/C][/ROW]
[ROW][C]-0.364333252566302[/C][/ROW]
[ROW][C]1.27450372562042[/C][/ROW]
[ROW][C]-1.35440590228669[/C][/ROW]
[ROW][C]-0.363598697892761[/C][/ROW]
[ROW][C]0.165785245479883[/C][/ROW]
[ROW][C]-0.850601443381676[/C][/ROW]
[ROW][C]-0.559434617578944[/C][/ROW]
[ROW][C]-0.731897929685193[/C][/ROW]
[ROW][C]-0.402813851620158[/C][/ROW]
[ROW][C]-0.0477724393926766[/C][/ROW]
[ROW][C]-0.776849659719344[/C][/ROW]
[ROW][C]-0.839353538148865[/C][/ROW]
[ROW][C]0.708971127756123[/C][/ROW]
[ROW][C]-0.699689662443406[/C][/ROW]
[ROW][C]0.895086298870522[/C][/ROW]
[ROW][C]-0.0956342525971721[/C][/ROW]
[ROW][C]-1.57974818082311[/C][/ROW]
[ROW][C]-1.09723588083731[/C][/ROW]
[ROW][C]0.417039933755797[/C][/ROW]
[ROW][C]0.0439997586358202[/C][/ROW]
[ROW][C]0.167496311961932[/C][/ROW]
[ROW][C]0.365238293646528[/C][/ROW]
[ROW][C]-0.251725164421644[/C][/ROW]
[ROW][C]0.318837141008799[/C][/ROW]
[ROW][C]0.865734156897206[/C][/ROW]
[ROW][C]0.124189179989358[/C][/ROW]
[ROW][C]0.0903329557718262[/C][/ROW]
[ROW][C]-1.20515699966855[/C][/ROW]
[ROW][C]-0.183214650334194[/C][/ROW]
[ROW][C]-0.0632739917527146[/C][/ROW]
[ROW][C]-0.348733259666055[/C][/ROW]
[ROW][C]0.593474101120229[/C][/ROW]
[ROW][C]0.492799630370638[/C][/ROW]
[ROW][C]-0.314844128424003[/C][/ROW]
[ROW][C]0.100870213882383[/C][/ROW]
[ROW][C]0.573039262465596[/C][/ROW]
[ROW][C]-0.494356778318471[/C][/ROW]
[ROW][C]-0.421225791561678[/C][/ROW]
[ROW][C]-0.119085783643399[/C][/ROW]
[ROW][C]-0.11701280593626[/C][/ROW]
[ROW][C]0.520332372628229[/C][/ROW]
[ROW][C]-0.993117055676768[/C][/ROW]
[ROW][C]0.337983590246786[/C][/ROW]
[ROW][C]0.853117145061822[/C][/ROW]
[ROW][C]-0.457610017301283[/C][/ROW]
[ROW][C]-0.413607276948185[/C][/ROW]
[ROW][C]-0.0766437063370465[/C][/ROW]
[ROW][C]0.306427995917046[/C][/ROW]
[ROW][C]0.875079154540586[/C][/ROW]
[ROW][C]0.46863723308168[/C][/ROW]
[ROW][C]0.823142611378267[/C][/ROW]
[ROW][C]0.915708764413595[/C][/ROW]
[ROW][C]1.20366939825228[/C][/ROW]
[ROW][C]0.416221221675754[/C][/ROW]
[ROW][C]0.273455917532051[/C][/ROW]
[ROW][C]-0.224500131058835[/C][/ROW]
[ROW][C]-0.243846205053668[/C][/ROW]
[ROW][C]-1.10646962222807[/C][/ROW]
[ROW][C]-0.0326091552420104[/C][/ROW]
[ROW][C]0.549057328741296[/C][/ROW]
[ROW][C]0.103171731616491[/C][/ROW]
[ROW][C]-0.884283826308935[/C][/ROW]
[ROW][C]-0.333679106856095[/C][/ROW]
[ROW][C]-0.414771400310296[/C][/ROW]
[ROW][C]-0.335151159773555[/C][/ROW]
[ROW][C]-0.445011430699749[/C][/ROW]
[ROW][C]-0.0128575803428709[/C][/ROW]
[ROW][C]0.519556851467222[/C][/ROW]
[ROW][C]-0.696980776543239[/C][/ROW]
[ROW][C]-0.0498598988496553[/C][/ROW]
[ROW][C]-0.514252271806842[/C][/ROW]
[ROW][C]0.583668608805387[/C][/ROW]
[ROW][C]-0.33331912268081[/C][/ROW]
[ROW][C]0.662837243255079[/C][/ROW]
[ROW][C]0.0561917843531383[/C][/ROW]
[ROW][C]-0.0411524988783707[/C][/ROW]
[ROW][C]-0.853189729429448[/C][/ROW]
[ROW][C]-0.11309147244877[/C][/ROW]
[ROW][C]0.734507297070408[/C][/ROW]
[ROW][C]-0.506413554077716[/C][/ROW]
[ROW][C]1.0234265491194[/C][/ROW]
[ROW][C]0.411021441055682[/C][/ROW]
[ROW][C]-0.600246450481634[/C][/ROW]
[ROW][C]-0.99896682505811[/C][/ROW]
[ROW][C]-0.252766410112452[/C][/ROW]
[ROW][C]0.252299554016176[/C][/ROW]
[ROW][C]1.00571064234172[/C][/ROW]
[ROW][C]0.010224691390479[/C][/ROW]
[ROW][C]-0.537293110285251[/C][/ROW]
[ROW][C]-0.563639188482655[/C][/ROW]
[ROW][C]-0.275112654692135[/C][/ROW]
[ROW][C]0.307454959289824[/C][/ROW]
[ROW][C]0.64264543457022[/C][/ROW]
[ROW][C]0.633466901617811[/C][/ROW]
[ROW][C]-0.703923160578168[/C][/ROW]
[ROW][C]-0.161817893587373[/C][/ROW]
[ROW][C]0.360736549247296[/C][/ROW]
[ROW][C]0.511094850147124[/C][/ROW]
[ROW][C]0.835857699547514[/C][/ROW]
[ROW][C]0.189891890381882[/C][/ROW]
[ROW][C]0.722949814938076[/C][/ROW]
[ROW][C]1.18106818342907[/C][/ROW]
[ROW][C]0.164913912888807[/C][/ROW]
[ROW][C]0.0100164911171993[/C][/ROW]
[ROW][C]-0.502761819772201[/C][/ROW]
[ROW][C]-0.318345596277904[/C][/ROW]
[ROW][C]0.134347356689117[/C][/ROW]
[ROW][C]-0.168654846277167[/C][/ROW]
[ROW][C]-1.04340733884281[/C][/ROW]
[ROW][C]-0.178322272031546[/C][/ROW]
[ROW][C]-0.957227809693615[/C][/ROW]
[ROW][C]0.690930423786887[/C][/ROW]
[ROW][C]-0.395368903395507[/C][/ROW]
[ROW][C]-0.311809593233093[/C][/ROW]
[ROW][C]-0.415378679943547[/C][/ROW]
[ROW][C]-1.11444294807947[/C][/ROW]
[ROW][C]0.0777377628864085[/C][/ROW]
[ROW][C]0.626822820272136[/C][/ROW]
[ROW][C]0.105795346797318[/C][/ROW]
[ROW][C]0.325709217207496[/C][/ROW]
[ROW][C]0.154354363564152[/C][/ROW]
[ROW][C]0.598011483866889[/C][/ROW]
[ROW][C]0.0114304215592837[/C][/ROW]
[ROW][C]-0.884708349666059[/C][/ROW]
[ROW][C]-0.452863222883427[/C][/ROW]
[ROW][C]-0.758032195821606[/C][/ROW]
[ROW][C]1.41250623844311[/C][/ROW]
[ROW][C]-0.340443068695051[/C][/ROW]
[ROW][C]-0.272356294025885[/C][/ROW]
[ROW][C]1.07383377974078[/C][/ROW]
[ROW][C]-0.341684612404454[/C][/ROW]
[ROW][C]0.288713147933651[/C][/ROW]
[ROW][C]-0.570178375885347[/C][/ROW]
[ROW][C]0.920864593251684[/C][/ROW]
[ROW][C]0.0990618268165434[/C][/ROW]
[ROW][C]0.823573065885147[/C][/ROW]
[ROW][C]-0.0609090710142616[/C][/ROW]
[ROW][C]0.332837290159821[/C][/ROW]
[ROW][C]-0.497230844234429[/C][/ROW]
[ROW][C]-0.274357415417183[/C][/ROW]
[ROW][C]0.0211320082408941[/C][/ROW]
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[ROW][C]0.330625072619694[/C][/ROW]
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[ROW][C]-0.0584059785953535[/C][/ROW]
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[ROW][C]0.335777311933669[/C][/ROW]
[ROW][C]-0.360563116352467[/C][/ROW]
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[ROW][C]0.110062420831778[/C][/ROW]
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[ROW][C]-0.671792342940494[/C][/ROW]
[ROW][C]0.443222996035537[/C][/ROW]
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[ROW][C]0.266124407078502[/C][/ROW]
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[ROW][C]0.0242214757972601[/C][/ROW]
[ROW][C]-0.13072888053403[/C][/ROW]
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[ROW][C]0.146465384764294[/C][/ROW]
[ROW][C]-0.285944693672895[/C][/ROW]
[ROW][C]0.31685027587315[/C][/ROW]
[ROW][C]-0.223099239196909[/C][/ROW]
[ROW][C]0.301762330419675[/C][/ROW]
[ROW][C]-0.618747380878247[/C][/ROW]
[ROW][C]0.84544589076605[/C][/ROW]
[ROW][C]-0.330790135656626[/C][/ROW]
[ROW][C]-0.0371750233168321[/C][/ROW]
[ROW][C]-0.226828455001578[/C][/ROW]
[ROW][C]-0.0121392875472843[/C][/ROW]
[ROW][C]0.516891082298516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149761&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149761&T=2

As an alternative you can also use a QR Code:

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

Estimated ARIMA Residuals
Value
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1.20366939825228
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0.0762442180067965
-0.213133096648745
0.0554242325054169
-0.545106021668063
-0.0970187825674411
-0.414561793489955
-0.3541642272954
-0.247488453879097
-0.0173177706182127
-0.401574770741385
0.302548944571315
0.590591902273397
0.350161203024818
-0.574360264097611
0.0527131229411632
0.110062420831778
-0.218477278123741
-0.671792342940494
0.443222996035537
-0.272979855535611
-0.823082143797428
0.046480262185613
0.266124407078502
-0.400171439089707
0.443833900250728
-0.312784943982657
0.0242214757972601
-0.13072888053403
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0.146465384764294
-0.285944693672895
0.31685027587315
-0.223099239196909
0.301762330419675
-0.618747380878247
0.84544589076605
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0.516891082298516

Figure 1

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Postscript link

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Parameters (Session):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 2 ; par7 = 1 ; par8 = 0 ; par9 = 1 ;

R code (references can be found in the software module):

library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- as.numeric(par5) #seasonal period
par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial
par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial
armaGR <- function(arima.out, names, n){
try1 <- arima.out$coef
try2 <- sqrt(diag(arima.out$var.coef))
try.data.frame  <- data.frame(matrix(NA,ncol=4,nrow=length(names)))
dimnames(try.data.frame) <- list(names,c('coef','std','tstat','pv'))
try.data.frame[,1] <- try1
for(i in 1:length(try2)) try.data.frame[which(rownames(try.data.frame)==names(try2)[i]),2] <- try2[i]
try.data.frame[,3] <- try.data.frame[,1] / try.data.frame[,2]
try.data.frame[,4] <- round((1-pt(abs(try.data.frame[,3]),df=n-(length(try2)+1)))*2,5)
vector <- rep(NA,length(names))
vector[is.na(try.data.frame[,4])] <- 0
maxi <- which.max(try.data.frame[,4])
continue <- max(try.data.frame[,4],na.rm=TRUE) > .05
vector[maxi] <- 0
list(summary=try.data.frame,next.vector=vector,continue=continue)
}
arimaSelect <- function(series, order=c(13,0,0), seasonal=list(order=c(2,0,0),period=12), include.mean=F){
nrc <- order[1]+order[3]+seasonal$order[1]+seasonal$order[3]
coeff <- matrix(NA, nrow=nrc*2, ncol=nrc)
pval <- matrix(NA, nrow=nrc*2, ncol=nrc)
mylist <- rep(list(NULL), nrc)
names  <- NULL
if(order[1] > 0) names <- paste('ar',1:order[1],sep='')
if(order[3] > 0) names <- c( names , paste('ma',1:order[3],sep='') )
if(seasonal$order[1] > 0) names <- c(names, paste('sar',1:seasonal$order[1],sep=''))
if(seasonal$order[3] > 0) names <- c(names, paste('sma',1:seasonal$order[3],sep=''))
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML')
mylist[[1]] <- arima.out
last.arma <- armaGR(arima.out, names, length(series))
mystop <- FALSE
i <- 1
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- 2
aic <- arima.out$aic
while(!mystop){
mylist[[i]] <- arima.out
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML', fixed=last.arma$next.vector)
aic <- c(aic, arima.out$aic)
last.arma <- armaGR(arima.out, names, length(series))
mystop <- !last.arma$continue
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- i+1
}
list(coeff, pval, mylist, aic=aic)
}
arimaSelectplot <- function(arimaSelect.out,noms,choix){
noms <- names(arimaSelect.out[[3]][[1]]$coef)
coeff <- arimaSelect.out[[1]]
k <- min(which(is.na(coeff[,1])))-1
coeff <- coeff[1:k,]
pval  <- arimaSelect.out[[2]][1:k,]
aic   <- arimaSelect.out$aic[1:k]
coeff[coeff==0] <- NA
n <- ncol(coeff)
if(missing(choix)) choix <- k
layout(matrix(c(1,1,1,2,
3,3,3,2,
3,3,3,4,
5,6,7,7),nr=4),
widths=c(10,35,45,15),
heights=c(30,30,15,15))
couleurs <- rainbow(75)[1:50]#(50)
ticks <- pretty(coeff)
par(mar=c(1,1,3,1))
plot(aic,k:1-.5,type='o',pch=21,bg='blue',cex=2,axes=F,lty=2,xpd=NA)
points(aic[choix],k-choix+.5,pch=21,cex=4,bg=2,xpd=NA)
title('aic',line=2)
par(mar=c(3,0,0,0))
plot(0,axes=F,xlab='',ylab='',xlim=range(ticks),ylim=c(.1,1))
rect(xleft  = min(ticks) + (0:49)/50*(max(ticks)-min(ticks)),
xright = min(ticks) + (1:50)/50*(max(ticks)-min(ticks)),
ytop   = rep(1,50),
ybottom= rep(0,50),col=couleurs,border=NA)
axis(1,ticks)
rect(xleft=min(ticks),xright=max(ticks),ytop=1,ybottom=0)
text(mean(coeff,na.rm=T),.5,'coefficients',cex=2,font=2)
par(mar=c(1,1,3,1))
image(1:n,1:k,t(coeff[k:1,]),axes=F,col=couleurs,zlim=range(ticks))
for(i in 1:n) for(j in 1:k) if(!is.na(coeff[j,i])) {
if(pval[j,i]<.01)                            symb = 'green'
else if( (pval[j,i]<.05) & (pval[j,i]>=.01)) symb = 'orange'
else if( (pval[j,i]<.1)  & (pval[j,i]>=.05)) symb = 'red'
else                                         symb = 'black'
polygon(c(i+.5   ,i+.2   ,i+.5   ,i+.5),
c(k-j+0.5,k-j+0.5,k-j+0.8,k-j+0.5),
col=symb)
if(j==choix)  {
rect(xleft=i-.5,
xright=i+.5,
ybottom=k-j+1.5,
ytop=k-j+.5,
lwd=4)
text(i,
k-j+1,
round(coeff[j,i],2),
cex=1.2,
font=2)
}
else{
rect(xleft=i-.5,xright=i+.5,ybottom=k-j+1.5,ytop=k-j+.5)
text(i,k-j+1,round(coeff[j,i],2),cex=1.2,font=1)
}
}
axis(3,1:n,noms)
par(mar=c(0.5,0,0,0.5))
plot(0,axes=F,xlab='',ylab='',type='n',xlim=c(0,8),ylim=c(-.2,.8))
cols <- c('green','orange','red','black')
niv  <- c('0','0.01','0.05','0.1')
for(i in 0:3){
polygon(c(1+2*i   ,1+2*i   ,1+2*i-.5   ,1+2*i),
c(.4      ,.7      , .4        , .4),
col=cols[i+1])
text(2*i,0.5,niv[i+1],cex=1.5)
}
text(8,.5,1,cex=1.5)
text(4,0,'p-value',cex=2)
box()
residus <- arimaSelect.out[[3]][[choix]]$res
par(mar=c(1,2,4,1))
acf(residus,main='')
title('acf',line=.5)
par(mar=c(1,2,4,1))
pacf(residus,main='')
title('pacf',line=.5)
par(mar=c(2,2,4,1))
qqnorm(residus,main='')
title('qq-norm',line=.5)
qqline(residus)
residus
}
if (par2 == 0) x <- log(x)
if (par2 != 0) x <- x^par2
(selection <- arimaSelect(x, order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5)))
bitmap(file='test1.png')
resid <- arimaSelectplot(selection)
dev.off()
resid
bitmap(file='test2.png')
acf(resid,length(resid)/2, main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test3.png')
pacf(resid,length(resid)/2, main='Residual Partial Autocorrelation Function')
dev.off()
bitmap(file='test4.png')
cpgram(resid, main='Residual Cumulative Periodogram')
dev.off()
bitmap(file='test5.png')
hist(resid, main='Residual Histogram', xlab='values of Residuals')
dev.off()
bitmap(file='test6.png')
densityplot(~resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test7.png')
qqnorm(resid, main='Residual Normal Q-Q Plot')
qqline(resid)
dev.off()
ncols <- length(selection[[1]][1,])
nrows <- length(selection[[2]][,1])-1
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ARIMA Parameter Estimation and Backward Selection', ncols+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Iteration', header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,names(selection[[3]][[1]]$coef)[i],header=TRUE)
}
a<-table.row.end(a)
for (j in 1:nrows) {
a<-table.row.start(a)
mydum <- 'Estimates ('
mydum <- paste(mydum,j)
mydum <- paste(mydum,')')
a<-table.element(a,mydum, header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,round(selection[[1]][j,i],4))
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(p-val)', header=TRUE)
for (i in 1:ncols) {
mydum <- '('
mydum <- paste(mydum,round(selection[[2]][j,i],4),sep='')
mydum <- paste(mydum,')')
a<-table.element(a,mydum)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated ARIMA Residuals', 1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Value', 1,TRUE)
a<-table.row.end(a)
for (i in (par4*par5+par3):length(resid)) {
a<-table.row.start(a)
a<-table.element(a,resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code