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Author

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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Mon, 19 Dec 2011 05:16:49 -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/19/t1324290239xannzw9pp9xfx6u.htm/, Retrieved Thu, 16 May 2024 04:13:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157260, Retrieved Thu, 16 May 2024 04:13:36 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

163

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- RMPD            [ARIMA Backward Selection] [] [2011-12-19 10:16:49] [c8f7c4812ba63eaa5bf379ee3b4bd6a3] [Current]

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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	14 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 & 14 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157260&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]14 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=157260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157260&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	14 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	-0.1097	0.0417	0.0617	-0.0456	1.1388	-0.1741	-0.8353
(p-val)	(0.8481 )	(0.7009 )	(0.3499 )	(0.9364 )	(0 )	(0.0926 )	(0 )
Estimates ( 2 )	-0.1551	0.0346	0.0628	0	1.1382	-0.1739	-0.8343
(p-val)	(0.0154 )	(0.5908 )	(0.325 )	(NA )	(0 )	(0.0929 )	(0 )
Estimates ( 3 )	-0.16	0	0.0584	0	1.138	-0.1742	-0.8307
(p-val)	(0.0117 )	(NA )	(0.3567 )	(NA )	(0 )	(0.1027 )	(0 )
Estimates ( 4 )	-0.1586	0	0	0	1.1443	-0.1759	-0.845
(p-val)	(0.0125 )	(NA )	(NA )	(NA )	(0 )	(0.0959 )	(0 )
Estimates ( 5 )	-0.1501	0	0	0	0.9028	0	-0.6467
(p-val)	(0.0181 )	(NA )	(NA )	(NA )	(0 )	(NA )	(0 )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & -0.1097 & 0.0417 & 0.0617 & -0.0456 & 1.1388 & -0.1741 & -0.8353 \tabularnewline
(p-val) & (0.8481 ) & (0.7009 ) & (0.3499 ) & (0.9364 ) & (0 ) & (0.0926 ) & (0 ) \tabularnewline
Estimates ( 2 ) & -0.1551 & 0.0346 & 0.0628 & 0 & 1.1382 & -0.1739 & -0.8343 \tabularnewline
(p-val) & (0.0154 ) & (0.5908 ) & (0.325 ) & (NA ) & (0 ) & (0.0929 ) & (0 ) \tabularnewline
Estimates ( 3 ) & -0.16 & 0 & 0.0584 & 0 & 1.138 & -0.1742 & -0.8307 \tabularnewline
(p-val) & (0.0117 ) & (NA ) & (0.3567 ) & (NA ) & (0 ) & (0.1027 ) & (0 ) \tabularnewline
Estimates ( 4 ) & -0.1586 & 0 & 0 & 0 & 1.1443 & -0.1759 & -0.845 \tabularnewline
(p-val) & (0.0125 ) & (NA ) & (NA ) & (NA ) & (0 ) & (0.0959 ) & (0 ) \tabularnewline
Estimates ( 5 ) & -0.1501 & 0 & 0 & 0 & 0.9028 & 0 & -0.6467 \tabularnewline
(p-val) & (0.0181 ) & (NA ) & (NA ) & (NA ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157260&T=1

[TABLE]
[ROW][C]ARIMA Parameter Estimation and Backward Selection[/C][/ROW]
[ROW][C]Iteration[/C][C]ar1[/C][C]ar2[/C][C]ar3[/C][C]ma1[/C][C]sar1[/C][C]sar2[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]-0.1097[/C][C]0.0417[/C][C]0.0617[/C][C]-0.0456[/C][C]1.1388[/C][C]-0.1741[/C][C]-0.8353[/C][/ROW]
[ROW][C](p-val)[/C][C](0.8481 )[/C][C](0.7009 )[/C][C](0.3499 )[/C][C](0.9364 )[/C][C](0 )[/C][C](0.0926 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]-0.1551[/C][C]0.0346[/C][C]0.0628[/C][C]0[/C][C]1.1382[/C][C]-0.1739[/C][C]-0.8343[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0154 )[/C][C](0.5908 )[/C][C](0.325 )[/C][C](NA )[/C][C](0 )[/C][C](0.0929 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]-0.16[/C][C]0[/C][C]0.0584[/C][C]0[/C][C]1.138[/C][C]-0.1742[/C][C]-0.8307[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0117 )[/C][C](NA )[/C][C](0.3567 )[/C][C](NA )[/C][C](0 )[/C][C](0.1027 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]-0.1586[/C][C]0[/C][C]0[/C][C]0[/C][C]1.1443[/C][C]-0.1759[/C][C]-0.845[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0125 )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][C](0.0959 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]-0.1501[/C][C]0[/C][C]0[/C][C]0[/C][C]0.9028[/C][C]0[/C][C]-0.6467[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0181 )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][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][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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157260&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	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	-0.1097	0.0417	0.0617	-0.0456	1.1388	-0.1741	-0.8353
(p-val)	(0.8481 )	(0.7009 )	(0.3499 )	(0.9364 )	(0 )	(0.0926 )	(0 )
Estimates ( 2 )	-0.1551	0.0346	0.0628	0	1.1382	-0.1739	-0.8343
(p-val)	(0.0154 )	(0.5908 )	(0.325 )	(NA )	(0 )	(0.0929 )	(0 )
Estimates ( 3 )	-0.16	0	0.0584	0	1.138	-0.1742	-0.8307
(p-val)	(0.0117 )	(NA )	(0.3567 )	(NA )	(0 )	(0.1027 )	(0 )
Estimates ( 4 )	-0.1586	0	0	0	1.1443	-0.1759	-0.845
(p-val)	(0.0125 )	(NA )	(NA )	(NA )	(0 )	(0.0959 )	(0 )
Estimates ( 5 )	-0.1501	0	0	0	0.9028	0	-0.6467
(p-val)	(0.0181 )	(NA )	(NA )	(NA )	(0 )	(NA )	(0 )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
0.179256875677864
0.585898685865044
-0.639445075461233
2.05937327381773
3.20872450269628
3.01168310477853
-0.262590563669271
2.30880405713405
2.56127352056664
-0.849194592919632
0.356800146615566
0.572836548498284
-0.137524995670927
-0.233050204266973
0.362556638423538
1.32920988007051
0.555490500729116
1.2891599741498
-0.323777813171111
-0.0348672816095581
0.440840713994695
0.925229881793727
0.237785114900613
0.931752396096505
1.61261028136892
1.38746173059139
0.187251148432255
4.15477964854928
1.20155535756421
2.73680875903016
3.06626959844886
-0.0536797328805762
0.535258545704739
-0.316400102729433
0.621134048293918
0.135373809534807
0.163899141062386
0.638514408149176
0.984377047880417
-1.01651543993548
-3.01369420187938
-0.269740567261515
1.68418521640463
-0.502455529875136
-0.360123837976992
-0.331401647390845
1.13482649735569
1.25637815886426
-0.0353562191048679
-1.75465437276721
-0.542851859205721
-0.872152794125151
2.43697526509938
-0.874299956393336
-0.964662062678601
0.312415146078827
1.51137245991996
-1.09352100568438
-0.856134057511867
1.36139152239617
-0.979389512381262
3.13916458630237
-4.69264817621577
0.573078468553487
0.689556189978787
0.255776605152841
-0.278941020192851
0.455391852923305
0.156020455796364
-0.397380832032537
0.970315751079127
-0.540702004917908
0.400806900772568
-3.60647811153427
-3.79785601546969
1.45231943200256
-1.52926356432606
0.770949995830107
-1.33114849199024
1.80965872160891
0.143604805838041
-1.01848206257988
-0.141600415069238
1.4902462667138
-2.04147017471794
0.934718726607229
-0.718975164599076
0.161054671939041
-2.28111922785988
1.56963631781339
-1.72541534538231
-0.493263662409164
-0.40450601198697
-1.34623868931537
0.674398104653962
-1.21165805276618
-0.0398791147151022
-0.237055219367763
-1.89272621354607
-0.88854540715011
4.82278500043748
-0.833801530212871
-0.749379540002424
0.636774269790684
-0.872324793648153
1.25343072453951
0.982116345064804
1.99628033756236
-2.69220195498959
-1.08480677289215
-0.77300627823094
2.34501543448694
-2.00997640909672
4.00175265672691
0.0967200370905188
-1.94861165673216
-1.03199014702557
-0.644640931198793
0.0921923409943925
1.72344133320323
0.00112158616656156
3.07454851910107
-4.95875445090906
0.569889386010528
-0.115633553403722
0.719233714150627
-0.0569965093412451
0.712515925742635
-0.462779441223622
-0.0989952132047275
1.89203603077513
0.68494723286546
-0.659267203919723
-0.830212314965507
-0.78333300654374
1.07626677780368
-1.44861239717495
2.61438204272822
-1.96117101745497
-0.790136996870398
-1.05726855696614
-2.13701534148242
-0.612315684557254
1.60182832551408
0.526740976245725
0.80542971752884
2.17478827880249
1.59397948587967
1.42644081511026
-4.3991445085498
-2.60856074709457
1.63214474247441
-0.678094609661813
6.64381720951634
-0.569927736049631
-2.90237465932354
-2.36915942850488
-0.125978366516772
-1.83961145871711
3.45235415033111
0.497635388034799
0.0636510261334541
-2.68024993859368
2.75601507927104
-0.806373829335563
0.103011288208988
-1.48399206340155
0.401801033465815
-2.77473576515214
-4.1553154957446
3.32409748757518
1.16250655395073
-1.09608884825524
2.1057487458302
-1.91957939403357
-2.43582107750425
2.44307214711506
2.17766628758215
-0.00640549978587277
-3.28275714709888
1.84524951263242
0.569288620242119
-0.262606601994391
1.91616560726914
-0.0275730239402359
0.640359260989485
0.0555389769762925
-3.96455659746656
-1.60976982022994
-1.15188033465658
2.70442113550402
0.591070046785817
-1.3694284773754
1.22983840779505
-0.982337104748476
-0.471606975959943
1.6391841653228
4.08670084056728
-1.15595820415796
2.107720244095
2.83683074595928
-2.17959847146332
0.543818394700017
7.91976421901354
-4.27018401127073
2.96060586647185
-0.108230386524165
-0.495610410201071
1.38649242260519
-3.3424361723577
0.653948731447044
1.07845843637007
-1.29045339190027
-1.06221980613255
-0.0869886388820684
2.65416696558001
13.7681012586364
4.38465731683804
3.42171287602827
9.68911085907986
4.3444820709941
-5.73704866794159
2.59011934508771
-3.70406680528535
1.14897386070476
-0.216146242136942
2.76516066159561
-1.8799388383601
-4.28747489173775
-0.766067088949204
-2.03940270976294
0.968868855602036
5.06146443451046
-0.607937097498527
2.3253015431137
1.30836433342552
3.66631831736349
3.83857601037553
3.00774988313366
-12.0194005645689
0.361760815166075
1.3994167068115
3.92586435202663
-1.38624012979332
2.55298696117562
-2.18348162465833
1.52607331941111
-0.0454523765101509
-3.40577539952215
3.31876685834751
2.76260084089148
-1.9468620564465
4.11267764775243

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.179256875677864 \tabularnewline
0.585898685865044 \tabularnewline
-0.639445075461233 \tabularnewline
2.05937327381773 \tabularnewline
3.20872450269628 \tabularnewline
3.01168310477853 \tabularnewline
-0.262590563669271 \tabularnewline
2.30880405713405 \tabularnewline
2.56127352056664 \tabularnewline
-0.849194592919632 \tabularnewline
0.356800146615566 \tabularnewline
0.572836548498284 \tabularnewline
-0.137524995670927 \tabularnewline
-0.233050204266973 \tabularnewline
0.362556638423538 \tabularnewline
1.32920988007051 \tabularnewline
0.555490500729116 \tabularnewline
1.2891599741498 \tabularnewline
-0.323777813171111 \tabularnewline
-0.0348672816095581 \tabularnewline
0.440840713994695 \tabularnewline
0.925229881793727 \tabularnewline
0.237785114900613 \tabularnewline
0.931752396096505 \tabularnewline
1.61261028136892 \tabularnewline
1.38746173059139 \tabularnewline
0.187251148432255 \tabularnewline
4.15477964854928 \tabularnewline
1.20155535756421 \tabularnewline
2.73680875903016 \tabularnewline
3.06626959844886 \tabularnewline
-0.0536797328805762 \tabularnewline
0.535258545704739 \tabularnewline
-0.316400102729433 \tabularnewline
0.621134048293918 \tabularnewline
0.135373809534807 \tabularnewline
0.163899141062386 \tabularnewline
0.638514408149176 \tabularnewline
0.984377047880417 \tabularnewline
-1.01651543993548 \tabularnewline
-3.01369420187938 \tabularnewline
-0.269740567261515 \tabularnewline
1.68418521640463 \tabularnewline
-0.502455529875136 \tabularnewline
-0.360123837976992 \tabularnewline
-0.331401647390845 \tabularnewline
1.13482649735569 \tabularnewline
1.25637815886426 \tabularnewline
-0.0353562191048679 \tabularnewline
-1.75465437276721 \tabularnewline
-0.542851859205721 \tabularnewline
-0.872152794125151 \tabularnewline
2.43697526509938 \tabularnewline
-0.874299956393336 \tabularnewline
-0.964662062678601 \tabularnewline
0.312415146078827 \tabularnewline
1.51137245991996 \tabularnewline
-1.09352100568438 \tabularnewline
-0.856134057511867 \tabularnewline
1.36139152239617 \tabularnewline
-0.979389512381262 \tabularnewline
3.13916458630237 \tabularnewline
-4.69264817621577 \tabularnewline
0.573078468553487 \tabularnewline
0.689556189978787 \tabularnewline
0.255776605152841 \tabularnewline
-0.278941020192851 \tabularnewline
0.455391852923305 \tabularnewline
0.156020455796364 \tabularnewline
-0.397380832032537 \tabularnewline
0.970315751079127 \tabularnewline
-0.540702004917908 \tabularnewline
0.400806900772568 \tabularnewline
-3.60647811153427 \tabularnewline
-3.79785601546969 \tabularnewline
1.45231943200256 \tabularnewline
-1.52926356432606 \tabularnewline
0.770949995830107 \tabularnewline
-1.33114849199024 \tabularnewline
1.80965872160891 \tabularnewline
0.143604805838041 \tabularnewline
-1.01848206257988 \tabularnewline
-0.141600415069238 \tabularnewline
1.4902462667138 \tabularnewline
-2.04147017471794 \tabularnewline
0.934718726607229 \tabularnewline
-0.718975164599076 \tabularnewline
0.161054671939041 \tabularnewline
-2.28111922785988 \tabularnewline
1.56963631781339 \tabularnewline
-1.72541534538231 \tabularnewline
-0.493263662409164 \tabularnewline
-0.40450601198697 \tabularnewline
-1.34623868931537 \tabularnewline
0.674398104653962 \tabularnewline
-1.21165805276618 \tabularnewline
-0.0398791147151022 \tabularnewline
-0.237055219367763 \tabularnewline
-1.89272621354607 \tabularnewline
-0.88854540715011 \tabularnewline
4.82278500043748 \tabularnewline
-0.833801530212871 \tabularnewline
-0.749379540002424 \tabularnewline
0.636774269790684 \tabularnewline
-0.872324793648153 \tabularnewline
1.25343072453951 \tabularnewline
0.982116345064804 \tabularnewline
1.99628033756236 \tabularnewline
-2.69220195498959 \tabularnewline
-1.08480677289215 \tabularnewline
-0.77300627823094 \tabularnewline
2.34501543448694 \tabularnewline
-2.00997640909672 \tabularnewline
4.00175265672691 \tabularnewline
0.0967200370905188 \tabularnewline
-1.94861165673216 \tabularnewline
-1.03199014702557 \tabularnewline
-0.644640931198793 \tabularnewline
0.0921923409943925 \tabularnewline
1.72344133320323 \tabularnewline
0.00112158616656156 \tabularnewline
3.07454851910107 \tabularnewline
-4.95875445090906 \tabularnewline
0.569889386010528 \tabularnewline
-0.115633553403722 \tabularnewline
0.719233714150627 \tabularnewline
-0.0569965093412451 \tabularnewline
0.712515925742635 \tabularnewline
-0.462779441223622 \tabularnewline
-0.0989952132047275 \tabularnewline
1.89203603077513 \tabularnewline
0.68494723286546 \tabularnewline
-0.659267203919723 \tabularnewline
-0.830212314965507 \tabularnewline
-0.78333300654374 \tabularnewline
1.07626677780368 \tabularnewline
-1.44861239717495 \tabularnewline
2.61438204272822 \tabularnewline
-1.96117101745497 \tabularnewline
-0.790136996870398 \tabularnewline
-1.05726855696614 \tabularnewline
-2.13701534148242 \tabularnewline
-0.612315684557254 \tabularnewline
1.60182832551408 \tabularnewline
0.526740976245725 \tabularnewline
0.80542971752884 \tabularnewline
2.17478827880249 \tabularnewline
1.59397948587967 \tabularnewline
1.42644081511026 \tabularnewline
-4.3991445085498 \tabularnewline
-2.60856074709457 \tabularnewline
1.63214474247441 \tabularnewline
-0.678094609661813 \tabularnewline
6.64381720951634 \tabularnewline
-0.569927736049631 \tabularnewline
-2.90237465932354 \tabularnewline
-2.36915942850488 \tabularnewline
-0.125978366516772 \tabularnewline
-1.83961145871711 \tabularnewline
3.45235415033111 \tabularnewline
0.497635388034799 \tabularnewline
0.0636510261334541 \tabularnewline
-2.68024993859368 \tabularnewline
2.75601507927104 \tabularnewline
-0.806373829335563 \tabularnewline
0.103011288208988 \tabularnewline
-1.48399206340155 \tabularnewline
0.401801033465815 \tabularnewline
-2.77473576515214 \tabularnewline
-4.1553154957446 \tabularnewline
3.32409748757518 \tabularnewline
1.16250655395073 \tabularnewline
-1.09608884825524 \tabularnewline
2.1057487458302 \tabularnewline
-1.91957939403357 \tabularnewline
-2.43582107750425 \tabularnewline
2.44307214711506 \tabularnewline
2.17766628758215 \tabularnewline
-0.00640549978587277 \tabularnewline
-3.28275714709888 \tabularnewline
1.84524951263242 \tabularnewline
0.569288620242119 \tabularnewline
-0.262606601994391 \tabularnewline
1.91616560726914 \tabularnewline
-0.0275730239402359 \tabularnewline
0.640359260989485 \tabularnewline
0.0555389769762925 \tabularnewline
-3.96455659746656 \tabularnewline
-1.60976982022994 \tabularnewline
-1.15188033465658 \tabularnewline
2.70442113550402 \tabularnewline
0.591070046785817 \tabularnewline
-1.3694284773754 \tabularnewline
1.22983840779505 \tabularnewline
-0.982337104748476 \tabularnewline
-0.471606975959943 \tabularnewline
1.6391841653228 \tabularnewline
4.08670084056728 \tabularnewline
-1.15595820415796 \tabularnewline
2.107720244095 \tabularnewline
2.83683074595928 \tabularnewline
-2.17959847146332 \tabularnewline
0.543818394700017 \tabularnewline
7.91976421901354 \tabularnewline
-4.27018401127073 \tabularnewline
2.96060586647185 \tabularnewline
-0.108230386524165 \tabularnewline
-0.495610410201071 \tabularnewline
1.38649242260519 \tabularnewline
-3.3424361723577 \tabularnewline
0.653948731447044 \tabularnewline
1.07845843637007 \tabularnewline
-1.29045339190027 \tabularnewline
-1.06221980613255 \tabularnewline
-0.0869886388820684 \tabularnewline
2.65416696558001 \tabularnewline
13.7681012586364 \tabularnewline
4.38465731683804 \tabularnewline
3.42171287602827 \tabularnewline
9.68911085907986 \tabularnewline
4.3444820709941 \tabularnewline
-5.73704866794159 \tabularnewline
2.59011934508771 \tabularnewline
-3.70406680528535 \tabularnewline
1.14897386070476 \tabularnewline
-0.216146242136942 \tabularnewline
2.76516066159561 \tabularnewline
-1.8799388383601 \tabularnewline
-4.28747489173775 \tabularnewline
-0.766067088949204 \tabularnewline
-2.03940270976294 \tabularnewline
0.968868855602036 \tabularnewline
5.06146443451046 \tabularnewline
-0.607937097498527 \tabularnewline
2.3253015431137 \tabularnewline
1.30836433342552 \tabularnewline
3.66631831736349 \tabularnewline
3.83857601037553 \tabularnewline
3.00774988313366 \tabularnewline
-12.0194005645689 \tabularnewline
0.361760815166075 \tabularnewline
1.3994167068115 \tabularnewline
3.92586435202663 \tabularnewline
-1.38624012979332 \tabularnewline
2.55298696117562 \tabularnewline
-2.18348162465833 \tabularnewline
1.52607331941111 \tabularnewline
-0.0454523765101509 \tabularnewline
-3.40577539952215 \tabularnewline
3.31876685834751 \tabularnewline
2.76260084089148 \tabularnewline
-1.9468620564465 \tabularnewline
4.11267764775243 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157260&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.179256875677864[/C][/ROW]
[ROW][C]0.585898685865044[/C][/ROW]
[ROW][C]-0.639445075461233[/C][/ROW]
[ROW][C]2.05937327381773[/C][/ROW]
[ROW][C]3.20872450269628[/C][/ROW]
[ROW][C]3.01168310477853[/C][/ROW]
[ROW][C]-0.262590563669271[/C][/ROW]
[ROW][C]2.30880405713405[/C][/ROW]
[ROW][C]2.56127352056664[/C][/ROW]
[ROW][C]-0.849194592919632[/C][/ROW]
[ROW][C]0.356800146615566[/C][/ROW]
[ROW][C]0.572836548498284[/C][/ROW]
[ROW][C]-0.137524995670927[/C][/ROW]
[ROW][C]-0.233050204266973[/C][/ROW]
[ROW][C]0.362556638423538[/C][/ROW]
[ROW][C]1.32920988007051[/C][/ROW]
[ROW][C]0.555490500729116[/C][/ROW]
[ROW][C]1.2891599741498[/C][/ROW]
[ROW][C]-0.323777813171111[/C][/ROW]
[ROW][C]-0.0348672816095581[/C][/ROW]
[ROW][C]0.440840713994695[/C][/ROW]
[ROW][C]0.925229881793727[/C][/ROW]
[ROW][C]0.237785114900613[/C][/ROW]
[ROW][C]0.931752396096505[/C][/ROW]
[ROW][C]1.61261028136892[/C][/ROW]
[ROW][C]1.38746173059139[/C][/ROW]
[ROW][C]0.187251148432255[/C][/ROW]
[ROW][C]4.15477964854928[/C][/ROW]
[ROW][C]1.20155535756421[/C][/ROW]
[ROW][C]2.73680875903016[/C][/ROW]
[ROW][C]3.06626959844886[/C][/ROW]
[ROW][C]-0.0536797328805762[/C][/ROW]
[ROW][C]0.535258545704739[/C][/ROW]
[ROW][C]-0.316400102729433[/C][/ROW]
[ROW][C]0.621134048293918[/C][/ROW]
[ROW][C]0.135373809534807[/C][/ROW]
[ROW][C]0.163899141062386[/C][/ROW]
[ROW][C]0.638514408149176[/C][/ROW]
[ROW][C]0.984377047880417[/C][/ROW]
[ROW][C]-1.01651543993548[/C][/ROW]
[ROW][C]-3.01369420187938[/C][/ROW]
[ROW][C]-0.269740567261515[/C][/ROW]
[ROW][C]1.68418521640463[/C][/ROW]
[ROW][C]-0.502455529875136[/C][/ROW]
[ROW][C]-0.360123837976992[/C][/ROW]
[ROW][C]-0.331401647390845[/C][/ROW]
[ROW][C]1.13482649735569[/C][/ROW]
[ROW][C]1.25637815886426[/C][/ROW]
[ROW][C]-0.0353562191048679[/C][/ROW]
[ROW][C]-1.75465437276721[/C][/ROW]
[ROW][C]-0.542851859205721[/C][/ROW]
[ROW][C]-0.872152794125151[/C][/ROW]
[ROW][C]2.43697526509938[/C][/ROW]
[ROW][C]-0.874299956393336[/C][/ROW]
[ROW][C]-0.964662062678601[/C][/ROW]
[ROW][C]0.312415146078827[/C][/ROW]
[ROW][C]1.51137245991996[/C][/ROW]
[ROW][C]-1.09352100568438[/C][/ROW]
[ROW][C]-0.856134057511867[/C][/ROW]
[ROW][C]1.36139152239617[/C][/ROW]
[ROW][C]-0.979389512381262[/C][/ROW]
[ROW][C]3.13916458630237[/C][/ROW]
[ROW][C]-4.69264817621577[/C][/ROW]
[ROW][C]0.573078468553487[/C][/ROW]
[ROW][C]0.689556189978787[/C][/ROW]
[ROW][C]0.255776605152841[/C][/ROW]
[ROW][C]-0.278941020192851[/C][/ROW]
[ROW][C]0.455391852923305[/C][/ROW]
[ROW][C]0.156020455796364[/C][/ROW]
[ROW][C]-0.397380832032537[/C][/ROW]
[ROW][C]0.970315751079127[/C][/ROW]
[ROW][C]-0.540702004917908[/C][/ROW]
[ROW][C]0.400806900772568[/C][/ROW]
[ROW][C]-3.60647811153427[/C][/ROW]
[ROW][C]-3.79785601546969[/C][/ROW]
[ROW][C]1.45231943200256[/C][/ROW]
[ROW][C]-1.52926356432606[/C][/ROW]
[ROW][C]0.770949995830107[/C][/ROW]
[ROW][C]-1.33114849199024[/C][/ROW]
[ROW][C]1.80965872160891[/C][/ROW]
[ROW][C]0.143604805838041[/C][/ROW]
[ROW][C]-1.01848206257988[/C][/ROW]
[ROW][C]-0.141600415069238[/C][/ROW]
[ROW][C]1.4902462667138[/C][/ROW]
[ROW][C]-2.04147017471794[/C][/ROW]
[ROW][C]0.934718726607229[/C][/ROW]
[ROW][C]-0.718975164599076[/C][/ROW]
[ROW][C]0.161054671939041[/C][/ROW]
[ROW][C]-2.28111922785988[/C][/ROW]
[ROW][C]1.56963631781339[/C][/ROW]
[ROW][C]-1.72541534538231[/C][/ROW]
[ROW][C]-0.493263662409164[/C][/ROW]
[ROW][C]-0.40450601198697[/C][/ROW]
[ROW][C]-1.34623868931537[/C][/ROW]
[ROW][C]0.674398104653962[/C][/ROW]
[ROW][C]-1.21165805276618[/C][/ROW]
[ROW][C]-0.0398791147151022[/C][/ROW]
[ROW][C]-0.237055219367763[/C][/ROW]
[ROW][C]-1.89272621354607[/C][/ROW]
[ROW][C]-0.88854540715011[/C][/ROW]
[ROW][C]4.82278500043748[/C][/ROW]
[ROW][C]-0.833801530212871[/C][/ROW]
[ROW][C]-0.749379540002424[/C][/ROW]
[ROW][C]0.636774269790684[/C][/ROW]
[ROW][C]-0.872324793648153[/C][/ROW]
[ROW][C]1.25343072453951[/C][/ROW]
[ROW][C]0.982116345064804[/C][/ROW]
[ROW][C]1.99628033756236[/C][/ROW]
[ROW][C]-2.69220195498959[/C][/ROW]
[ROW][C]-1.08480677289215[/C][/ROW]
[ROW][C]-0.77300627823094[/C][/ROW]
[ROW][C]2.34501543448694[/C][/ROW]
[ROW][C]-2.00997640909672[/C][/ROW]
[ROW][C]4.00175265672691[/C][/ROW]
[ROW][C]0.0967200370905188[/C][/ROW]
[ROW][C]-1.94861165673216[/C][/ROW]
[ROW][C]-1.03199014702557[/C][/ROW]
[ROW][C]-0.644640931198793[/C][/ROW]
[ROW][C]0.0921923409943925[/C][/ROW]
[ROW][C]1.72344133320323[/C][/ROW]
[ROW][C]0.00112158616656156[/C][/ROW]
[ROW][C]3.07454851910107[/C][/ROW]
[ROW][C]-4.95875445090906[/C][/ROW]
[ROW][C]0.569889386010528[/C][/ROW]
[ROW][C]-0.115633553403722[/C][/ROW]
[ROW][C]0.719233714150627[/C][/ROW]
[ROW][C]-0.0569965093412451[/C][/ROW]
[ROW][C]0.712515925742635[/C][/ROW]
[ROW][C]-0.462779441223622[/C][/ROW]
[ROW][C]-0.0989952132047275[/C][/ROW]
[ROW][C]1.89203603077513[/C][/ROW]
[ROW][C]0.68494723286546[/C][/ROW]
[ROW][C]-0.659267203919723[/C][/ROW]
[ROW][C]-0.830212314965507[/C][/ROW]
[ROW][C]-0.78333300654374[/C][/ROW]
[ROW][C]1.07626677780368[/C][/ROW]
[ROW][C]-1.44861239717495[/C][/ROW]
[ROW][C]2.61438204272822[/C][/ROW]
[ROW][C]-1.96117101745497[/C][/ROW]
[ROW][C]-0.790136996870398[/C][/ROW]
[ROW][C]-1.05726855696614[/C][/ROW]
[ROW][C]-2.13701534148242[/C][/ROW]
[ROW][C]-0.612315684557254[/C][/ROW]
[ROW][C]1.60182832551408[/C][/ROW]
[ROW][C]0.526740976245725[/C][/ROW]
[ROW][C]0.80542971752884[/C][/ROW]
[ROW][C]2.17478827880249[/C][/ROW]
[ROW][C]1.59397948587967[/C][/ROW]
[ROW][C]1.42644081511026[/C][/ROW]
[ROW][C]-4.3991445085498[/C][/ROW]
[ROW][C]-2.60856074709457[/C][/ROW]
[ROW][C]1.63214474247441[/C][/ROW]
[ROW][C]-0.678094609661813[/C][/ROW]
[ROW][C]6.64381720951634[/C][/ROW]
[ROW][C]-0.569927736049631[/C][/ROW]
[ROW][C]-2.90237465932354[/C][/ROW]
[ROW][C]-2.36915942850488[/C][/ROW]
[ROW][C]-0.125978366516772[/C][/ROW]
[ROW][C]-1.83961145871711[/C][/ROW]
[ROW][C]3.45235415033111[/C][/ROW]
[ROW][C]0.497635388034799[/C][/ROW]
[ROW][C]0.0636510261334541[/C][/ROW]
[ROW][C]-2.68024993859368[/C][/ROW]
[ROW][C]2.75601507927104[/C][/ROW]
[ROW][C]-0.806373829335563[/C][/ROW]
[ROW][C]0.103011288208988[/C][/ROW]
[ROW][C]-1.48399206340155[/C][/ROW]
[ROW][C]0.401801033465815[/C][/ROW]
[ROW][C]-2.77473576515214[/C][/ROW]
[ROW][C]-4.1553154957446[/C][/ROW]
[ROW][C]3.32409748757518[/C][/ROW]
[ROW][C]1.16250655395073[/C][/ROW]
[ROW][C]-1.09608884825524[/C][/ROW]
[ROW][C]2.1057487458302[/C][/ROW]
[ROW][C]-1.91957939403357[/C][/ROW]
[ROW][C]-2.43582107750425[/C][/ROW]
[ROW][C]2.44307214711506[/C][/ROW]
[ROW][C]2.17766628758215[/C][/ROW]
[ROW][C]-0.00640549978587277[/C][/ROW]
[ROW][C]-3.28275714709888[/C][/ROW]
[ROW][C]1.84524951263242[/C][/ROW]
[ROW][C]0.569288620242119[/C][/ROW]
[ROW][C]-0.262606601994391[/C][/ROW]
[ROW][C]1.91616560726914[/C][/ROW]
[ROW][C]-0.0275730239402359[/C][/ROW]
[ROW][C]0.640359260989485[/C][/ROW]
[ROW][C]0.0555389769762925[/C][/ROW]
[ROW][C]-3.96455659746656[/C][/ROW]
[ROW][C]-1.60976982022994[/C][/ROW]
[ROW][C]-1.15188033465658[/C][/ROW]
[ROW][C]2.70442113550402[/C][/ROW]
[ROW][C]0.591070046785817[/C][/ROW]
[ROW][C]-1.3694284773754[/C][/ROW]
[ROW][C]1.22983840779505[/C][/ROW]
[ROW][C]-0.982337104748476[/C][/ROW]
[ROW][C]-0.471606975959943[/C][/ROW]
[ROW][C]1.6391841653228[/C][/ROW]
[ROW][C]4.08670084056728[/C][/ROW]
[ROW][C]-1.15595820415796[/C][/ROW]
[ROW][C]2.107720244095[/C][/ROW]
[ROW][C]2.83683074595928[/C][/ROW]
[ROW][C]-2.17959847146332[/C][/ROW]
[ROW][C]0.543818394700017[/C][/ROW]
[ROW][C]7.91976421901354[/C][/ROW]
[ROW][C]-4.27018401127073[/C][/ROW]
[ROW][C]2.96060586647185[/C][/ROW]
[ROW][C]-0.108230386524165[/C][/ROW]
[ROW][C]-0.495610410201071[/C][/ROW]
[ROW][C]1.38649242260519[/C][/ROW]
[ROW][C]-3.3424361723577[/C][/ROW]
[ROW][C]0.653948731447044[/C][/ROW]
[ROW][C]1.07845843637007[/C][/ROW]
[ROW][C]-1.29045339190027[/C][/ROW]
[ROW][C]-1.06221980613255[/C][/ROW]
[ROW][C]-0.0869886388820684[/C][/ROW]
[ROW][C]2.65416696558001[/C][/ROW]
[ROW][C]13.7681012586364[/C][/ROW]
[ROW][C]4.38465731683804[/C][/ROW]
[ROW][C]3.42171287602827[/C][/ROW]
[ROW][C]9.68911085907986[/C][/ROW]
[ROW][C]4.3444820709941[/C][/ROW]
[ROW][C]-5.73704866794159[/C][/ROW]
[ROW][C]2.59011934508771[/C][/ROW]
[ROW][C]-3.70406680528535[/C][/ROW]
[ROW][C]1.14897386070476[/C][/ROW]
[ROW][C]-0.216146242136942[/C][/ROW]
[ROW][C]2.76516066159561[/C][/ROW]
[ROW][C]-1.8799388383601[/C][/ROW]
[ROW][C]-4.28747489173775[/C][/ROW]
[ROW][C]-0.766067088949204[/C][/ROW]
[ROW][C]-2.03940270976294[/C][/ROW]
[ROW][C]0.968868855602036[/C][/ROW]
[ROW][C]5.06146443451046[/C][/ROW]
[ROW][C]-0.607937097498527[/C][/ROW]
[ROW][C]2.3253015431137[/C][/ROW]
[ROW][C]1.30836433342552[/C][/ROW]
[ROW][C]3.66631831736349[/C][/ROW]
[ROW][C]3.83857601037553[/C][/ROW]
[ROW][C]3.00774988313366[/C][/ROW]
[ROW][C]-12.0194005645689[/C][/ROW]
[ROW][C]0.361760815166075[/C][/ROW]
[ROW][C]1.3994167068115[/C][/ROW]
[ROW][C]3.92586435202663[/C][/ROW]
[ROW][C]-1.38624012979332[/C][/ROW]
[ROW][C]2.55298696117562[/C][/ROW]
[ROW][C]-2.18348162465833[/C][/ROW]
[ROW][C]1.52607331941111[/C][/ROW]
[ROW][C]-0.0454523765101509[/C][/ROW]
[ROW][C]-3.40577539952215[/C][/ROW]
[ROW][C]3.31876685834751[/C][/ROW]
[ROW][C]2.76260084089148[/C][/ROW]
[ROW][C]-1.9468620564465[/C][/ROW]
[ROW][C]4.11267764775243[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157260&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157260&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
0.179256875677864
0.585898685865044
-0.639445075461233
2.05937327381773
3.20872450269628
3.01168310477853
-0.262590563669271
2.30880405713405
2.56127352056664
-0.849194592919632
0.356800146615566
0.572836548498284
-0.137524995670927
-0.233050204266973
0.362556638423538
1.32920988007051
0.555490500729116
1.2891599741498
-0.323777813171111
-0.0348672816095581
0.440840713994695
0.925229881793727
0.237785114900613
0.931752396096505
1.61261028136892
1.38746173059139
0.187251148432255
4.15477964854928
1.20155535756421
2.73680875903016
3.06626959844886
-0.0536797328805762
0.535258545704739
-0.316400102729433
0.621134048293918
0.135373809534807
0.163899141062386
0.638514408149176
0.984377047880417
-1.01651543993548
-3.01369420187938
-0.269740567261515
1.68418521640463
-0.502455529875136
-0.360123837976992
-0.331401647390845
1.13482649735569
1.25637815886426
-0.0353562191048679
-1.75465437276721
-0.542851859205721
-0.872152794125151
2.43697526509938
-0.874299956393336
-0.964662062678601
0.312415146078827
1.51137245991996
-1.09352100568438
-0.856134057511867
1.36139152239617
-0.979389512381262
3.13916458630237
-4.69264817621577
0.573078468553487
0.689556189978787
0.255776605152841
-0.278941020192851
0.455391852923305
0.156020455796364
-0.397380832032537
0.970315751079127
-0.540702004917908
0.400806900772568
-3.60647811153427
-3.79785601546969
1.45231943200256
-1.52926356432606
0.770949995830107
-1.33114849199024
1.80965872160891
0.143604805838041
-1.01848206257988
-0.141600415069238
1.4902462667138
-2.04147017471794
0.934718726607229
-0.718975164599076
0.161054671939041
-2.28111922785988
1.56963631781339
-1.72541534538231
-0.493263662409164
-0.40450601198697
-1.34623868931537
0.674398104653962
-1.21165805276618
-0.0398791147151022
-0.237055219367763
-1.89272621354607
-0.88854540715011
4.82278500043748
-0.833801530212871
-0.749379540002424
0.636774269790684
-0.872324793648153
1.25343072453951
0.982116345064804
1.99628033756236
-2.69220195498959
-1.08480677289215
-0.77300627823094
2.34501543448694
-2.00997640909672
4.00175265672691
0.0967200370905188
-1.94861165673216
-1.03199014702557
-0.644640931198793
0.0921923409943925
1.72344133320323
0.00112158616656156
3.07454851910107
-4.95875445090906
0.569889386010528
-0.115633553403722
0.719233714150627
-0.0569965093412451
0.712515925742635
-0.462779441223622
-0.0989952132047275
1.89203603077513
0.68494723286546
-0.659267203919723
-0.830212314965507
-0.78333300654374
1.07626677780368
-1.44861239717495
2.61438204272822
-1.96117101745497
-0.790136996870398
-1.05726855696614
-2.13701534148242
-0.612315684557254
1.60182832551408
0.526740976245725
0.80542971752884
2.17478827880249
1.59397948587967
1.42644081511026
-4.3991445085498
-2.60856074709457
1.63214474247441
-0.678094609661813
6.64381720951634
-0.569927736049631
-2.90237465932354
-2.36915942850488
-0.125978366516772
-1.83961145871711
3.45235415033111
0.497635388034799
0.0636510261334541
-2.68024993859368
2.75601507927104
-0.806373829335563
0.103011288208988
-1.48399206340155
0.401801033465815
-2.77473576515214
-4.1553154957446
3.32409748757518
1.16250655395073
-1.09608884825524
2.1057487458302
-1.91957939403357
-2.43582107750425
2.44307214711506
2.17766628758215
-0.00640549978587277
-3.28275714709888
1.84524951263242
0.569288620242119
-0.262606601994391
1.91616560726914
-0.0275730239402359
0.640359260989485
0.0555389769762925
-3.96455659746656
-1.60976982022994
-1.15188033465658
2.70442113550402
0.591070046785817
-1.3694284773754
1.22983840779505
-0.982337104748476
-0.471606975959943
1.6391841653228
4.08670084056728
-1.15595820415796
2.107720244095
2.83683074595928
-2.17959847146332
0.543818394700017
7.91976421901354
-4.27018401127073
2.96060586647185
-0.108230386524165
-0.495610410201071
1.38649242260519
-3.3424361723577
0.653948731447044
1.07845843637007
-1.29045339190027
-1.06221980613255
-0.0869886388820684
2.65416696558001
13.7681012586364
4.38465731683804
3.42171287602827
9.68911085907986
4.3444820709941
-5.73704866794159
2.59011934508771
-3.70406680528535
1.14897386070476
-0.216146242136942
2.76516066159561
-1.8799388383601
-4.28747489173775
-0.766067088949204
-2.03940270976294
0.968868855602036
5.06146443451046
-0.607937097498527
2.3253015431137
1.30836433342552
3.66631831736349
3.83857601037553
3.00774988313366
-12.0194005645689
0.361760815166075
1.3994167068115
3.92586435202663
-1.38624012979332
2.55298696117562
-2.18348162465833
1.52607331941111
-0.0454523765101509
-3.40577539952215
3.31876685834751
2.76260084089148
-1.9468620564465
4.11267764775243

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

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Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; 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