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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

Tue, 06 Dec 2011 16:08:38 -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/06/t132320575218fjxsnm5izkka9.htm/, Retrieved Mon, 29 Apr 2024 07:50:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151949, Retrieved Mon, 29 Apr 2024 07:50:30 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

107

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Backward Selection] [Unemployment] [2010-11-29 17:10:28] [b98453cac15ba1066b407e146608df68]
-           [ARIMA Backward Selection] [ws9 error] [2011-12-05 18:13:45] [8501ca4b76170905b8a207a77f626994]
- R P           [ARIMA Backward Selection] [ws9 arima] [2011-12-06 21:08:38] [5ecdd7f9023ba8f0fbc3191d3a9c3da8] [Current]
-                 [ARIMA Backward Selection] [Paper Deel 2 Arim...] [2011-12-22 14:22:54] [8501ca4b76170905b8a207a77f626994] 
-   PD              [ARIMA Backward Selection] [Paper: ARIMA Back...] [2011-12-23 14:03:19] [f722e8e78b9e5c5ebaa2263f273aa636] 

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'AstonUniversity' @ aston.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 & 9 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151949&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151949&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151949&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	9 seconds
R Server	'AstonUniversity' @ aston.wessa.net

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	sar1	sar2	sma1
Estimates ( 1 )	0.098	0.2276	0.0655	-0.0891	-0.0526	-0.6512
(p-val)	(0.0672 )	(0 )	(0.2171 )	(0.4288 )	(0.5606 )	(0 )
Estimates ( 2 )	0.0953	0.2323	0.0652	-0.043	0	-0.6971
(p-val)	(0.0735 )	(0 )	(0.2186 )	(0.5812 )	(NA )	(0 )
Estimates ( 3 )	0.0938	0.235	0.0655	0	0	-0.7207
(p-val)	(0.0777 )	(0 )	(0.2165 )	(NA )	(NA )	(0 )
Estimates ( 4 )	0.1094	0.2417	0	0	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(NA )	(NA )	(0 )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & 0.098 & 0.2276 & 0.0655 & -0.0891 & -0.0526 & -0.6512 \tabularnewline
(p-val) & (0.0672 ) & (0 ) & (0.2171 ) & (0.4288 ) & (0.5606 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.0953 & 0.2323 & 0.0652 & -0.043 & 0 & -0.6971 \tabularnewline
(p-val) & (0.0735 ) & (0 ) & (0.2186 ) & (0.5812 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0.0938 & 0.235 & 0.0655 & 0 & 0 & -0.7207 \tabularnewline
(p-val) & (0.0777 ) & (0 ) & (0.2165 ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0.1094 & 0.2417 & 0 & 0 & 0 & -0.724 \tabularnewline
(p-val) & (0.0348 ) & (0 ) & (NA ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151949&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]sar1[/C][C]sar2[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]0.098[/C][C]0.2276[/C][C]0.0655[/C][C]-0.0891[/C][C]-0.0526[/C][C]-0.6512[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0672 )[/C][C](0 )[/C][C](0.2171 )[/C][C](0.4288 )[/C][C](0.5606 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.0953[/C][C]0.2323[/C][C]0.0652[/C][C]-0.043[/C][C]0[/C][C]-0.6971[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0735 )[/C][C](0 )[/C][C](0.2186 )[/C][C](0.5812 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0.0938[/C][C]0.235[/C][C]0.0655[/C][C]0[/C][C]0[/C][C]-0.7207[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0777 )[/C][C](0 )[/C][C](0.2165 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0.1094[/C][C]0.2417[/C][C]0[/C][C]0[/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](NA )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/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][/ROW]
[ROW][C]Estimates ( 6 )[/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][/ROW]
[ROW][C]Estimates ( 7 )[/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][/ROW]
[ROW][C]Estimates ( 8 )[/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][/ROW]
[ROW][C]Estimates ( 9 )[/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][/ROW]
[ROW][C]Estimates ( 10 )[/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][/ROW]
[ROW][C]Estimates ( 11 )[/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][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151949&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151949&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	sar1	sar2	sma1
Estimates ( 1 )	0.098	0.2276	0.0655	-0.0891	-0.0526	-0.6512
(p-val)	(0.0672 )	(0 )	(0.2171 )	(0.4288 )	(0.5606 )	(0 )
Estimates ( 2 )	0.0953	0.2323	0.0652	-0.043	0	-0.6971
(p-val)	(0.0735 )	(0 )	(0.2186 )	(0.5812 )	(NA )	(0 )
Estimates ( 3 )	0.0938	0.235	0.0655	0	0	-0.7207
(p-val)	(0.0777 )	(0 )	(0.2165 )	(NA )	(NA )	(0 )
Estimates ( 4 )	0.1094	0.2417	0	0	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(NA )	(NA )	(0 )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.0447137390230372
-0.0687783621797698
0.200064905468958
0.369647506078354
1.5230252016251
-0.382348236883874
0.442481124106618
-0.548688226625169
-0.326734158085415
1.30468259741215
-1.34999611361679
-0.389444329321606
0.182875957532909
-0.827655945392066
-0.571203435431581
-0.727773843876007
-0.408616832201768
-0.0704102116180478
-0.812911801986553
-0.878889741504348
0.689887045661697
-0.73070071588398
0.83514602992555
-0.138182611099785
-1.62611373660868
-1.1003489225231
0.45677503000225
0.0327527399141363
0.101998162564366
0.314319979365983
-0.280297381560136
0.300458424513065
0.864927194574199
0.113438692229274
0.0734383808004924
-1.19439085857496
-0.151865081640933
-0.0210499033038676
-0.34332826780972
0.574181409297989
0.47781406936538
-0.345526543847195
0.0869606035899537
0.590525692907638
-0.490002115089082
-0.42266409137097
-0.0950390600916404
-0.100980417211215
0.509364851830624
-1.00698273667972
0.328828309743278
0.863393026980703
-0.476121983127133
-0.442131906488378
-0.0557930321974531
0.32725522022826
0.866297964155573
0.446075301000411
0.800999595219834
0.91338184439289
1.21106666185213
0.432277274338901
0.307401635858294
-0.163324595203689
-0.171057239382783
-1.03961279564403
0.0264096956690344
0.590971943542331
0.0976706765255999
-0.913730369925244
-0.330725944786726
-0.391957876013934
-0.335950344555535
-0.460376741540404
-0.0292544639838915
0.49616447226297
-0.7336280649127
-0.0817196745305824
-0.515669890139459
0.578909015153022
-0.353325631064129
0.636523097113649
0.0383900133516997
-0.0571795492597641
-0.858265740879829
-0.0909909660032941
0.755512537116653
-0.518648218707543
0.99449242383029
0.406664941461209
-0.616393294532457
-0.995857996661196
-0.203823891882659
0.28578054265563
0.99284896825491
-0.0326397212497139
-0.57212453969984
-0.55254808119219
-0.240243601800396
0.322411611800009
0.630311946522547
0.60143526031478
-0.733286674135061
-0.160048873647465
0.395985412842838
0.52588749721034
0.819053314546454
0.175417251012814
0.722306904780725
1.20239659459036
0.181074935166371
0.0276801513692066
-0.448687018973049
-0.252681576271681
0.188300611159091
-0.140216623141471
-1.04008096610996
-0.165183747256138
-0.93809857303899
0.684172589908009
-0.4201255345531
-0.354904956286963
-0.440209568359698
-1.11887539934479
0.068640003010714
0.616722079452865
0.0574427533623594
0.267702495945972
0.130908770050157
0.588947022053609
0.00572931369785768
-0.884969238896738
-0.428900390357213
-0.717442437870696
1.42772319473128
-0.36153102666427
-0.321237195335522
1.06722596847934
-0.332899506065791
0.267554935998101
-0.558802728676614
0.942244603542415
0.107679922970091
0.814030269011075
-0.0649701598114813
0.345683591465392
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0.0553112759324222
0.177992064299507
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-0.207811604597472
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-0.0650415674393966
-0.234295874111282
-0.41803092723909
0.0635320707535762
0.132842597261158
0.79419064909374
-0.733779191712504
-0.499463117615231
1.0823913949269
-0.195664377201616
-0.575471991222576
0.555335920543568
-0.271927109954584
0.319592470794683
0.48105087288375
-0.812620213536131
-0.0584292455689943
0.319300018289749
0.34016241030223
-0.380473819906876
-0.388108344831478
0.168514421024259
0.196618846332724
0.265969913815876
-0.564467948591433
-0.0741103946298093
-0.245462478984907
-0.000631389130694023
0.2136918686706
-0.514624434050636
1.10591298664042
-1.14042349372873
0.295885099728987
0.192716128562493
0.0823072360901547
-0.731740593631138
0.099310882268086
-0.291266196587147
0.526798105365212
-0.626284046161079
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-0.325457743058622
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-0.57553668406704
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0.375158033749647
-0.979807119801264
-0.738198924749119
-0.295608029910084
0.782269509032293
-0.284789999593329
-0.508090777083817
-0.101173612478615
1.69597904198098
0.0868296996851484
-0.93543797177881
0.0840202440456799
-0.0643789068827894
-0.198880992866796
-0.384724065582397
0.0966832602462867
0.0394759569039031
0.241746013350898
0.371825824956125
-0.398580802269844
0.453543850388816
0.616055634902418
-0.182235403454581
0.705125508320765
-0.285630486746989
-0.940748067936384
-0.0149619041223966
1.03118125955965
0.812714621914979
0.243127768316856
0.127520356571724
-0.118773509057475
0.201560301384726
0.562828109185303
0.0391841115599751
0.360470641990829
0.00772967822311359
0.520052219849974
0.139321005840949
-0.101107123930484
-0.484393930327139
-0.057754279039374
-0.217551105441796
-0.118845039456261
-0.403654242508065
0.601786011597929
0.320911327830857
-0.378816315160814
-0.500309884420751
0.315580203935121
-0.0462215703679691
-0.00959682693806873
-0.380509116219345
0.161104299921256
-0.215810335251697
-0.231483682165426
-0.287379169473631
0.264765750403482
0.147438035615534
-0.172258313089147
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-0.84524989277095
-0.0711699861591582
-0.0997707754006913
0.312584621741617
-0.184888311802177
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-0.258926987522457
-0.183942477667873
0.0508125238015787
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0.264522266056075
-0.669526688880409
0.598261633758342
0.315603412390072
0.542034140562915
-0.123599550925941
-0.45576812610609
-0.180828955521262
0.423548877849226
0.194698871817651
0.318093988184699
-0.167334118203339
0.882620358580327
0.0779770142006728
0.822929220395405
0.82078582335905
1.77156595754176
-0.557596464347272
0.184472788459779
-0.192694837134699
0.102324611256454
-1.12766298531624
-0.0361697361559068
0.110558330924144
-0.216038204859256
0.0312628049352559
-0.555202236637242
-0.105295179261148
-0.417645223996272
-0.36308787586902
-0.259927749206962
-0.0304011840414261
-0.425424354678137
0.278579064357363
0.570200202017799
0.317954382193139
-0.606007243143389
0.0543284804685288
0.133601531323599
-0.213625062568398
-0.677702388064595
0.454032417363355
-0.267527781486841
-0.842082468564818
0.0427494967943826
0.274541114944775
-0.425880299953958
0.414783000990572
-0.322934639718811
0.00915482778130383
-0.135962089679246
-0.916593232790992
0.147517728743762
-0.278725545758281
0.297054816419426
-0.249411714902135
0.28114796454196
-0.63317398361933
0.839472882357591
-0.335288305886153
-0.0537324985391935
-0.226994781079176
0.000315598163692917
0.516500742386455

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0447137390230372 \tabularnewline
-0.0687783621797698 \tabularnewline
0.200064905468958 \tabularnewline
0.369647506078354 \tabularnewline
1.5230252016251 \tabularnewline
-0.382348236883874 \tabularnewline
0.442481124106618 \tabularnewline
-0.548688226625169 \tabularnewline
-0.326734158085415 \tabularnewline
1.30468259741215 \tabularnewline
-1.34999611361679 \tabularnewline
-0.389444329321606 \tabularnewline
0.182875957532909 \tabularnewline
-0.827655945392066 \tabularnewline
-0.571203435431581 \tabularnewline
-0.727773843876007 \tabularnewline
-0.408616832201768 \tabularnewline
-0.0704102116180478 \tabularnewline
-0.812911801986553 \tabularnewline
-0.878889741504348 \tabularnewline
0.689887045661697 \tabularnewline
-0.73070071588398 \tabularnewline
0.83514602992555 \tabularnewline
-0.138182611099785 \tabularnewline
-1.62611373660868 \tabularnewline
-1.1003489225231 \tabularnewline
0.45677503000225 \tabularnewline
0.0327527399141363 \tabularnewline
0.101998162564366 \tabularnewline
0.314319979365983 \tabularnewline
-0.280297381560136 \tabularnewline
0.300458424513065 \tabularnewline
0.864927194574199 \tabularnewline
0.113438692229274 \tabularnewline
0.0734383808004924 \tabularnewline
-1.19439085857496 \tabularnewline
-0.151865081640933 \tabularnewline
-0.0210499033038676 \tabularnewline
-0.34332826780972 \tabularnewline
0.574181409297989 \tabularnewline
0.47781406936538 \tabularnewline
-0.345526543847195 \tabularnewline
0.0869606035899537 \tabularnewline
0.590525692907638 \tabularnewline
-0.490002115089082 \tabularnewline
-0.42266409137097 \tabularnewline
-0.0950390600916404 \tabularnewline
-0.100980417211215 \tabularnewline
0.509364851830624 \tabularnewline
-1.00698273667972 \tabularnewline
0.328828309743278 \tabularnewline
0.863393026980703 \tabularnewline
-0.476121983127133 \tabularnewline
-0.442131906488378 \tabularnewline
-0.0557930321974531 \tabularnewline
0.32725522022826 \tabularnewline
0.866297964155573 \tabularnewline
0.446075301000411 \tabularnewline
0.800999595219834 \tabularnewline
0.91338184439289 \tabularnewline
1.21106666185213 \tabularnewline
0.432277274338901 \tabularnewline
0.307401635858294 \tabularnewline
-0.163324595203689 \tabularnewline
-0.171057239382783 \tabularnewline
-1.03961279564403 \tabularnewline
0.0264096956690344 \tabularnewline
0.590971943542331 \tabularnewline
0.0976706765255999 \tabularnewline
-0.913730369925244 \tabularnewline
-0.330725944786726 \tabularnewline
-0.391957876013934 \tabularnewline
-0.335950344555535 \tabularnewline
-0.460376741540404 \tabularnewline
-0.0292544639838915 \tabularnewline
0.49616447226297 \tabularnewline
-0.7336280649127 \tabularnewline
-0.0817196745305824 \tabularnewline
-0.515669890139459 \tabularnewline
0.578909015153022 \tabularnewline
-0.353325631064129 \tabularnewline
0.636523097113649 \tabularnewline
0.0383900133516997 \tabularnewline
-0.0571795492597641 \tabularnewline
-0.858265740879829 \tabularnewline
-0.0909909660032941 \tabularnewline
0.755512537116653 \tabularnewline
-0.518648218707543 \tabularnewline
0.99449242383029 \tabularnewline
0.406664941461209 \tabularnewline
-0.616393294532457 \tabularnewline
-0.995857996661196 \tabularnewline
-0.203823891882659 \tabularnewline
0.28578054265563 \tabularnewline
0.99284896825491 \tabularnewline
-0.0326397212497139 \tabularnewline
-0.57212453969984 \tabularnewline
-0.55254808119219 \tabularnewline
-0.240243601800396 \tabularnewline
0.322411611800009 \tabularnewline
0.630311946522547 \tabularnewline
0.60143526031478 \tabularnewline
-0.733286674135061 \tabularnewline
-0.160048873647465 \tabularnewline
0.395985412842838 \tabularnewline
0.52588749721034 \tabularnewline
0.819053314546454 \tabularnewline
0.175417251012814 \tabularnewline
0.722306904780725 \tabularnewline
1.20239659459036 \tabularnewline
0.181074935166371 \tabularnewline
0.0276801513692066 \tabularnewline
-0.448687018973049 \tabularnewline
-0.252681576271681 \tabularnewline
0.188300611159091 \tabularnewline
-0.140216623141471 \tabularnewline
-1.04008096610996 \tabularnewline
-0.165183747256138 \tabularnewline
-0.93809857303899 \tabularnewline
0.684172589908009 \tabularnewline
-0.4201255345531 \tabularnewline
-0.354904956286963 \tabularnewline
-0.440209568359698 \tabularnewline
-1.11887539934479 \tabularnewline
0.068640003010714 \tabularnewline
0.616722079452865 \tabularnewline
0.0574427533623594 \tabularnewline
0.267702495945972 \tabularnewline
0.130908770050157 \tabularnewline
0.588947022053609 \tabularnewline
0.00572931369785768 \tabularnewline
-0.884969238896738 \tabularnewline
-0.428900390357213 \tabularnewline
-0.717442437870696 \tabularnewline
1.42772319473128 \tabularnewline
-0.36153102666427 \tabularnewline
-0.321237195335522 \tabularnewline
1.06722596847934 \tabularnewline
-0.332899506065791 \tabularnewline
0.267554935998101 \tabularnewline
-0.558802728676614 \tabularnewline
0.942244603542415 \tabularnewline
0.107679922970091 \tabularnewline
0.814030269011075 \tabularnewline
-0.0649701598114813 \tabularnewline
0.345683591465392 \tabularnewline
-0.473259367602333 \tabularnewline
-0.240987316964619 \tabularnewline
0.0553112759324222 \tabularnewline
0.177992064299507 \tabularnewline
-0.284191254043013 \tabularnewline
-0.425390201110039 \tabularnewline
-0.207811604597472 \tabularnewline
-0.175665137016655 \tabularnewline
-0.705543673947574 \tabularnewline
-0.0650415674393966 \tabularnewline
-0.234295874111282 \tabularnewline
-0.41803092723909 \tabularnewline
0.0635320707535762 \tabularnewline
0.132842597261158 \tabularnewline
0.79419064909374 \tabularnewline
-0.733779191712504 \tabularnewline
-0.499463117615231 \tabularnewline
1.0823913949269 \tabularnewline
-0.195664377201616 \tabularnewline
-0.575471991222576 \tabularnewline
0.555335920543568 \tabularnewline
-0.271927109954584 \tabularnewline
0.319592470794683 \tabularnewline
0.48105087288375 \tabularnewline
-0.812620213536131 \tabularnewline
-0.0584292455689943 \tabularnewline
0.319300018289749 \tabularnewline
0.34016241030223 \tabularnewline
-0.380473819906876 \tabularnewline
-0.388108344831478 \tabularnewline
0.168514421024259 \tabularnewline
0.196618846332724 \tabularnewline
0.265969913815876 \tabularnewline
-0.564467948591433 \tabularnewline
-0.0741103946298093 \tabularnewline
-0.245462478984907 \tabularnewline
-0.000631389130694023 \tabularnewline
0.2136918686706 \tabularnewline
-0.514624434050636 \tabularnewline
1.10591298664042 \tabularnewline
-1.14042349372873 \tabularnewline
0.295885099728987 \tabularnewline
0.192716128562493 \tabularnewline
0.0823072360901547 \tabularnewline
-0.731740593631138 \tabularnewline
0.099310882268086 \tabularnewline
-0.291266196587147 \tabularnewline
0.526798105365212 \tabularnewline
-0.626284046161079 \tabularnewline
0.508876658305956 \tabularnewline
-0.280279967057594 \tabularnewline
0.627929970024853 \tabularnewline
-0.540421905805387 \tabularnewline
-0.193912942565409 \tabularnewline
-0.0379846562359361 \tabularnewline
-0.073762093985459 \tabularnewline
-0.242637924961539 \tabularnewline
-0.430619662493265 \tabularnewline
-0.266578729863338 \tabularnewline
-0.450848285345905 \tabularnewline
0.543203274624043 \tabularnewline
0.292437549848942 \tabularnewline
0.629960879906417 \tabularnewline
0.386023444609388 \tabularnewline
-0.464131363134327 \tabularnewline
-0.162091264949172 \tabularnewline
-0.109311710625318 \tabularnewline
0.206779067871808 \tabularnewline
-0.37094182466382 \tabularnewline
0.205887156505417 \tabularnewline
-0.0868138861290567 \tabularnewline
-0.00924483495568296 \tabularnewline
-0.0350282520712355 \tabularnewline
0.0295215508933412 \tabularnewline
-0.325457743058622 \tabularnewline
1.52876883857954 \tabularnewline
0.227700385976822 \tabularnewline
-0.57553668406704 \tabularnewline
0.594316510090436 \tabularnewline
0.375158033749647 \tabularnewline
-0.979807119801264 \tabularnewline
-0.738198924749119 \tabularnewline
-0.295608029910084 \tabularnewline
0.782269509032293 \tabularnewline
-0.284789999593329 \tabularnewline
-0.508090777083817 \tabularnewline
-0.101173612478615 \tabularnewline
1.69597904198098 \tabularnewline
0.0868296996851484 \tabularnewline
-0.93543797177881 \tabularnewline
0.0840202440456799 \tabularnewline
-0.0643789068827894 \tabularnewline
-0.198880992866796 \tabularnewline
-0.384724065582397 \tabularnewline
0.0966832602462867 \tabularnewline
0.0394759569039031 \tabularnewline
0.241746013350898 \tabularnewline
0.371825824956125 \tabularnewline
-0.398580802269844 \tabularnewline
0.453543850388816 \tabularnewline
0.616055634902418 \tabularnewline
-0.182235403454581 \tabularnewline
0.705125508320765 \tabularnewline
-0.285630486746989 \tabularnewline
-0.940748067936384 \tabularnewline
-0.0149619041223966 \tabularnewline
1.03118125955965 \tabularnewline
0.812714621914979 \tabularnewline
0.243127768316856 \tabularnewline
0.127520356571724 \tabularnewline
-0.118773509057475 \tabularnewline
0.201560301384726 \tabularnewline
0.562828109185303 \tabularnewline
0.0391841115599751 \tabularnewline
0.360470641990829 \tabularnewline
0.00772967822311359 \tabularnewline
0.520052219849974 \tabularnewline
0.139321005840949 \tabularnewline
-0.101107123930484 \tabularnewline
-0.484393930327139 \tabularnewline
-0.057754279039374 \tabularnewline
-0.217551105441796 \tabularnewline
-0.118845039456261 \tabularnewline
-0.403654242508065 \tabularnewline
0.601786011597929 \tabularnewline
0.320911327830857 \tabularnewline
-0.378816315160814 \tabularnewline
-0.500309884420751 \tabularnewline
0.315580203935121 \tabularnewline
-0.0462215703679691 \tabularnewline
-0.00959682693806873 \tabularnewline
-0.380509116219345 \tabularnewline
0.161104299921256 \tabularnewline
-0.215810335251697 \tabularnewline
-0.231483682165426 \tabularnewline
-0.287379169473631 \tabularnewline
0.264765750403482 \tabularnewline
0.147438035615534 \tabularnewline
-0.172258313089147 \tabularnewline
-0.141335814880891 \tabularnewline
-0.84524989277095 \tabularnewline
-0.0711699861591582 \tabularnewline
-0.0997707754006913 \tabularnewline
0.312584621741617 \tabularnewline
-0.184888311802177 \tabularnewline
0.142210938788583 \tabularnewline
-0.258926987522457 \tabularnewline
-0.183942477667873 \tabularnewline
0.0508125238015787 \tabularnewline
-0.00280282669520279 \tabularnewline
0.264522266056075 \tabularnewline
-0.669526688880409 \tabularnewline
0.598261633758342 \tabularnewline
0.315603412390072 \tabularnewline
0.542034140562915 \tabularnewline
-0.123599550925941 \tabularnewline
-0.45576812610609 \tabularnewline
-0.180828955521262 \tabularnewline
0.423548877849226 \tabularnewline
0.194698871817651 \tabularnewline
0.318093988184699 \tabularnewline
-0.167334118203339 \tabularnewline
0.882620358580327 \tabularnewline
0.0779770142006728 \tabularnewline
0.822929220395405 \tabularnewline
0.82078582335905 \tabularnewline
1.77156595754176 \tabularnewline
-0.557596464347272 \tabularnewline
0.184472788459779 \tabularnewline
-0.192694837134699 \tabularnewline
0.102324611256454 \tabularnewline
-1.12766298531624 \tabularnewline
-0.0361697361559068 \tabularnewline
0.110558330924144 \tabularnewline
-0.216038204859256 \tabularnewline
0.0312628049352559 \tabularnewline
-0.555202236637242 \tabularnewline
-0.105295179261148 \tabularnewline
-0.417645223996272 \tabularnewline
-0.36308787586902 \tabularnewline
-0.259927749206962 \tabularnewline
-0.0304011840414261 \tabularnewline
-0.425424354678137 \tabularnewline
0.278579064357363 \tabularnewline
0.570200202017799 \tabularnewline
0.317954382193139 \tabularnewline
-0.606007243143389 \tabularnewline
0.0543284804685288 \tabularnewline
0.133601531323599 \tabularnewline
-0.213625062568398 \tabularnewline
-0.677702388064595 \tabularnewline
0.454032417363355 \tabularnewline
-0.267527781486841 \tabularnewline
-0.842082468564818 \tabularnewline
0.0427494967943826 \tabularnewline
0.274541114944775 \tabularnewline
-0.425880299953958 \tabularnewline
0.414783000990572 \tabularnewline
-0.322934639718811 \tabularnewline
0.00915482778130383 \tabularnewline
-0.135962089679246 \tabularnewline
-0.916593232790992 \tabularnewline
0.147517728743762 \tabularnewline
-0.278725545758281 \tabularnewline
0.297054816419426 \tabularnewline
-0.249411714902135 \tabularnewline
0.28114796454196 \tabularnewline
-0.63317398361933 \tabularnewline
0.839472882357591 \tabularnewline
-0.335288305886153 \tabularnewline
-0.0537324985391935 \tabularnewline
-0.226994781079176 \tabularnewline
0.000315598163692917 \tabularnewline
0.516500742386455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151949&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0447137390230372[/C][/ROW]
[ROW][C]-0.0687783621797698[/C][/ROW]
[ROW][C]0.200064905468958[/C][/ROW]
[ROW][C]0.369647506078354[/C][/ROW]
[ROW][C]1.5230252016251[/C][/ROW]
[ROW][C]-0.382348236883874[/C][/ROW]
[ROW][C]0.442481124106618[/C][/ROW]
[ROW][C]-0.548688226625169[/C][/ROW]
[ROW][C]-0.326734158085415[/C][/ROW]
[ROW][C]1.30468259741215[/C][/ROW]
[ROW][C]-1.34999611361679[/C][/ROW]
[ROW][C]-0.389444329321606[/C][/ROW]
[ROW][C]0.182875957532909[/C][/ROW]
[ROW][C]-0.827655945392066[/C][/ROW]
[ROW][C]-0.571203435431581[/C][/ROW]
[ROW][C]-0.727773843876007[/C][/ROW]
[ROW][C]-0.408616832201768[/C][/ROW]
[ROW][C]-0.0704102116180478[/C][/ROW]
[ROW][C]-0.812911801986553[/C][/ROW]
[ROW][C]-0.878889741504348[/C][/ROW]
[ROW][C]0.689887045661697[/C][/ROW]
[ROW][C]-0.73070071588398[/C][/ROW]
[ROW][C]0.83514602992555[/C][/ROW]
[ROW][C]-0.138182611099785[/C][/ROW]
[ROW][C]-1.62611373660868[/C][/ROW]
[ROW][C]-1.1003489225231[/C][/ROW]
[ROW][C]0.45677503000225[/C][/ROW]
[ROW][C]0.0327527399141363[/C][/ROW]
[ROW][C]0.101998162564366[/C][/ROW]
[ROW][C]0.314319979365983[/C][/ROW]
[ROW][C]-0.280297381560136[/C][/ROW]
[ROW][C]0.300458424513065[/C][/ROW]
[ROW][C]0.864927194574199[/C][/ROW]
[ROW][C]0.113438692229274[/C][/ROW]
[ROW][C]0.0734383808004924[/C][/ROW]
[ROW][C]-1.19439085857496[/C][/ROW]
[ROW][C]-0.151865081640933[/C][/ROW]
[ROW][C]-0.0210499033038676[/C][/ROW]
[ROW][C]-0.34332826780972[/C][/ROW]
[ROW][C]0.574181409297989[/C][/ROW]
[ROW][C]0.47781406936538[/C][/ROW]
[ROW][C]-0.345526543847195[/C][/ROW]
[ROW][C]0.0869606035899537[/C][/ROW]
[ROW][C]0.590525692907638[/C][/ROW]
[ROW][C]-0.490002115089082[/C][/ROW]
[ROW][C]-0.42266409137097[/C][/ROW]
[ROW][C]-0.0950390600916404[/C][/ROW]
[ROW][C]-0.100980417211215[/C][/ROW]
[ROW][C]0.509364851830624[/C][/ROW]
[ROW][C]-1.00698273667972[/C][/ROW]
[ROW][C]0.328828309743278[/C][/ROW]
[ROW][C]0.863393026980703[/C][/ROW]
[ROW][C]-0.476121983127133[/C][/ROW]
[ROW][C]-0.442131906488378[/C][/ROW]
[ROW][C]-0.0557930321974531[/C][/ROW]
[ROW][C]0.32725522022826[/C][/ROW]
[ROW][C]0.866297964155573[/C][/ROW]
[ROW][C]0.446075301000411[/C][/ROW]
[ROW][C]0.800999595219834[/C][/ROW]
[ROW][C]0.91338184439289[/C][/ROW]
[ROW][C]1.21106666185213[/C][/ROW]
[ROW][C]0.432277274338901[/C][/ROW]
[ROW][C]0.307401635858294[/C][/ROW]
[ROW][C]-0.163324595203689[/C][/ROW]
[ROW][C]-0.171057239382783[/C][/ROW]
[ROW][C]-1.03961279564403[/C][/ROW]
[ROW][C]0.0264096956690344[/C][/ROW]
[ROW][C]0.590971943542331[/C][/ROW]
[ROW][C]0.0976706765255999[/C][/ROW]
[ROW][C]-0.913730369925244[/C][/ROW]
[ROW][C]-0.330725944786726[/C][/ROW]
[ROW][C]-0.391957876013934[/C][/ROW]
[ROW][C]-0.335950344555535[/C][/ROW]
[ROW][C]-0.460376741540404[/C][/ROW]
[ROW][C]-0.0292544639838915[/C][/ROW]
[ROW][C]0.49616447226297[/C][/ROW]
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[ROW][C]0.454032417363355[/C][/ROW]
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[ROW][C]-0.278725545758281[/C][/ROW]
[ROW][C]0.297054816419426[/C][/ROW]
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[ROW][C]0.28114796454196[/C][/ROW]
[ROW][C]-0.63317398361933[/C][/ROW]
[ROW][C]0.839472882357591[/C][/ROW]
[ROW][C]-0.335288305886153[/C][/ROW]
[ROW][C]-0.0537324985391935[/C][/ROW]
[ROW][C]-0.226994781079176[/C][/ROW]
[ROW][C]0.000315598163692917[/C][/ROW]
[ROW][C]0.516500742386455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151949&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151949&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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0.0327527399141363
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0.113438692229274
0.0734383808004924
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0.574181409297989
0.47781406936538
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0.590525692907638
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0.91338184439289
1.21106666185213
0.432277274338901
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1.0823913949269
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Figure 1

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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 = 0 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 0 ; 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