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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Sat, 04 Dec 2010 12:20:20 +0000

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/2010/Dec/04/t1291465177wnikkngd8qc6f3x.htm/, Retrieved Sun, 05 May 2024 01:53:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105114, Retrieved Sun, 05 May 2024 01:53:12 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

182

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         [Standard Deviation-Mean Plot] [Births] [2010-11-29 10:52:49] [b98453cac15ba1066b407e146608df68]
- RMP           [ARIMA Backward Selection] [Births] [2010-11-29 17:42:52] [b98453cac15ba1066b407e146608df68]
-   PD              [ARIMA Backward Selection] [Model 2: CPI] [2010-12-04 12:20:20] [b6992a7b26e556359948e164e4227eba] [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	34 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 34 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105114&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]34 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105114&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	34 seconds
R Server	'George Udny Yule' @ 72.249.76.132

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	0.0605	0.0366	-0.0087	0.0944	0.022	0.0958	-0.8731
(p-val)	(0.9772 )	(0.9142 )	(0.9089 )	(0.9645 )	(0.8552 )	(0.364 )	(0 )
Estimates ( 2 )	0	0.0461	-0.0079	0.1551	0.022	0.0957	-0.8731
(p-val)	(NA )	(0.544 )	(0.9141 )	(0.0334 )	(0.8548 )	(0.3643 )	(0 )
Estimates ( 3 )	0	0.0464	0	0.1549	0.0238	0.0958	-0.8733
(p-val)	(NA )	(0.5416 )	(NA )	(0.0334 )	(0.8416 )	(0.3627 )	(0 )
Estimates ( 4 )	0	0.0428	0	0.1545	0	0.0835	-0.8544
(p-val)	(NA )	(0.562 )	(NA )	(0.0338 )	(NA )	(0.3341 )	(0 )
Estimates ( 5 )	0	0	0	0.1481	0	0.0828	-1.1638
(p-val)	(NA )	(NA )	(NA )	(0.0322 )	(NA )	(0.3381 )	(0 )
Estimates ( 6 )	0	0	0	0.1484	0	0	-1.2074
(p-val)	(NA )	(NA )	(NA )	(0.0323 )	(NA )	(NA )	(0 )
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 ) & 0.0605 & 0.0366 & -0.0087 & 0.0944 & 0.022 & 0.0958 & -0.8731 \tabularnewline
(p-val) & (0.9772 ) & (0.9142 ) & (0.9089 ) & (0.9645 ) & (0.8552 ) & (0.364 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0 & 0.0461 & -0.0079 & 0.1551 & 0.022 & 0.0957 & -0.8731 \tabularnewline
(p-val) & (NA ) & (0.544 ) & (0.9141 ) & (0.0334 ) & (0.8548 ) & (0.3643 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0 & 0.0464 & 0 & 0.1549 & 0.0238 & 0.0958 & -0.8733 \tabularnewline
(p-val) & (NA ) & (0.5416 ) & (NA ) & (0.0334 ) & (0.8416 ) & (0.3627 ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0 & 0.0428 & 0 & 0.1545 & 0 & 0.0835 & -0.8544 \tabularnewline
(p-val) & (NA ) & (0.562 ) & (NA ) & (0.0338 ) & (NA ) & (0.3341 ) & (0 ) \tabularnewline
Estimates ( 5 ) & 0 & 0 & 0 & 0.1481 & 0 & 0.0828 & -1.1638 \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (0.0322 ) & (NA ) & (0.3381 ) & (0 ) \tabularnewline
Estimates ( 6 ) & 0 & 0 & 0 & 0.1484 & 0 & 0 & -1.2074 \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (0.0323 ) & (NA ) & (NA ) & (0 ) \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=105114&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]0.0605[/C][C]0.0366[/C][C]-0.0087[/C][C]0.0944[/C][C]0.022[/C][C]0.0958[/C][C]-0.8731[/C][/ROW]
[ROW][C](p-val)[/C][C](0.9772 )[/C][C](0.9142 )[/C][C](0.9089 )[/C][C](0.9645 )[/C][C](0.8552 )[/C][C](0.364 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0[/C][C]0.0461[/C][C]-0.0079[/C][C]0.1551[/C][C]0.022[/C][C]0.0957[/C][C]-0.8731[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.544 )[/C][C](0.9141 )[/C][C](0.0334 )[/C][C](0.8548 )[/C][C](0.3643 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0[/C][C]0.0464[/C][C]0[/C][C]0.1549[/C][C]0.0238[/C][C]0.0958[/C][C]-0.8733[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.5416 )[/C][C](NA )[/C][C](0.0334 )[/C][C](0.8416 )[/C][C](0.3627 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0[/C][C]0.0428[/C][C]0[/C][C]0.1545[/C][C]0[/C][C]0.0835[/C][C]-0.8544[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.562 )[/C][C](NA )[/C][C](0.0338 )[/C][C](NA )[/C][C](0.3341 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]0[/C][C]0[/C][C]0[/C][C]0.1481[/C][C]0[/C][C]0.0828[/C][C]-1.1638[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](0.0322 )[/C][C](NA )[/C][C](0.3381 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]0[/C][C]0[/C][C]0[/C][C]0.1484[/C][C]0[/C][C]0[/C][C]-1.2074[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](0.0323 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/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=105114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105114&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 )	0.0605	0.0366	-0.0087	0.0944	0.022	0.0958	-0.8731
(p-val)	(0.9772 )	(0.9142 )	(0.9089 )	(0.9645 )	(0.8552 )	(0.364 )	(0 )
Estimates ( 2 )	0	0.0461	-0.0079	0.1551	0.022	0.0957	-0.8731
(p-val)	(NA )	(0.544 )	(0.9141 )	(0.0334 )	(0.8548 )	(0.3643 )	(0 )
Estimates ( 3 )	0	0.0464	0	0.1549	0.0238	0.0958	-0.8733
(p-val)	(NA )	(0.5416 )	(NA )	(0.0334 )	(0.8416 )	(0.3627 )	(0 )
Estimates ( 4 )	0	0.0428	0	0.1545	0	0.0835	-0.8544
(p-val)	(NA )	(0.562 )	(NA )	(0.0338 )	(NA )	(0.3341 )	(0 )
Estimates ( 5 )	0	0	0	0.1481	0	0.0828	-1.1638
(p-val)	(NA )	(NA )	(NA )	(0.0322 )	(NA )	(0.3381 )	(0 )
Estimates ( 6 )	0	0	0	0.1484	0	0	-1.2074
(p-val)	(NA )	(NA )	(NA )	(0.0323 )	(NA )	(NA )	(0 )
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
-0.0165859829292113
0.000186353626444102
-0.000199197179476593
-0.000339247963278821
-0.00231429326843788
-0.000418781474011947
-3.31126234015015e-05
0.00115220207608897
-0.00162228031030884
0.000202396090914095
0.00089606531211412
-0.00058030504181526
0.00206837226123038
-0.0012108468375665
0.00104438158471849
-0.00103733023456532
-0.00242097506541786
2.23178126958749e-06
0.000124316371826446
0.000555433286158178
-0.000636151459751881
0.00251685308567781
-0.000242351250902772
0.00103597845556983
0.000212232611719494
-0.00365038850220962
-0.00285024973908551
-0.000177229921864769
0.000881313654460326
0.000471534102757927
0.00171529613588996
-0.00175956704220560
-0.000878332483240928
0.000803816541248092
0.00137013582328515
-0.000832322929558675
-0.00447212690738475
0.00138061788395098
-0.000108537262437096
0.00341131095625933
0.00387714349925295
-0.00246970017465541
-0.00368979319840634
-0.00423721323015237
0.00287325767181741
-0.000259526991084133
-0.00125661612959231
-7.50053983249742e-05
-0.00125264733797913
0.000926830424115593
0.00143593911175533
0.000505600809556560
9.54881478609351e-05
-0.00218468032811835
-0.00492988979263503
-0.00170577784444942
0.00398864502782814
0.000499455359191681
0.000366042027851961
0.00131896133337462
-0.00156727640735166
0.000790661842972716
0.00272741559478478
9.67422751354997e-05
-0.000534923679449294
0.00177673066264775
-0.00224117820549838
0.00114056584836739
0.00460914072239721
-0.00203922742187566
0.00267378767437341
-0.00124139812863644
-0.00267180931821752
0.00141095109519303
0.00266488147988298
0.00417759616551806
0.00222973067938681
0.00203927854136964
-0.0030045057702474
0.00119338908890667
0.00120021155251896
0.000462857071363687
6.28348132334067e-05
-0.00197704849471161
0.00278042217727574
-0.00107283476725229
0.00170032291339414
-0.00440007256404917
0.000814956447928946
-0.0031185950501061
-0.000111119169024147
-0.000530458302028211
0.00149312895184481
-0.00141551327451055
-0.00125155548363335
0.000949607761391365
-0.000342022805619645
0.00292668652462104
0.000980737309943812
-0.00300308441470097
-0.00273231505422962
0.00194122188177788
-0.00178256283111001
0.00124379589793602
0.00155965505925879
-0.00243871062434028
0.000653475063619638
-0.000375415472656659
-0.00080948576633366
0.000541969634081379
-0.000601003610951221
0.00246674883549269
-0.00041709534575804
-0.000525351092027777
-0.000310369776544022
0.000130997507533765
-0.000285997449741945
0.00382920686593782
-0.00184094855879256
-0.00156994247096548
0.000210982698328599
0.00184126073343253
0.00368662883138069
-0.00229473756152991
0.00095290531029708
0.000606016721874194
0.000525481051274699
-0.000253920493406769
-0.00156430448830184
-0.000842069547808903
0.00160426195860981
0.00068505360415789
-0.0028328482824668
0.00180443209602214
-0.00201743663259361
0.00178847912744523
0.00128874201503841
-0.00101190828430290
-0.000246616301547269
0.000910711284703739
-0.000564863083339317
-0.000246924291179783
0.00090810905660419
0.000937146277221189
-0.00102996767739388
0.00152060935353078
-0.00332007370038068
0.00183500449987932
-0.00382386271188843
-0.00056173266305133
0.000467987722391927
-0.000626610583376753
0.000312321390560326
0.00422751621927621
0.00378459352649550
0.0034009593010552
0.000245617037625587
0.0035824066665942
0.00391907498008884
-0.00118248761689021
0.00451193261175983
0.00226316957942455
0.00124817088564199
-0.00315113329916103
0.00237711994794962
0.000448116777861707
-0.0038085926946116
0.00103793480710880
-0.00125925815018764
-0.00126035941707056
-0.00594114431456639
-0.000200597528053036
-0.00301143238845049
-0.00386439179854945
-0.00287540896154426
0.00199943526968855
-0.00231186665677521
0.000913558393155477
-0.00118389465699617
0.000710692013150484
0.000307322641771452
0.000363478152704443
0.00104112384341694
3.77510290824436e-05
0.00129326093289256
-0.000471470602787296
-0.00198342160946690
0.00109399704886254
0.00214557773207580
0.000312551286901702
-0.000506616775935753

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0165859829292113 \tabularnewline
0.000186353626444102 \tabularnewline
-0.000199197179476593 \tabularnewline
-0.000339247963278821 \tabularnewline
-0.00231429326843788 \tabularnewline
-0.000418781474011947 \tabularnewline
-3.31126234015015e-05 \tabularnewline
0.00115220207608897 \tabularnewline
-0.00162228031030884 \tabularnewline
0.000202396090914095 \tabularnewline
0.00089606531211412 \tabularnewline
-0.00058030504181526 \tabularnewline
0.00206837226123038 \tabularnewline
-0.0012108468375665 \tabularnewline
0.00104438158471849 \tabularnewline
-0.00103733023456532 \tabularnewline
-0.00242097506541786 \tabularnewline
2.23178126958749e-06 \tabularnewline
0.000124316371826446 \tabularnewline
0.000555433286158178 \tabularnewline
-0.000636151459751881 \tabularnewline
0.00251685308567781 \tabularnewline
-0.000242351250902772 \tabularnewline
0.00103597845556983 \tabularnewline
0.000212232611719494 \tabularnewline
-0.00365038850220962 \tabularnewline
-0.00285024973908551 \tabularnewline
-0.000177229921864769 \tabularnewline
0.000881313654460326 \tabularnewline
0.000471534102757927 \tabularnewline
0.00171529613588996 \tabularnewline
-0.00175956704220560 \tabularnewline
-0.000878332483240928 \tabularnewline
0.000803816541248092 \tabularnewline
0.00137013582328515 \tabularnewline
-0.000832322929558675 \tabularnewline
-0.00447212690738475 \tabularnewline
0.00138061788395098 \tabularnewline
-0.000108537262437096 \tabularnewline
0.00341131095625933 \tabularnewline
0.00387714349925295 \tabularnewline
-0.00246970017465541 \tabularnewline
-0.00368979319840634 \tabularnewline
-0.00423721323015237 \tabularnewline
0.00287325767181741 \tabularnewline
-0.000259526991084133 \tabularnewline
-0.00125661612959231 \tabularnewline
-7.50053983249742e-05 \tabularnewline
-0.00125264733797913 \tabularnewline
0.000926830424115593 \tabularnewline
0.00143593911175533 \tabularnewline
0.000505600809556560 \tabularnewline
9.54881478609351e-05 \tabularnewline
-0.00218468032811835 \tabularnewline
-0.00492988979263503 \tabularnewline
-0.00170577784444942 \tabularnewline
0.00398864502782814 \tabularnewline
0.000499455359191681 \tabularnewline
0.000366042027851961 \tabularnewline
0.00131896133337462 \tabularnewline
-0.00156727640735166 \tabularnewline
0.000790661842972716 \tabularnewline
0.00272741559478478 \tabularnewline
9.67422751354997e-05 \tabularnewline
-0.000534923679449294 \tabularnewline
0.00177673066264775 \tabularnewline
-0.00224117820549838 \tabularnewline
0.00114056584836739 \tabularnewline
0.00460914072239721 \tabularnewline
-0.00203922742187566 \tabularnewline
0.00267378767437341 \tabularnewline
-0.00124139812863644 \tabularnewline
-0.00267180931821752 \tabularnewline
0.00141095109519303 \tabularnewline
0.00266488147988298 \tabularnewline
0.00417759616551806 \tabularnewline
0.00222973067938681 \tabularnewline
0.00203927854136964 \tabularnewline
-0.0030045057702474 \tabularnewline
0.00119338908890667 \tabularnewline
0.00120021155251896 \tabularnewline
0.000462857071363687 \tabularnewline
6.28348132334067e-05 \tabularnewline
-0.00197704849471161 \tabularnewline
0.00278042217727574 \tabularnewline
-0.00107283476725229 \tabularnewline
0.00170032291339414 \tabularnewline
-0.00440007256404917 \tabularnewline
0.000814956447928946 \tabularnewline
-0.0031185950501061 \tabularnewline
-0.000111119169024147 \tabularnewline
-0.000530458302028211 \tabularnewline
0.00149312895184481 \tabularnewline
-0.00141551327451055 \tabularnewline
-0.00125155548363335 \tabularnewline
0.000949607761391365 \tabularnewline
-0.000342022805619645 \tabularnewline
0.00292668652462104 \tabularnewline
0.000980737309943812 \tabularnewline
-0.00300308441470097 \tabularnewline
-0.00273231505422962 \tabularnewline
0.00194122188177788 \tabularnewline
-0.00178256283111001 \tabularnewline
0.00124379589793602 \tabularnewline
0.00155965505925879 \tabularnewline
-0.00243871062434028 \tabularnewline
0.000653475063619638 \tabularnewline
-0.000375415472656659 \tabularnewline
-0.00080948576633366 \tabularnewline
0.000541969634081379 \tabularnewline
-0.000601003610951221 \tabularnewline
0.00246674883549269 \tabularnewline
-0.00041709534575804 \tabularnewline
-0.000525351092027777 \tabularnewline
-0.000310369776544022 \tabularnewline
0.000130997507533765 \tabularnewline
-0.000285997449741945 \tabularnewline
0.00382920686593782 \tabularnewline
-0.00184094855879256 \tabularnewline
-0.00156994247096548 \tabularnewline
0.000210982698328599 \tabularnewline
0.00184126073343253 \tabularnewline
0.00368662883138069 \tabularnewline
-0.00229473756152991 \tabularnewline
0.00095290531029708 \tabularnewline
0.000606016721874194 \tabularnewline
0.000525481051274699 \tabularnewline
-0.000253920493406769 \tabularnewline
-0.00156430448830184 \tabularnewline
-0.000842069547808903 \tabularnewline
0.00160426195860981 \tabularnewline
0.00068505360415789 \tabularnewline
-0.0028328482824668 \tabularnewline
0.00180443209602214 \tabularnewline
-0.00201743663259361 \tabularnewline
0.00178847912744523 \tabularnewline
0.00128874201503841 \tabularnewline
-0.00101190828430290 \tabularnewline
-0.000246616301547269 \tabularnewline
0.000910711284703739 \tabularnewline
-0.000564863083339317 \tabularnewline
-0.000246924291179783 \tabularnewline
0.00090810905660419 \tabularnewline
0.000937146277221189 \tabularnewline
-0.00102996767739388 \tabularnewline
0.00152060935353078 \tabularnewline
-0.00332007370038068 \tabularnewline
0.00183500449987932 \tabularnewline
-0.00382386271188843 \tabularnewline
-0.00056173266305133 \tabularnewline
0.000467987722391927 \tabularnewline
-0.000626610583376753 \tabularnewline
0.000312321390560326 \tabularnewline
0.00422751621927621 \tabularnewline
0.00378459352649550 \tabularnewline
0.0034009593010552 \tabularnewline
0.000245617037625587 \tabularnewline
0.0035824066665942 \tabularnewline
0.00391907498008884 \tabularnewline
-0.00118248761689021 \tabularnewline
0.00451193261175983 \tabularnewline
0.00226316957942455 \tabularnewline
0.00124817088564199 \tabularnewline
-0.00315113329916103 \tabularnewline
0.00237711994794962 \tabularnewline
0.000448116777861707 \tabularnewline
-0.0038085926946116 \tabularnewline
0.00103793480710880 \tabularnewline
-0.00125925815018764 \tabularnewline
-0.00126035941707056 \tabularnewline
-0.00594114431456639 \tabularnewline
-0.000200597528053036 \tabularnewline
-0.00301143238845049 \tabularnewline
-0.00386439179854945 \tabularnewline
-0.00287540896154426 \tabularnewline
0.00199943526968855 \tabularnewline
-0.00231186665677521 \tabularnewline
0.000913558393155477 \tabularnewline
-0.00118389465699617 \tabularnewline
0.000710692013150484 \tabularnewline
0.000307322641771452 \tabularnewline
0.000363478152704443 \tabularnewline
0.00104112384341694 \tabularnewline
3.77510290824436e-05 \tabularnewline
0.00129326093289256 \tabularnewline
-0.000471470602787296 \tabularnewline
-0.00198342160946690 \tabularnewline
0.00109399704886254 \tabularnewline
0.00214557773207580 \tabularnewline
0.000312551286901702 \tabularnewline
-0.000506616775935753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105114&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0165859829292113[/C][/ROW]
[ROW][C]0.000186353626444102[/C][/ROW]
[ROW][C]-0.000199197179476593[/C][/ROW]
[ROW][C]-0.000339247963278821[/C][/ROW]
[ROW][C]-0.00231429326843788[/C][/ROW]
[ROW][C]-0.000418781474011947[/C][/ROW]
[ROW][C]-3.31126234015015e-05[/C][/ROW]
[ROW][C]0.00115220207608897[/C][/ROW]
[ROW][C]-0.00162228031030884[/C][/ROW]
[ROW][C]0.000202396090914095[/C][/ROW]
[ROW][C]0.00089606531211412[/C][/ROW]
[ROW][C]-0.00058030504181526[/C][/ROW]
[ROW][C]0.00206837226123038[/C][/ROW]
[ROW][C]-0.0012108468375665[/C][/ROW]
[ROW][C]0.00104438158471849[/C][/ROW]
[ROW][C]-0.00103733023456532[/C][/ROW]
[ROW][C]-0.00242097506541786[/C][/ROW]
[ROW][C]2.23178126958749e-06[/C][/ROW]
[ROW][C]0.000124316371826446[/C][/ROW]
[ROW][C]0.000555433286158178[/C][/ROW]
[ROW][C]-0.000636151459751881[/C][/ROW]
[ROW][C]0.00251685308567781[/C][/ROW]
[ROW][C]-0.000242351250902772[/C][/ROW]
[ROW][C]0.00103597845556983[/C][/ROW]
[ROW][C]0.000212232611719494[/C][/ROW]
[ROW][C]-0.00365038850220962[/C][/ROW]
[ROW][C]-0.00285024973908551[/C][/ROW]
[ROW][C]-0.000177229921864769[/C][/ROW]
[ROW][C]0.000881313654460326[/C][/ROW]
[ROW][C]0.000471534102757927[/C][/ROW]
[ROW][C]0.00171529613588996[/C][/ROW]
[ROW][C]-0.00175956704220560[/C][/ROW]
[ROW][C]-0.000878332483240928[/C][/ROW]
[ROW][C]0.000803816541248092[/C][/ROW]
[ROW][C]0.00137013582328515[/C][/ROW]
[ROW][C]-0.000832322929558675[/C][/ROW]
[ROW][C]-0.00447212690738475[/C][/ROW]
[ROW][C]0.00138061788395098[/C][/ROW]
[ROW][C]-0.000108537262437096[/C][/ROW]
[ROW][C]0.00341131095625933[/C][/ROW]
[ROW][C]0.00387714349925295[/C][/ROW]
[ROW][C]-0.00246970017465541[/C][/ROW]
[ROW][C]-0.00368979319840634[/C][/ROW]
[ROW][C]-0.00423721323015237[/C][/ROW]
[ROW][C]0.00287325767181741[/C][/ROW]
[ROW][C]-0.000259526991084133[/C][/ROW]
[ROW][C]-0.00125661612959231[/C][/ROW]
[ROW][C]-7.50053983249742e-05[/C][/ROW]
[ROW][C]-0.00125264733797913[/C][/ROW]
[ROW][C]0.000926830424115593[/C][/ROW]
[ROW][C]0.00143593911175533[/C][/ROW]
[ROW][C]0.000505600809556560[/C][/ROW]
[ROW][C]9.54881478609351e-05[/C][/ROW]
[ROW][C]-0.00218468032811835[/C][/ROW]
[ROW][C]-0.00492988979263503[/C][/ROW]
[ROW][C]-0.00170577784444942[/C][/ROW]
[ROW][C]0.00398864502782814[/C][/ROW]
[ROW][C]0.000499455359191681[/C][/ROW]
[ROW][C]0.000366042027851961[/C][/ROW]
[ROW][C]0.00131896133337462[/C][/ROW]
[ROW][C]-0.00156727640735166[/C][/ROW]
[ROW][C]0.000790661842972716[/C][/ROW]
[ROW][C]0.00272741559478478[/C][/ROW]
[ROW][C]9.67422751354997e-05[/C][/ROW]
[ROW][C]-0.000534923679449294[/C][/ROW]
[ROW][C]0.00177673066264775[/C][/ROW]
[ROW][C]-0.00224117820549838[/C][/ROW]
[ROW][C]0.00114056584836739[/C][/ROW]
[ROW][C]0.00460914072239721[/C][/ROW]
[ROW][C]-0.00203922742187566[/C][/ROW]
[ROW][C]0.00267378767437341[/C][/ROW]
[ROW][C]-0.00124139812863644[/C][/ROW]
[ROW][C]-0.00267180931821752[/C][/ROW]
[ROW][C]0.00141095109519303[/C][/ROW]
[ROW][C]0.00266488147988298[/C][/ROW]
[ROW][C]0.00417759616551806[/C][/ROW]
[ROW][C]0.00222973067938681[/C][/ROW]
[ROW][C]0.00203927854136964[/C][/ROW]
[ROW][C]-0.0030045057702474[/C][/ROW]
[ROW][C]0.00119338908890667[/C][/ROW]
[ROW][C]0.00120021155251896[/C][/ROW]
[ROW][C]0.000462857071363687[/C][/ROW]
[ROW][C]6.28348132334067e-05[/C][/ROW]
[ROW][C]-0.00197704849471161[/C][/ROW]
[ROW][C]0.00278042217727574[/C][/ROW]
[ROW][C]-0.00107283476725229[/C][/ROW]
[ROW][C]0.00170032291339414[/C][/ROW]
[ROW][C]-0.00440007256404917[/C][/ROW]
[ROW][C]0.000814956447928946[/C][/ROW]
[ROW][C]-0.0031185950501061[/C][/ROW]
[ROW][C]-0.000111119169024147[/C][/ROW]
[ROW][C]-0.000530458302028211[/C][/ROW]
[ROW][C]0.00149312895184481[/C][/ROW]
[ROW][C]-0.00141551327451055[/C][/ROW]
[ROW][C]-0.00125155548363335[/C][/ROW]
[ROW][C]0.000949607761391365[/C][/ROW]
[ROW][C]-0.000342022805619645[/C][/ROW]
[ROW][C]0.00292668652462104[/C][/ROW]
[ROW][C]0.000980737309943812[/C][/ROW]
[ROW][C]-0.00300308441470097[/C][/ROW]
[ROW][C]-0.00273231505422962[/C][/ROW]
[ROW][C]0.00194122188177788[/C][/ROW]
[ROW][C]-0.00178256283111001[/C][/ROW]
[ROW][C]0.00124379589793602[/C][/ROW]
[ROW][C]0.00155965505925879[/C][/ROW]
[ROW][C]-0.00243871062434028[/C][/ROW]
[ROW][C]0.000653475063619638[/C][/ROW]
[ROW][C]-0.000375415472656659[/C][/ROW]
[ROW][C]-0.00080948576633366[/C][/ROW]
[ROW][C]0.000541969634081379[/C][/ROW]
[ROW][C]-0.000601003610951221[/C][/ROW]
[ROW][C]0.00246674883549269[/C][/ROW]
[ROW][C]-0.00041709534575804[/C][/ROW]
[ROW][C]-0.000525351092027777[/C][/ROW]
[ROW][C]-0.000310369776544022[/C][/ROW]
[ROW][C]0.000130997507533765[/C][/ROW]
[ROW][C]-0.000285997449741945[/C][/ROW]
[ROW][C]0.00382920686593782[/C][/ROW]
[ROW][C]-0.00184094855879256[/C][/ROW]
[ROW][C]-0.00156994247096548[/C][/ROW]
[ROW][C]0.000210982698328599[/C][/ROW]
[ROW][C]0.00184126073343253[/C][/ROW]
[ROW][C]0.00368662883138069[/C][/ROW]
[ROW][C]-0.00229473756152991[/C][/ROW]
[ROW][C]0.00095290531029708[/C][/ROW]
[ROW][C]0.000606016721874194[/C][/ROW]
[ROW][C]0.000525481051274699[/C][/ROW]
[ROW][C]-0.000253920493406769[/C][/ROW]
[ROW][C]-0.00156430448830184[/C][/ROW]
[ROW][C]-0.000842069547808903[/C][/ROW]
[ROW][C]0.00160426195860981[/C][/ROW]
[ROW][C]0.00068505360415789[/C][/ROW]
[ROW][C]-0.0028328482824668[/C][/ROW]
[ROW][C]0.00180443209602214[/C][/ROW]
[ROW][C]-0.00201743663259361[/C][/ROW]
[ROW][C]0.00178847912744523[/C][/ROW]
[ROW][C]0.00128874201503841[/C][/ROW]
[ROW][C]-0.00101190828430290[/C][/ROW]
[ROW][C]-0.000246616301547269[/C][/ROW]
[ROW][C]0.000910711284703739[/C][/ROW]
[ROW][C]-0.000564863083339317[/C][/ROW]
[ROW][C]-0.000246924291179783[/C][/ROW]
[ROW][C]0.00090810905660419[/C][/ROW]
[ROW][C]0.000937146277221189[/C][/ROW]
[ROW][C]-0.00102996767739388[/C][/ROW]
[ROW][C]0.00152060935353078[/C][/ROW]
[ROW][C]-0.00332007370038068[/C][/ROW]
[ROW][C]0.00183500449987932[/C][/ROW]
[ROW][C]-0.00382386271188843[/C][/ROW]
[ROW][C]-0.00056173266305133[/C][/ROW]
[ROW][C]0.000467987722391927[/C][/ROW]
[ROW][C]-0.000626610583376753[/C][/ROW]
[ROW][C]0.000312321390560326[/C][/ROW]
[ROW][C]0.00422751621927621[/C][/ROW]
[ROW][C]0.00378459352649550[/C][/ROW]
[ROW][C]0.0034009593010552[/C][/ROW]
[ROW][C]0.000245617037625587[/C][/ROW]
[ROW][C]0.0035824066665942[/C][/ROW]
[ROW][C]0.00391907498008884[/C][/ROW]
[ROW][C]-0.00118248761689021[/C][/ROW]
[ROW][C]0.00451193261175983[/C][/ROW]
[ROW][C]0.00226316957942455[/C][/ROW]
[ROW][C]0.00124817088564199[/C][/ROW]
[ROW][C]-0.00315113329916103[/C][/ROW]
[ROW][C]0.00237711994794962[/C][/ROW]
[ROW][C]0.000448116777861707[/C][/ROW]
[ROW][C]-0.0038085926946116[/C][/ROW]
[ROW][C]0.00103793480710880[/C][/ROW]
[ROW][C]-0.00125925815018764[/C][/ROW]
[ROW][C]-0.00126035941707056[/C][/ROW]
[ROW][C]-0.00594114431456639[/C][/ROW]
[ROW][C]-0.000200597528053036[/C][/ROW]
[ROW][C]-0.00301143238845049[/C][/ROW]
[ROW][C]-0.00386439179854945[/C][/ROW]
[ROW][C]-0.00287540896154426[/C][/ROW]
[ROW][C]0.00199943526968855[/C][/ROW]
[ROW][C]-0.00231186665677521[/C][/ROW]
[ROW][C]0.000913558393155477[/C][/ROW]
[ROW][C]-0.00118389465699617[/C][/ROW]
[ROW][C]0.000710692013150484[/C][/ROW]
[ROW][C]0.000307322641771452[/C][/ROW]
[ROW][C]0.000363478152704443[/C][/ROW]
[ROW][C]0.00104112384341694[/C][/ROW]
[ROW][C]3.77510290824436e-05[/C][/ROW]
[ROW][C]0.00129326093289256[/C][/ROW]
[ROW][C]-0.000471470602787296[/C][/ROW]
[ROW][C]-0.00198342160946690[/C][/ROW]
[ROW][C]0.00109399704886254[/C][/ROW]
[ROW][C]0.00214557773207580[/C][/ROW]
[ROW][C]0.000312551286901702[/C][/ROW]
[ROW][C]-0.000506616775935753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105114&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105114&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
-0.0165859829292113
0.000186353626444102
-0.000199197179476593
-0.000339247963278821
-0.00231429326843788
-0.000418781474011947
-3.31126234015015e-05
0.00115220207608897
-0.00162228031030884
0.000202396090914095
0.00089606531211412
-0.00058030504181526
0.00206837226123038
-0.0012108468375665
0.00104438158471849
-0.00103733023456532
-0.00242097506541786
2.23178126958749e-06
0.000124316371826446
0.000555433286158178
-0.000636151459751881
0.00251685308567781
-0.000242351250902772
0.00103597845556983
0.000212232611719494
-0.00365038850220962
-0.00285024973908551
-0.000177229921864769
0.000881313654460326
0.000471534102757927
0.00171529613588996
-0.00175956704220560
-0.000878332483240928
0.000803816541248092
0.00137013582328515
-0.000832322929558675
-0.00447212690738475
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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 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; 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