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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Wed, 22 Dec 2010 22:09:56 +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/22/t1293055707swnpehj4ndiyue8.htm/, Retrieved Mon, 06 May 2024 02:47:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114606, Retrieved Mon, 06 May 2024 02:47:29 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

172

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

-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [WS9 - Variance Re...] [2010-12-04 11:04:59] [8ef49741e164ec6343c90c7935194465]
-   P     [Variance Reduction Matrix] [WS 9 VRM] [2010-12-05 14:01:21] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD      [(Partial) Autocorrelation Function] [paper ACF] [2010-12-10 10:47:04] [8214fe6d084e5ad7598b249a26cc9f06]
-   P         [(Partial) Autocorrelation Function] [paper acf met D=1] [2010-12-10 11:19:24] [8214fe6d084e5ad7598b249a26cc9f06]
- RMP           [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:22:34] [8214fe6d084e5ad7598b249a26cc9f06]
-   P             [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:27:22] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD              [Spectral Analysis] [cum periodogram 2 ] [2010-12-20 20:28:39] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                [Spectral Analysis] [cum per 2  paper] [2010-12-22 13:46:56] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                  [Spectral Analysis] [cum per 1 middeng...] [2010-12-22 19:06:59] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                     [Spectral Analysis] [cum per 2 middeng...] [2010-12-22 19:08:52] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                      [Spectral Analysis] [cum per 1 hoogges...] [2010-12-22 19:10:38] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                         [Spectral Analysis] [cum per 2 hoogges...] [2010-12-22 19:12:39] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                          [Standard Deviation-Mean Plot] [sdmp laaggeschoolden] [2010-12-22 19:15:16] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                            [Standard Deviation-Mean Plot] [sdmp middengescho...] [2010-12-22 19:17:33] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                              [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:29:00] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                                [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:34:28] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                    [ARIMA Backward Selection] [arima backward se...] [2010-12-22 22:09:56] [b47314d83d48c7bf812ec2bcd743b159] [Current]

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114606&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114606&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114606&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	3 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3
Estimates ( 1 )	-0.0272	0.1465	-0.0018
(p-val)	(0.7684 )	(0.1092 )	(0.9847 )
Estimates ( 2 )	-0.0274	0.1465	0
(p-val)	(0.7636 )	(0.109 )	(NA )
Estimates ( 3 )	0	0.1474	0
(p-val)	(NA )	(0.1068 )	(NA )
Estimates ( 4 )	0	0	0
(p-val)	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 \tabularnewline
Estimates ( 1 ) & -0.0272 & 0.1465 & -0.0018 \tabularnewline
(p-val) & (0.7684 ) & (0.1092 ) & (0.9847 ) \tabularnewline
Estimates ( 2 ) & -0.0274 & 0.1465 & 0 \tabularnewline
(p-val) & (0.7636 ) & (0.109 ) & (NA ) \tabularnewline
Estimates ( 3 ) & 0 & 0.1474 & 0 \tabularnewline
(p-val) & (NA ) & (0.1068 ) & (NA ) \tabularnewline
Estimates ( 4 ) & 0 & 0 & 0 \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114606&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][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]-0.0272[/C][C]0.1465[/C][C]-0.0018[/C][/ROW]
[ROW][C](p-val)[/C][C](0.7684 )[/C][C](0.1092 )[/C][C](0.9847 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]-0.0274[/C][C]0.1465[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0.7636 )[/C][C](0.109 )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0[/C][C]0.1474[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.1068 )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114606&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114606&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
Estimates ( 1 )	-0.0272	0.1465	-0.0018
(p-val)	(0.7684 )	(0.1092 )	(0.9847 )
Estimates ( 2 )	-0.0274	0.1465	0
(p-val)	(0.7636 )	(0.109 )	(NA )
Estimates ( 3 )	0	0.1474	0
(p-val)	(NA )	(0.1068 )	(NA )
Estimates ( 4 )	0	0	0
(p-val)	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.068885693314329
0.126572604143523
0.0483829084958972
-0.0927330106922004
0.105828785323538
-0.00144101434433747
0.232962680293775
-0.251871219483529
0.826278267520738
0.196446528874682
-0.160458847438412
0.029325649114606
-0.0954948891663683
0.0374000135802335
0.0767129634791493
-0.0584130679844418
0.0306318157894732
0.116799452656103
0.526226556538655
-0.528451827016542
-0.054780632110017
-0.062578494405267
0.125961894941609
-0.0240740347528834
0.0301620700506833
-0.204650485391612
-0.0872501453214247
0.232224817409499
-0.00151277621302341
0.202567079924424
-0.0781581820222848
-0.0317684344532889
-0.200793140587537
-0.138343166304208
-0.0321156750461273
0.0639583741232267
0.0797172568187897
0.303246277776138
-0.041529898268927
-0.279906327756374
-0.0579421858950845
-0.137938132962596
-0.343980708004516
0.157819994939029
0.0692432508377429
0.00387208909768483
-0.000284642702158385
-0.119451468241278
-0.194995138199204
-0.143907786518754
0.139538419594428
-0.164715818404426
0.0397726628144313
0.0343959138646523
0.086373075962306
-0.127140341244916
-0.498945418807487
0.236248645831743
-0.0372524857634758
0.0356201644484227
-0.485335007497648
0.23040361611286
-0.101400793950517
0.440546557194862
0.0774810362721573
-0.083678950548237
-0.372473804481123
-0.158652518436256
-0.0550911928292818
-0.377902357348888
0.020805884786717
-0.0209960474901373
0.486997831015025
-0.170427459546054
-0.125944541333158
-0.242103866868115
-0.0340620214676104
0.0905054515814488
0.230206090577608
-0.156966718691292
-0.507919055431671
0.263410775659937
0.161667875231993
0.4196633309499
-0.140683891290982
-0.0839721417035634
0.530983365331613
-0.174248339343484
-0.237235958037279
0.357357732489537
-0.2947743530296
0.0181454581623197
0.183884790869387
0.15665854560631
0.202121328929579
0.186157667090938
0.432539371524876
0.461382785448547
-0.192386642468495
0.282196702270624
0.289046028695891
-0.076477414728366
-0.182406346648576
0.0996543393797456
0.411495049940968
-0.0654682511194529
0.191025356824682
-0.0192013636893822
-0.498365666984428
-0.211877535540853
-0.261864046434133
-0.0589895433886087
-0.0926128100396111
-0.296624699116424
-0.181530504753092
-0.0473948204665046
-0.04529573579265
0.0365813702380886
-0.234866302173685

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.068885693314329 \tabularnewline
0.126572604143523 \tabularnewline
0.0483829084958972 \tabularnewline
-0.0927330106922004 \tabularnewline
0.105828785323538 \tabularnewline
-0.00144101434433747 \tabularnewline
0.232962680293775 \tabularnewline
-0.251871219483529 \tabularnewline
0.826278267520738 \tabularnewline
0.196446528874682 \tabularnewline
-0.160458847438412 \tabularnewline
0.029325649114606 \tabularnewline
-0.0954948891663683 \tabularnewline
0.0374000135802335 \tabularnewline
0.0767129634791493 \tabularnewline
-0.0584130679844418 \tabularnewline
0.0306318157894732 \tabularnewline
0.116799452656103 \tabularnewline
0.526226556538655 \tabularnewline
-0.528451827016542 \tabularnewline
-0.054780632110017 \tabularnewline
-0.062578494405267 \tabularnewline
0.125961894941609 \tabularnewline
-0.0240740347528834 \tabularnewline
0.0301620700506833 \tabularnewline
-0.204650485391612 \tabularnewline
-0.0872501453214247 \tabularnewline
0.232224817409499 \tabularnewline
-0.00151277621302341 \tabularnewline
0.202567079924424 \tabularnewline
-0.0781581820222848 \tabularnewline
-0.0317684344532889 \tabularnewline
-0.200793140587537 \tabularnewline
-0.138343166304208 \tabularnewline
-0.0321156750461273 \tabularnewline
0.0639583741232267 \tabularnewline
0.0797172568187897 \tabularnewline
0.303246277776138 \tabularnewline
-0.041529898268927 \tabularnewline
-0.279906327756374 \tabularnewline
-0.0579421858950845 \tabularnewline
-0.137938132962596 \tabularnewline
-0.343980708004516 \tabularnewline
0.157819994939029 \tabularnewline
0.0692432508377429 \tabularnewline
0.00387208909768483 \tabularnewline
-0.000284642702158385 \tabularnewline
-0.119451468241278 \tabularnewline
-0.194995138199204 \tabularnewline
-0.143907786518754 \tabularnewline
0.139538419594428 \tabularnewline
-0.164715818404426 \tabularnewline
0.0397726628144313 \tabularnewline
0.0343959138646523 \tabularnewline
0.086373075962306 \tabularnewline
-0.127140341244916 \tabularnewline
-0.498945418807487 \tabularnewline
0.236248645831743 \tabularnewline
-0.0372524857634758 \tabularnewline
0.0356201644484227 \tabularnewline
-0.485335007497648 \tabularnewline
0.23040361611286 \tabularnewline
-0.101400793950517 \tabularnewline
0.440546557194862 \tabularnewline
0.0774810362721573 \tabularnewline
-0.083678950548237 \tabularnewline
-0.372473804481123 \tabularnewline
-0.158652518436256 \tabularnewline
-0.0550911928292818 \tabularnewline
-0.377902357348888 \tabularnewline
0.020805884786717 \tabularnewline
-0.0209960474901373 \tabularnewline
0.486997831015025 \tabularnewline
-0.170427459546054 \tabularnewline
-0.125944541333158 \tabularnewline
-0.242103866868115 \tabularnewline
-0.0340620214676104 \tabularnewline
0.0905054515814488 \tabularnewline
0.230206090577608 \tabularnewline
-0.156966718691292 \tabularnewline
-0.507919055431671 \tabularnewline
0.263410775659937 \tabularnewline
0.161667875231993 \tabularnewline
0.4196633309499 \tabularnewline
-0.140683891290982 \tabularnewline
-0.0839721417035634 \tabularnewline
0.530983365331613 \tabularnewline
-0.174248339343484 \tabularnewline
-0.237235958037279 \tabularnewline
0.357357732489537 \tabularnewline
-0.2947743530296 \tabularnewline
0.0181454581623197 \tabularnewline
0.183884790869387 \tabularnewline
0.15665854560631 \tabularnewline
0.202121328929579 \tabularnewline
0.186157667090938 \tabularnewline
0.432539371524876 \tabularnewline
0.461382785448547 \tabularnewline
-0.192386642468495 \tabularnewline
0.282196702270624 \tabularnewline
0.289046028695891 \tabularnewline
-0.076477414728366 \tabularnewline
-0.182406346648576 \tabularnewline
0.0996543393797456 \tabularnewline
0.411495049940968 \tabularnewline
-0.0654682511194529 \tabularnewline
0.191025356824682 \tabularnewline
-0.0192013636893822 \tabularnewline
-0.498365666984428 \tabularnewline
-0.211877535540853 \tabularnewline
-0.261864046434133 \tabularnewline
-0.0589895433886087 \tabularnewline
-0.0926128100396111 \tabularnewline
-0.296624699116424 \tabularnewline
-0.181530504753092 \tabularnewline
-0.0473948204665046 \tabularnewline
-0.04529573579265 \tabularnewline
0.0365813702380886 \tabularnewline
-0.234866302173685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114606&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.068885693314329[/C][/ROW]
[ROW][C]0.126572604143523[/C][/ROW]
[ROW][C]0.0483829084958972[/C][/ROW]
[ROW][C]-0.0927330106922004[/C][/ROW]
[ROW][C]0.105828785323538[/C][/ROW]
[ROW][C]-0.00144101434433747[/C][/ROW]
[ROW][C]0.232962680293775[/C][/ROW]
[ROW][C]-0.251871219483529[/C][/ROW]
[ROW][C]0.826278267520738[/C][/ROW]
[ROW][C]0.196446528874682[/C][/ROW]
[ROW][C]-0.160458847438412[/C][/ROW]
[ROW][C]0.029325649114606[/C][/ROW]
[ROW][C]-0.0954948891663683[/C][/ROW]
[ROW][C]0.0374000135802335[/C][/ROW]
[ROW][C]0.0767129634791493[/C][/ROW]
[ROW][C]-0.0584130679844418[/C][/ROW]
[ROW][C]0.0306318157894732[/C][/ROW]
[ROW][C]0.116799452656103[/C][/ROW]
[ROW][C]0.526226556538655[/C][/ROW]
[ROW][C]-0.528451827016542[/C][/ROW]
[ROW][C]-0.054780632110017[/C][/ROW]
[ROW][C]-0.062578494405267[/C][/ROW]
[ROW][C]0.125961894941609[/C][/ROW]
[ROW][C]-0.0240740347528834[/C][/ROW]
[ROW][C]0.0301620700506833[/C][/ROW]
[ROW][C]-0.204650485391612[/C][/ROW]
[ROW][C]-0.0872501453214247[/C][/ROW]
[ROW][C]0.232224817409499[/C][/ROW]
[ROW][C]-0.00151277621302341[/C][/ROW]
[ROW][C]0.202567079924424[/C][/ROW]
[ROW][C]-0.0781581820222848[/C][/ROW]
[ROW][C]-0.0317684344532889[/C][/ROW]
[ROW][C]-0.200793140587537[/C][/ROW]
[ROW][C]-0.138343166304208[/C][/ROW]
[ROW][C]-0.0321156750461273[/C][/ROW]
[ROW][C]0.0639583741232267[/C][/ROW]
[ROW][C]0.0797172568187897[/C][/ROW]
[ROW][C]0.303246277776138[/C][/ROW]
[ROW][C]-0.041529898268927[/C][/ROW]
[ROW][C]-0.279906327756374[/C][/ROW]
[ROW][C]-0.0579421858950845[/C][/ROW]
[ROW][C]-0.137938132962596[/C][/ROW]
[ROW][C]-0.343980708004516[/C][/ROW]
[ROW][C]0.157819994939029[/C][/ROW]
[ROW][C]0.0692432508377429[/C][/ROW]
[ROW][C]0.00387208909768483[/C][/ROW]
[ROW][C]-0.000284642702158385[/C][/ROW]
[ROW][C]-0.119451468241278[/C][/ROW]
[ROW][C]-0.194995138199204[/C][/ROW]
[ROW][C]-0.143907786518754[/C][/ROW]
[ROW][C]0.139538419594428[/C][/ROW]
[ROW][C]-0.164715818404426[/C][/ROW]
[ROW][C]0.0397726628144313[/C][/ROW]
[ROW][C]0.0343959138646523[/C][/ROW]
[ROW][C]0.086373075962306[/C][/ROW]
[ROW][C]-0.127140341244916[/C][/ROW]
[ROW][C]-0.498945418807487[/C][/ROW]
[ROW][C]0.236248645831743[/C][/ROW]
[ROW][C]-0.0372524857634758[/C][/ROW]
[ROW][C]0.0356201644484227[/C][/ROW]
[ROW][C]-0.485335007497648[/C][/ROW]
[ROW][C]0.23040361611286[/C][/ROW]
[ROW][C]-0.101400793950517[/C][/ROW]
[ROW][C]0.440546557194862[/C][/ROW]
[ROW][C]0.0774810362721573[/C][/ROW]
[ROW][C]-0.083678950548237[/C][/ROW]
[ROW][C]-0.372473804481123[/C][/ROW]
[ROW][C]-0.158652518436256[/C][/ROW]
[ROW][C]-0.0550911928292818[/C][/ROW]
[ROW][C]-0.377902357348888[/C][/ROW]
[ROW][C]0.020805884786717[/C][/ROW]
[ROW][C]-0.0209960474901373[/C][/ROW]
[ROW][C]0.486997831015025[/C][/ROW]
[ROW][C]-0.170427459546054[/C][/ROW]
[ROW][C]-0.125944541333158[/C][/ROW]
[ROW][C]-0.242103866868115[/C][/ROW]
[ROW][C]-0.0340620214676104[/C][/ROW]
[ROW][C]0.0905054515814488[/C][/ROW]
[ROW][C]0.230206090577608[/C][/ROW]
[ROW][C]-0.156966718691292[/C][/ROW]
[ROW][C]-0.507919055431671[/C][/ROW]
[ROW][C]0.263410775659937[/C][/ROW]
[ROW][C]0.161667875231993[/C][/ROW]
[ROW][C]0.4196633309499[/C][/ROW]
[ROW][C]-0.140683891290982[/C][/ROW]
[ROW][C]-0.0839721417035634[/C][/ROW]
[ROW][C]0.530983365331613[/C][/ROW]
[ROW][C]-0.174248339343484[/C][/ROW]
[ROW][C]-0.237235958037279[/C][/ROW]
[ROW][C]0.357357732489537[/C][/ROW]
[ROW][C]-0.2947743530296[/C][/ROW]
[ROW][C]0.0181454581623197[/C][/ROW]
[ROW][C]0.183884790869387[/C][/ROW]
[ROW][C]0.15665854560631[/C][/ROW]
[ROW][C]0.202121328929579[/C][/ROW]
[ROW][C]0.186157667090938[/C][/ROW]
[ROW][C]0.432539371524876[/C][/ROW]
[ROW][C]0.461382785448547[/C][/ROW]
[ROW][C]-0.192386642468495[/C][/ROW]
[ROW][C]0.282196702270624[/C][/ROW]
[ROW][C]0.289046028695891[/C][/ROW]
[ROW][C]-0.076477414728366[/C][/ROW]
[ROW][C]-0.182406346648576[/C][/ROW]
[ROW][C]0.0996543393797456[/C][/ROW]
[ROW][C]0.411495049940968[/C][/ROW]
[ROW][C]-0.0654682511194529[/C][/ROW]
[ROW][C]0.191025356824682[/C][/ROW]
[ROW][C]-0.0192013636893822[/C][/ROW]
[ROW][C]-0.498365666984428[/C][/ROW]
[ROW][C]-0.211877535540853[/C][/ROW]
[ROW][C]-0.261864046434133[/C][/ROW]
[ROW][C]-0.0589895433886087[/C][/ROW]
[ROW][C]-0.0926128100396111[/C][/ROW]
[ROW][C]-0.296624699116424[/C][/ROW]
[ROW][C]-0.181530504753092[/C][/ROW]
[ROW][C]-0.0473948204665046[/C][/ROW]
[ROW][C]-0.04529573579265[/C][/ROW]
[ROW][C]0.0365813702380886[/C][/ROW]
[ROW][C]-0.234866302173685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114606&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114606&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
-0.068885693314329
0.126572604143523
0.0483829084958972
-0.0927330106922004
0.105828785323538
-0.00144101434433747
0.232962680293775
-0.251871219483529
0.826278267520738
0.196446528874682
-0.160458847438412
0.029325649114606
-0.0954948891663683
0.0374000135802335
0.0767129634791493
-0.0584130679844418
0.0306318157894732
0.116799452656103
0.526226556538655
-0.528451827016542
-0.054780632110017
-0.062578494405267
0.125961894941609
-0.0240740347528834
0.0301620700506833
-0.204650485391612
-0.0872501453214247
0.232224817409499
-0.00151277621302341
0.202567079924424
-0.0781581820222848
-0.0317684344532889
-0.200793140587537
-0.138343166304208
-0.0321156750461273
0.0639583741232267
0.0797172568187897
0.303246277776138
-0.041529898268927
-0.279906327756374
-0.0579421858950845
-0.137938132962596
-0.343980708004516
0.157819994939029
0.0692432508377429
0.00387208909768483
-0.000284642702158385
-0.119451468241278
-0.194995138199204
-0.143907786518754
0.139538419594428
-0.164715818404426
0.0397726628144313
0.0343959138646523
0.086373075962306
-0.127140341244916
-0.498945418807487
0.236248645831743
-0.0372524857634758
0.0356201644484227
-0.485335007497648
0.23040361611286
-0.101400793950517
0.440546557194862
0.0774810362721573
-0.083678950548237
-0.372473804481123
-0.158652518436256
-0.0550911928292818
-0.377902357348888
0.020805884786717
-0.0209960474901373
0.486997831015025
-0.170427459546054
-0.125944541333158
-0.242103866868115
-0.0340620214676104
0.0905054515814488
0.230206090577608
-0.156966718691292
-0.507919055431671
0.263410775659937
0.161667875231993
0.4196633309499
-0.140683891290982
-0.0839721417035634
0.530983365331613
-0.174248339343484
-0.237235958037279
0.357357732489537
-0.2947743530296
0.0181454581623197
0.183884790869387
0.15665854560631
0.202121328929579
0.186157667090938
0.432539371524876
0.461382785448547
-0.192386642468495
0.282196702270624
0.289046028695891
-0.076477414728366
-0.182406346648576
0.0996543393797456
0.411495049940968
-0.0654682511194529
0.191025356824682
-0.0192013636893822
-0.498365666984428
-0.211877535540853
-0.261864046434133
-0.0589895433886087
-0.0926128100396111
-0.296624699116424
-0.181530504753092
-0.0473948204665046
-0.04529573579265
0.0365813702380886
-0.234866302173685

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 0 ; par8 = 0 ; par9 = 0 ;

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