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*Unverified author*

R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Wed, 02 Feb 2011 09:19:32 +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/2011/Feb/02/t1296638272uawkojblxxcy4ga.htm/, Retrieved Wed, 15 May 2024 18:59:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=118020, Retrieved Wed, 15 May 2024 18:59:23 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

240

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   [Spectral Analysis] [ws8 spectraalanal...] [2010-11-30 09:38:02] [74be16979710d4c4e7c6647856088456]
- RMPD    [(Partial) Autocorrelation Function] [ws8 autocorrelati...] [2010-11-30 10:25:41] [74be16979710d4c4e7c6647856088456]
- R  D      [(Partial) Autocorrelation Function] [PaperTimDamen] [2011-01-31 10:42:34] [74be16979710d4c4e7c6647856088456]
- R P         [(Partial) Autocorrelation Function] [PaperTimDamen] [2011-02-01 18:25:09] [74be16979710d4c4e7c6647856088456]
-   P           [(Partial) Autocorrelation Function] [PaperTimDamen] [2011-02-02 08:27:39] [74be16979710d4c4e7c6647856088456]
- RMP               [ARIMA Backward Selection] [PaperTimDamen] [2011-02-02 09:19:32] [d41d8cd98f00b204e9800998ecf8427e] [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	25 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 25 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118020&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]25 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118020&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	25 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	0.8164	0.1081	-0.2009	-0.6651	0.0228	0.8212	0.4255
(p-val)	(0 )	(0.0969 )	(0 )	(6e-04 )	(0.5111 )	(0 )	(0 )
Estimates ( 2 )	0.823	0.1037	-0.1995	-0.6724	0	0.8251	0.4573
(p-val)	(0 )	(0.1109 )	(0 )	(6e-04 )	(NA )	(0 )	(0 )
Estimates ( 3 )	1.0012	0	-0.166	-0.8139	0	0.8239	0.4552
(p-val)	(0 )	(NA )	(0 )	(0 )	(NA )	(0 )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & 0.8164 & 0.1081 & -0.2009 & -0.6651 & 0.0228 & 0.8212 & 0.4255 \tabularnewline
(p-val) & (0 ) & (0.0969 ) & (0 ) & (6e-04 ) & (0.5111 ) & (0 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.823 & 0.1037 & -0.1995 & -0.6724 & 0 & 0.8251 & 0.4573 \tabularnewline
(p-val) & (0 ) & (0.1109 ) & (0 ) & (6e-04 ) & (NA ) & (0 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 1.0012 & 0 & -0.166 & -0.8139 & 0 & 0.8239 & 0.4552 \tabularnewline
(p-val) & (0 ) & (NA ) & (0 ) & (0 ) & (NA ) & (0 ) & (0 ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118020&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]0.8164[/C][C]0.1081[/C][C]-0.2009[/C][C]-0.6651[/C][C]0.0228[/C][C]0.8212[/C][C]0.4255[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.0969 )[/C][C](0 )[/C][C](6e-04 )[/C][C](0.5111 )[/C][C](0 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.823[/C][C]0.1037[/C][C]-0.1995[/C][C]-0.6724[/C][C]0[/C][C]0.8251[/C][C]0.4573[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.1109 )[/C][C](0 )[/C][C](6e-04 )[/C][C](NA )[/C][C](0 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]1.0012[/C][C]0[/C][C]-0.166[/C][C]-0.8139[/C][C]0[/C][C]0.8239[/C][C]0.4552[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/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 ( 5 )[/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 ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118020&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 )	0.8164	0.1081	-0.2009	-0.6651	0.0228	0.8212	0.4255
(p-val)	(0 )	(0.0969 )	(0 )	(6e-04 )	(0.5111 )	(0 )	(0 )
Estimates ( 2 )	0.823	0.1037	-0.1995	-0.6724	0	0.8251	0.4573
(p-val)	(0 )	(0.1109 )	(0 )	(6e-04 )	(NA )	(0 )	(0 )
Estimates ( 3 )	1.0012	0	-0.166	-0.8139	0	0.8239	0.4552
(p-val)	(0 )	(NA )	(0 )	(0 )	(NA )	(0 )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
0.348999286178619
-6.42767614641707
-1.37012850153732
-0.458837636949241
-1.78275291152041
-0.388069901278568
32.2732661416117
4.99405136246779
-4.96137887107981
-1.23614159675221
0.94451730516309
5.38765635575823
1.29565427511765
3.92945197406167
-0.0483980366567702
2.80768629484107
2.53160780523421
3.18756766394823
12.9688725101544
1.03533758300484
-3.66035175078133
-1.82007863756105
2.7449450497612
4.57293895884601
3.89029946700118
6.9430887614411
-4.44671656668951
-5.28704113397158
-0.323883631922875
1.27054030179152
6.83195808277417
-1.59098311320093
-3.67714192097057
1.30865312766499
3.7962768014678
-1.30193139807972
-1.27065356288138
-6.46126964270759
-5.92403306955794
-4.09462731547645
-7.63372636027495
-2.82763651725840
7.03629255144971
6.49310610329448
-2.62380075833867
-4.00486732825757
-13.7888486054450
-10.6522140007174
-1.98182856213597
-6.15204495880044
-4.58195807481792
-5.83698903858845
3.33980102802581
-4.02340665179769
5.34196867177401
10.5774245751415
-11.6173501603854
-7.57252957532668
2.11195486588501
-9.6445578587022
18.5636656882922
-14.5764547262866
-16.5179897978528
-9.49192830158234
-6.29318257923702
-16.0030573173993
-0.139996753104996
-8.58945169236974
-2.95797521117692
-3.12405506588326
-2.35023388592161
12.2161999281814
-9.31592420616906
-4.46007493560023
4.63651347017263
5.68147268069583
-0.887118648147182
8.42697119892087
-5.03921598827169
-11.9512613661816
9.6514666304572
17.9783315837234
-14.3958502650654
11.1969778658952
-9.37948569001152
-4.11272731374209
10.6473784579932
3.54634850698809
0.110928888811245
8.73406858657804
8.75248931385755
-5.87838337121173
-2.44670512441347
-1.38154450247784
5.05127421409642
-8.23327910644875
3.09773928614974
0.764169823631509
-8.82595382883443
-4.00954547203885
-4.35781492236395
-5.60156714628166
11.8998476233803
-1.29165414304582
-14.1457372656741
-13.3671531195525
6.22368940311794
-1.51392521177440
-6.72235963375533
5.10192835999333
6.08926522631541
-10.5837694677953
1.51110061628773
3.05201930483237
1.92198453880959
10.7926477669013
-10.6309154777340
2.04311384503321
3.36622874809406
2.54946366148257
2.27672881178436
-2.02194827836195
-1.12664736095800
4.77879019730655
0.662085716488124
3.37434999197773
8.24561457253533
-1.40389390010645
7.41762385259506
3.26235963421998
1.03205821892089
5.03673884084083
3.15484720597157
8.02333617046944
-7.15684305085085
7.36856920421915
1.85563515793244
1.90397984548549
9.47375015815935
2.65388784270069
1.30850003410585
5.40962301823997
-0.189043860115248
4.10880264188663
2.91488916371353
-3.24304234875038
5.94109585756203
2.81369420264208
-3.09527295351448
4.84614099861639
4.18444230066584
6.51873545253609
-3.78361127099407
-1.92558532911326
4.55881172903833
7.16875642297591
3.25450142374114
1.64955361750172
-0.588983692318374
2.45948971544163
3.74771881921173
2.55687951374447
12.7557817704554
3.09494324993065
4.1480333135099
-9.22628697137911
2.80328179377081
-0.346171480585316
-1.45465230065187
7.86634279338631
-2.11582488348808
0.937571046778002
-7.82648918876307
-5.44047796325023
-55.1947605689596
-7.53576482265421
5.90726038922625
5.3447831265896
-4.67966726260879
-13.8775284408875
43.0526470484753
-7.88120371355266
18.3428989457725
-0.683308393644523
-3.02710036085052
-0.255784560559111
-31.5395531802413
-3.59084503180392
0.0587368486616024
6.4000044917508
4.34484479674339
-3.62226432391142
-22.0644207781856
3.85293305515452
-10.540485743537
-0.112638763716239
-4.20521753887335
0.564077296664794
14.7146651486313
1.22367802812397
-5.64796255625998
-2.37700015170488
-0.232171605962178
1.08005649439090
23.8380478912322
-4.05789336255406
7.47469595706925
0.00428168725680793
3.42828217632826
0.136680034906415
-2.60825356797125
-0.71942844317364
-2.87148026515205
2.28547719137587
4.12237883039848
-0.997794667390793
-7.34509904497307
1.34925855447508
-14.5910646352939
1.87752521463306
-5.19900481350345
0.33762648961285
-1.31794326944702
0.246843352596179
-7.48850995644058
-0.152630188949750
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\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.348999286178619 \tabularnewline
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1.03533758300484 \tabularnewline
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0.210198935547339 \tabularnewline
7.14959627898247 \tabularnewline
-0.994285872790215 \tabularnewline
-1.74310241028758 \tabularnewline
0.509125669054697 \tabularnewline
12.2991765233822 \tabularnewline
-1.61128900294551 \tabularnewline
-2.14123976837806 \tabularnewline
0.791591138880335 \tabularnewline
18.0266859471181 \tabularnewline
-2.25739096256154 \tabularnewline
-0.000513136479980858 \tabularnewline
0.749669088014969 \tabularnewline
-17.7061417772143 \tabularnewline
3.46300938133544 \tabularnewline
7.64208224734364 \tabularnewline
-1.27410418200543 \tabularnewline
-7.44247102937731 \tabularnewline
0.811221284889314 \tabularnewline
5.88523330586799 \tabularnewline
-1.14846549516170 \tabularnewline
-4.36677717991637 \tabularnewline
0.558127386904858 \tabularnewline
-5.70151275419494 \tabularnewline
0.813143870452791 \tabularnewline
9.15548959432431 \tabularnewline
-1.65979928748425 \tabularnewline
1.60274507101445 \tabularnewline
-0.253047331826565 \tabularnewline
19.5805127936504 \tabularnewline
-2.68550672294896 \tabularnewline
-19.4910564009685 \tabularnewline
3.74654339100539 \tabularnewline
1.08289048331142 \tabularnewline
0.129642309591418 \tabularnewline
7.58111442376469 \tabularnewline
-1.41898147021891 \tabularnewline
11.0708920053042 \tabularnewline
-1.63382485403969 \tabularnewline
-1.04312749400583 \tabularnewline
0.710498151006959 \tabularnewline
-5.99090357573914 \tabularnewline
1.45320535331109 \tabularnewline
7.59160257089787 \tabularnewline
-1.06151760675607 \tabularnewline
-2.80968762633563 \tabularnewline
0.515966545518893 \tabularnewline
3.64382382325130 \tabularnewline
-0.432104672318872 \tabularnewline
-9.50557166823552 \tabularnewline
1.55170035198631 \tabularnewline
6.50918955733499 \tabularnewline
-1.13652167480274 \tabularnewline
13.3271000255451 \tabularnewline
-2.11802668904318 \tabularnewline
-1.26001775984866 \tabularnewline
0.679927346741806 \tabularnewline
0.609507653516175 \tabularnewline
0.475548270783747 \tabularnewline
-10.8513238643586 \tabularnewline
1.93512320692025 \tabularnewline
-3.22792305742416 \tabularnewline
0.285944105742601 \tabularnewline
4.22864556960531 \tabularnewline
-1.12760839936846 \tabularnewline
-6.55075890997432 \tabularnewline
-0.243684272964515 \tabularnewline
-3.89268867405031 \tabularnewline
-10.3876847779339 \tabularnewline
1.02644865728689 \tabularnewline
7.940932844582 \tabularnewline
55.267216832701 \tabularnewline
6.41881181161193 \tabularnewline
-3.18204971565774 \tabularnewline
-3.76525753130591 \tabularnewline
-22.1824780633498 \tabularnewline
7.89005492036279 \tabularnewline
-46.1465091605299 \tabularnewline
5.98064677885565 \tabularnewline
-0.783203106164478 \tabularnewline
-7.18466318324385 \tabularnewline
-2.72973598156625 \tabularnewline
-1.23844794583067 \tabularnewline
35.6717839843981 \tabularnewline
-6.6574559890305 \tabularnewline
0.112869298884902 \tabularnewline
-14.8963793783902 \tabularnewline
-11.3025067769872 \tabularnewline
7.81859554116761 \tabularnewline
16.6201021777549 \tabularnewline
-4.7943703127188 \tabularnewline
-2.87306627547150 \tabularnewline
6.62006962513408 \tabularnewline
5.82421393322227 \tabularnewline
-6.564297331474 \tabularnewline
-11.9938081885722 \tabularnewline
-4.66162234933734 \tabularnewline
-7.77524318466908 \tabularnewline
-20.6203432734764 \tabularnewline
2.92103553300706 \tabularnewline
-6.7276922952052 \tabularnewline
0.438817514723269 \tabularnewline
-9.33201808887827 \tabularnewline
-13.5086430753222 \tabularnewline
3.20834692039853 \tabularnewline
-11.7812264895681 \tabularnewline
-11.3954400958915 \tabularnewline
21.7905195981409 \tabularnewline
5.12748270328677 \tabularnewline
-23.484320952266 \tabularnewline
9.96071666998557 \tabularnewline
0.506158863531255 \tabularnewline
4.87478856087148 \tabularnewline
5.3243447504185 \tabularnewline
-4.56460369320212 \tabularnewline
-1.32476447203214 \tabularnewline
2.92739411977482 \tabularnewline
-14.0395332772984 \tabularnewline
16.2045459427046 \tabularnewline
3.72232205322888 \tabularnewline
-6.28609989980248 \tabularnewline
-3.19212234453153 \tabularnewline
11.7042131328247 \tabularnewline
14.3543552319271 \tabularnewline
13.6580178553389 \tabularnewline
0.718657389903456 \tabularnewline
12.5497661638753 \tabularnewline
15.7751568516759 \tabularnewline
0.98815359912794 \tabularnewline
3.67049797423112 \tabularnewline
15.9347104383683 \tabularnewline
2.01645907223030 \tabularnewline
0.781458352248137 \tabularnewline
5.4616534656119 \tabularnewline
-8.96019625713552 \tabularnewline
2.88196336309272 \tabularnewline
8.27275194162428 \tabularnewline
-1.07210962550926 \tabularnewline
-5.71073747875676 \tabularnewline
-6.34391725813134 \tabularnewline
-8.4491799692762 \tabularnewline
2.73205236797253 \tabularnewline
-4.70291858750807 \tabularnewline
13.1464534043095 \tabularnewline
-4.58004933413975 \tabularnewline
-9.94507887801194 \tabularnewline
-5.91535408078596 \tabularnewline
-9.68364298853874 \tabularnewline
-9.03254467378042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=118020&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.348999286178619[/C][/ROW]
[ROW][C]-6.42767614641707[/C][/ROW]
[ROW][C]-1.37012850153732[/C][/ROW]
[ROW][C]-0.458837636949241[/C][/ROW]
[ROW][C]-1.78275291152041[/C][/ROW]
[ROW][C]-0.388069901278568[/C][/ROW]
[ROW][C]32.2732661416117[/C][/ROW]
[ROW][C]4.99405136246779[/C][/ROW]
[ROW][C]-4.96137887107981[/C][/ROW]
[ROW][C]-1.23614159675221[/C][/ROW]
[ROW][C]0.94451730516309[/C][/ROW]
[ROW][C]5.38765635575823[/C][/ROW]
[ROW][C]1.29565427511765[/C][/ROW]
[ROW][C]3.92945197406167[/C][/ROW]
[ROW][C]-0.0483980366567702[/C][/ROW]
[ROW][C]2.80768629484107[/C][/ROW]
[ROW][C]2.53160780523421[/C][/ROW]
[ROW][C]3.18756766394823[/C][/ROW]
[ROW][C]12.9688725101544[/C][/ROW]
[ROW][C]1.03533758300484[/C][/ROW]
[ROW][C]-3.66035175078133[/C][/ROW]
[ROW][C]-1.82007863756105[/C][/ROW]
[ROW][C]2.7449450497612[/C][/ROW]
[ROW][C]4.57293895884601[/C][/ROW]
[ROW][C]3.89029946700118[/C][/ROW]
[ROW][C]6.9430887614411[/C][/ROW]
[ROW][C]-4.44671656668951[/C][/ROW]
[ROW][C]-5.28704113397158[/C][/ROW]
[ROW][C]-0.323883631922875[/C][/ROW]
[ROW][C]1.27054030179152[/C][/ROW]
[ROW][C]6.83195808277417[/C][/ROW]
[ROW][C]-1.59098311320093[/C][/ROW]
[ROW][C]-3.67714192097057[/C][/ROW]
[ROW][C]1.30865312766499[/C][/ROW]
[ROW][C]3.7962768014678[/C][/ROW]
[ROW][C]-1.30193139807972[/C][/ROW]
[ROW][C]-1.27065356288138[/C][/ROW]
[ROW][C]-6.46126964270759[/C][/ROW]
[ROW][C]-5.92403306955794[/C][/ROW]
[ROW][C]-4.09462731547645[/C][/ROW]
[ROW][C]-7.63372636027495[/C][/ROW]
[ROW][C]-2.82763651725840[/C][/ROW]
[ROW][C]7.03629255144971[/C][/ROW]
[ROW][C]6.49310610329448[/C][/ROW]
[ROW][C]-2.62380075833867[/C][/ROW]
[ROW][C]-4.00486732825757[/C][/ROW]
[ROW][C]-13.7888486054450[/C][/ROW]
[ROW][C]-10.6522140007174[/C][/ROW]
[ROW][C]-1.98182856213597[/C][/ROW]
[ROW][C]-6.15204495880044[/C][/ROW]
[ROW][C]-4.58195807481792[/C][/ROW]
[ROW][C]-5.83698903858845[/C][/ROW]
[ROW][C]3.33980102802581[/C][/ROW]
[ROW][C]-4.02340665179769[/C][/ROW]
[ROW][C]5.34196867177401[/C][/ROW]
[ROW][C]10.5774245751415[/C][/ROW]
[ROW][C]-11.6173501603854[/C][/ROW]
[ROW][C]-7.57252957532668[/C][/ROW]
[ROW][C]2.11195486588501[/C][/ROW]
[ROW][C]-9.6445578587022[/C][/ROW]
[ROW][C]18.5636656882922[/C][/ROW]
[ROW][C]-14.5764547262866[/C][/ROW]
[ROW][C]-16.5179897978528[/C][/ROW]
[ROW][C]-9.49192830158234[/C][/ROW]
[ROW][C]-6.29318257923702[/C][/ROW]
[ROW][C]-16.0030573173993[/C][/ROW]
[ROW][C]-0.139996753104996[/C][/ROW]
[ROW][C]-8.58945169236974[/C][/ROW]
[ROW][C]-2.95797521117692[/C][/ROW]
[ROW][C]-3.12405506588326[/C][/ROW]
[ROW][C]-2.35023388592161[/C][/ROW]
[ROW][C]12.2161999281814[/C][/ROW]
[ROW][C]-9.31592420616906[/C][/ROW]
[ROW][C]-4.46007493560023[/C][/ROW]
[ROW][C]4.63651347017263[/C][/ROW]
[ROW][C]5.68147268069583[/C][/ROW]
[ROW][C]-0.887118648147182[/C][/ROW]
[ROW][C]8.42697119892087[/C][/ROW]
[ROW][C]-5.03921598827169[/C][/ROW]
[ROW][C]-11.9512613661816[/C][/ROW]
[ROW][C]9.6514666304572[/C][/ROW]
[ROW][C]17.9783315837234[/C][/ROW]
[ROW][C]-14.3958502650654[/C][/ROW]
[ROW][C]11.1969778658952[/C][/ROW]
[ROW][C]-9.37948569001152[/C][/ROW]
[ROW][C]-4.11272731374209[/C][/ROW]
[ROW][C]10.6473784579932[/C][/ROW]
[ROW][C]3.54634850698809[/C][/ROW]
[ROW][C]0.110928888811245[/C][/ROW]
[ROW][C]8.73406858657804[/C][/ROW]
[ROW][C]8.75248931385755[/C][/ROW]
[ROW][C]-5.87838337121173[/C][/ROW]
[ROW][C]-2.44670512441347[/C][/ROW]
[ROW][C]-1.38154450247784[/C][/ROW]
[ROW][C]5.05127421409642[/C][/ROW]
[ROW][C]-8.23327910644875[/C][/ROW]
[ROW][C]3.09773928614974[/C][/ROW]
[ROW][C]0.764169823631509[/C][/ROW]
[ROW][C]-8.82595382883443[/C][/ROW]
[ROW][C]-4.00954547203885[/C][/ROW]
[ROW][C]-4.35781492236395[/C][/ROW]
[ROW][C]-5.60156714628166[/C][/ROW]
[ROW][C]11.8998476233803[/C][/ROW]
[ROW][C]-1.29165414304582[/C][/ROW]
[ROW][C]-14.1457372656741[/C][/ROW]
[ROW][C]-13.3671531195525[/C][/ROW]
[ROW][C]6.22368940311794[/C][/ROW]
[ROW][C]-1.51392521177440[/C][/ROW]
[ROW][C]-6.72235963375533[/C][/ROW]
[ROW][C]5.10192835999333[/C][/ROW]
[ROW][C]6.08926522631541[/C][/ROW]
[ROW][C]-10.5837694677953[/C][/ROW]
[ROW][C]1.51110061628773[/C][/ROW]
[ROW][C]3.05201930483237[/C][/ROW]
[ROW][C]1.92198453880959[/C][/ROW]
[ROW][C]10.7926477669013[/C][/ROW]
[ROW][C]-10.6309154777340[/C][/ROW]
[ROW][C]2.04311384503321[/C][/ROW]
[ROW][C]3.36622874809406[/C][/ROW]
[ROW][C]2.54946366148257[/C][/ROW]
[ROW][C]2.27672881178436[/C][/ROW]
[ROW][C]-2.02194827836195[/C][/ROW]
[ROW][C]-1.12664736095800[/C][/ROW]
[ROW][C]4.77879019730655[/C][/ROW]
[ROW][C]0.662085716488124[/C][/ROW]
[ROW][C]3.37434999197773[/C][/ROW]
[ROW][C]8.24561457253533[/C][/ROW]
[ROW][C]-1.40389390010645[/C][/ROW]
[ROW][C]7.41762385259506[/C][/ROW]
[ROW][C]3.26235963421998[/C][/ROW]
[ROW][C]1.03205821892089[/C][/ROW]
[ROW][C]5.03673884084083[/C][/ROW]
[ROW][C]3.15484720597157[/C][/ROW]
[ROW][C]8.02333617046944[/C][/ROW]
[ROW][C]-7.15684305085085[/C][/ROW]
[ROW][C]7.36856920421915[/C][/ROW]
[ROW][C]1.85563515793244[/C][/ROW]
[ROW][C]1.90397984548549[/C][/ROW]
[ROW][C]9.47375015815935[/C][/ROW]
[ROW][C]2.65388784270069[/C][/ROW]
[ROW][C]1.30850003410585[/C][/ROW]
[ROW][C]5.40962301823997[/C][/ROW]
[ROW][C]-0.189043860115248[/C][/ROW]
[ROW][C]4.10880264188663[/C][/ROW]
[ROW][C]2.91488916371353[/C][/ROW]
[ROW][C]-3.24304234875038[/C][/ROW]
[ROW][C]5.94109585756203[/C][/ROW]
[ROW][C]2.81369420264208[/C][/ROW]
[ROW][C]-3.09527295351448[/C][/ROW]
[ROW][C]4.84614099861639[/C][/ROW]
[ROW][C]4.18444230066584[/C][/ROW]
[ROW][C]6.51873545253609[/C][/ROW]
[ROW][C]-3.78361127099407[/C][/ROW]
[ROW][C]-1.92558532911326[/C][/ROW]
[ROW][C]4.55881172903833[/C][/ROW]
[ROW][C]7.16875642297591[/C][/ROW]
[ROW][C]3.25450142374114[/C][/ROW]
[ROW][C]1.64955361750172[/C][/ROW]
[ROW][C]-0.588983692318374[/C][/ROW]
[ROW][C]2.45948971544163[/C][/ROW]
[ROW][C]3.74771881921173[/C][/ROW]
[ROW][C]2.55687951374447[/C][/ROW]
[ROW][C]12.7557817704554[/C][/ROW]
[ROW][C]3.09494324993065[/C][/ROW]
[ROW][C]4.1480333135099[/C][/ROW]
[ROW][C]-9.22628697137911[/C][/ROW]
[ROW][C]2.80328179377081[/C][/ROW]
[ROW][C]-0.346171480585316[/C][/ROW]
[ROW][C]-1.45465230065187[/C][/ROW]
[ROW][C]7.86634279338631[/C][/ROW]
[ROW][C]-2.11582488348808[/C][/ROW]
[ROW][C]0.937571046778002[/C][/ROW]
[ROW][C]-7.82648918876307[/C][/ROW]
[ROW][C]-5.44047796325023[/C][/ROW]
[ROW][C]-55.1947605689596[/C][/ROW]
[ROW][C]-7.53576482265421[/C][/ROW]
[ROW][C]5.90726038922625[/C][/ROW]
[ROW][C]5.3447831265896[/C][/ROW]
[ROW][C]-4.67966726260879[/C][/ROW]
[ROW][C]-13.8775284408875[/C][/ROW]
[ROW][C]43.0526470484753[/C][/ROW]
[ROW][C]-7.88120371355266[/C][/ROW]
[ROW][C]18.3428989457725[/C][/ROW]
[ROW][C]-0.683308393644523[/C][/ROW]
[ROW][C]-3.02710036085052[/C][/ROW]
[ROW][C]-0.255784560559111[/C][/ROW]
[ROW][C]-31.5395531802413[/C][/ROW]
[ROW][C]-3.59084503180392[/C][/ROW]
[ROW][C]0.0587368486616024[/C][/ROW]
[ROW][C]6.4000044917508[/C][/ROW]
[ROW][C]4.34484479674339[/C][/ROW]
[ROW][C]-3.62226432391142[/C][/ROW]
[ROW][C]-22.0644207781856[/C][/ROW]
[ROW][C]3.85293305515452[/C][/ROW]
[ROW][C]-10.540485743537[/C][/ROW]
[ROW][C]-0.112638763716239[/C][/ROW]
[ROW][C]-4.20521753887335[/C][/ROW]
[ROW][C]0.564077296664794[/C][/ROW]
[ROW][C]14.7146651486313[/C][/ROW]
[ROW][C]1.22367802812397[/C][/ROW]
[ROW][C]-5.64796255625998[/C][/ROW]
[ROW][C]-2.37700015170488[/C][/ROW]
[ROW][C]-0.232171605962178[/C][/ROW]
[ROW][C]1.08005649439090[/C][/ROW]
[ROW][C]23.8380478912322[/C][/ROW]
[ROW][C]-4.05789336255406[/C][/ROW]
[ROW][C]7.47469595706925[/C][/ROW]
[ROW][C]0.00428168725680793[/C][/ROW]
[ROW][C]3.42828217632826[/C][/ROW]
[ROW][C]0.136680034906415[/C][/ROW]
[ROW][C]-2.60825356797125[/C][/ROW]
[ROW][C]-0.71942844317364[/C][/ROW]
[ROW][C]-2.87148026515205[/C][/ROW]
[ROW][C]2.28547719137587[/C][/ROW]
[ROW][C]4.12237883039848[/C][/ROW]
[ROW][C]-0.997794667390793[/C][/ROW]
[ROW][C]-7.34509904497307[/C][/ROW]
[ROW][C]1.34925855447508[/C][/ROW]
[ROW][C]-14.5910646352939[/C][/ROW]
[ROW][C]1.87752521463306[/C][/ROW]
[ROW][C]-5.19900481350345[/C][/ROW]
[ROW][C]0.33762648961285[/C][/ROW]
[ROW][C]-1.31794326944702[/C][/ROW]
[ROW][C]0.246843352596179[/C][/ROW]
[ROW][C]-7.48850995644058[/C][/ROW]
[ROW][C]-0.152630188949750[/C][/ROW]
[ROW][C]-10.3413084839248[/C][/ROW]
[ROW][C]1.18557131145530[/C][/ROW]
[ROW][C]15.1570556919012[/C][/ROW]
[ROW][C]-3.13224565853812[/C][/ROW]
[ROW][C]5.93918188259671[/C][/ROW]
[ROW][C]-0.967691299816109[/C][/ROW]
[ROW][C]-8.2555001811881[/C][/ROW]
[ROW][C]1.61802108985264[/C][/ROW]
[ROW][C]-11.0066673050985[/C][/ROW]
[ROW][C]1.43556664469740[/C][/ROW]
[ROW][C]6.45590992383573[/C][/ROW]
[ROW][C]-1.11364589474235[/C][/ROW]
[ROW][C]-0.0742645692803214[/C][/ROW]
[ROW][C]-0.410496721460681[/C][/ROW]
[ROW][C]-11.5585014152936[/C][/ROW]
[ROW][C]1.75142680873870[/C][/ROW]
[ROW][C]5.05654940758536[/C][/ROW]
[ROW][C]-1.13687570886097[/C][/ROW]
[ROW][C]6.48621178629668[/C][/ROW]
[ROW][C]-1.22033665322246[/C][/ROW]
[ROW][C]3.49428524165003[/C][/ROW]
[ROW][C]-0.176652014447081[/C][/ROW]
[ROW][C]-0.875386011534351[/C][/ROW]
[ROW][C]0.376399500856327[/C][/ROW]
[ROW][C]12.021559866422[/C][/ROW]
[ROW][C]-1.50038989907587[/C][/ROW]
[ROW][C]5.32550817231161[/C][/ROW]
[ROW][C]-0.342778162280635[/C][/ROW]
[ROW][C]-0.584737609828263[/C][/ROW]
[ROW][C]0.792274121544887[/C][/ROW]
[ROW][C]-1.05557406682669[/C][/ROW]
[ROW][C]0.611935274473804[/C][/ROW]
[ROW][C]-7.90739409241412[/C][/ROW]
[ROW][C]1.27809706661832[/C][/ROW]
[ROW][C]-4.08099851658935[/C][/ROW]
[ROW][C]0.463760671563475[/C][/ROW]
[ROW][C]-2.28057223784570[/C][/ROW]
[ROW][C]-0.122784869179554[/C][/ROW]
[ROW][C]-7.37975970387613[/C][/ROW]
[ROW][C]0.702246373369575[/C][/ROW]
[ROW][C]-0.157211342432561[/C][/ROW]
[ROW][C]-0.473001173802231[/C][/ROW]
[ROW][C]-3.56370422984491[/C][/ROW]
[ROW][C]0.128753432581220[/C][/ROW]
[ROW][C]-2.25829256684824[/C][/ROW]
[ROW][C]0.0587527112046472[/C][/ROW]
[ROW][C]0.531803713799263[/C][/ROW]
[ROW][C]-0.405473655402374[/C][/ROW]
[ROW][C]-9.13345652856883[/C][/ROW]
[ROW][C]1.20271034916192[/C][/ROW]
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[ROW][C]-9.03254467378042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=118020&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=118020&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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12.9688725101544
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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 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

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

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code