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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Thu, 29 Nov 2012 09:02:51 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/29/t1354197848n93jany4frcndar.htm/, Retrieved Sun, 28 Apr 2024 08:04:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194639, Retrieved Sun, 28 Apr 2024 08:04:03 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

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   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R P     [(Partial) Autocorrelation Function] [] [2012-11-29 12:37:07] [f6b89b7e4a7442873f7514a83779c1e1]
- RMP       [Spectral Analysis] [] [2012-11-29 13:01:19] [f6b89b7e4a7442873f7514a83779c1e1]
- RMP         [ARIMA Backward Selection] [] [2012-11-29 13:48:12] [f6b89b7e4a7442873f7514a83779c1e1]
- R               [ARIMA Backward Selection] [] [2012-11-29 14:02:51] [445c08979aafedc6c0243a83e6d65727] [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	9 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194639&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194639&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	sar1	sma1
Estimates ( 1 )	0.1361	0.243	0.0042	-0.0795	-0.6533
(p-val)	(0.0106 )	(0 )	(0.9365 )	(0.2988 )	(0 )
Estimates ( 2 )	0.1371	0.2435	0	-0.0797	-0.6535
(p-val)	(0.008 )	(0 )	(NA )	(0.2973 )	(0 )
Estimates ( 3 )	0.135	0.2464	0	0	-0.6953
(p-val)	(0.0089 )	(0 )	(NA )	(NA )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & sar1 & sma1 \tabularnewline
Estimates ( 1 ) & 0.1361 & 0.243 & 0.0042 & -0.0795 & -0.6533 \tabularnewline
(p-val) & (0.0106 ) & (0 ) & (0.9365 ) & (0.2988 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.1371 & 0.2435 & 0 & -0.0797 & -0.6535 \tabularnewline
(p-val) & (0.008 ) & (0 ) & (NA ) & (0.2973 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0.135 & 0.2464 & 0 & 0 & -0.6953 \tabularnewline
(p-val) & (0.0089 ) & (0 ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194639&T=1

[TABLE]
[ROW][C]ARIMA Parameter Estimation and Backward Selection[/C][/ROW]
[ROW][C]Iteration[/C][C]ar1[/C][C]ar2[/C][C]ar3[/C][C]sar1[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]0.1361[/C][C]0.243[/C][C]0.0042[/C][C]-0.0795[/C][C]-0.6533[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0106 )[/C][C](0 )[/C][C](0.9365 )[/C][C](0.2988 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.1371[/C][C]0.2435[/C][C]0[/C][C]-0.0797[/C][C]-0.6535[/C][/ROW]
[ROW][C](p-val)[/C][C](0.008 )[/C][C](0 )[/C][C](NA )[/C][C](0.2973 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0.135[/C][C]0.2464[/C][C]0[/C][C]0[/C][C]-0.6953[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0089 )[/C][C](0 )[/C][C](NA )[/C][C](NA )[/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][/ROW]
[ROW][C](p-val)[/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][/ROW]
[ROW][C](p-val)[/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][/ROW]
[ROW][C](p-val)[/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][/ROW]
[ROW][C](p-val)[/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][/ROW]
[ROW][C](p-val)[/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][/ROW]
[ROW][C](p-val)[/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=194639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194639&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	sar1	sma1
Estimates ( 1 )	0.1361	0.243	0.0042	-0.0795	-0.6533
(p-val)	(0.0106 )	(0 )	(0.9365 )	(0.2988 )	(0 )
Estimates ( 2 )	0.1371	0.2435	0	-0.0797	-0.6535
(p-val)	(0.008 )	(0 )	(NA )	(0.2973 )	(0 )
Estimates ( 3 )	0.135	0.2464	0	0	-0.6953
(p-val)	(0.0089 )	(0 )	(NA )	(NA )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.535784830976831
1.76903397191346
5.14628252916545
9.4926520027237
48.0757459925896
-5.06528498901834
20.7584381496093
-26.5568571295093
-16.8988462953076
44.40130259583
-42.7178616086099
-7.60463439085142
24.714388118564
-30.8433190421496
-31.1643180664074
-32.4428235024559
-16.0439783388515
2.40363875144062
-32.5951123833247
-28.7937725346551
26.816413022255
-25.684958916906
25.9796570937098
-5.07605046066862
-65.1521496061982
-34.7982371860641
23.599690712917
5.70418788137112
-0.151767950147911
-0.290378094906347
-12.5624234913062
20.2266249680593
28.7044304771356
-3.20566227508572
4.39937534246934
-33.8742686637881
-18.7777379531313
-1.22402047698739
-1.72395529219807
24.539804126782
12.2257481791746
-18.2527616563548
2.89326438817624
26.7848754154271
-11.9243674402666
-10.9010323693039
-2.47663537377535
-5.02404132959319
3.63602627734319
-29.1234512918508
17.778833844422
30.7382194275226
-14.8383568473524
-18.6503909597798
0.145804337718408
17.3503595327912
21.661014884809
8.86165761246452
21.0871971049756
28.2567763536581
50.7247607296956
19.6870387851375
9.31026526815972
-8.58112938200254
-10.405620201571
-27.2704222289155
3.28595724388374
14.0389278869765
1.89952483454334
-36.2758718335084
-0.55960945834314
-9.79499591585763
-4.37692306685266
-17.7030834036084
-6.60867563703818
14.8051720376241
-27.9044534130267
1.56528234357327
-16.0249763735606
16.4239315941089
-11.5878786835515
18.0459864645769
2.69788310540313
-3.59338082189156
-29.567532249738
-3.14406117948626
25.2046569288462
-20.3477913443421
32.9065928510913
18.7488484497254
-24.4104892633646
-32.6048832536814
-3.61178732053284
12.0439965759627
29.3551015047632
-2.72090261418846
-19.2438099413364
-16.8799372230402
-7.66028528526407
10.3942325211243
21.47535867844
21.6114008831411
-25.8554797710933
-6.34672786572312
14.6502264137583
14.7866001601947
30.6062985152381
6.94023464218742
40.4509362338861
53.4787344606328
-1.78205621572222
-3.67951362007862
-19.0815509231999
5.02229114364384
5.97739598780304
-19.7534101636705
-43.2839411583197
-5.31879784721217
-25.452995412496
28.2020581462457
-7.35727838508619
-17.7582030977024
-23.2668327028022
-46.8985450870398
4.60337282519803
24.4938073979864
-0.0894167220781985
8.20648203102952
5.12216480712498
18.5702197491549
2.30587714765411
-32.9871627068673
-12.5892512083707
-31.6654165962767
54.5593575376825
-18.9454763996064
-14.0400568812147
47.1473333063379
-16.5698046677318
8.94781236584361
-16.4609937150212
33.8648377086654
9.20038726761918
31.128962417314
9.01529322664593
14.5687893767886
-23.6105418878432
-15.5372206288923
2.54721910487765
17.4907170651471
-16.7186104541045
-24.2798602966992
-7.24693152325897
-6.97498058127626
-23.0880477901024
-1.02824871829531
-7.1104874880454
-19.7532631526219
-0.0748883998965978
7.2738901275672
30.3974478316699
-33.3476523387737
-17.3800821499326
44.7726767704997
-8.80525878988357
-25.2655605027819
24.1784712813431
-13.7923839678723
13.7297547645765
20.5006351245874
-37.6508806868545
1.64465281368277
15.1939533469807
10.0938344111377
-15.6373793710177
-13.4181636071579
10.1268173034072
4.82628047691192
11.8459605297286
-23.4412367927873
-1.06481124813955
-9.32672496432393
-1.08399438187233
10.8874757144825
-21.9468469623101
43.6235103443176
-45.0012271521586
10.7284056776388
12.7974666199096
-0.130451956435516
-27.3045708898671
4.12396240377367
-15.2500150024029
19.4598642561244
-21.4119586842466
22.8614865314854
-11.1308182284788
18.1385240484527
-16.6410192586275
-5.1921326888724
3.6192051546009
-3.51670900929658
-12.9163478768749
-13.898663044252
-17.470889464474
-15.9921245422155
26.4551794823846
14.8901898508295
19.3873080845169
3.0276875801971
-8.73934423798327
-1.12049363686786
-0.117355769955134
6.04001412227224
-15.7537444219845
6.64251571357321
-9.09564937093057
-1.96304269635448
6.43794300337987
4.25793207529969
-9.02835777049555
42.8760019769903
12.1252464661439
-19.5294307332982
23.9583301332121
12.3156680601464
-35.1272701295165
-21.2696664499641
-12.0628842667418
26.8579776602081
-8.89306793400264
-15.2686500325446
-0.749959796783489
48.7711015832542
5.04418415655933
-31.2546807807804
8.13922853636404
-1.76178329827789
-8.40063167145589
-11.3759090892664
-1.23156783161761
1.20422363840203
11.1883200911636
13.4407481778698
-13.053831000849
6.24340715431676
26.3225338647497
-5.70089842173531
23.4176610078893
-10.7875527764369
-29.6493947900414
3.63544392151567
35.7096773086633
27.0722935321706
7.74179440797446
3.30655551028347
-5.30560189250141
19.8293487230023
19.4895777363157
-5.66462879132965
13.7111366726853
0.432176552483553
25.6187628001013
5.8070263083149
12.9268532652652
-18.8094612520058
-10.6617626985004
-16.843976144291
-7.19959128575644
4.59881898650176
18.4753306910867
2.75714357643068
-20.8493504299649
-19.2612052501417
20.5709226920974
-3.71716444529074
9.34079932886775
-17.6920487272172
0.282780700131674
-15.6000550654091
-11.5268418992641
2.45322208522521
4.71093551425211
-0.747657464536695
-10.8720240914714
-5.15363348308538
-33.1092733909457
-1.88675374395731
-1.69643563100753
12.1289352281836
-10.8487629592757
4.42844002747247
-9.4063050320154
-5.85987916793011
-0.942332891197308
-1.90340972792835
10.3294439910607
-25.5527503267159
23.487923176158
12.4579953817512
23.1729726508223
-3.03145701760198
-22.2223306581653
-5.88322409353115
18.4007181993601
14.2110504118804
8.92875457423253
-11.6405367523245
40.2495539579375
1.74539419383237
41.930368637512
40.4142332127378
115.312864561629
-28.912923615866
0.519131229204766
-19.0273754382756
0.562758768508315
-15.6102413328833
-12.4343120383412
-11.877679591556
-12.5002435978047
0.844933570602423
-22.5899116468759
-4.91822524169806
-4.13095371917262
-21.8240050297471
-23.8100331572438
-8.95917808502537
-24.6994337769713
35.8657236279948
22.4770304336743
4.03655965147121
-34.0667326801478
4.29015384806397
10.4161002183014
-15.4465226108543
-31.1435878547975
28.8663626153941
-23.8712271992953
-49.9583288911025
4.78041795064893
28.6551580829978
-29.5952751669598
17.8411657728783
-16.86984516204
-0.586197663616276
-3.65875658596648
-47.7168811169054
5.75713700519138
-12.6426986145159
14.2909648643469
-10.3054160964647
13.7088308778022
-31.8091420679853
40.732918570457
-17.515245897683
-2.61849116994544
-7.46245913607824
-1.88121643904192
24.422384860429

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.535784830976831 \tabularnewline
1.76903397191346 \tabularnewline
5.14628252916545 \tabularnewline
9.4926520027237 \tabularnewline
48.0757459925896 \tabularnewline
-5.06528498901834 \tabularnewline
20.7584381496093 \tabularnewline
-26.5568571295093 \tabularnewline
-16.8988462953076 \tabularnewline
44.40130259583 \tabularnewline
-42.7178616086099 \tabularnewline
-7.60463439085142 \tabularnewline
24.714388118564 \tabularnewline
-30.8433190421496 \tabularnewline
-31.1643180664074 \tabularnewline
-32.4428235024559 \tabularnewline
-16.0439783388515 \tabularnewline
2.40363875144062 \tabularnewline
-32.5951123833247 \tabularnewline
-28.7937725346551 \tabularnewline
26.816413022255 \tabularnewline
-25.684958916906 \tabularnewline
25.9796570937098 \tabularnewline
-5.07605046066862 \tabularnewline
-65.1521496061982 \tabularnewline
-34.7982371860641 \tabularnewline
23.599690712917 \tabularnewline
5.70418788137112 \tabularnewline
-0.151767950147911 \tabularnewline
-0.290378094906347 \tabularnewline
-12.5624234913062 \tabularnewline
20.2266249680593 \tabularnewline
28.7044304771356 \tabularnewline
-3.20566227508572 \tabularnewline
4.39937534246934 \tabularnewline
-33.8742686637881 \tabularnewline
-18.7777379531313 \tabularnewline
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\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194639&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.535784830976831[/C][/ROW]
[ROW][C]1.76903397191346[/C][/ROW]
[ROW][C]5.14628252916545[/C][/ROW]
[ROW][C]9.4926520027237[/C][/ROW]
[ROW][C]48.0757459925896[/C][/ROW]
[ROW][C]-5.06528498901834[/C][/ROW]
[ROW][C]20.7584381496093[/C][/ROW]
[ROW][C]-26.5568571295093[/C][/ROW]
[ROW][C]-16.8988462953076[/C][/ROW]
[ROW][C]44.40130259583[/C][/ROW]
[ROW][C]-42.7178616086099[/C][/ROW]
[ROW][C]-7.60463439085142[/C][/ROW]
[ROW][C]24.714388118564[/C][/ROW]
[ROW][C]-30.8433190421496[/C][/ROW]
[ROW][C]-31.1643180664074[/C][/ROW]
[ROW][C]-32.4428235024559[/C][/ROW]
[ROW][C]-16.0439783388515[/C][/ROW]
[ROW][C]2.40363875144062[/C][/ROW]
[ROW][C]-32.5951123833247[/C][/ROW]
[ROW][C]-28.7937725346551[/C][/ROW]
[ROW][C]26.816413022255[/C][/ROW]
[ROW][C]-25.684958916906[/C][/ROW]
[ROW][C]25.9796570937098[/C][/ROW]
[ROW][C]-5.07605046066862[/C][/ROW]
[ROW][C]-65.1521496061982[/C][/ROW]
[ROW][C]-34.7982371860641[/C][/ROW]
[ROW][C]23.599690712917[/C][/ROW]
[ROW][C]5.70418788137112[/C][/ROW]
[ROW][C]-0.151767950147911[/C][/ROW]
[ROW][C]-0.290378094906347[/C][/ROW]
[ROW][C]-12.5624234913062[/C][/ROW]
[ROW][C]20.2266249680593[/C][/ROW]
[ROW][C]28.7044304771356[/C][/ROW]
[ROW][C]-3.20566227508572[/C][/ROW]
[ROW][C]4.39937534246934[/C][/ROW]
[ROW][C]-33.8742686637881[/C][/ROW]
[ROW][C]-18.7777379531313[/C][/ROW]
[ROW][C]-1.22402047698739[/C][/ROW]
[ROW][C]-1.72395529219807[/C][/ROW]
[ROW][C]24.539804126782[/C][/ROW]
[ROW][C]12.2257481791746[/C][/ROW]
[ROW][C]-18.2527616563548[/C][/ROW]
[ROW][C]2.89326438817624[/C][/ROW]
[ROW][C]26.7848754154271[/C][/ROW]
[ROW][C]-11.9243674402666[/C][/ROW]
[ROW][C]-10.9010323693039[/C][/ROW]
[ROW][C]-2.47663537377535[/C][/ROW]
[ROW][C]-5.02404132959319[/C][/ROW]
[ROW][C]3.63602627734319[/C][/ROW]
[ROW][C]-29.1234512918508[/C][/ROW]
[ROW][C]17.778833844422[/C][/ROW]
[ROW][C]30.7382194275226[/C][/ROW]
[ROW][C]-14.8383568473524[/C][/ROW]
[ROW][C]-18.6503909597798[/C][/ROW]
[ROW][C]0.145804337718408[/C][/ROW]
[ROW][C]17.3503595327912[/C][/ROW]
[ROW][C]21.661014884809[/C][/ROW]
[ROW][C]8.86165761246452[/C][/ROW]
[ROW][C]21.0871971049756[/C][/ROW]
[ROW][C]28.2567763536581[/C][/ROW]
[ROW][C]50.7247607296956[/C][/ROW]
[ROW][C]19.6870387851375[/C][/ROW]
[ROW][C]9.31026526815972[/C][/ROW]
[ROW][C]-8.58112938200254[/C][/ROW]
[ROW][C]-10.405620201571[/C][/ROW]
[ROW][C]-27.2704222289155[/C][/ROW]
[ROW][C]3.28595724388374[/C][/ROW]
[ROW][C]14.0389278869765[/C][/ROW]
[ROW][C]1.89952483454334[/C][/ROW]
[ROW][C]-36.2758718335084[/C][/ROW]
[ROW][C]-0.55960945834314[/C][/ROW]
[ROW][C]-9.79499591585763[/C][/ROW]
[ROW][C]-4.37692306685266[/C][/ROW]
[ROW][C]-17.7030834036084[/C][/ROW]
[ROW][C]-6.60867563703818[/C][/ROW]
[ROW][C]14.8051720376241[/C][/ROW]
[ROW][C]-27.9044534130267[/C][/ROW]
[ROW][C]1.56528234357327[/C][/ROW]
[ROW][C]-16.0249763735606[/C][/ROW]
[ROW][C]16.4239315941089[/C][/ROW]
[ROW][C]-11.5878786835515[/C][/ROW]
[ROW][C]18.0459864645769[/C][/ROW]
[ROW][C]2.69788310540313[/C][/ROW]
[ROW][C]-3.59338082189156[/C][/ROW]
[ROW][C]-29.567532249738[/C][/ROW]
[ROW][C]-3.14406117948626[/C][/ROW]
[ROW][C]25.2046569288462[/C][/ROW]
[ROW][C]-20.3477913443421[/C][/ROW]
[ROW][C]32.9065928510913[/C][/ROW]
[ROW][C]18.7488484497254[/C][/ROW]
[ROW][C]-24.4104892633646[/C][/ROW]
[ROW][C]-32.6048832536814[/C][/ROW]
[ROW][C]-3.61178732053284[/C][/ROW]
[ROW][C]12.0439965759627[/C][/ROW]
[ROW][C]29.3551015047632[/C][/ROW]
[ROW][C]-2.72090261418846[/C][/ROW]
[ROW][C]-19.2438099413364[/C][/ROW]
[ROW][C]-16.8799372230402[/C][/ROW]
[ROW][C]-7.66028528526407[/C][/ROW]
[ROW][C]10.3942325211243[/C][/ROW]
[ROW][C]21.47535867844[/C][/ROW]
[ROW][C]21.6114008831411[/C][/ROW]
[ROW][C]-25.8554797710933[/C][/ROW]
[ROW][C]-6.34672786572312[/C][/ROW]
[ROW][C]14.6502264137583[/C][/ROW]
[ROW][C]14.7866001601947[/C][/ROW]
[ROW][C]30.6062985152381[/C][/ROW]
[ROW][C]6.94023464218742[/C][/ROW]
[ROW][C]40.4509362338861[/C][/ROW]
[ROW][C]53.4787344606328[/C][/ROW]
[ROW][C]-1.78205621572222[/C][/ROW]
[ROW][C]-3.67951362007862[/C][/ROW]
[ROW][C]-19.0815509231999[/C][/ROW]
[ROW][C]5.02229114364384[/C][/ROW]
[ROW][C]5.97739598780304[/C][/ROW]
[ROW][C]-19.7534101636705[/C][/ROW]
[ROW][C]-43.2839411583197[/C][/ROW]
[ROW][C]-5.31879784721217[/C][/ROW]
[ROW][C]-25.452995412496[/C][/ROW]
[ROW][C]28.2020581462457[/C][/ROW]
[ROW][C]-7.35727838508619[/C][/ROW]
[ROW][C]-17.7582030977024[/C][/ROW]
[ROW][C]-23.2668327028022[/C][/ROW]
[ROW][C]-46.8985450870398[/C][/ROW]
[ROW][C]4.60337282519803[/C][/ROW]
[ROW][C]24.4938073979864[/C][/ROW]
[ROW][C]-0.0894167220781985[/C][/ROW]
[ROW][C]8.20648203102952[/C][/ROW]
[ROW][C]5.12216480712498[/C][/ROW]
[ROW][C]18.5702197491549[/C][/ROW]
[ROW][C]2.30587714765411[/C][/ROW]
[ROW][C]-32.9871627068673[/C][/ROW]
[ROW][C]-12.5892512083707[/C][/ROW]
[ROW][C]-31.6654165962767[/C][/ROW]
[ROW][C]54.5593575376825[/C][/ROW]
[ROW][C]-18.9454763996064[/C][/ROW]
[ROW][C]-14.0400568812147[/C][/ROW]
[ROW][C]47.1473333063379[/C][/ROW]
[ROW][C]-16.5698046677318[/C][/ROW]
[ROW][C]8.94781236584361[/C][/ROW]
[ROW][C]-16.4609937150212[/C][/ROW]
[ROW][C]33.8648377086654[/C][/ROW]
[ROW][C]9.20038726761918[/C][/ROW]
[ROW][C]31.128962417314[/C][/ROW]
[ROW][C]9.01529322664593[/C][/ROW]
[ROW][C]14.5687893767886[/C][/ROW]
[ROW][C]-23.6105418878432[/C][/ROW]
[ROW][C]-15.5372206288923[/C][/ROW]
[ROW][C]2.54721910487765[/C][/ROW]
[ROW][C]17.4907170651471[/C][/ROW]
[ROW][C]-16.7186104541045[/C][/ROW]
[ROW][C]-24.2798602966992[/C][/ROW]
[ROW][C]-7.24693152325897[/C][/ROW]
[ROW][C]-6.97498058127626[/C][/ROW]
[ROW][C]-23.0880477901024[/C][/ROW]
[ROW][C]-1.02824871829531[/C][/ROW]
[ROW][C]-7.1104874880454[/C][/ROW]
[ROW][C]-19.7532631526219[/C][/ROW]
[ROW][C]-0.0748883998965978[/C][/ROW]
[ROW][C]7.2738901275672[/C][/ROW]
[ROW][C]30.3974478316699[/C][/ROW]
[ROW][C]-33.3476523387737[/C][/ROW]
[ROW][C]-17.3800821499326[/C][/ROW]
[ROW][C]44.7726767704997[/C][/ROW]
[ROW][C]-8.80525878988357[/C][/ROW]
[ROW][C]-25.2655605027819[/C][/ROW]
[ROW][C]24.1784712813431[/C][/ROW]
[ROW][C]-13.7923839678723[/C][/ROW]
[ROW][C]13.7297547645765[/C][/ROW]
[ROW][C]20.5006351245874[/C][/ROW]
[ROW][C]-37.6508806868545[/C][/ROW]
[ROW][C]1.64465281368277[/C][/ROW]
[ROW][C]15.1939533469807[/C][/ROW]
[ROW][C]10.0938344111377[/C][/ROW]
[ROW][C]-15.6373793710177[/C][/ROW]
[ROW][C]-13.4181636071579[/C][/ROW]
[ROW][C]10.1268173034072[/C][/ROW]
[ROW][C]4.82628047691192[/C][/ROW]
[ROW][C]11.8459605297286[/C][/ROW]
[ROW][C]-23.4412367927873[/C][/ROW]
[ROW][C]-1.06481124813955[/C][/ROW]
[ROW][C]-9.32672496432393[/C][/ROW]
[ROW][C]-1.08399438187233[/C][/ROW]
[ROW][C]10.8874757144825[/C][/ROW]
[ROW][C]-21.9468469623101[/C][/ROW]
[ROW][C]43.6235103443176[/C][/ROW]
[ROW][C]-45.0012271521586[/C][/ROW]
[ROW][C]10.7284056776388[/C][/ROW]
[ROW][C]12.7974666199096[/C][/ROW]
[ROW][C]-0.130451956435516[/C][/ROW]
[ROW][C]-27.3045708898671[/C][/ROW]
[ROW][C]4.12396240377367[/C][/ROW]
[ROW][C]-15.2500150024029[/C][/ROW]
[ROW][C]19.4598642561244[/C][/ROW]
[ROW][C]-21.4119586842466[/C][/ROW]
[ROW][C]22.8614865314854[/C][/ROW]
[ROW][C]-11.1308182284788[/C][/ROW]
[ROW][C]18.1385240484527[/C][/ROW]
[ROW][C]-16.6410192586275[/C][/ROW]
[ROW][C]-5.1921326888724[/C][/ROW]
[ROW][C]3.6192051546009[/C][/ROW]
[ROW][C]-3.51670900929658[/C][/ROW]
[ROW][C]-12.9163478768749[/C][/ROW]
[ROW][C]-13.898663044252[/C][/ROW]
[ROW][C]-17.470889464474[/C][/ROW]
[ROW][C]-15.9921245422155[/C][/ROW]
[ROW][C]26.4551794823846[/C][/ROW]
[ROW][C]14.8901898508295[/C][/ROW]
[ROW][C]19.3873080845169[/C][/ROW]
[ROW][C]3.0276875801971[/C][/ROW]
[ROW][C]-8.73934423798327[/C][/ROW]
[ROW][C]-1.12049363686786[/C][/ROW]
[ROW][C]-0.117355769955134[/C][/ROW]
[ROW][C]6.04001412227224[/C][/ROW]
[ROW][C]-15.7537444219845[/C][/ROW]
[ROW][C]6.64251571357321[/C][/ROW]
[ROW][C]-9.09564937093057[/C][/ROW]
[ROW][C]-1.96304269635448[/C][/ROW]
[ROW][C]6.43794300337987[/C][/ROW]
[ROW][C]4.25793207529969[/C][/ROW]
[ROW][C]-9.02835777049555[/C][/ROW]
[ROW][C]42.8760019769903[/C][/ROW]
[ROW][C]12.1252464661439[/C][/ROW]
[ROW][C]-19.5294307332982[/C][/ROW]
[ROW][C]23.9583301332121[/C][/ROW]
[ROW][C]12.3156680601464[/C][/ROW]
[ROW][C]-35.1272701295165[/C][/ROW]
[ROW][C]-21.2696664499641[/C][/ROW]
[ROW][C]-12.0628842667418[/C][/ROW]
[ROW][C]26.8579776602081[/C][/ROW]
[ROW][C]-8.89306793400264[/C][/ROW]
[ROW][C]-15.2686500325446[/C][/ROW]
[ROW][C]-0.749959796783489[/C][/ROW]
[ROW][C]48.7711015832542[/C][/ROW]
[ROW][C]5.04418415655933[/C][/ROW]
[ROW][C]-31.2546807807804[/C][/ROW]
[ROW][C]8.13922853636404[/C][/ROW]
[ROW][C]-1.76178329827789[/C][/ROW]
[ROW][C]-8.40063167145589[/C][/ROW]
[ROW][C]-11.3759090892664[/C][/ROW]
[ROW][C]-1.23156783161761[/C][/ROW]
[ROW][C]1.20422363840203[/C][/ROW]
[ROW][C]11.1883200911636[/C][/ROW]
[ROW][C]13.4407481778698[/C][/ROW]
[ROW][C]-13.053831000849[/C][/ROW]
[ROW][C]6.24340715431676[/C][/ROW]
[ROW][C]26.3225338647497[/C][/ROW]
[ROW][C]-5.70089842173531[/C][/ROW]
[ROW][C]23.4176610078893[/C][/ROW]
[ROW][C]-10.7875527764369[/C][/ROW]
[ROW][C]-29.6493947900414[/C][/ROW]
[ROW][C]3.63544392151567[/C][/ROW]
[ROW][C]35.7096773086633[/C][/ROW]
[ROW][C]27.0722935321706[/C][/ROW]
[ROW][C]7.74179440797446[/C][/ROW]
[ROW][C]3.30655551028347[/C][/ROW]
[ROW][C]-5.30560189250141[/C][/ROW]
[ROW][C]19.8293487230023[/C][/ROW]
[ROW][C]19.4895777363157[/C][/ROW]
[ROW][C]-5.66462879132965[/C][/ROW]
[ROW][C]13.7111366726853[/C][/ROW]
[ROW][C]0.432176552483553[/C][/ROW]
[ROW][C]25.6187628001013[/C][/ROW]
[ROW][C]5.8070263083149[/C][/ROW]
[ROW][C]12.9268532652652[/C][/ROW]
[ROW][C]-18.8094612520058[/C][/ROW]
[ROW][C]-10.6617626985004[/C][/ROW]
[ROW][C]-16.843976144291[/C][/ROW]
[ROW][C]-7.19959128575644[/C][/ROW]
[ROW][C]4.59881898650176[/C][/ROW]
[ROW][C]18.4753306910867[/C][/ROW]
[ROW][C]2.75714357643068[/C][/ROW]
[ROW][C]-20.8493504299649[/C][/ROW]
[ROW][C]-19.2612052501417[/C][/ROW]
[ROW][C]20.5709226920974[/C][/ROW]
[ROW][C]-3.71716444529074[/C][/ROW]
[ROW][C]9.34079932886775[/C][/ROW]
[ROW][C]-17.6920487272172[/C][/ROW]
[ROW][C]0.282780700131674[/C][/ROW]
[ROW][C]-15.6000550654091[/C][/ROW]
[ROW][C]-11.5268418992641[/C][/ROW]
[ROW][C]2.45322208522521[/C][/ROW]
[ROW][C]4.71093551425211[/C][/ROW]
[ROW][C]-0.747657464536695[/C][/ROW]
[ROW][C]-10.8720240914714[/C][/ROW]
[ROW][C]-5.15363348308538[/C][/ROW]
[ROW][C]-33.1092733909457[/C][/ROW]
[ROW][C]-1.88675374395731[/C][/ROW]
[ROW][C]-1.69643563100753[/C][/ROW]
[ROW][C]12.1289352281836[/C][/ROW]
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[ROW][C]4.42844002747247[/C][/ROW]
[ROW][C]-9.4063050320154[/C][/ROW]
[ROW][C]-5.85987916793011[/C][/ROW]
[ROW][C]-0.942332891197308[/C][/ROW]
[ROW][C]-1.90340972792835[/C][/ROW]
[ROW][C]10.3294439910607[/C][/ROW]
[ROW][C]-25.5527503267159[/C][/ROW]
[ROW][C]23.487923176158[/C][/ROW]
[ROW][C]12.4579953817512[/C][/ROW]
[ROW][C]23.1729726508223[/C][/ROW]
[ROW][C]-3.03145701760198[/C][/ROW]
[ROW][C]-22.2223306581653[/C][/ROW]
[ROW][C]-5.88322409353115[/C][/ROW]
[ROW][C]18.4007181993601[/C][/ROW]
[ROW][C]14.2110504118804[/C][/ROW]
[ROW][C]8.92875457423253[/C][/ROW]
[ROW][C]-11.6405367523245[/C][/ROW]
[ROW][C]40.2495539579375[/C][/ROW]
[ROW][C]1.74539419383237[/C][/ROW]
[ROW][C]41.930368637512[/C][/ROW]
[ROW][C]40.4142332127378[/C][/ROW]
[ROW][C]115.312864561629[/C][/ROW]
[ROW][C]-28.912923615866[/C][/ROW]
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[ROW][C]-19.0273754382756[/C][/ROW]
[ROW][C]0.562758768508315[/C][/ROW]
[ROW][C]-15.6102413328833[/C][/ROW]
[ROW][C]-12.4343120383412[/C][/ROW]
[ROW][C]-11.877679591556[/C][/ROW]
[ROW][C]-12.5002435978047[/C][/ROW]
[ROW][C]0.844933570602423[/C][/ROW]
[ROW][C]-22.5899116468759[/C][/ROW]
[ROW][C]-4.91822524169806[/C][/ROW]
[ROW][C]-4.13095371917262[/C][/ROW]
[ROW][C]-21.8240050297471[/C][/ROW]
[ROW][C]-23.8100331572438[/C][/ROW]
[ROW][C]-8.95917808502537[/C][/ROW]
[ROW][C]-24.6994337769713[/C][/ROW]
[ROW][C]35.8657236279948[/C][/ROW]
[ROW][C]22.4770304336743[/C][/ROW]
[ROW][C]4.03655965147121[/C][/ROW]
[ROW][C]-34.0667326801478[/C][/ROW]
[ROW][C]4.29015384806397[/C][/ROW]
[ROW][C]10.4161002183014[/C][/ROW]
[ROW][C]-15.4465226108543[/C][/ROW]
[ROW][C]-31.1435878547975[/C][/ROW]
[ROW][C]28.8663626153941[/C][/ROW]
[ROW][C]-23.8712271992953[/C][/ROW]
[ROW][C]-49.9583288911025[/C][/ROW]
[ROW][C]4.78041795064893[/C][/ROW]
[ROW][C]28.6551580829978[/C][/ROW]
[ROW][C]-29.5952751669598[/C][/ROW]
[ROW][C]17.8411657728783[/C][/ROW]
[ROW][C]-16.86984516204[/C][/ROW]
[ROW][C]-0.586197663616276[/C][/ROW]
[ROW][C]-3.65875658596648[/C][/ROW]
[ROW][C]-47.7168811169054[/C][/ROW]
[ROW][C]5.75713700519138[/C][/ROW]
[ROW][C]-12.6426986145159[/C][/ROW]
[ROW][C]14.2909648643469[/C][/ROW]
[ROW][C]-10.3054160964647[/C][/ROW]
[ROW][C]13.7088308778022[/C][/ROW]
[ROW][C]-31.8091420679853[/C][/ROW]
[ROW][C]40.732918570457[/C][/ROW]
[ROW][C]-17.515245897683[/C][/ROW]
[ROW][C]-2.61849116994544[/C][/ROW]
[ROW][C]-7.46245913607824[/C][/ROW]
[ROW][C]-1.88121643904192[/C][/ROW]
[ROW][C]24.422384860429[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194639&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194639&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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1.76903397191346
5.14628252916545
9.4926520027237
48.0757459925896
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24.714388118564
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2.40363875144062
-32.5951123833247
-28.7937725346551
26.816413022255
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25.9796570937098
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23.599690712917
5.70418788137112
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20.2266249680593
28.7044304771356
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4.39937534246934
-33.8742686637881
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-1.22402047698739
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24.539804126782
12.2257481791746
-18.2527616563548
2.89326438817624
26.7848754154271
-11.9243674402666
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3.63602627734319
-29.1234512918508
17.778833844422
30.7382194275226
-14.8383568473524
-18.6503909597798
0.145804337718408
17.3503595327912
21.661014884809
8.86165761246452
21.0871971049756
28.2567763536581
50.7247607296956
19.6870387851375
9.31026526815972
-8.58112938200254
-10.405620201571
-27.2704222289155
3.28595724388374
14.0389278869765
1.89952483454334
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2.69788310540313
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25.2046569288462
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18.5702197491549
2.30587714765411
-32.9871627068673
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54.5593575376825
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-16.5698046677318
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33.8648377086654
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31.128962417314
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14.5687893767886
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-8.80525878988357
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24.1784712813431
-13.7923839678723
13.7297547645765
20.5006351245874
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1.64465281368277
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10.0938344111377
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10.1268173034072
4.82628047691192
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10.7284056776388
12.7974666199096
-0.130451956435516
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19.4598642561244
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22.8614865314854
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3.6192051546009
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26.4551794823846
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6.24340715431676
26.3225338647497
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23.4176610078893
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3.63544392151567
35.7096773086633
27.0722935321706
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3.30655551028347
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19.8293487230023
19.4895777363157
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0.432176552483553
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12.9268532652652
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4.59881898650176
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2.75714357643068
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20.5709226920974
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9.34079932886775
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0.282780700131674
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2.45322208522521
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40.732918570457
-17.515245897683
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-7.46245913607824
-1.88121643904192
24.422384860429

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Postscript link

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Figure 5

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Figure 6

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Figure 7

PNG link

Postscript link

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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 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 0 ; par8 = 1 ; 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