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Author

*The author of this computation has been verified*

R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Mon, 08 Dec 2008 15:38:06 -0700

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/2008/Dec/08/t122877593921rgvu5619qmhr8.htm/, Retrieved Thu, 16 May 2024 12:05:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31105, Retrieved Thu, 16 May 2024 12:05:51 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

209

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

-     [Spectral Analysis] [Unemployment - St...] [2008-12-08 17:28:52] [57850c80fd59ccfb28f882be994e814e]
F RMP   [ARIMA Backward Selection] [Unemployment - St...] [2008-12-08 18:25:12] [57850c80fd59ccfb28f882be994e814e]
F         [ARIMA Backward Selection] [Step 5] [2008-12-08 21:03:53] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
F   PD        [ARIMA Backward Selection] [step 5] [2008-12-08 22:38:06] [e4cb5a8878d0401c2e8d19a1768b515b] [Current]
F   P           [ARIMA Backward Selection] [Step 5] [2008-12-08 23:15:27] [6816386b1f3c2f6c0c9f2aa1e5bc9362] 
-                 [ARIMA Backward Selection] [step 5] [2008-12-08 23:45:15] [73d6180dc45497329efd1b6934a84aba] 
F                 [ARIMA Backward Selection] [] [2008-12-09 00:23:28] [74be16979710d4c4e7c6647856088456] 
-   P           [ARIMA Backward Selection] [Verbetering works...] [2008-12-15 10:37:49] [cf9c64468d04c2c4dd548cc66b4e3677] 

Feedback Forum

2008-12-15 10:42:44 [Jan Van Riet] [reply] 
Doordat ik in vraag 4 de verkeerde orde van mijn AR-proces heb afgeleid, moet ik dit nog aanpassen in m'n laatste antwoord: 
 
http://www.freestatistics.org/blog/index.php?v=date/2008/Dec/15/t122933753645wxt9ejfmsxefi.htm 
 
Ook was de lambda-waarde nog ingesteld op 0,5 ipv 0,4.  
Het resultaat is een verwacht AR(2)-proces evenals een onverwacht seizonaal MA 1-proces.  
Aan de assumpties wordt ook voldaan; er is geen autocorrelatie, en de verdeling is recht.

Post a new message

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	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31105&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31105&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31105&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	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	sma1
Estimates ( 1 )	0.0938	0.235	0.0655	-0.7207
(p-val)	(0.0776 )	(0 )	(0.2165 )	(0 )
Estimates ( 2 )	0.1094	0.2417	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(0 )
Estimates ( 3 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 4 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & sma1 \tabularnewline
Estimates ( 1 ) & 0.0938 & 0.235 & 0.0655 & -0.7207 \tabularnewline
(p-val) & (0.0776 ) & (0 ) & (0.2165 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.1094 & 0.2417 & 0 & -0.724 \tabularnewline
(p-val) & (0.0348 ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 3 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31105&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]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]0.0938[/C][C]0.235[/C][C]0.0655[/C][C]-0.7207[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0776 )[/C][C](0 )[/C][C](0.2165 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.1094[/C][C]0.2417[/C][C]0[/C][C]-0.724[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0348 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/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][/ROW]
[ROW][C]Estimates ( 4 )[/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][/ROW]
[ROW][C]Estimates ( 5 )[/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][/ROW]
[ROW][C]Estimates ( 6 )[/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][/ROW]
[ROW][C]Estimates ( 7 )[/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][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31105&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31105&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	sma1
Estimates ( 1 )	0.0938	0.235	0.0655	-0.7207
(p-val)	(0.0776 )	(0 )	(0.2165 )	(0 )
Estimates ( 2 )	0.1094	0.2417	0	-0.724
(p-val)	(0.0348 )	(0 )	(NA )	(0 )
Estimates ( 3 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 4 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.0447137390272567
-0.0687784008980725
0.200065259604162
0.369647192697172
1.52302500804669
-0.382351653825391
0.442484703616506
-0.548687740049578
-0.326732336781395
1.30468453848548
-1.35000107765406
-0.389439577471342
0.182876612030267
-0.827658536279032
-0.57120158498098
-0.72777390338725
-0.408617479927003
-0.0704110713086128
-0.812914050800825
-0.878889027747955
0.68988797338111
-0.73070568425279
0.835147695365076
-0.138185215483514
-1.62611469562507
-1.10034403406178
0.456775968063903
0.0327483761250721
0.101996608243826
0.314319634672247
-0.280298441689737
0.30046002827176
0.86492645904486
0.113436639546888
0.0734396482850683
-1.19438957705465
-0.151861124505455
-0.0210495617341295
-0.34332989640696
0.574182228476322
0.47781168712296
-0.345527950474858
0.0869630771866805
0.590525901473323
-0.490004401466136
-0.422661783131678
-0.095037722338622
-0.100980271807732
0.509364889254326
-1.00698399488026
0.328831448342701
0.86339135455198
-0.476125702549517
-0.442129103993584
-0.0557913094619822
0.32725411045344
0.866296661809851
0.446073571144705
0.800999913477185
0.913382349953513
1.21106609296917
0.432278106208988
0.307403813088903
-0.163323144511499
-0.171054709131086
-1.03961068497591
0.0264129123770215
0.59097046455602
0.0976671927320991
-0.913730175077028
-0.330723544596436
-0.391958183079887
-0.335951957286511
-0.46037649165173
-0.0292549877889282
0.496162672370802
-0.733630308565248
-0.0817164970074697
-0.515670155733217
0.57890832473816
-0.35332857694994
0.636524322986328
0.0383883349847803
-0.0571793866673809
-0.85826514961422
-0.0909880068317557
0.755511697912875
-0.51865221542344
0.994495178416067
0.406663354524112
-0.616393390496254
-0.995855439583286
-0.203821482872209
0.285779412803567
0.992846605314575
-0.0326424009931274
-0.572122960882824
-0.552544804398143
-0.240243505055926
0.322411020680407
0.630309714287468
0.601433684871232
-0.733286458582107
-0.160045382026631
0.395986068639077
0.525885325501417
0.819051451339774
0.175416332710445
0.722308994179288
1.20239730786413
0.181073064953674
0.0276823997368094
-0.448685381060263
-0.252679590698609
0.188302912601137
-0.140217353547074
-1.04008080365458
-0.165181657145492
-0.938101045772961
0.684173307480327
-0.420129106509927
-0.354905310310897
-0.440209108638009
-1.11887600530722
0.0686415999073764
0.616719548072293
0.0574399814483076
0.267702851983427
0.130909091877193
0.588946602843224
0.00572821805640984
-0.884968902855682
-0.428896750123102
-0.717442098706048
1.42772367814757
-0.361535509724408
-0.321236121612646
1.06722741780056
-0.332902829131289
0.267556896218221
-0.55880200903484
0.942245288670044
0.107677379285031
0.814030747649796
-0.0649701394647751
0.345685645970771
-0.473259980240578
-0.240984461636316
0.0553124598061947
0.177989891077107
-0.284191159038638
-0.425389537570375
-0.207809875835799
-0.175666895148093
-0.705544296979916
-0.0650409438581232
-0.234296610330386
-0.418031505154584
0.0635319560152546
0.132841999709956
0.794189538843223
-0.7337825046774
-0.499459632308561
1.08239302960889
-0.195667967064271
-0.575471603112938
0.55533892801943
-0.271929833587416
0.319593878143402
0.481050892726717
-0.81262191504133
-0.0584254773387107
0.319299220357209
0.340160416654446
-0.380473371484065
-0.388107553150321
0.168516166415319
0.196617445048809
0.265968973922322
-0.564468306945424
-0.0741083392346166
-0.245462630950218
-0.000631084613962726
0.213691874846621
-0.514626313062927
1.10591401094891
-1.14042582586266
0.295888384696412
0.192715845850636
0.0823052468056668
-0.731740373439665
0.099313414196176
-0.291267008405325
0.526798164724809
-0.626285429902881
0.508878352127627
-0.280281532475886
0.627929054317186
-0.540421396396689
-0.193911734738479
-0.0379837419594666
-0.0737632003622048
-0.242637536040275
-0.430619069974224
-0.266577768990055
-0.450848922870321
0.543204146382887
0.292434553671412
0.629959973756787
0.386021086298326
-0.464129624339823
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0.206778799682832
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-0.086814134477421
-0.00924476179476522
-0.0350279845112993
0.0295208739753532
-0.325458295354019
1.52876820660533
0.227697703378292
-0.575535865934898
0.594320596432332
0.375156083591140
-0.979806834718508
-0.738194594728149
-0.295606192519384
0.782268464749814
-0.284793330811666
-0.508090380025296
-0.101172002600055
1.69597572967343
0.0868254998646056
-0.935435964818216
0.0840245624186819
-0.064380409581959
-0.198880029327971
-0.384722598443245
0.0966843258728106
0.0394743019059452
0.241745681581251
0.371825326144601
-0.398581545902409
0.453542387343188
0.616055175842729
-0.182235632142905
0.70512712019379
-0.285631941024027
-0.9407452069579
-0.0149575246137639
1.03118034037152
0.812710396364028
0.24312672825514
0.127521646711908
-0.118771837966749
0.201558931649108
0.562828099025611
0.0391841699436770
0.360470874031593
0.00772979598552257
0.520054703402974
0.139321233535653
-0.101107243533491
-0.484393526572003
-0.0577528588483668
-0.217551597587264
-0.118844640687450
-0.403656468261592
0.601785878398861
0.320909681401839
-0.378818152869663
-0.500307852316455
0.315582161181543
-0.0462229563273987
-0.00959737167965635
-0.380509231692807
0.161104962267398
-0.215811218013589
-0.231483118654409
-0.287379903858895
0.264764817483933
0.147436824887513
-0.172259332509254
-0.141334578297495
-0.845249406280006
-0.0711678520288063
-0.0997721099342033
0.312583567203097
-0.184889861583018
0.142211411663771
-0.258926888074305
-0.183942617118415
0.0508119518066803
-0.00280358323315295
0.264521921089744
-0.669527014401922
0.59826452275097
0.315601661797499
0.542032989812912
-0.123599993100018
-0.455766781433172
-0.180826877070865
0.423549519608619
0.194696921935535
0.318093031698897
-0.167334221596811
0.88262114717252
0.0779760734987962
0.822930203441135
0.820785154310528
1.77156462928895
-0.5575984685242
0.184478454204415
-0.192692525521358
0.102325645378361
-1.12766260306145
-0.0361673755495256
0.110557679549491
-0.216041049313559
0.0312638997882393
-0.555203488862734
-0.105294958193306
-0.417647715779018
-0.363087406058837
-0.259927536476961
-0.0304015841763502
-0.425425471837619
0.278580107524609
0.570197986957242
0.317952341768077
-0.606007798318431
0.0543314453825707
0.133601264480095
-0.213626415828529
-0.677702580457283
0.454034649408554
-0.267529750400614
-0.842081978996457
0.0427521089252451
0.274539655374324
-0.425883109546494
0.41478388809867
-0.32293610892551
0.00915568168050528
-0.135962115754885
-0.916593602248472
0.147519810357598
-0.278727304282181
0.297054787742795
-0.249412013011796
0.281148357175223
-0.633174844558302
0.839474076687053
-0.335291480552041
-0.0537311851693173
-0.226993759667176
0.000315636943853517
0.516501275737427

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0447137390272567 \tabularnewline
-0.0687784008980725 \tabularnewline
0.200065259604162 \tabularnewline
0.369647192697172 \tabularnewline
1.52302500804669 \tabularnewline
-0.382351653825391 \tabularnewline
0.442484703616506 \tabularnewline
-0.548687740049578 \tabularnewline
-0.326732336781395 \tabularnewline
1.30468453848548 \tabularnewline
-1.35000107765406 \tabularnewline
-0.389439577471342 \tabularnewline
0.182876612030267 \tabularnewline
-0.827658536279032 \tabularnewline
-0.57120158498098 \tabularnewline
-0.72777390338725 \tabularnewline
-0.408617479927003 \tabularnewline
-0.0704110713086128 \tabularnewline
-0.812914050800825 \tabularnewline
-0.878889027747955 \tabularnewline
0.68988797338111 \tabularnewline
-0.73070568425279 \tabularnewline
0.835147695365076 \tabularnewline
-0.138185215483514 \tabularnewline
-1.62611469562507 \tabularnewline
-1.10034403406178 \tabularnewline
0.456775968063903 \tabularnewline
0.0327483761250721 \tabularnewline
0.101996608243826 \tabularnewline
0.314319634672247 \tabularnewline
-0.280298441689737 \tabularnewline
0.30046002827176 \tabularnewline
0.86492645904486 \tabularnewline
0.113436639546888 \tabularnewline
0.0734396482850683 \tabularnewline
-1.19438957705465 \tabularnewline
-0.151861124505455 \tabularnewline
-0.0210495617341295 \tabularnewline
-0.34332989640696 \tabularnewline
0.574182228476322 \tabularnewline
0.47781168712296 \tabularnewline
-0.345527950474858 \tabularnewline
0.0869630771866805 \tabularnewline
0.590525901473323 \tabularnewline
-0.490004401466136 \tabularnewline
-0.422661783131678 \tabularnewline
-0.095037722338622 \tabularnewline
-0.100980271807732 \tabularnewline
0.509364889254326 \tabularnewline
-1.00698399488026 \tabularnewline
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\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31105&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0447137390272567[/C][/ROW]
[ROW][C]-0.0687784008980725[/C][/ROW]
[ROW][C]0.200065259604162[/C][/ROW]
[ROW][C]0.369647192697172[/C][/ROW]
[ROW][C]1.52302500804669[/C][/ROW]
[ROW][C]-0.382351653825391[/C][/ROW]
[ROW][C]0.442484703616506[/C][/ROW]
[ROW][C]-0.548687740049578[/C][/ROW]
[ROW][C]-0.326732336781395[/C][/ROW]
[ROW][C]1.30468453848548[/C][/ROW]
[ROW][C]-1.35000107765406[/C][/ROW]
[ROW][C]-0.389439577471342[/C][/ROW]
[ROW][C]0.182876612030267[/C][/ROW]
[ROW][C]-0.827658536279032[/C][/ROW]
[ROW][C]-0.57120158498098[/C][/ROW]
[ROW][C]-0.72777390338725[/C][/ROW]
[ROW][C]-0.408617479927003[/C][/ROW]
[ROW][C]-0.0704110713086128[/C][/ROW]
[ROW][C]-0.812914050800825[/C][/ROW]
[ROW][C]-0.878889027747955[/C][/ROW]
[ROW][C]0.68988797338111[/C][/ROW]
[ROW][C]-0.73070568425279[/C][/ROW]
[ROW][C]0.835147695365076[/C][/ROW]
[ROW][C]-0.138185215483514[/C][/ROW]
[ROW][C]-1.62611469562507[/C][/ROW]
[ROW][C]-1.10034403406178[/C][/ROW]
[ROW][C]0.456775968063903[/C][/ROW]
[ROW][C]0.0327483761250721[/C][/ROW]
[ROW][C]0.101996608243826[/C][/ROW]
[ROW][C]0.314319634672247[/C][/ROW]
[ROW][C]-0.280298441689737[/C][/ROW]
[ROW][C]0.30046002827176[/C][/ROW]
[ROW][C]0.86492645904486[/C][/ROW]
[ROW][C]0.113436639546888[/C][/ROW]
[ROW][C]0.0734396482850683[/C][/ROW]
[ROW][C]-1.19438957705465[/C][/ROW]
[ROW][C]-0.151861124505455[/C][/ROW]
[ROW][C]-0.0210495617341295[/C][/ROW]
[ROW][C]-0.34332989640696[/C][/ROW]
[ROW][C]0.574182228476322[/C][/ROW]
[ROW][C]0.47781168712296[/C][/ROW]
[ROW][C]-0.345527950474858[/C][/ROW]
[ROW][C]0.0869630771866805[/C][/ROW]
[ROW][C]0.590525901473323[/C][/ROW]
[ROW][C]-0.490004401466136[/C][/ROW]
[ROW][C]-0.422661783131678[/C][/ROW]
[ROW][C]-0.095037722338622[/C][/ROW]
[ROW][C]-0.100980271807732[/C][/ROW]
[ROW][C]0.509364889254326[/C][/ROW]
[ROW][C]-1.00698399488026[/C][/ROW]
[ROW][C]0.328831448342701[/C][/ROW]
[ROW][C]0.86339135455198[/C][/ROW]
[ROW][C]-0.476125702549517[/C][/ROW]
[ROW][C]-0.442129103993584[/C][/ROW]
[ROW][C]-0.0557913094619822[/C][/ROW]
[ROW][C]0.32725411045344[/C][/ROW]
[ROW][C]0.866296661809851[/C][/ROW]
[ROW][C]0.446073571144705[/C][/ROW]
[ROW][C]0.800999913477185[/C][/ROW]
[ROW][C]0.913382349953513[/C][/ROW]
[ROW][C]1.21106609296917[/C][/ROW]
[ROW][C]0.432278106208988[/C][/ROW]
[ROW][C]0.307403813088903[/C][/ROW]
[ROW][C]-0.163323144511499[/C][/ROW]
[ROW][C]-0.171054709131086[/C][/ROW]
[ROW][C]-1.03961068497591[/C][/ROW]
[ROW][C]0.0264129123770215[/C][/ROW]
[ROW][C]0.59097046455602[/C][/ROW]
[ROW][C]0.0976671927320991[/C][/ROW]
[ROW][C]-0.913730175077028[/C][/ROW]
[ROW][C]-0.330723544596436[/C][/ROW]
[ROW][C]-0.391958183079887[/C][/ROW]
[ROW][C]-0.335951957286511[/C][/ROW]
[ROW][C]-0.46037649165173[/C][/ROW]
[ROW][C]-0.0292549877889282[/C][/ROW]
[ROW][C]0.496162672370802[/C][/ROW]
[ROW][C]-0.733630308565248[/C][/ROW]
[ROW][C]-0.0817164970074697[/C][/ROW]
[ROW][C]-0.515670155733217[/C][/ROW]
[ROW][C]0.57890832473816[/C][/ROW]
[ROW][C]-0.35332857694994[/C][/ROW]
[ROW][C]0.636524322986328[/C][/ROW]
[ROW][C]0.0383883349847803[/C][/ROW]
[ROW][C]-0.0571793866673809[/C][/ROW]
[ROW][C]-0.85826514961422[/C][/ROW]
[ROW][C]-0.0909880068317557[/C][/ROW]
[ROW][C]0.755511697912875[/C][/ROW]
[ROW][C]-0.51865221542344[/C][/ROW]
[ROW][C]0.994495178416067[/C][/ROW]
[ROW][C]0.406663354524112[/C][/ROW]
[ROW][C]-0.616393390496254[/C][/ROW]
[ROW][C]-0.995855439583286[/C][/ROW]
[ROW][C]-0.203821482872209[/C][/ROW]
[ROW][C]0.285779412803567[/C][/ROW]
[ROW][C]0.992846605314575[/C][/ROW]
[ROW][C]-0.0326424009931274[/C][/ROW]
[ROW][C]-0.572122960882824[/C][/ROW]
[ROW][C]-0.552544804398143[/C][/ROW]
[ROW][C]-0.240243505055926[/C][/ROW]
[ROW][C]0.322411020680407[/C][/ROW]
[ROW][C]0.630309714287468[/C][/ROW]
[ROW][C]0.601433684871232[/C][/ROW]
[ROW][C]-0.733286458582107[/C][/ROW]
[ROW][C]-0.160045382026631[/C][/ROW]
[ROW][C]0.395986068639077[/C][/ROW]
[ROW][C]0.525885325501417[/C][/ROW]
[ROW][C]0.819051451339774[/C][/ROW]
[ROW][C]0.175416332710445[/C][/ROW]
[ROW][C]0.722308994179288[/C][/ROW]
[ROW][C]1.20239730786413[/C][/ROW]
[ROW][C]0.181073064953674[/C][/ROW]
[ROW][C]0.0276823997368094[/C][/ROW]
[ROW][C]-0.448685381060263[/C][/ROW]
[ROW][C]-0.252679590698609[/C][/ROW]
[ROW][C]0.188302912601137[/C][/ROW]
[ROW][C]-0.140217353547074[/C][/ROW]
[ROW][C]-1.04008080365458[/C][/ROW]
[ROW][C]-0.165181657145492[/C][/ROW]
[ROW][C]-0.938101045772961[/C][/ROW]
[ROW][C]0.684173307480327[/C][/ROW]
[ROW][C]-0.420129106509927[/C][/ROW]
[ROW][C]-0.354905310310897[/C][/ROW]
[ROW][C]-0.440209108638009[/C][/ROW]
[ROW][C]-1.11887600530722[/C][/ROW]
[ROW][C]0.0686415999073764[/C][/ROW]
[ROW][C]0.616719548072293[/C][/ROW]
[ROW][C]0.0574399814483076[/C][/ROW]
[ROW][C]0.267702851983427[/C][/ROW]
[ROW][C]0.130909091877193[/C][/ROW]
[ROW][C]0.588946602843224[/C][/ROW]
[ROW][C]0.00572821805640984[/C][/ROW]
[ROW][C]-0.884968902855682[/C][/ROW]
[ROW][C]-0.428896750123102[/C][/ROW]
[ROW][C]-0.717442098706048[/C][/ROW]
[ROW][C]1.42772367814757[/C][/ROW]
[ROW][C]-0.361535509724408[/C][/ROW]
[ROW][C]-0.321236121612646[/C][/ROW]
[ROW][C]1.06722741780056[/C][/ROW]
[ROW][C]-0.332902829131289[/C][/ROW]
[ROW][C]0.267556896218221[/C][/ROW]
[ROW][C]-0.55880200903484[/C][/ROW]
[ROW][C]0.942245288670044[/C][/ROW]
[ROW][C]0.107677379285031[/C][/ROW]
[ROW][C]0.814030747649796[/C][/ROW]
[ROW][C]-0.0649701394647751[/C][/ROW]
[ROW][C]0.345685645970771[/C][/ROW]
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[ROW][C]-0.240984461636316[/C][/ROW]
[ROW][C]0.0553124598061947[/C][/ROW]
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[ROW][C]-0.234296610330386[/C][/ROW]
[ROW][C]-0.418031505154584[/C][/ROW]
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[ROW][C]0.794189538843223[/C][/ROW]
[ROW][C]-0.7337825046774[/C][/ROW]
[ROW][C]-0.499459632308561[/C][/ROW]
[ROW][C]1.08239302960889[/C][/ROW]
[ROW][C]-0.195667967064271[/C][/ROW]
[ROW][C]-0.575471603112938[/C][/ROW]
[ROW][C]0.55533892801943[/C][/ROW]
[ROW][C]-0.271929833587416[/C][/ROW]
[ROW][C]0.319593878143402[/C][/ROW]
[ROW][C]0.481050892726717[/C][/ROW]
[ROW][C]-0.81262191504133[/C][/ROW]
[ROW][C]-0.0584254773387107[/C][/ROW]
[ROW][C]0.319299220357209[/C][/ROW]
[ROW][C]0.340160416654446[/C][/ROW]
[ROW][C]-0.380473371484065[/C][/ROW]
[ROW][C]-0.388107553150321[/C][/ROW]
[ROW][C]0.168516166415319[/C][/ROW]
[ROW][C]0.196617445048809[/C][/ROW]
[ROW][C]0.265968973922322[/C][/ROW]
[ROW][C]-0.564468306945424[/C][/ROW]
[ROW][C]-0.0741083392346166[/C][/ROW]
[ROW][C]-0.245462630950218[/C][/ROW]
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[ROW][C]0.213691874846621[/C][/ROW]
[ROW][C]-0.514626313062927[/C][/ROW]
[ROW][C]1.10591401094891[/C][/ROW]
[ROW][C]-1.14042582586266[/C][/ROW]
[ROW][C]0.295888384696412[/C][/ROW]
[ROW][C]0.192715845850636[/C][/ROW]
[ROW][C]0.0823052468056668[/C][/ROW]
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[ROW][C]0.099313414196176[/C][/ROW]
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[ROW][C]0.508878352127627[/C][/ROW]
[ROW][C]-0.280281532475886[/C][/ROW]
[ROW][C]0.627929054317186[/C][/ROW]
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[ROW][C]-0.217551597587264[/C][/ROW]
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[ROW][C]-0.500307852316455[/C][/ROW]
[ROW][C]0.315582161181543[/C][/ROW]
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[ROW][C]-0.380509231692807[/C][/ROW]
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[ROW][C]-0.0304015841763502[/C][/ROW]
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[ROW][C]0.570197986957242[/C][/ROW]
[ROW][C]0.317952341768077[/C][/ROW]
[ROW][C]-0.606007798318431[/C][/ROW]
[ROW][C]0.0543314453825707[/C][/ROW]
[ROW][C]0.133601264480095[/C][/ROW]
[ROW][C]-0.213626415828529[/C][/ROW]
[ROW][C]-0.677702580457283[/C][/ROW]
[ROW][C]0.454034649408554[/C][/ROW]
[ROW][C]-0.267529750400614[/C][/ROW]
[ROW][C]-0.842081978996457[/C][/ROW]
[ROW][C]0.0427521089252451[/C][/ROW]
[ROW][C]0.274539655374324[/C][/ROW]
[ROW][C]-0.425883109546494[/C][/ROW]
[ROW][C]0.41478388809867[/C][/ROW]
[ROW][C]-0.32293610892551[/C][/ROW]
[ROW][C]0.00915568168050528[/C][/ROW]
[ROW][C]-0.135962115754885[/C][/ROW]
[ROW][C]-0.916593602248472[/C][/ROW]
[ROW][C]0.147519810357598[/C][/ROW]
[ROW][C]-0.278727304282181[/C][/ROW]
[ROW][C]0.297054787742795[/C][/ROW]
[ROW][C]-0.249412013011796[/C][/ROW]
[ROW][C]0.281148357175223[/C][/ROW]
[ROW][C]-0.633174844558302[/C][/ROW]
[ROW][C]0.839474076687053[/C][/ROW]
[ROW][C]-0.335291480552041[/C][/ROW]
[ROW][C]-0.0537311851693173[/C][/ROW]
[ROW][C]-0.226993759667176[/C][/ROW]
[ROW][C]0.000315636943853517[/C][/ROW]
[ROW][C]0.516501275737427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31105&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31105&T=2

As an alternative you can also use a QR Code:

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

Estimated ARIMA Residuals
Value
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0.800999913477185
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1.21106609296917
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-0.192692525521358
0.102325645378361
-1.12766260306145
-0.0361673755495256
0.110557679549491
-0.216041049313559
0.0312638997882393
-0.555203488862734
-0.105294958193306
-0.417647715779018
-0.363087406058837
-0.259927536476961
-0.0304015841763502
-0.425425471837619
0.278580107524609
0.570197986957242
0.317952341768077
-0.606007798318431
0.0543314453825707
0.133601264480095
-0.213626415828529
-0.677702580457283
0.454034649408554
-0.267529750400614
-0.842081978996457
0.0427521089252451
0.274539655374324
-0.425883109546494
0.41478388809867
-0.32293610892551
0.00915568168050528
-0.135962115754885
-0.916593602248472
0.147519810357598
-0.278727304282181
0.297054787742795
-0.249412013011796
0.281148357175223
-0.633174844558302
0.839474076687053
-0.335291480552041
-0.0537311851693173
-0.226993759667176
0.000315636943853517
0.516501275737427

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 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 0 ; par8 = 0 ; 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