Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_arimabackwardselection.wasp
Title produced by softwareARIMA Backward Selection
Date of computationThu, 10 Dec 2009 08:52:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/10/t12604604154w1oxk1kyx2pank.htm/, Retrieved Thu, 28 Mar 2024 18:26:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65513, Retrieved Thu, 28 Mar 2024 18:26:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [] [2009-12-07 09:18:36] [b98453cac15ba1066b407e146608df68]
-    D    [ARIMA Backward Selection] [ARIMA Parameter E...] [2009-12-10 15:52:42] [2622964eb3e61db9b0dfd11950e3a18c] [Current]
Feedback Forum

Post a new message
Dataseries X:
255
280.2
299.9
339.2
374.2
393.5
389.2
381.7
375.2
369
357.4
352.1
346.5
342.9
340.3
328.3
322.9
314.3
308.9
294
285.6
281.2
280.3
278.8
274.5
270.4
263.4
259.9
258
262.7
284.7
311.3
322.1
327
331.3
333.3
321.4
327
320
314.7
316.7
314.4
321.3
318.2
307.2
301.3
287.5
277.7
274.4
258.8
253.3
251
248.4
249.5
246.1
244.5
243.6
244
240.8
249.8
248
259.4
260.5
260.8
261.3
259.5
256.6
257.9
256.5
254.2
253.3
253.8
255.5
257.1
257.3
253.2
252.8
252
250.7
252.2
250
251
253.4
251.2
255.6
261.1
258.9
259.9
261.2
264.7
267.1
266.4
267.7
268.6
267.5
268.5
268.5
270.5
270.9
270.1
269.3
269.8
270.1
264.9
263.7
264.8
263.7
255.9
276.2
360.1
380.5
373.7
369.8
366.6
359.3
345.8
326.2
324.5
328.1
327.5
324.4
316.5
310.9
301.5
291.7
290.4
287.4
277.7
281.6
288
276
272.9
283
283.3
276.8
284.5
282.7
281.2
287.4
283.1
284
285.5
289.2
292.5
296.4
305.2
303.9
311.5
316.3
316.7
322.5
317.1
309.8
303.8
290.3
293.7
291.7
296.5
289.1
288.5
293.8
297.7
305.4
302.7
302.5
303
294.5
294.1
294.5
297.1
289.4
292.4
287.9
286.6
280.5
272.4
269.2
270.6
267.3
262.5
266.8
268.8
263.1
261.2
266
262.5
265.2
261.3
253.7
249.2
239.1
236.4
235.2
245.2
246.2
247.7
251.4
253.3
254.8
250
249.3
241.5
243.3
248
253
252.9
251.5
251.6
253.5
259.8
334.1
448
445.8
445
448.2
438.2
439.8
423.4
410.8
408.4
406.7
405.9
402.7
405.1
399.6
386.5
381.4
375.2
357.7
359
355
352.7
344.4
343.8
338
339
333.3
334.4
328.3
330.7
330
331.6
351.2
389.4
410.9
442.8
462.8
466.9
461.7
439.2
430.3
416.1
402.5
397.3
403.3
395.9
387.8
378.6
377.1
370.4
362
350.3
348.2
344.6
343.5
342.8
347.6
346.6
349.5
342.1
342
342.8
339.3
348.2
333.7
334.7
354
367.7
363.3
358.4
353.1
343.1
344.6
344.4
333.9
331.7
324.3
321.2
322.4
321.7
320.5
312.8
309.7
315.6
309.7
304.6
302.5
301.5
298.8
291.3
293.6
294.6
285.9
297.6
301.1
293.8
297.7
292.9
292.1
287.2
288.2
283.8
299.9
292.4
293.3
300.8
293.7
293.1
294.4
292.1
291.9
282.5
277.9
287.5
289.2
285.6
293.2
290.8
283.1
275
287.8
287.8
287.4
284
277.8
277.6
304.9
294
300.9
324
332.9
341.6
333.4
348.2
344.7
344.7
329.3
323.5
323.2
317.4
330.1
329.2
334.9
315.8
315.4
319.6
317.3
313.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 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 & 11 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65513&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]11 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=65513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65513&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2ar3ma1ma2ma3
Estimates ( 1 )1.00860.2746-0.3401-0.5622-0.64140.2148
(p-val)(0.0159 )(0.6073 )(0.0403 )(0.1762 )(0.0532 )(0.1223 )
Estimates ( 2 )1.21030-0.2582-0.7808-0.47130.2421
(p-val)(0 )(NA )(2e-04 )(0 )(0 )(0.0365 )
Estimates ( 3 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 4 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 5 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & ma2 & ma3 \tabularnewline
Estimates ( 1 ) & 1.0086 & 0.2746 & -0.3401 & -0.5622 & -0.6414 & 0.2148 \tabularnewline
(p-val) & (0.0159 ) & (0.6073 ) & (0.0403 ) & (0.1762 ) & (0.0532 ) & (0.1223 ) \tabularnewline
Estimates ( 2 ) & 1.2103 & 0 & -0.2582 & -0.7808 & -0.4713 & 0.2421 \tabularnewline
(p-val) & (0 ) & (NA ) & (2e-04 ) & (0 ) & (0 ) & (0.0365 ) \tabularnewline
Estimates ( 3 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65513&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]ma2[/C][C]ma3[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]1.0086[/C][C]0.2746[/C][C]-0.3401[/C][C]-0.5622[/C][C]-0.6414[/C][C]0.2148[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0159 )[/C][C](0.6073 )[/C][C](0.0403 )[/C][C](0.1762 )[/C][C](0.0532 )[/C][C](0.1223 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]1.2103[/C][C]0[/C][C]-0.2582[/C][C]-0.7808[/C][C]-0.4713[/C][C]0.2421[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](2e-04 )[/C][C](0 )[/C][C](0 )[/C][C](0.0365 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/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][/ROW]
[ROW][C]Estimates ( 4 )[/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][/ROW]
[ROW][C]Estimates ( 5 )[/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][/ROW]
[ROW][C]Estimates ( 6 )[/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][/ROW]
[ROW][C]Estimates ( 7 )[/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][/ROW]
[ROW][C]Estimates ( 8 )[/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][/ROW]
[ROW][C]Estimates ( 9 )[/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][/ROW]
[ROW][C]Estimates ( 10 )[/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][/ROW]
[ROW][C]Estimates ( 11 )[/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][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65513&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
Iterationar1ar2ar3ma1ma2ma3
Estimates ( 1 )1.00860.2746-0.3401-0.5622-0.64140.2148
(p-val)(0.0159 )(0.6073 )(0.0403 )(0.1762 )(0.0532 )(0.1223 )
Estimates ( 2 )1.21030-0.2582-0.7808-0.47130.2421
(p-val)(0 )(NA )(2e-04 )(0 )(0 )(0.0365 )
Estimates ( 3 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 4 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 5 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )







Estimated ARIMA Residuals
Value
0.254999833678585
22.0637261808084
8.36506702663681
30.7736225164389
16.2536172739003
6.31978649995719
-12.541117501616
-2.71828068186466
-1.95485182804324
0.795323839092208
-6.27025377287568
3.35942030976075
-1.50205913407284
2.18998540092784
0.286527874254407
-8.33192720797185
1.33542284983531
-5.34660777953769
0.364188612555605
-12.3214965463108
-0.213044567062289
-1.73356760237912
2.29142250093452
-2.02682736956204
-3.29373825168995
-3.23571182705352
-5.615995118748
-1.23778396837417
-1.42061601175765
4.78655450552501
18.4793975643124
15.9725830862441
-0.815453366740222
0.0128967393884164
1.50544251506978
1.00271938473857
-11.8529674379466
12.1980261840451
-9.68599559713978
1.13547342393710
2.97921792827975
-0.785621719367919
8.0612033007036
-5.3827839300902
-8.17937461872397
-1.32446661791628
-10.6659441156235
-3.02656088860777
0.132458876970117
-13.8069274078262
0.845394639204114
-1.98702099406847
-1.68051929598893
0.0920394990564467
-5.16130221400508
-1.81108668490266
-2.30834063101787
-0.750037072168237
-5.3947253707732
8.7899235566845
-8.22983416568617
11.8176501211661
-7.38155547009886
0.66017315673276
-3.1132813129022
-1.74260226748968
-4.22016188206140
2.07668572745188
-3.68932481139297
-2.05347410919604
-1.70755960864552
0.0829944172946436
0.0525549970276853
-0.109176343264101
-1.75225518561125
-5.21419429128494
0.207419244972166
-2.04931938452986
-1.67050644923471
0.600794441571788
-3.91634951705187
0.914568891401787
0.377723332076606
-3.99940809812258
4.10028250058595
2.13034996185799
-5.01697363654706
0.88039167914142
-0.413243946878691
2.57141732481777
-0.160150074002167
-1.98942813155873
0.7674956209968
-0.213395806083973
-1.80123192327119
0.992418294813898
-0.95211431483235
1.83819052465494
-1.06894403308982
-0.967855575986486
-1.04385118507898
0.68556571118867
-0.333611701816567
-5.42973137859667
0.726314763980147
0.836961921847186
-1.54679449185316
-7.8797704326756
23.2308862131186
73.4327268612729
-14.6645292085857
-9.62846152611605
-4.66720646366489
3.8925108206267
-4.05357962489037
-5.35670102610004
-11.4983109457654
10.2692632816308
5.63923822623881
1.78510286719011
-1.64736847168137
-4.37111600313939
-0.876583756406526
-5.5740602532695
-4.21723385655859
3.50567394001677
-1.73390387012663
-7.46542812892844
8.0054837398301
4.18546728005985
-13.7313182373306
1.82878940228257
10.0155579065071
-3.37214346334616
-6.48996798141223
9.6473667518257
-5.69796739984453
0.371151024442422
5.30635805916157
-6.30971196519032
2.80333497540805
0.270046937839979
3.77981376962364
1.15533503538918
3.07905278265261
6.8737812354031
-4.5358851269508
9.01702970670762
1.16292889183652
0.43906294216717
5.71704440086086
-6.48195048465036
-3.3771192690953
-2.46183738505908
-9.4332170478525
10.0254880254123
-3.6516456200049
7.693301985708
-10.7057717832237
4.56866205647999
3.61676400060875
3.46179306421813
5.3878867826985
-5.26297325753655
1.49032895923109
0.36686024838641
-7.5732456232995
3.62764903211999
0.409731769739903
3.59745812899038
-9.0611941902361
7.31512435053738
-6.99945832309867
2.50056869596632
-7.1861942788887
-4.05022671664802
-1.21845103060777
3.03774182373883
-4.7921212364757
-3.42612756365544
4.87177621486511
-0.571983040663883
-6.99016600656002
-0.578214274045576
4.27589152699226
-6.22391088396299
3.63440273116448
-6.89605965031704
-5.80423260014768
-3.30945017603603
-8.89989135836323
0.260861313135902
-2.08392600299732
9.42271343761112
-5.77164971672163
0.584727813518678
-0.0832801114183283
-0.335508700929775
-1.28959513732277
-6.4970557028598
-0.0303888613728142
-9.1712080472086
4.44832241535643
1.41242818753703
2.72857369163921
-4.33717329448005
-2.06398916829018
-1.28737940523640
1.03389998358603
4.07815747299849
70.680390149993
79.9818416960065
-45.9300065960566
5.71397251462954
-0.0749843966945638
-0.266852026256099
9.10829932808554
-9.21407413321306
0.820808807789241
7.95052153138217
5.57603449472473
5.34408631927167
2.12906752858874
8.6944001894836
-2.20976120002873
-5.42264607294396
4.1062779034885
-0.0247656628911190
-10.5163680477176
12.1087027909069
-2.54802877509056
4.01787439149142
-6.41629534761968
6.56002640103825
-4.98879924592385
6.97282180701915
-6.00931791282875
6.76746248482652
-6.85198897035633
8.09124679413805
-2.37194657629316
4.90013519294542
18.4881168353484
31.7957991454662
6.80941613821293
26.6385275415374
7.4239153957207
2.27603064636658
-3.65879611664405
-13.7690645412414
6.04069899429226
-5.46277773511517
-0.72506330358951
4.1800135357596
13.2068834623433
-6.38897038378853
-0.0712758329369337
-3.93220420438954
6.6027471441143
-4.21094573244433
-1.64693460147216
-6.94276544661195
5.67403414201086
-2.03581550066680
3.11432108484884
-0.0903742286704932
6.96735622389218
-2.83373530847393
5.24744829558373
-8.78199410466493
5.26489849727183
0.118882356783456
-1.46603585678454
10.2970302433447
-17.4202795266392
9.11687777733601
17.0394192801121
8.19516693723836
-9.60063917927087
-1.46068295426731
-3.2289150706764
-5.49455425461115
6.52874007680252
0.0700478921275509
-8.70409015124608
2.70488454549233
-6.44266317614946
1.37951957696978
1.67256111003965
-0.366890497398470
-1.30779836765487
-7.2188499274107
-0.0602583283628524
6.34987794214778
-8.5365896870992
-2.53689208377038
-1.59455319589641
-0.177706525718108
-3.42697291271657
-6.91410461247586
4.21920632827082
-1.5051088470175
-9.54557480984756
13.7444712278056
-3.64399804965439
-8.18429399897193
4.39036969183338
-7.53658234508268
0.824813048826962
-6.76172520478722
2.87625204867673
-7.23222531133672
17.8281607190264
-17.4243508125199
5.74006400880912
2.34880294646782
-8.71705004163573
0.180515148654599
0.411888011590863
-3.64129245468668
-0.262849417281658
-10.6960419754128
-1.24558421319947
9.24870255625867
-3.21841613993072
-5.12513973971504
7.0970248582296
-7.10456857488375
-6.93165440219085
-7.06770348981991
15.3750237413062
-7.70558344110681
0.377896979993898
-6.6757390204842
-4.51572160727773
-0.0505720049182764
26.5570261772454
-24.6216484357648
13.5317069122056
14.5288769435857
2.13533498546174
3.33852898616035
-11.4364766534799
18.9618532714349
-10.6090984426418
5.33161028294894
-17.2858133906791
4.52359461541178
0.089430796980405
-2.47733269172918
14.3520865451798
-5.75839557891212
7.64761494220882
-22.7595213775452
10.3405975911693
1.3596072827078
-0.636512109852905
-4.17710009767726

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.254999833678585 \tabularnewline
22.0637261808084 \tabularnewline
8.36506702663681 \tabularnewline
30.7736225164389 \tabularnewline
16.2536172739003 \tabularnewline
6.31978649995719 \tabularnewline
-12.541117501616 \tabularnewline
-2.71828068186466 \tabularnewline
-1.95485182804324 \tabularnewline
0.795323839092208 \tabularnewline
-6.27025377287568 \tabularnewline
3.35942030976075 \tabularnewline
-1.50205913407284 \tabularnewline
2.18998540092784 \tabularnewline
0.286527874254407 \tabularnewline
-8.33192720797185 \tabularnewline
1.33542284983531 \tabularnewline
-5.34660777953769 \tabularnewline
0.364188612555605 \tabularnewline
-12.3214965463108 \tabularnewline
-0.213044567062289 \tabularnewline
-1.73356760237912 \tabularnewline
2.29142250093452 \tabularnewline
-2.02682736956204 \tabularnewline
-3.29373825168995 \tabularnewline
-3.23571182705352 \tabularnewline
-5.615995118748 \tabularnewline
-1.23778396837417 \tabularnewline
-1.42061601175765 \tabularnewline
4.78655450552501 \tabularnewline
18.4793975643124 \tabularnewline
15.9725830862441 \tabularnewline
-0.815453366740222 \tabularnewline
0.0128967393884164 \tabularnewline
1.50544251506978 \tabularnewline
1.00271938473857 \tabularnewline
-11.8529674379466 \tabularnewline
12.1980261840451 \tabularnewline
-9.68599559713978 \tabularnewline
1.13547342393710 \tabularnewline
2.97921792827975 \tabularnewline
-0.785621719367919 \tabularnewline
8.0612033007036 \tabularnewline
-5.3827839300902 \tabularnewline
-8.17937461872397 \tabularnewline
-1.32446661791628 \tabularnewline
-10.6659441156235 \tabularnewline
-3.02656088860777 \tabularnewline
0.132458876970117 \tabularnewline
-13.8069274078262 \tabularnewline
0.845394639204114 \tabularnewline
-1.98702099406847 \tabularnewline
-1.68051929598893 \tabularnewline
0.0920394990564467 \tabularnewline
-5.16130221400508 \tabularnewline
-1.81108668490266 \tabularnewline
-2.30834063101787 \tabularnewline
-0.750037072168237 \tabularnewline
-5.3947253707732 \tabularnewline
8.7899235566845 \tabularnewline
-8.22983416568617 \tabularnewline
11.8176501211661 \tabularnewline
-7.38155547009886 \tabularnewline
0.66017315673276 \tabularnewline
-3.1132813129022 \tabularnewline
-1.74260226748968 \tabularnewline
-4.22016188206140 \tabularnewline
2.07668572745188 \tabularnewline
-3.68932481139297 \tabularnewline
-2.05347410919604 \tabularnewline
-1.70755960864552 \tabularnewline
0.0829944172946436 \tabularnewline
0.0525549970276853 \tabularnewline
-0.109176343264101 \tabularnewline
-1.75225518561125 \tabularnewline
-5.21419429128494 \tabularnewline
0.207419244972166 \tabularnewline
-2.04931938452986 \tabularnewline
-1.67050644923471 \tabularnewline
0.600794441571788 \tabularnewline
-3.91634951705187 \tabularnewline
0.914568891401787 \tabularnewline
0.377723332076606 \tabularnewline
-3.99940809812258 \tabularnewline
4.10028250058595 \tabularnewline
2.13034996185799 \tabularnewline
-5.01697363654706 \tabularnewline
0.88039167914142 \tabularnewline
-0.413243946878691 \tabularnewline
2.57141732481777 \tabularnewline
-0.160150074002167 \tabularnewline
-1.98942813155873 \tabularnewline
0.7674956209968 \tabularnewline
-0.213395806083973 \tabularnewline
-1.80123192327119 \tabularnewline
0.992418294813898 \tabularnewline
-0.95211431483235 \tabularnewline
1.83819052465494 \tabularnewline
-1.06894403308982 \tabularnewline
-0.967855575986486 \tabularnewline
-1.04385118507898 \tabularnewline
0.68556571118867 \tabularnewline
-0.333611701816567 \tabularnewline
-5.42973137859667 \tabularnewline
0.726314763980147 \tabularnewline
0.836961921847186 \tabularnewline
-1.54679449185316 \tabularnewline
-7.8797704326756 \tabularnewline
23.2308862131186 \tabularnewline
73.4327268612729 \tabularnewline
-14.6645292085857 \tabularnewline
-9.62846152611605 \tabularnewline
-4.66720646366489 \tabularnewline
3.8925108206267 \tabularnewline
-4.05357962489037 \tabularnewline
-5.35670102610004 \tabularnewline
-11.4983109457654 \tabularnewline
10.2692632816308 \tabularnewline
5.63923822623881 \tabularnewline
1.78510286719011 \tabularnewline
-1.64736847168137 \tabularnewline
-4.37111600313939 \tabularnewline
-0.876583756406526 \tabularnewline
-5.5740602532695 \tabularnewline
-4.21723385655859 \tabularnewline
3.50567394001677 \tabularnewline
-1.73390387012663 \tabularnewline
-7.46542812892844 \tabularnewline
8.0054837398301 \tabularnewline
4.18546728005985 \tabularnewline
-13.7313182373306 \tabularnewline
1.82878940228257 \tabularnewline
10.0155579065071 \tabularnewline
-3.37214346334616 \tabularnewline
-6.48996798141223 \tabularnewline
9.6473667518257 \tabularnewline
-5.69796739984453 \tabularnewline
0.371151024442422 \tabularnewline
5.30635805916157 \tabularnewline
-6.30971196519032 \tabularnewline
2.80333497540805 \tabularnewline
0.270046937839979 \tabularnewline
3.77981376962364 \tabularnewline
1.15533503538918 \tabularnewline
3.07905278265261 \tabularnewline
6.8737812354031 \tabularnewline
-4.5358851269508 \tabularnewline
9.01702970670762 \tabularnewline
1.16292889183652 \tabularnewline
0.43906294216717 \tabularnewline
5.71704440086086 \tabularnewline
-6.48195048465036 \tabularnewline
-3.3771192690953 \tabularnewline
-2.46183738505908 \tabularnewline
-9.4332170478525 \tabularnewline
10.0254880254123 \tabularnewline
-3.6516456200049 \tabularnewline
7.693301985708 \tabularnewline
-10.7057717832237 \tabularnewline
4.56866205647999 \tabularnewline
3.61676400060875 \tabularnewline
3.46179306421813 \tabularnewline
5.3878867826985 \tabularnewline
-5.26297325753655 \tabularnewline
1.49032895923109 \tabularnewline
0.36686024838641 \tabularnewline
-7.5732456232995 \tabularnewline
3.62764903211999 \tabularnewline
0.409731769739903 \tabularnewline
3.59745812899038 \tabularnewline
-9.0611941902361 \tabularnewline
7.31512435053738 \tabularnewline
-6.99945832309867 \tabularnewline
2.50056869596632 \tabularnewline
-7.1861942788887 \tabularnewline
-4.05022671664802 \tabularnewline
-1.21845103060777 \tabularnewline
3.03774182373883 \tabularnewline
-4.7921212364757 \tabularnewline
-3.42612756365544 \tabularnewline
4.87177621486511 \tabularnewline
-0.571983040663883 \tabularnewline
-6.99016600656002 \tabularnewline
-0.578214274045576 \tabularnewline
4.27589152699226 \tabularnewline
-6.22391088396299 \tabularnewline
3.63440273116448 \tabularnewline
-6.89605965031704 \tabularnewline
-5.80423260014768 \tabularnewline
-3.30945017603603 \tabularnewline
-8.89989135836323 \tabularnewline
0.260861313135902 \tabularnewline
-2.08392600299732 \tabularnewline
9.42271343761112 \tabularnewline
-5.77164971672163 \tabularnewline
0.584727813518678 \tabularnewline
-0.0832801114183283 \tabularnewline
-0.335508700929775 \tabularnewline
-1.28959513732277 \tabularnewline
-6.4970557028598 \tabularnewline
-0.0303888613728142 \tabularnewline
-9.1712080472086 \tabularnewline
4.44832241535643 \tabularnewline
1.41242818753703 \tabularnewline
2.72857369163921 \tabularnewline
-4.33717329448005 \tabularnewline
-2.06398916829018 \tabularnewline
-1.28737940523640 \tabularnewline
1.03389998358603 \tabularnewline
4.07815747299849 \tabularnewline
70.680390149993 \tabularnewline
79.9818416960065 \tabularnewline
-45.9300065960566 \tabularnewline
5.71397251462954 \tabularnewline
-0.0749843966945638 \tabularnewline
-0.266852026256099 \tabularnewline
9.10829932808554 \tabularnewline
-9.21407413321306 \tabularnewline
0.820808807789241 \tabularnewline
7.95052153138217 \tabularnewline
5.57603449472473 \tabularnewline
5.34408631927167 \tabularnewline
2.12906752858874 \tabularnewline
8.6944001894836 \tabularnewline
-2.20976120002873 \tabularnewline
-5.42264607294396 \tabularnewline
4.1062779034885 \tabularnewline
-0.0247656628911190 \tabularnewline
-10.5163680477176 \tabularnewline
12.1087027909069 \tabularnewline
-2.54802877509056 \tabularnewline
4.01787439149142 \tabularnewline
-6.41629534761968 \tabularnewline
6.56002640103825 \tabularnewline
-4.98879924592385 \tabularnewline
6.97282180701915 \tabularnewline
-6.00931791282875 \tabularnewline
6.76746248482652 \tabularnewline
-6.85198897035633 \tabularnewline
8.09124679413805 \tabularnewline
-2.37194657629316 \tabularnewline
4.90013519294542 \tabularnewline
18.4881168353484 \tabularnewline
31.7957991454662 \tabularnewline
6.80941613821293 \tabularnewline
26.6385275415374 \tabularnewline
7.4239153957207 \tabularnewline
2.27603064636658 \tabularnewline
-3.65879611664405 \tabularnewline
-13.7690645412414 \tabularnewline
6.04069899429226 \tabularnewline
-5.46277773511517 \tabularnewline
-0.72506330358951 \tabularnewline
4.1800135357596 \tabularnewline
13.2068834623433 \tabularnewline
-6.38897038378853 \tabularnewline
-0.0712758329369337 \tabularnewline
-3.93220420438954 \tabularnewline
6.6027471441143 \tabularnewline
-4.21094573244433 \tabularnewline
-1.64693460147216 \tabularnewline
-6.94276544661195 \tabularnewline
5.67403414201086 \tabularnewline
-2.03581550066680 \tabularnewline
3.11432108484884 \tabularnewline
-0.0903742286704932 \tabularnewline
6.96735622389218 \tabularnewline
-2.83373530847393 \tabularnewline
5.24744829558373 \tabularnewline
-8.78199410466493 \tabularnewline
5.26489849727183 \tabularnewline
0.118882356783456 \tabularnewline
-1.46603585678454 \tabularnewline
10.2970302433447 \tabularnewline
-17.4202795266392 \tabularnewline
9.11687777733601 \tabularnewline
17.0394192801121 \tabularnewline
8.19516693723836 \tabularnewline
-9.60063917927087 \tabularnewline
-1.46068295426731 \tabularnewline
-3.2289150706764 \tabularnewline
-5.49455425461115 \tabularnewline
6.52874007680252 \tabularnewline
0.0700478921275509 \tabularnewline
-8.70409015124608 \tabularnewline
2.70488454549233 \tabularnewline
-6.44266317614946 \tabularnewline
1.37951957696978 \tabularnewline
1.67256111003965 \tabularnewline
-0.366890497398470 \tabularnewline
-1.30779836765487 \tabularnewline
-7.2188499274107 \tabularnewline
-0.0602583283628524 \tabularnewline
6.34987794214778 \tabularnewline
-8.5365896870992 \tabularnewline
-2.53689208377038 \tabularnewline
-1.59455319589641 \tabularnewline
-0.177706525718108 \tabularnewline
-3.42697291271657 \tabularnewline
-6.91410461247586 \tabularnewline
4.21920632827082 \tabularnewline
-1.5051088470175 \tabularnewline
-9.54557480984756 \tabularnewline
13.7444712278056 \tabularnewline
-3.64399804965439 \tabularnewline
-8.18429399897193 \tabularnewline
4.39036969183338 \tabularnewline
-7.53658234508268 \tabularnewline
0.824813048826962 \tabularnewline
-6.76172520478722 \tabularnewline
2.87625204867673 \tabularnewline
-7.23222531133672 \tabularnewline
17.8281607190264 \tabularnewline
-17.4243508125199 \tabularnewline
5.74006400880912 \tabularnewline
2.34880294646782 \tabularnewline
-8.71705004163573 \tabularnewline
0.180515148654599 \tabularnewline
0.411888011590863 \tabularnewline
-3.64129245468668 \tabularnewline
-0.262849417281658 \tabularnewline
-10.6960419754128 \tabularnewline
-1.24558421319947 \tabularnewline
9.24870255625867 \tabularnewline
-3.21841613993072 \tabularnewline
-5.12513973971504 \tabularnewline
7.0970248582296 \tabularnewline
-7.10456857488375 \tabularnewline
-6.93165440219085 \tabularnewline
-7.06770348981991 \tabularnewline
15.3750237413062 \tabularnewline
-7.70558344110681 \tabularnewline
0.377896979993898 \tabularnewline
-6.6757390204842 \tabularnewline
-4.51572160727773 \tabularnewline
-0.0505720049182764 \tabularnewline
26.5570261772454 \tabularnewline
-24.6216484357648 \tabularnewline
13.5317069122056 \tabularnewline
14.5288769435857 \tabularnewline
2.13533498546174 \tabularnewline
3.33852898616035 \tabularnewline
-11.4364766534799 \tabularnewline
18.9618532714349 \tabularnewline
-10.6090984426418 \tabularnewline
5.33161028294894 \tabularnewline
-17.2858133906791 \tabularnewline
4.52359461541178 \tabularnewline
0.089430796980405 \tabularnewline
-2.47733269172918 \tabularnewline
14.3520865451798 \tabularnewline
-5.75839557891212 \tabularnewline
7.64761494220882 \tabularnewline
-22.7595213775452 \tabularnewline
10.3405975911693 \tabularnewline
1.3596072827078 \tabularnewline
-0.636512109852905 \tabularnewline
-4.17710009767726 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65513&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.254999833678585[/C][/ROW]
[ROW][C]22.0637261808084[/C][/ROW]
[ROW][C]8.36506702663681[/C][/ROW]
[ROW][C]30.7736225164389[/C][/ROW]
[ROW][C]16.2536172739003[/C][/ROW]
[ROW][C]6.31978649995719[/C][/ROW]
[ROW][C]-12.541117501616[/C][/ROW]
[ROW][C]-2.71828068186466[/C][/ROW]
[ROW][C]-1.95485182804324[/C][/ROW]
[ROW][C]0.795323839092208[/C][/ROW]
[ROW][C]-6.27025377287568[/C][/ROW]
[ROW][C]3.35942030976075[/C][/ROW]
[ROW][C]-1.50205913407284[/C][/ROW]
[ROW][C]2.18998540092784[/C][/ROW]
[ROW][C]0.286527874254407[/C][/ROW]
[ROW][C]-8.33192720797185[/C][/ROW]
[ROW][C]1.33542284983531[/C][/ROW]
[ROW][C]-5.34660777953769[/C][/ROW]
[ROW][C]0.364188612555605[/C][/ROW]
[ROW][C]-12.3214965463108[/C][/ROW]
[ROW][C]-0.213044567062289[/C][/ROW]
[ROW][C]-1.73356760237912[/C][/ROW]
[ROW][C]2.29142250093452[/C][/ROW]
[ROW][C]-2.02682736956204[/C][/ROW]
[ROW][C]-3.29373825168995[/C][/ROW]
[ROW][C]-3.23571182705352[/C][/ROW]
[ROW][C]-5.615995118748[/C][/ROW]
[ROW][C]-1.23778396837417[/C][/ROW]
[ROW][C]-1.42061601175765[/C][/ROW]
[ROW][C]4.78655450552501[/C][/ROW]
[ROW][C]18.4793975643124[/C][/ROW]
[ROW][C]15.9725830862441[/C][/ROW]
[ROW][C]-0.815453366740222[/C][/ROW]
[ROW][C]0.0128967393884164[/C][/ROW]
[ROW][C]1.50544251506978[/C][/ROW]
[ROW][C]1.00271938473857[/C][/ROW]
[ROW][C]-11.8529674379466[/C][/ROW]
[ROW][C]12.1980261840451[/C][/ROW]
[ROW][C]-9.68599559713978[/C][/ROW]
[ROW][C]1.13547342393710[/C][/ROW]
[ROW][C]2.97921792827975[/C][/ROW]
[ROW][C]-0.785621719367919[/C][/ROW]
[ROW][C]8.0612033007036[/C][/ROW]
[ROW][C]-5.3827839300902[/C][/ROW]
[ROW][C]-8.17937461872397[/C][/ROW]
[ROW][C]-1.32446661791628[/C][/ROW]
[ROW][C]-10.6659441156235[/C][/ROW]
[ROW][C]-3.02656088860777[/C][/ROW]
[ROW][C]0.132458876970117[/C][/ROW]
[ROW][C]-13.8069274078262[/C][/ROW]
[ROW][C]0.845394639204114[/C][/ROW]
[ROW][C]-1.98702099406847[/C][/ROW]
[ROW][C]-1.68051929598893[/C][/ROW]
[ROW][C]0.0920394990564467[/C][/ROW]
[ROW][C]-5.16130221400508[/C][/ROW]
[ROW][C]-1.81108668490266[/C][/ROW]
[ROW][C]-2.30834063101787[/C][/ROW]
[ROW][C]-0.750037072168237[/C][/ROW]
[ROW][C]-5.3947253707732[/C][/ROW]
[ROW][C]8.7899235566845[/C][/ROW]
[ROW][C]-8.22983416568617[/C][/ROW]
[ROW][C]11.8176501211661[/C][/ROW]
[ROW][C]-7.38155547009886[/C][/ROW]
[ROW][C]0.66017315673276[/C][/ROW]
[ROW][C]-3.1132813129022[/C][/ROW]
[ROW][C]-1.74260226748968[/C][/ROW]
[ROW][C]-4.22016188206140[/C][/ROW]
[ROW][C]2.07668572745188[/C][/ROW]
[ROW][C]-3.68932481139297[/C][/ROW]
[ROW][C]-2.05347410919604[/C][/ROW]
[ROW][C]-1.70755960864552[/C][/ROW]
[ROW][C]0.0829944172946436[/C][/ROW]
[ROW][C]0.0525549970276853[/C][/ROW]
[ROW][C]-0.109176343264101[/C][/ROW]
[ROW][C]-1.75225518561125[/C][/ROW]
[ROW][C]-5.21419429128494[/C][/ROW]
[ROW][C]0.207419244972166[/C][/ROW]
[ROW][C]-2.04931938452986[/C][/ROW]
[ROW][C]-1.67050644923471[/C][/ROW]
[ROW][C]0.600794441571788[/C][/ROW]
[ROW][C]-3.91634951705187[/C][/ROW]
[ROW][C]0.914568891401787[/C][/ROW]
[ROW][C]0.377723332076606[/C][/ROW]
[ROW][C]-3.99940809812258[/C][/ROW]
[ROW][C]4.10028250058595[/C][/ROW]
[ROW][C]2.13034996185799[/C][/ROW]
[ROW][C]-5.01697363654706[/C][/ROW]
[ROW][C]0.88039167914142[/C][/ROW]
[ROW][C]-0.413243946878691[/C][/ROW]
[ROW][C]2.57141732481777[/C][/ROW]
[ROW][C]-0.160150074002167[/C][/ROW]
[ROW][C]-1.98942813155873[/C][/ROW]
[ROW][C]0.7674956209968[/C][/ROW]
[ROW][C]-0.213395806083973[/C][/ROW]
[ROW][C]-1.80123192327119[/C][/ROW]
[ROW][C]0.992418294813898[/C][/ROW]
[ROW][C]-0.95211431483235[/C][/ROW]
[ROW][C]1.83819052465494[/C][/ROW]
[ROW][C]-1.06894403308982[/C][/ROW]
[ROW][C]-0.967855575986486[/C][/ROW]
[ROW][C]-1.04385118507898[/C][/ROW]
[ROW][C]0.68556571118867[/C][/ROW]
[ROW][C]-0.333611701816567[/C][/ROW]
[ROW][C]-5.42973137859667[/C][/ROW]
[ROW][C]0.726314763980147[/C][/ROW]
[ROW][C]0.836961921847186[/C][/ROW]
[ROW][C]-1.54679449185316[/C][/ROW]
[ROW][C]-7.8797704326756[/C][/ROW]
[ROW][C]23.2308862131186[/C][/ROW]
[ROW][C]73.4327268612729[/C][/ROW]
[ROW][C]-14.6645292085857[/C][/ROW]
[ROW][C]-9.62846152611605[/C][/ROW]
[ROW][C]-4.66720646366489[/C][/ROW]
[ROW][C]3.8925108206267[/C][/ROW]
[ROW][C]-4.05357962489037[/C][/ROW]
[ROW][C]-5.35670102610004[/C][/ROW]
[ROW][C]-11.4983109457654[/C][/ROW]
[ROW][C]10.2692632816308[/C][/ROW]
[ROW][C]5.63923822623881[/C][/ROW]
[ROW][C]1.78510286719011[/C][/ROW]
[ROW][C]-1.64736847168137[/C][/ROW]
[ROW][C]-4.37111600313939[/C][/ROW]
[ROW][C]-0.876583756406526[/C][/ROW]
[ROW][C]-5.5740602532695[/C][/ROW]
[ROW][C]-4.21723385655859[/C][/ROW]
[ROW][C]3.50567394001677[/C][/ROW]
[ROW][C]-1.73390387012663[/C][/ROW]
[ROW][C]-7.46542812892844[/C][/ROW]
[ROW][C]8.0054837398301[/C][/ROW]
[ROW][C]4.18546728005985[/C][/ROW]
[ROW][C]-13.7313182373306[/C][/ROW]
[ROW][C]1.82878940228257[/C][/ROW]
[ROW][C]10.0155579065071[/C][/ROW]
[ROW][C]-3.37214346334616[/C][/ROW]
[ROW][C]-6.48996798141223[/C][/ROW]
[ROW][C]9.6473667518257[/C][/ROW]
[ROW][C]-5.69796739984453[/C][/ROW]
[ROW][C]0.371151024442422[/C][/ROW]
[ROW][C]5.30635805916157[/C][/ROW]
[ROW][C]-6.30971196519032[/C][/ROW]
[ROW][C]2.80333497540805[/C][/ROW]
[ROW][C]0.270046937839979[/C][/ROW]
[ROW][C]3.77981376962364[/C][/ROW]
[ROW][C]1.15533503538918[/C][/ROW]
[ROW][C]3.07905278265261[/C][/ROW]
[ROW][C]6.8737812354031[/C][/ROW]
[ROW][C]-4.5358851269508[/C][/ROW]
[ROW][C]9.01702970670762[/C][/ROW]
[ROW][C]1.16292889183652[/C][/ROW]
[ROW][C]0.43906294216717[/C][/ROW]
[ROW][C]5.71704440086086[/C][/ROW]
[ROW][C]-6.48195048465036[/C][/ROW]
[ROW][C]-3.3771192690953[/C][/ROW]
[ROW][C]-2.46183738505908[/C][/ROW]
[ROW][C]-9.4332170478525[/C][/ROW]
[ROW][C]10.0254880254123[/C][/ROW]
[ROW][C]-3.6516456200049[/C][/ROW]
[ROW][C]7.693301985708[/C][/ROW]
[ROW][C]-10.7057717832237[/C][/ROW]
[ROW][C]4.56866205647999[/C][/ROW]
[ROW][C]3.61676400060875[/C][/ROW]
[ROW][C]3.46179306421813[/C][/ROW]
[ROW][C]5.3878867826985[/C][/ROW]
[ROW][C]-5.26297325753655[/C][/ROW]
[ROW][C]1.49032895923109[/C][/ROW]
[ROW][C]0.36686024838641[/C][/ROW]
[ROW][C]-7.5732456232995[/C][/ROW]
[ROW][C]3.62764903211999[/C][/ROW]
[ROW][C]0.409731769739903[/C][/ROW]
[ROW][C]3.59745812899038[/C][/ROW]
[ROW][C]-9.0611941902361[/C][/ROW]
[ROW][C]7.31512435053738[/C][/ROW]
[ROW][C]-6.99945832309867[/C][/ROW]
[ROW][C]2.50056869596632[/C][/ROW]
[ROW][C]-7.1861942788887[/C][/ROW]
[ROW][C]-4.05022671664802[/C][/ROW]
[ROW][C]-1.21845103060777[/C][/ROW]
[ROW][C]3.03774182373883[/C][/ROW]
[ROW][C]-4.7921212364757[/C][/ROW]
[ROW][C]-3.42612756365544[/C][/ROW]
[ROW][C]4.87177621486511[/C][/ROW]
[ROW][C]-0.571983040663883[/C][/ROW]
[ROW][C]-6.99016600656002[/C][/ROW]
[ROW][C]-0.578214274045576[/C][/ROW]
[ROW][C]4.27589152699226[/C][/ROW]
[ROW][C]-6.22391088396299[/C][/ROW]
[ROW][C]3.63440273116448[/C][/ROW]
[ROW][C]-6.89605965031704[/C][/ROW]
[ROW][C]-5.80423260014768[/C][/ROW]
[ROW][C]-3.30945017603603[/C][/ROW]
[ROW][C]-8.89989135836323[/C][/ROW]
[ROW][C]0.260861313135902[/C][/ROW]
[ROW][C]-2.08392600299732[/C][/ROW]
[ROW][C]9.42271343761112[/C][/ROW]
[ROW][C]-5.77164971672163[/C][/ROW]
[ROW][C]0.584727813518678[/C][/ROW]
[ROW][C]-0.0832801114183283[/C][/ROW]
[ROW][C]-0.335508700929775[/C][/ROW]
[ROW][C]-1.28959513732277[/C][/ROW]
[ROW][C]-6.4970557028598[/C][/ROW]
[ROW][C]-0.0303888613728142[/C][/ROW]
[ROW][C]-9.1712080472086[/C][/ROW]
[ROW][C]4.44832241535643[/C][/ROW]
[ROW][C]1.41242818753703[/C][/ROW]
[ROW][C]2.72857369163921[/C][/ROW]
[ROW][C]-4.33717329448005[/C][/ROW]
[ROW][C]-2.06398916829018[/C][/ROW]
[ROW][C]-1.28737940523640[/C][/ROW]
[ROW][C]1.03389998358603[/C][/ROW]
[ROW][C]4.07815747299849[/C][/ROW]
[ROW][C]70.680390149993[/C][/ROW]
[ROW][C]79.9818416960065[/C][/ROW]
[ROW][C]-45.9300065960566[/C][/ROW]
[ROW][C]5.71397251462954[/C][/ROW]
[ROW][C]-0.0749843966945638[/C][/ROW]
[ROW][C]-0.266852026256099[/C][/ROW]
[ROW][C]9.10829932808554[/C][/ROW]
[ROW][C]-9.21407413321306[/C][/ROW]
[ROW][C]0.820808807789241[/C][/ROW]
[ROW][C]7.95052153138217[/C][/ROW]
[ROW][C]5.57603449472473[/C][/ROW]
[ROW][C]5.34408631927167[/C][/ROW]
[ROW][C]2.12906752858874[/C][/ROW]
[ROW][C]8.6944001894836[/C][/ROW]
[ROW][C]-2.20976120002873[/C][/ROW]
[ROW][C]-5.42264607294396[/C][/ROW]
[ROW][C]4.1062779034885[/C][/ROW]
[ROW][C]-0.0247656628911190[/C][/ROW]
[ROW][C]-10.5163680477176[/C][/ROW]
[ROW][C]12.1087027909069[/C][/ROW]
[ROW][C]-2.54802877509056[/C][/ROW]
[ROW][C]4.01787439149142[/C][/ROW]
[ROW][C]-6.41629534761968[/C][/ROW]
[ROW][C]6.56002640103825[/C][/ROW]
[ROW][C]-4.98879924592385[/C][/ROW]
[ROW][C]6.97282180701915[/C][/ROW]
[ROW][C]-6.00931791282875[/C][/ROW]
[ROW][C]6.76746248482652[/C][/ROW]
[ROW][C]-6.85198897035633[/C][/ROW]
[ROW][C]8.09124679413805[/C][/ROW]
[ROW][C]-2.37194657629316[/C][/ROW]
[ROW][C]4.90013519294542[/C][/ROW]
[ROW][C]18.4881168353484[/C][/ROW]
[ROW][C]31.7957991454662[/C][/ROW]
[ROW][C]6.80941613821293[/C][/ROW]
[ROW][C]26.6385275415374[/C][/ROW]
[ROW][C]7.4239153957207[/C][/ROW]
[ROW][C]2.27603064636658[/C][/ROW]
[ROW][C]-3.65879611664405[/C][/ROW]
[ROW][C]-13.7690645412414[/C][/ROW]
[ROW][C]6.04069899429226[/C][/ROW]
[ROW][C]-5.46277773511517[/C][/ROW]
[ROW][C]-0.72506330358951[/C][/ROW]
[ROW][C]4.1800135357596[/C][/ROW]
[ROW][C]13.2068834623433[/C][/ROW]
[ROW][C]-6.38897038378853[/C][/ROW]
[ROW][C]-0.0712758329369337[/C][/ROW]
[ROW][C]-3.93220420438954[/C][/ROW]
[ROW][C]6.6027471441143[/C][/ROW]
[ROW][C]-4.21094573244433[/C][/ROW]
[ROW][C]-1.64693460147216[/C][/ROW]
[ROW][C]-6.94276544661195[/C][/ROW]
[ROW][C]5.67403414201086[/C][/ROW]
[ROW][C]-2.03581550066680[/C][/ROW]
[ROW][C]3.11432108484884[/C][/ROW]
[ROW][C]-0.0903742286704932[/C][/ROW]
[ROW][C]6.96735622389218[/C][/ROW]
[ROW][C]-2.83373530847393[/C][/ROW]
[ROW][C]5.24744829558373[/C][/ROW]
[ROW][C]-8.78199410466493[/C][/ROW]
[ROW][C]5.26489849727183[/C][/ROW]
[ROW][C]0.118882356783456[/C][/ROW]
[ROW][C]-1.46603585678454[/C][/ROW]
[ROW][C]10.2970302433447[/C][/ROW]
[ROW][C]-17.4202795266392[/C][/ROW]
[ROW][C]9.11687777733601[/C][/ROW]
[ROW][C]17.0394192801121[/C][/ROW]
[ROW][C]8.19516693723836[/C][/ROW]
[ROW][C]-9.60063917927087[/C][/ROW]
[ROW][C]-1.46068295426731[/C][/ROW]
[ROW][C]-3.2289150706764[/C][/ROW]
[ROW][C]-5.49455425461115[/C][/ROW]
[ROW][C]6.52874007680252[/C][/ROW]
[ROW][C]0.0700478921275509[/C][/ROW]
[ROW][C]-8.70409015124608[/C][/ROW]
[ROW][C]2.70488454549233[/C][/ROW]
[ROW][C]-6.44266317614946[/C][/ROW]
[ROW][C]1.37951957696978[/C][/ROW]
[ROW][C]1.67256111003965[/C][/ROW]
[ROW][C]-0.366890497398470[/C][/ROW]
[ROW][C]-1.30779836765487[/C][/ROW]
[ROW][C]-7.2188499274107[/C][/ROW]
[ROW][C]-0.0602583283628524[/C][/ROW]
[ROW][C]6.34987794214778[/C][/ROW]
[ROW][C]-8.5365896870992[/C][/ROW]
[ROW][C]-2.53689208377038[/C][/ROW]
[ROW][C]-1.59455319589641[/C][/ROW]
[ROW][C]-0.177706525718108[/C][/ROW]
[ROW][C]-3.42697291271657[/C][/ROW]
[ROW][C]-6.91410461247586[/C][/ROW]
[ROW][C]4.21920632827082[/C][/ROW]
[ROW][C]-1.5051088470175[/C][/ROW]
[ROW][C]-9.54557480984756[/C][/ROW]
[ROW][C]13.7444712278056[/C][/ROW]
[ROW][C]-3.64399804965439[/C][/ROW]
[ROW][C]-8.18429399897193[/C][/ROW]
[ROW][C]4.39036969183338[/C][/ROW]
[ROW][C]-7.53658234508268[/C][/ROW]
[ROW][C]0.824813048826962[/C][/ROW]
[ROW][C]-6.76172520478722[/C][/ROW]
[ROW][C]2.87625204867673[/C][/ROW]
[ROW][C]-7.23222531133672[/C][/ROW]
[ROW][C]17.8281607190264[/C][/ROW]
[ROW][C]-17.4243508125199[/C][/ROW]
[ROW][C]5.74006400880912[/C][/ROW]
[ROW][C]2.34880294646782[/C][/ROW]
[ROW][C]-8.71705004163573[/C][/ROW]
[ROW][C]0.180515148654599[/C][/ROW]
[ROW][C]0.411888011590863[/C][/ROW]
[ROW][C]-3.64129245468668[/C][/ROW]
[ROW][C]-0.262849417281658[/C][/ROW]
[ROW][C]-10.6960419754128[/C][/ROW]
[ROW][C]-1.24558421319947[/C][/ROW]
[ROW][C]9.24870255625867[/C][/ROW]
[ROW][C]-3.21841613993072[/C][/ROW]
[ROW][C]-5.12513973971504[/C][/ROW]
[ROW][C]7.0970248582296[/C][/ROW]
[ROW][C]-7.10456857488375[/C][/ROW]
[ROW][C]-6.93165440219085[/C][/ROW]
[ROW][C]-7.06770348981991[/C][/ROW]
[ROW][C]15.3750237413062[/C][/ROW]
[ROW][C]-7.70558344110681[/C][/ROW]
[ROW][C]0.377896979993898[/C][/ROW]
[ROW][C]-6.6757390204842[/C][/ROW]
[ROW][C]-4.51572160727773[/C][/ROW]
[ROW][C]-0.0505720049182764[/C][/ROW]
[ROW][C]26.5570261772454[/C][/ROW]
[ROW][C]-24.6216484357648[/C][/ROW]
[ROW][C]13.5317069122056[/C][/ROW]
[ROW][C]14.5288769435857[/C][/ROW]
[ROW][C]2.13533498546174[/C][/ROW]
[ROW][C]3.33852898616035[/C][/ROW]
[ROW][C]-11.4364766534799[/C][/ROW]
[ROW][C]18.9618532714349[/C][/ROW]
[ROW][C]-10.6090984426418[/C][/ROW]
[ROW][C]5.33161028294894[/C][/ROW]
[ROW][C]-17.2858133906791[/C][/ROW]
[ROW][C]4.52359461541178[/C][/ROW]
[ROW][C]0.089430796980405[/C][/ROW]
[ROW][C]-2.47733269172918[/C][/ROW]
[ROW][C]14.3520865451798[/C][/ROW]
[ROW][C]-5.75839557891212[/C][/ROW]
[ROW][C]7.64761494220882[/C][/ROW]
[ROW][C]-22.7595213775452[/C][/ROW]
[ROW][C]10.3405975911693[/C][/ROW]
[ROW][C]1.3596072827078[/C][/ROW]
[ROW][C]-0.636512109852905[/C][/ROW]
[ROW][C]-4.17710009767726[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65513&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65513&T=2

As an alternative you can also use a QR Code:  

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

Estimated ARIMA Residuals
Value
0.254999833678585
22.0637261808084
8.36506702663681
30.7736225164389
16.2536172739003
6.31978649995719
-12.541117501616
-2.71828068186466
-1.95485182804324
0.795323839092208
-6.27025377287568
3.35942030976075
-1.50205913407284
2.18998540092784
0.286527874254407
-8.33192720797185
1.33542284983531
-5.34660777953769
0.364188612555605
-12.3214965463108
-0.213044567062289
-1.73356760237912
2.29142250093452
-2.02682736956204
-3.29373825168995
-3.23571182705352
-5.615995118748
-1.23778396837417
-1.42061601175765
4.78655450552501
18.4793975643124
15.9725830862441
-0.815453366740222
0.0128967393884164
1.50544251506978
1.00271938473857
-11.8529674379466
12.1980261840451
-9.68599559713978
1.13547342393710
2.97921792827975
-0.785621719367919
8.0612033007036
-5.3827839300902
-8.17937461872397
-1.32446661791628
-10.6659441156235
-3.02656088860777
0.132458876970117
-13.8069274078262
0.845394639204114
-1.98702099406847
-1.68051929598893
0.0920394990564467
-5.16130221400508
-1.81108668490266
-2.30834063101787
-0.750037072168237
-5.3947253707732
8.7899235566845
-8.22983416568617
11.8176501211661
-7.38155547009886
0.66017315673276
-3.1132813129022
-1.74260226748968
-4.22016188206140
2.07668572745188
-3.68932481139297
-2.05347410919604
-1.70755960864552
0.0829944172946436
0.0525549970276853
-0.109176343264101
-1.75225518561125
-5.21419429128494
0.207419244972166
-2.04931938452986
-1.67050644923471
0.600794441571788
-3.91634951705187
0.914568891401787
0.377723332076606
-3.99940809812258
4.10028250058595
2.13034996185799
-5.01697363654706
0.88039167914142
-0.413243946878691
2.57141732481777
-0.160150074002167
-1.98942813155873
0.7674956209968
-0.213395806083973
-1.80123192327119
0.992418294813898
-0.95211431483235
1.83819052465494
-1.06894403308982
-0.967855575986486
-1.04385118507898
0.68556571118867
-0.333611701816567
-5.42973137859667
0.726314763980147
0.836961921847186
-1.54679449185316
-7.8797704326756
23.2308862131186
73.4327268612729
-14.6645292085857
-9.62846152611605
-4.66720646366489
3.8925108206267
-4.05357962489037
-5.35670102610004
-11.4983109457654
10.2692632816308
5.63923822623881
1.78510286719011
-1.64736847168137
-4.37111600313939
-0.876583756406526
-5.5740602532695
-4.21723385655859
3.50567394001677
-1.73390387012663
-7.46542812892844
8.0054837398301
4.18546728005985
-13.7313182373306
1.82878940228257
10.0155579065071
-3.37214346334616
-6.48996798141223
9.6473667518257
-5.69796739984453
0.371151024442422
5.30635805916157
-6.30971196519032
2.80333497540805
0.270046937839979
3.77981376962364
1.15533503538918
3.07905278265261
6.8737812354031
-4.5358851269508
9.01702970670762
1.16292889183652
0.43906294216717
5.71704440086086
-6.48195048465036
-3.3771192690953
-2.46183738505908
-9.4332170478525
10.0254880254123
-3.6516456200049
7.693301985708
-10.7057717832237
4.56866205647999
3.61676400060875
3.46179306421813
5.3878867826985
-5.26297325753655
1.49032895923109
0.36686024838641
-7.5732456232995
3.62764903211999
0.409731769739903
3.59745812899038
-9.0611941902361
7.31512435053738
-6.99945832309867
2.50056869596632
-7.1861942788887
-4.05022671664802
-1.21845103060777
3.03774182373883
-4.7921212364757
-3.42612756365544
4.87177621486511
-0.571983040663883
-6.99016600656002
-0.578214274045576
4.27589152699226
-6.22391088396299
3.63440273116448
-6.89605965031704
-5.80423260014768
-3.30945017603603
-8.89989135836323
0.260861313135902
-2.08392600299732
9.42271343761112
-5.77164971672163
0.584727813518678
-0.0832801114183283
-0.335508700929775
-1.28959513732277
-6.4970557028598
-0.0303888613728142
-9.1712080472086
4.44832241535643
1.41242818753703
2.72857369163921
-4.33717329448005
-2.06398916829018
-1.28737940523640
1.03389998358603
4.07815747299849
70.680390149993
79.9818416960065
-45.9300065960566
5.71397251462954
-0.0749843966945638
-0.266852026256099
9.10829932808554
-9.21407413321306
0.820808807789241
7.95052153138217
5.57603449472473
5.34408631927167
2.12906752858874
8.6944001894836
-2.20976120002873
-5.42264607294396
4.1062779034885
-0.0247656628911190
-10.5163680477176
12.1087027909069
-2.54802877509056
4.01787439149142
-6.41629534761968
6.56002640103825
-4.98879924592385
6.97282180701915
-6.00931791282875
6.76746248482652
-6.85198897035633
8.09124679413805
-2.37194657629316
4.90013519294542
18.4881168353484
31.7957991454662
6.80941613821293
26.6385275415374
7.4239153957207
2.27603064636658
-3.65879611664405
-13.7690645412414
6.04069899429226
-5.46277773511517
-0.72506330358951
4.1800135357596
13.2068834623433
-6.38897038378853
-0.0712758329369337
-3.93220420438954
6.6027471441143
-4.21094573244433
-1.64693460147216
-6.94276544661195
5.67403414201086
-2.03581550066680
3.11432108484884
-0.0903742286704932
6.96735622389218
-2.83373530847393
5.24744829558373
-8.78199410466493
5.26489849727183
0.118882356783456
-1.46603585678454
10.2970302433447
-17.4202795266392
9.11687777733601
17.0394192801121
8.19516693723836
-9.60063917927087
-1.46068295426731
-3.2289150706764
-5.49455425461115
6.52874007680252
0.0700478921275509
-8.70409015124608
2.70488454549233
-6.44266317614946
1.37951957696978
1.67256111003965
-0.366890497398470
-1.30779836765487
-7.2188499274107
-0.0602583283628524
6.34987794214778
-8.5365896870992
-2.53689208377038
-1.59455319589641
-0.177706525718108
-3.42697291271657
-6.91410461247586
4.21920632827082
-1.5051088470175
-9.54557480984756
13.7444712278056
-3.64399804965439
-8.18429399897193
4.39036969183338
-7.53658234508268
0.824813048826962
-6.76172520478722
2.87625204867673
-7.23222531133672
17.8281607190264
-17.4243508125199
5.74006400880912
2.34880294646782
-8.71705004163573
0.180515148654599
0.411888011590863
-3.64129245468668
-0.262849417281658
-10.6960419754128
-1.24558421319947
9.24870255625867
-3.21841613993072
-5.12513973971504
7.0970248582296
-7.10456857488375
-6.93165440219085
-7.06770348981991
15.3750237413062
-7.70558344110681
0.377896979993898
-6.6757390204842
-4.51572160727773
-0.0505720049182764
26.5570261772454
-24.6216484357648
13.5317069122056
14.5288769435857
2.13533498546174
3.33852898616035
-11.4364766534799
18.9618532714349
-10.6090984426418
5.33161028294894
-17.2858133906791
4.52359461541178
0.089430796980405
-2.47733269172918
14.3520865451798
-5.75839557891212
7.64761494220882
-22.7595213775452
10.3405975911693
1.3596072827078
-0.636512109852905
-4.17710009767726



Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 0 ; par9 = 0 ;
Parameters (R input):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 0 ; par9 = 0 ;
R code (references can be found in the software module):
library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- as.numeric(par5) #seasonal period
par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
par6 <- 3
par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
par7 <- 3
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')