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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 computationMon, 08 Dec 2008 06:52:11 -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/2008/Dec/08/t12287443969brp00yrdqz23df.htm/, Retrieved Thu, 31 Oct 2024 23:19:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30492, Retrieved Thu, 31 Oct 2024 23:19:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact234
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]
F RMP   [ARIMA Backward Selection] [Taak 10 Stap 5 AR...] [2008-12-03 22:04:14] [819b576fab25b35cfda70f80599828ec]
-   P       [ARIMA Backward Selection] [Opdracht 8 - Stap...] [2008-12-08 13:52:11] [f1a30f1149cef3ef3ef69d586c6c3c1c] [Current]
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Dataseries X:
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388.4
371.1
331.5
353.7
396.7
447
533.5
565.4
542.3
488.7
467.1
531.3
496.1
444
403.4
386.3
394.1
404.1
462.1
448.1
432.3
386.3
395.2
421.9
382.9
384.2
345.5
323.4
372.6
376
462.7
487
444.2
399.3
394.9
455.4
414
375.5
347
339.4
385.8
378.8
451.8
446.1
422.5
383.1
352.8
445.3
367.5
355.1
326.2
319.8
331.8
340.9
394.1
417.2
369.9
349.2
321.4
405.7
342.9
316.5
284.2
270.9
288.8
278.8
324.4
310.9
299
273
279.3
359.2
305
282.1
250.3
246.5
257.9
266.5
315.9
318.4
295.4
266.4
245.8
362.8
324.9
294.2
289.5
295.2
290.3
272
307.4
328.7
292.9
249.1
230.4
361.5
321.7
277.2
260.7
251
257.6
241.8
287.5
292.3
274.7
254.2
230
339
318.2
287
295.8
284
271
262.7
340.6
379.4
373.3
355.2
338.4
466.9
451
422
429.2
425.9
460.7
463.6
541.4
544.2
517.5
469.4
439.4
549
533
506.1
484
457
481.5
469.5
544.7
541.2
521.5
469.7
434.4
542.6
517.3
485.7
465.8
447
426.6
411.6
467.5
484.5
451.2
417.4
379.9
484.7
455
420.8
416.5
376.3
405.6
405.8
500.8
514
475.5
430.1
414.4
538
526
488.5
520.2
504.4
568.5
610.6
818
830.9
835.9
782
762.3
856.9
820.9
769.6
752.2
724.4
723.1
719.5
817.4
803.3
752.5
689
630.4
765.5
757.7
732.2
702.6
683.3
709.5
702.2
784.8
810.9
755.6
656.8
615.1
745.3
694.1
675.7
643.7
622.1
634.6
588
689.7
673.9
647.9
568.8
545.7
632.6
643.8
593.1
579.7
546
562.9
572.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time22 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 & 22 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30492&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]22 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=30492&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30492&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 time22 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2ar3ma1sar1sar2sma1
Estimates ( 1 )0.46070.1801-0.0062-0.3737-0.0967-0.0621-0.6433
(p-val)(0 )(0 )(0.147 )(0 )(0 )(0.0043 )(0 )
Estimates ( 2 )0.48660.17540-0.3973-0.1005-0.0616-0.6417
(p-val)(0.0054 )(0.0103 )(NA )(0.0223 )(0.3732 )(0.4941 )(0 )
Estimates ( 3 )0.47060.18360-0.3842-0.04620-0.6958
(p-val)(0.0074 )(0.0062 )(NA )(0.0293 )(0.5533 )(NA )(0 )
Estimates ( 4 )0.46170.18820-0.376700-0.7209
(p-val)(0.0078 )(0.0044 )(NA )(0.0307 )(NA )(NA )(0 )
Estimates ( 5 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 12 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 13 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & 0.4607 & 0.1801 & -0.0062 & -0.3737 & -0.0967 & -0.0621 & -0.6433 \tabularnewline
(p-val) & (0 ) & (0 ) & (0.147 ) & (0 ) & (0 ) & (0.0043 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.4866 & 0.1754 & 0 & -0.3973 & -0.1005 & -0.0616 & -0.6417 \tabularnewline
(p-val) & (0.0054 ) & (0.0103 ) & (NA ) & (0.0223 ) & (0.3732 ) & (0.4941 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0.4706 & 0.1836 & 0 & -0.3842 & -0.0462 & 0 & -0.6958 \tabularnewline
(p-val) & (0.0074 ) & (0.0062 ) & (NA ) & (0.0293 ) & (0.5533 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0.4617 & 0.1882 & 0 & -0.3767 & 0 & 0 & -0.7209 \tabularnewline
(p-val) & (0.0078 ) & (0.0044 ) & (NA ) & (0.0307 ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30492&T=1

[TABLE]
[ROW][C]ARIMA Parameter Estimation and Backward Selection[/C][/ROW]
[ROW][C]Iteration[/C][C]ar1[/C][C]ar2[/C][C]ar3[/C][C]ma1[/C][C]sar1[/C][C]sar2[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]0.4607[/C][C]0.1801[/C][C]-0.0062[/C][C]-0.3737[/C][C]-0.0967[/C][C]-0.0621[/C][C]-0.6433[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0 )[/C][C](0.147 )[/C][C](0 )[/C][C](0 )[/C][C](0.0043 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.4866[/C][C]0.1754[/C][C]0[/C][C]-0.3973[/C][C]-0.1005[/C][C]-0.0616[/C][C]-0.6417[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0054 )[/C][C](0.0103 )[/C][C](NA )[/C][C](0.0223 )[/C][C](0.3732 )[/C][C](0.4941 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0.4706[/C][C]0.1836[/C][C]0[/C][C]-0.3842[/C][C]-0.0462[/C][C]0[/C][C]-0.6958[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0074 )[/C][C](0.0062 )[/C][C](NA )[/C][C](0.0293 )[/C][C](0.5533 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0.4617[/C][C]0.1882[/C][C]0[/C][C]-0.3767[/C][C]0[/C][C]0[/C][C]-0.7209[/C][/ROW]
[ROW][C](p-val)[/C][C](0.0078 )[/C][C](0.0044 )[/C][C](NA )[/C][C](0.0307 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30492&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30492&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
Iterationar1ar2ar3ma1sar1sar2sma1
Estimates ( 1 )0.46070.1801-0.0062-0.3737-0.0967-0.0621-0.6433
(p-val)(0 )(0 )(0.147 )(0 )(0 )(0.0043 )(0 )
Estimates ( 2 )0.48660.17540-0.3973-0.1005-0.0616-0.6417
(p-val)(0.0054 )(0.0103 )(NA )(0.0223 )(0.3732 )(0.4941 )(0 )
Estimates ( 3 )0.47060.18360-0.3842-0.04620-0.6958
(p-val)(0.0074 )(0.0062 )(NA )(0.0293 )(0.5533 )(NA )(0 )
Estimates ( 4 )0.46170.18820-0.376700-0.7209
(p-val)(0.0078 )(0.0044 )(NA )(0.0307 )(NA )(NA )(0 )
Estimates ( 5 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 12 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 13 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )







Estimated ARIMA Residuals
Value
-0.0447135253960225
-0.0681917363421248
0.197918284222177
0.364977451074597
1.51337974853374
-0.359462346770864
0.457274701618375
-0.576200797223743
-0.35806159298279
1.26000921879800
-1.34266167067388
-0.353289536833081
0.161396045139561
-0.857822824071549
-0.555144480575985
-0.727027306896834
-0.369041527982607
-0.0578965046249842
-0.769036314017041
-0.853702996099126
0.700855327126076
-0.67605835057151
0.868578314018324
-0.108845849033489
-1.57887213540104
-1.12268894715059
0.396924811287499
0.0148501374104653
0.140259622902458
0.369865280208383
-0.279776174113751
0.304546119543323
0.892466305762528
0.0893796274958521
0.135269038003123
-1.20736792439930
-0.230372906495734
-0.0877968012618119
-0.33323266650054
0.601966581020134
0.489790368570760
-0.30040059136885
0.101350920891626
0.596346925270986
-0.476839102991622
-0.418379495419168
-0.117112854652920
-0.147180675626801
0.532294134646671
-0.976528372414816
0.331179899785833
0.869619582675694
-0.452578724852337
-0.421389632285535
-0.0683598944374235
0.326102832750419
0.84894940837525
0.455827472703429
0.823472792059655
0.933735481712974
1.23343828434357
0.408338767056766
0.287975024888324
-0.211204160843567
-0.267469446531546
-1.11645456256678
-0.0317245230877202
0.547972521125301
0.120802508791779
-0.868321690772969
-0.311155435761481
-0.380688690591098
-0.305618207625699
-0.409940481502841
-0.00967747172687254
0.495426680797454
-0.70434733099138
-0.0634697192462326
-0.513898520689418
0.589511832114578
-0.349423083406549
0.641305348572241
0.0343657044269518
-0.0527523752155572
-0.880138188317385
-0.110617568497234
0.725017900327504
-0.505210310136047
1.01506156059005
0.432165289840235
-0.605966973659667
-0.99965767981201
-0.273898172730602
0.276039109320686
1.00336917683793
0.0129975707447026
-0.560227463080412
-0.549704180559844
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\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0447135253960225 \tabularnewline
-0.0681917363421248 \tabularnewline
0.197918284222177 \tabularnewline
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1.26000921879800 \tabularnewline
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0.161396045139561 \tabularnewline
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0.700855327126076 \tabularnewline
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0.868578314018324 \tabularnewline
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-1.57887213540104 \tabularnewline
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0.396924811287499 \tabularnewline
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0.827781264436336 \tabularnewline
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0.161914543778047 \tabularnewline
0.157622162847613 \tabularnewline
0.301928829658718 \tabularnewline
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0.228470776412080 \tabularnewline
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1.12387579697604 \tabularnewline
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0.290323801161599 \tabularnewline
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-0.400592939434611 \tabularnewline
0.273305576912483 \tabularnewline
0.571671016934307 \tabularnewline
0.355106915028324 \tabularnewline
-0.598053523446333 \tabularnewline
0.0680124459677498 \tabularnewline
0.0825158104754481 \tabularnewline
-0.236688938906495 \tabularnewline
-0.720993011661793 \tabularnewline
0.445855834707783 \tabularnewline
-0.278184253464566 \tabularnewline
-0.813695595258521 \tabularnewline
0.0382227577078328 \tabularnewline
0.287981855878777 \tabularnewline
-0.397401149791228 \tabularnewline
0.45344200538109 \tabularnewline
-0.336993623900836 \tabularnewline
0.0350017590941607 \tabularnewline
-0.129073953075969 \tabularnewline
-0.929487174586825 \tabularnewline
0.112538667866079 \tabularnewline
-0.266214449984403 \tabularnewline
0.318919618407674 \tabularnewline
-0.235823651106797 \tabularnewline
0.312056159183962 \tabularnewline
-0.607348852365163 \tabularnewline
0.821439691373018 \tabularnewline
-0.330769451500635 \tabularnewline
-0.0368471782124595 \tabularnewline
-0.223411452689536 \tabularnewline
-0.0162392677684860 \tabularnewline
0.494328806219962 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30492&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0447135253960225[/C][/ROW]
[ROW][C]-0.0681917363421248[/C][/ROW]
[ROW][C]0.197918284222177[/C][/ROW]
[ROW][C]0.364977451074597[/C][/ROW]
[ROW][C]1.51337974853374[/C][/ROW]
[ROW][C]-0.359462346770864[/C][/ROW]
[ROW][C]0.457274701618375[/C][/ROW]
[ROW][C]-0.576200797223743[/C][/ROW]
[ROW][C]-0.35806159298279[/C][/ROW]
[ROW][C]1.26000921879800[/C][/ROW]
[ROW][C]-1.34266167067388[/C][/ROW]
[ROW][C]-0.353289536833081[/C][/ROW]
[ROW][C]0.161396045139561[/C][/ROW]
[ROW][C]-0.857822824071549[/C][/ROW]
[ROW][C]-0.555144480575985[/C][/ROW]
[ROW][C]-0.727027306896834[/C][/ROW]
[ROW][C]-0.369041527982607[/C][/ROW]
[ROW][C]-0.0578965046249842[/C][/ROW]
[ROW][C]-0.769036314017041[/C][/ROW]
[ROW][C]-0.853702996099126[/C][/ROW]
[ROW][C]0.700855327126076[/C][/ROW]
[ROW][C]-0.67605835057151[/C][/ROW]
[ROW][C]0.868578314018324[/C][/ROW]
[ROW][C]-0.108845849033489[/C][/ROW]
[ROW][C]-1.57887213540104[/C][/ROW]
[ROW][C]-1.12268894715059[/C][/ROW]
[ROW][C]0.396924811287499[/C][/ROW]
[ROW][C]0.0148501374104653[/C][/ROW]
[ROW][C]0.140259622902458[/C][/ROW]
[ROW][C]0.369865280208383[/C][/ROW]
[ROW][C]-0.279776174113751[/C][/ROW]
[ROW][C]0.304546119543323[/C][/ROW]
[ROW][C]0.892466305762528[/C][/ROW]
[ROW][C]0.0893796274958521[/C][/ROW]
[ROW][C]0.135269038003123[/C][/ROW]
[ROW][C]-1.20736792439930[/C][/ROW]
[ROW][C]-0.230372906495734[/C][/ROW]
[ROW][C]-0.0877968012618119[/C][/ROW]
[ROW][C]-0.33323266650054[/C][/ROW]
[ROW][C]0.601966581020134[/C][/ROW]
[ROW][C]0.489790368570760[/C][/ROW]
[ROW][C]-0.30040059136885[/C][/ROW]
[ROW][C]0.101350920891626[/C][/ROW]
[ROW][C]0.596346925270986[/C][/ROW]
[ROW][C]-0.476839102991622[/C][/ROW]
[ROW][C]-0.418379495419168[/C][/ROW]
[ROW][C]-0.117112854652920[/C][/ROW]
[ROW][C]-0.147180675626801[/C][/ROW]
[ROW][C]0.532294134646671[/C][/ROW]
[ROW][C]-0.976528372414816[/C][/ROW]
[ROW][C]0.331179899785833[/C][/ROW]
[ROW][C]0.869619582675694[/C][/ROW]
[ROW][C]-0.452578724852337[/C][/ROW]
[ROW][C]-0.421389632285535[/C][/ROW]
[ROW][C]-0.0683598944374235[/C][/ROW]
[ROW][C]0.326102832750419[/C][/ROW]
[ROW][C]0.84894940837525[/C][/ROW]
[ROW][C]0.455827472703429[/C][/ROW]
[ROW][C]0.823472792059655[/C][/ROW]
[ROW][C]0.933735481712974[/C][/ROW]
[ROW][C]1.23343828434357[/C][/ROW]
[ROW][C]0.408338767056766[/C][/ROW]
[ROW][C]0.287975024888324[/C][/ROW]
[ROW][C]-0.211204160843567[/C][/ROW]
[ROW][C]-0.267469446531546[/C][/ROW]
[ROW][C]-1.11645456256678[/C][/ROW]
[ROW][C]-0.0317245230877202[/C][/ROW]
[ROW][C]0.547972521125301[/C][/ROW]
[ROW][C]0.120802508791779[/C][/ROW]
[ROW][C]-0.868321690772969[/C][/ROW]
[ROW][C]-0.311155435761481[/C][/ROW]
[ROW][C]-0.380688690591098[/C][/ROW]
[ROW][C]-0.305618207625699[/C][/ROW]
[ROW][C]-0.409940481502841[/C][/ROW]
[ROW][C]-0.00967747172687254[/C][/ROW]
[ROW][C]0.495426680797454[/C][/ROW]
[ROW][C]-0.70434733099138[/C][/ROW]
[ROW][C]-0.0634697192462326[/C][/ROW]
[ROW][C]-0.513898520689418[/C][/ROW]
[ROW][C]0.589511832114578[/C][/ROW]
[ROW][C]-0.349423083406549[/C][/ROW]
[ROW][C]0.641305348572241[/C][/ROW]
[ROW][C]0.0343657044269518[/C][/ROW]
[ROW][C]-0.0527523752155572[/C][/ROW]
[ROW][C]-0.880138188317385[/C][/ROW]
[ROW][C]-0.110617568497234[/C][/ROW]
[ROW][C]0.725017900327504[/C][/ROW]
[ROW][C]-0.505210310136047[/C][/ROW]
[ROW][C]1.01506156059005[/C][/ROW]
[ROW][C]0.432165289840235[/C][/ROW]
[ROW][C]-0.605966973659667[/C][/ROW]
[ROW][C]-0.99965767981201[/C][/ROW]
[ROW][C]-0.273898172730602[/C][/ROW]
[ROW][C]0.276039109320686[/C][/ROW]
[ROW][C]1.00336917683793[/C][/ROW]
[ROW][C]0.0129975707447026[/C][/ROW]
[ROW][C]-0.560227463080412[/C][/ROW]
[ROW][C]-0.549704180559844[/C][/ROW]
[ROW][C]-0.264710308451806[/C][/ROW]
[ROW][C]0.279629152070149[/C][/ROW]
[ROW][C]0.678639057401087[/C][/ROW]
[ROW][C]0.661068987945098[/C][/ROW]
[ROW][C]-0.704450849658691[/C][/ROW]
[ROW][C]-0.201260637302684[/C][/ROW]
[ROW][C]0.350125495958601[/C][/ROW]
[ROW][C]0.51207399543742[/C][/ROW]
[ROW][C]0.855206697928782[/C][/ROW]
[ROW][C]0.194069017384391[/C][/ROW]
[ROW][C]0.723928491599931[/C][/ROW]
[ROW][C]1.1813100622767[/C][/ROW]
[ROW][C]0.142880603048506[/C][/ROW]
[ROW][C]0.0179250176101248[/C][/ROW]
[ROW][C]-0.497957163141791[/C][/ROW]
[ROW][C]-0.299719858005128[/C][/ROW]
[ROW][C]0.135788254277837[/C][/ROW]
[ROW][C]-0.170331294462608[/C][/ROW]
[ROW][C]-1.03309845887421[/C][/ROW]
[ROW][C]-0.173818867620375[/C][/ROW]
[ROW][C]-0.963023604159095[/C][/ROW]
[ROW][C]0.698380354889[/C][/ROW]
[ROW][C]-0.367088748962493[/C][/ROW]
[ROW][C]-0.263848199408000[/C][/ROW]
[ROW][C]-0.418818686259234[/C][/ROW]
[ROW][C]-1.12067646578046[/C][/ROW]
[ROW][C]0.0500591744429748[/C][/ROW]
[ROW][C]0.608904151186532[/C][/ROW]
[ROW][C]0.134690460462483[/C][/ROW]
[ROW][C]0.33004133104308[/C][/ROW]
[ROW][C]0.127838527435568[/C][/ROW]
[ROW][C]0.581318960613691[/C][/ROW]
[ROW][C]-0.0387083124201542[/C][/ROW]
[ROW][C]-0.870097428406274[/C][/ROW]
[ROW][C]-0.46211368029843[/C][/ROW]
[ROW][C]-0.775456171566771[/C][/ROW]
[ROW][C]1.39586997252140[/C][/ROW]
[ROW][C]-0.373271811454794[/C][/ROW]
[ROW][C]-0.268080285209629[/C][/ROW]
[ROW][C]1.08656249985181[/C][/ROW]
[ROW][C]-0.325880205863577[/C][/ROW]
[ROW][C]0.306618345261008[/C][/ROW]
[ROW][C]-0.552774334353198[/C][/ROW]
[ROW][C]0.92873555615258[/C][/ROW]
[ROW][C]0.0930551939788035[/C][/ROW]
[ROW][C]0.793725089311601[/C][/ROW]
[ROW][C]-0.065520090108497[/C][/ROW]
[ROW][C]0.319389284571386[/C][/ROW]
[ROW][C]-0.46622517579406[/C][/ROW]
[ROW][C]-0.262872950917163[/C][/ROW]
[ROW][C]0.0101377862503099[/C][/ROW]
[ROW][C]0.166709648190932[/C][/ROW]
[ROW][C]-0.279488745822847[/C][/ROW]
[ROW][C]-0.416437688916389[/C][/ROW]
[ROW][C]-0.22115546346038[/C][/ROW]
[ROW][C]-0.180257621944250[/C][/ROW]
[ROW][C]-0.698512011653876[/C][/ROW]
[ROW][C]-0.0309656726131541[/C][/ROW]
[ROW][C]-0.218026906428136[/C][/ROW]
[ROW][C]-0.373584097623305[/C][/ROW]
[ROW][C]0.052951771649411[/C][/ROW]
[ROW][C]0.162727178662852[/C][/ROW]
[ROW][C]0.827781264436336[/C][/ROW]
[ROW][C]-0.724326083790065[/C][/ROW]
[ROW][C]-0.470004768297604[/C][/ROW]
[ROW][C]1.04570519030629[/C][/ROW]
[ROW][C]-0.192863515103884[/C][/ROW]
[ROW][C]-0.571180444692155[/C][/ROW]
[ROW][C]0.531291251566343[/C][/ROW]
[ROW][C]-0.305718253125133[/C][/ROW]
[ROW][C]0.33805003414274[/C][/ROW]
[ROW][C]0.476242057434918[/C][/ROW]
[ROW][C]-0.813898733638944[/C][/ROW]
[ROW][C]-0.0347525563928053[/C][/ROW]
[ROW][C]0.307275497587149[/C][/ROW]
[ROW][C]0.298265382877775[/C][/ROW]
[ROW][C]-0.356205719078896[/C][/ROW]
[ROW][C]-0.356604197590328[/C][/ROW]
[ROW][C]0.161914543778047[/C][/ROW]
[ROW][C]0.157622162847613[/C][/ROW]
[ROW][C]0.301928829658718[/C][/ROW]
[ROW][C]-0.561982089534344[/C][/ROW]
[ROW][C]-0.054344347508442[/C][/ROW]
[ROW][C]-0.242625267253262[/C][/ROW]
[ROW][C]-0.0291186961212278[/C][/ROW]
[ROW][C]0.228470776412080[/C][/ROW]
[ROW][C]-0.510675358256579[/C][/ROW]
[ROW][C]1.12387579697604[/C][/ROW]
[ROW][C]-1.12598819760342[/C][/ROW]
[ROW][C]0.290323801161599[/C][/ROW]
[ROW][C]0.190186300269668[/C][/ROW]
[ROW][C]0.0853118886191468[/C][/ROW]
[ROW][C]-0.708039034695266[/C][/ROW]
[ROW][C]0.0821218447021978[/C][/ROW]
[ROW][C]-0.307060659060198[/C][/ROW]
[ROW][C]0.525053530012375[/C][/ROW]
[ROW][C]-0.601608762786724[/C][/ROW]
[ROW][C]0.538181952703111[/C][/ROW]
[ROW][C]-0.306512089790133[/C][/ROW]
[ROW][C]0.654542109027372[/C][/ROW]
[ROW][C]-0.537375053347636[/C][/ROW]
[ROW][C]-0.186945164903575[/C][/ROW]
[ROW][C]-0.0415284808030801[/C][/ROW]
[ROW][C]-0.0882629264500877[/C][/ROW]
[ROW][C]-0.256492242506079[/C][/ROW]
[ROW][C]-0.413059044491092[/C][/ROW]
[ROW][C]-0.270151412032309[/C][/ROW]
[ROW][C]-0.435615332936426[/C][/ROW]
[ROW][C]0.546649723056766[/C][/ROW]
[ROW][C]0.323884703994657[/C][/ROW]
[ROW][C]0.661931879765847[/C][/ROW]
[ROW][C]0.402774072398312[/C][/ROW]
[ROW][C]-0.428180087570848[/C][/ROW]
[ROW][C]-0.185363916598877[/C][/ROW]
[ROW][C]-0.146275794492277[/C][/ROW]
[ROW][C]0.177901356497660[/C][/ROW]
[ROW][C]-0.370503402127386[/C][/ROW]
[ROW][C]0.205238744482440[/C][/ROW]
[ROW][C]-0.0894107314201245[/C][/ROW]
[ROW][C]-0.0207802774234968[/C][/ROW]
[ROW][C]-0.00240147466918447[/C][/ROW]
[ROW][C]0.0272373003487647[/C][/ROW]
[ROW][C]-0.304012066368563[/C][/ROW]
[ROW][C]1.50787095266035[/C][/ROW]
[ROW][C]0.259049422299152[/C][/ROW]
[ROW][C]-0.546358234600257[/C][/ROW]
[ROW][C]0.581469091275693[/C][/ROW]
[ROW][C]0.330213566204811[/C][/ROW]
[ROW][C]-0.983366983108753[/C][/ROW]
[ROW][C]-0.736262917615728[/C][/ROW]
[ROW][C]-0.338743982691545[/C][/ROW]
[ROW][C]0.760537651914641[/C][/ROW]
[ROW][C]-0.261709498346797[/C][/ROW]
[ROW][C]-0.47604803547735[/C][/ROW]
[ROW][C]-0.110367517983504[/C][/ROW]
[ROW][C]1.69081027549721[/C][/ROW]
[ROW][C]0.149871596331350[/C][/ROW]
[ROW][C]-0.894444542196924[/C][/ROW]
[ROW][C]0.0854708075667523[/C][/ROW]
[ROW][C]-0.117915923744172[/C][/ROW]
[ROW][C]-0.215892880169748[/C][/ROW]
[ROW][C]-0.394091945119024[/C][/ROW]
[ROW][C]0.0924265412117942[/C][/ROW]
[ROW][C]0.0585918903210802[/C][/ROW]
[ROW][C]0.253245928619104[/C][/ROW]
[ROW][C]0.370567963868723[/C][/ROW]
[ROW][C]-0.38652413184425[/C][/ROW]
[ROW][C]0.447110927340878[/C][/ROW]
[ROW][C]0.623154200281104[/C][/ROW]
[ROW][C]-0.184203534512804[/C][/ROW]
[ROW][C]0.70547796714482[/C][/ROW]
[ROW][C]-0.317031093509232[/C][/ROW]
[ROW][C]-0.92747549796465[/C][/ROW]
[ROW][C]-0.039375681616147[/C][/ROW]
[ROW][C]1.00274784411106[/C][/ROW]
[ROW][C]0.812619095704321[/C][/ROW]
[ROW][C]0.298292892235012[/C][/ROW]
[ROW][C]0.152550524539197[/C][/ROW]
[ROW][C]-0.150639740840877[/C][/ROW]
[ROW][C]0.110741666419495[/C][/ROW]
[ROW][C]0.552786388883019[/C][/ROW]
[ROW][C]0.0434949724888247[/C][/ROW]
[ROW][C]0.363209473863399[/C][/ROW]
[ROW][C]-0.0227973565953720[/C][/ROW]
[ROW][C]0.504138360948928[/C][/ROW]
[ROW][C]0.138778955376779[/C][/ROW]
[ROW][C]-0.0853038304936802[/C][/ROW]
[ROW][C]-0.496485082805071[/C][/ROW]
[ROW][C]-0.0852251450917002[/C][/ROW]
[ROW][C]-0.247830857149674[/C][/ROW]
[ROW][C]-0.120849074890955[/C][/ROW]
[ROW][C]-0.451770068374317[/C][/ROW]
[ROW][C]0.612150763626651[/C][/ROW]
[ROW][C]0.35062535298691[/C][/ROW]
[ROW][C]-0.35929067221423[/C][/ROW]
[ROW][C]-0.484436552186736[/C][/ROW]
[ROW][C]0.339431103527959[/C][/ROW]
[ROW][C]-0.0417943935488771[/C][/ROW]
[ROW][C]-0.0100069109609526[/C][/ROW]
[ROW][C]-0.403912584026003[/C][/ROW]
[ROW][C]0.151831352275733[/C][/ROW]
[ROW][C]-0.229700910015304[/C][/ROW]
[ROW][C]-0.217361534162363[/C][/ROW]
[ROW][C]-0.332188782691632[/C][/ROW]
[ROW][C]0.264418283965544[/C][/ROW]
[ROW][C]0.176869530719773[/C][/ROW]
[ROW][C]-0.176677848623492[/C][/ROW]
[ROW][C]-0.135670353522087[/C][/ROW]
[ROW][C]-0.827944073126056[/C][/ROW]
[ROW][C]-0.0722730790378322[/C][/ROW]
[ROW][C]-0.117607467218364[/C][/ROW]
[ROW][C]0.314635302823227[/C][/ROW]
[ROW][C]-0.154386069584883[/C][/ROW]
[ROW][C]0.163002829796398[/C][/ROW]
[ROW][C]-0.244739185557085[/C][/ROW]
[ROW][C]-0.204481508560033[/C][/ROW]
[ROW][C]0.0360261045935815[/C][/ROW]
[ROW][C]0.00417180929449017[/C][/ROW]
[ROW][C]0.266111923849542[/C][/ROW]
[ROW][C]-0.65100315551287[/C][/ROW]
[ROW][C]0.589994645813113[/C][/ROW]
[ROW][C]0.312322966733607[/C][/ROW]
[ROW][C]0.552669708368232[/C][/ROW]
[ROW][C]-0.0962290660197571[/C][/ROW]
[ROW][C]-0.467083890564838[/C][/ROW]
[ROW][C]-0.198196760456308[/C][/ROW]
[ROW][C]0.395575462290874[/C][/ROW]
[ROW][C]0.175735179347610[/C][/ROW]
[ROW][C]0.315653466585352[/C][/ROW]
[ROW][C]-0.161149292211250[/C][/ROW]
[ROW][C]0.88204080346832[/C][/ROW]
[ROW][C]0.0637844933947768[/C][/ROW]
[ROW][C]0.858633498510782[/C][/ROW]
[ROW][C]0.822761091616062[/C][/ROW]
[ROW][C]1.77266813303013[/C][/ROW]
[ROW][C]-0.566982300074028[/C][/ROW]
[ROW][C]0.153260805137179[/C][/ROW]
[ROW][C]-0.279233420311874[/C][/ROW]
[ROW][C]0.0495717686133491[/C][/ROW]
[ROW][C]-1.16973347629522[/C][/ROW]
[ROW][C]-0.0821091546617858[/C][/ROW]
[ROW][C]0.0681024760498389[/C][/ROW]
[ROW][C]-0.201544761070500[/C][/ROW]
[ROW][C]0.0764371954094521[/C][/ROW]
[ROW][C]-0.526359969868041[/C][/ROW]
[ROW][C]-0.0804137024998847[/C][/ROW]
[ROW][C]-0.390603365076393[/C][/ROW]
[ROW][C]-0.366201255689232[/C][/ROW]
[ROW][C]-0.236325223213095[/C][/ROW]
[ROW][C]-0.0197745234670869[/C][/ROW]
[ROW][C]-0.400592939434611[/C][/ROW]
[ROW][C]0.273305576912483[/C][/ROW]
[ROW][C]0.571671016934307[/C][/ROW]
[ROW][C]0.355106915028324[/C][/ROW]
[ROW][C]-0.598053523446333[/C][/ROW]
[ROW][C]0.0680124459677498[/C][/ROW]
[ROW][C]0.0825158104754481[/C][/ROW]
[ROW][C]-0.236688938906495[/C][/ROW]
[ROW][C]-0.720993011661793[/C][/ROW]
[ROW][C]0.445855834707783[/C][/ROW]
[ROW][C]-0.278184253464566[/C][/ROW]
[ROW][C]-0.813695595258521[/C][/ROW]
[ROW][C]0.0382227577078328[/C][/ROW]
[ROW][C]0.287981855878777[/C][/ROW]
[ROW][C]-0.397401149791228[/C][/ROW]
[ROW][C]0.45344200538109[/C][/ROW]
[ROW][C]-0.336993623900836[/C][/ROW]
[ROW][C]0.0350017590941607[/C][/ROW]
[ROW][C]-0.129073953075969[/C][/ROW]
[ROW][C]-0.929487174586825[/C][/ROW]
[ROW][C]0.112538667866079[/C][/ROW]
[ROW][C]-0.266214449984403[/C][/ROW]
[ROW][C]0.318919618407674[/C][/ROW]
[ROW][C]-0.235823651106797[/C][/ROW]
[ROW][C]0.312056159183962[/C][/ROW]
[ROW][C]-0.607348852365163[/C][/ROW]
[ROW][C]0.821439691373018[/C][/ROW]
[ROW][C]-0.330769451500635[/C][/ROW]
[ROW][C]-0.0368471782124595[/C][/ROW]
[ROW][C]-0.223411452689536[/C][/ROW]
[ROW][C]-0.0162392677684860[/C][/ROW]
[ROW][C]0.494328806219962[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30492&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30492&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
-0.0447135253960225
-0.0681917363421248
0.197918284222177
0.364977451074597
1.51337974853374
-0.359462346770864
0.457274701618375
-0.576200797223743
-0.35806159298279
1.26000921879800
-1.34266167067388
-0.353289536833081
0.161396045139561
-0.857822824071549
-0.555144480575985
-0.727027306896834
-0.369041527982607
-0.0578965046249842
-0.769036314017041
-0.853702996099126
0.700855327126076
-0.67605835057151
0.868578314018324
-0.108845849033489
-1.57887213540104
-1.12268894715059
0.396924811287499
0.0148501374104653
0.140259622902458
0.369865280208383
-0.279776174113751
0.304546119543323
0.892466305762528
0.0893796274958521
0.135269038003123
-1.20736792439930
-0.230372906495734
-0.0877968012618119
-0.33323266650054
0.601966581020134
0.489790368570760
-0.30040059136885
0.101350920891626
0.596346925270986
-0.476839102991622
-0.418379495419168
-0.117112854652920
-0.147180675626801
0.532294134646671
-0.976528372414816
0.331179899785833
0.869619582675694
-0.452578724852337
-0.421389632285535
-0.0683598944374235
0.326102832750419
0.84894940837525
0.455827472703429
0.823472792059655
0.933735481712974
1.23343828434357
0.408338767056766
0.287975024888324
-0.211204160843567
-0.267469446531546
-1.11645456256678
-0.0317245230877202
0.547972521125301
0.120802508791779
-0.868321690772969
-0.311155435761481
-0.380688690591098
-0.305618207625699
-0.409940481502841
-0.00967747172687254
0.495426680797454
-0.70434733099138
-0.0634697192462326
-0.513898520689418
0.589511832114578
-0.349423083406549
0.641305348572241
0.0343657044269518
-0.0527523752155572
-0.880138188317385
-0.110617568497234
0.725017900327504
-0.505210310136047
1.01506156059005
0.432165289840235
-0.605966973659667
-0.99965767981201
-0.273898172730602
0.276039109320686
1.00336917683793
0.0129975707447026
-0.560227463080412
-0.549704180559844
-0.264710308451806
0.279629152070149
0.678639057401087
0.661068987945098
-0.704450849658691
-0.201260637302684
0.350125495958601
0.51207399543742
0.855206697928782
0.194069017384391
0.723928491599931
1.1813100622767
0.142880603048506
0.0179250176101248
-0.497957163141791
-0.299719858005128
0.135788254277837
-0.170331294462608
-1.03309845887421
-0.173818867620375
-0.963023604159095
0.698380354889
-0.367088748962493
-0.263848199408000
-0.418818686259234
-1.12067646578046
0.0500591744429748
0.608904151186532
0.134690460462483
0.33004133104308
0.127838527435568
0.581318960613691
-0.0387083124201542
-0.870097428406274
-0.46211368029843
-0.775456171566771
1.39586997252140
-0.373271811454794
-0.268080285209629
1.08656249985181
-0.325880205863577
0.306618345261008
-0.552774334353198
0.92873555615258
0.0930551939788035
0.793725089311601
-0.065520090108497
0.319389284571386
-0.46622517579406
-0.262872950917163
0.0101377862503099
0.166709648190932
-0.279488745822847
-0.416437688916389
-0.22115546346038
-0.180257621944250
-0.698512011653876
-0.0309656726131541
-0.218026906428136
-0.373584097623305
0.052951771649411
0.162727178662852
0.827781264436336
-0.724326083790065
-0.470004768297604
1.04570519030629
-0.192863515103884
-0.571180444692155
0.531291251566343
-0.305718253125133
0.33805003414274
0.476242057434918
-0.813898733638944
-0.0347525563928053
0.307275497587149
0.298265382877775
-0.356205719078896
-0.356604197590328
0.161914543778047
0.157622162847613
0.301928829658718
-0.561982089534344
-0.054344347508442
-0.242625267253262
-0.0291186961212278
0.228470776412080
-0.510675358256579
1.12387579697604
-1.12598819760342
0.290323801161599
0.190186300269668
0.0853118886191468
-0.708039034695266
0.0821218447021978
-0.307060659060198
0.525053530012375
-0.601608762786724
0.538181952703111
-0.306512089790133
0.654542109027372
-0.537375053347636
-0.186945164903575
-0.0415284808030801
-0.0882629264500877
-0.256492242506079
-0.413059044491092
-0.270151412032309
-0.435615332936426
0.546649723056766
0.323884703994657
0.661931879765847
0.402774072398312
-0.428180087570848
-0.185363916598877
-0.146275794492277
0.177901356497660
-0.370503402127386
0.205238744482440
-0.0894107314201245
-0.0207802774234968
-0.00240147466918447
0.0272373003487647
-0.304012066368563
1.50787095266035
0.259049422299152
-0.546358234600257
0.581469091275693
0.330213566204811
-0.983366983108753
-0.736262917615728
-0.338743982691545
0.760537651914641
-0.261709498346797
-0.47604803547735
-0.110367517983504
1.69081027549721
0.149871596331350
-0.894444542196924
0.0854708075667523
-0.117915923744172
-0.215892880169748
-0.394091945119024
0.0924265412117942
0.0585918903210802
0.253245928619104
0.370567963868723
-0.38652413184425
0.447110927340878
0.623154200281104
-0.184203534512804
0.70547796714482
-0.317031093509232
-0.92747549796465
-0.039375681616147
1.00274784411106
0.812619095704321
0.298292892235012
0.152550524539197
-0.150639740840877
0.110741666419495
0.552786388883019
0.0434949724888247
0.363209473863399
-0.0227973565953720
0.504138360948928
0.138778955376779
-0.0853038304936802
-0.496485082805071
-0.0852251450917002
-0.247830857149674
-0.120849074890955
-0.451770068374317
0.612150763626651
0.35062535298691
-0.35929067221423
-0.484436552186736
0.339431103527959
-0.0417943935488771
-0.0100069109609526
-0.403912584026003
0.151831352275733
-0.229700910015304
-0.217361534162363
-0.332188782691632
0.264418283965544
0.176869530719773
-0.176677848623492
-0.135670353522087
-0.827944073126056
-0.0722730790378322
-0.117607467218364
0.314635302823227
-0.154386069584883
0.163002829796398
-0.244739185557085
-0.204481508560033
0.0360261045935815
0.00417180929449017
0.266111923849542
-0.65100315551287
0.589994645813113
0.312322966733607
0.552669708368232
-0.0962290660197571
-0.467083890564838
-0.198196760456308
0.395575462290874
0.175735179347610
0.315653466585352
-0.161149292211250
0.88204080346832
0.0637844933947768
0.858633498510782
0.822761091616062
1.77266813303013
-0.566982300074028
0.153260805137179
-0.279233420311874
0.0495717686133491
-1.16973347629522
-0.0821091546617858
0.0681024760498389
-0.201544761070500
0.0764371954094521
-0.526359969868041
-0.0804137024998847
-0.390603365076393
-0.366201255689232
-0.236325223213095
-0.0197745234670869
-0.400592939434611
0.273305576912483
0.571671016934307
0.355106915028324
-0.598053523446333
0.0680124459677498
0.0825158104754481
-0.236688938906495
-0.720993011661793
0.445855834707783
-0.278184253464566
-0.813695595258521
0.0382227577078328
0.287981855878777
-0.397401149791228
0.45344200538109
-0.336993623900836
0.0350017590941607
-0.129073953075969
-0.929487174586825
0.112538667866079
-0.266214449984403
0.318919618407674
-0.235823651106797
0.312056159183962
-0.607348852365163
0.821439691373018
-0.330769451500635
-0.0368471782124595
-0.223411452689536
-0.0162392677684860
0.494328806219962



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
R code (references can be found in the software module):
library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- as.numeric(par5) #seasonal period
par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial
par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial
armaGR <- function(arima.out, names, n){
try1 <- arima.out$coef
try2 <- sqrt(diag(arima.out$var.coef))
try.data.frame <- data.frame(matrix(NA,ncol=4,nrow=length(names)))
dimnames(try.data.frame) <- list(names,c('coef','std','tstat','pv'))
try.data.frame[,1] <- try1
for(i in 1:length(try2)) try.data.frame[which(rownames(try.data.frame)==names(try2)[i]),2] <- try2[i]
try.data.frame[,3] <- try.data.frame[,1] / try.data.frame[,2]
try.data.frame[,4] <- round((1-pt(abs(try.data.frame[,3]),df=n-(length(try2)+1)))*2,5)
vector <- rep(NA,length(names))
vector[is.na(try.data.frame[,4])] <- 0
maxi <- which.max(try.data.frame[,4])
continue <- max(try.data.frame[,4],na.rm=TRUE) > .05
vector[maxi] <- 0
list(summary=try.data.frame,next.vector=vector,continue=continue)
}
arimaSelect <- function(series, order=c(13,0,0), seasonal=list(order=c(2,0,0),period=12), include.mean=F){
nrc <- order[1]+order[3]+seasonal$order[1]+seasonal$order[3]
coeff <- matrix(NA, nrow=nrc*2, ncol=nrc)
pval <- matrix(NA, nrow=nrc*2, ncol=nrc)
mylist <- rep(list(NULL), nrc)
names <- NULL
if(order[1] > 0) names <- paste('ar',1:order[1],sep='')
if(order[3] > 0) names <- c( names , paste('ma',1:order[3],sep='') )
if(seasonal$order[1] > 0) names <- c(names, paste('sar',1:seasonal$order[1],sep=''))
if(seasonal$order[3] > 0) names <- c(names, paste('sma',1:seasonal$order[3],sep=''))
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML')
mylist[[1]] <- arima.out
last.arma <- armaGR(arima.out, names, length(series))
mystop <- FALSE
i <- 1
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- 2
aic <- arima.out$aic
while(!mystop){
mylist[[i]] <- arima.out
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML', fixed=last.arma$next.vector)
aic <- c(aic, arima.out$aic)
last.arma <- armaGR(arima.out, names, length(series))
mystop <- !last.arma$continue
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- i+1
}
list(coeff, pval, mylist, aic=aic)
}
arimaSelectplot <- function(arimaSelect.out,noms,choix){
noms <- names(arimaSelect.out[[3]][[1]]$coef)
coeff <- arimaSelect.out[[1]]
k <- min(which(is.na(coeff[,1])))-1
coeff <- coeff[1:k,]
pval <- arimaSelect.out[[2]][1:k,]
aic <- arimaSelect.out$aic[1:k]
coeff[coeff==0] <- NA
n <- ncol(coeff)
if(missing(choix)) choix <- k
layout(matrix(c(1,1,1,2,
3,3,3,2,
3,3,3,4,
5,6,7,7),nr=4),
widths=c(10,35,45,15),
heights=c(30,30,15,15))
couleurs <- rainbow(75)[1:50]#(50)
ticks <- pretty(coeff)
par(mar=c(1,1,3,1))
plot(aic,k:1-.5,type='o',pch=21,bg='blue',cex=2,axes=F,lty=2,xpd=NA)
points(aic[choix],k-choix+.5,pch=21,cex=4,bg=2,xpd=NA)
title('aic',line=2)
par(mar=c(3,0,0,0))
plot(0,axes=F,xlab='',ylab='',xlim=range(ticks),ylim=c(.1,1))
rect(xleft = min(ticks) + (0:49)/50*(max(ticks)-min(ticks)),
xright = min(ticks) + (1:50)/50*(max(ticks)-min(ticks)),
ytop = rep(1,50),
ybottom= rep(0,50),col=couleurs,border=NA)
axis(1,ticks)
rect(xleft=min(ticks),xright=max(ticks),ytop=1,ybottom=0)
text(mean(coeff,na.rm=T),.5,'coefficients',cex=2,font=2)
par(mar=c(1,1,3,1))
image(1:n,1:k,t(coeff[k:1,]),axes=F,col=couleurs,zlim=range(ticks))
for(i in 1:n) for(j in 1:k) if(!is.na(coeff[j,i])) {
if(pval[j,i]<.01) symb = 'green'
else if( (pval[j,i]<.05) & (pval[j,i]>=.01)) symb = 'orange'
else if( (pval[j,i]<.1) & (pval[j,i]>=.05)) symb = 'red'
else symb = 'black'
polygon(c(i+.5 ,i+.2 ,i+.5 ,i+.5),
c(k-j+0.5,k-j+0.5,k-j+0.8,k-j+0.5),
col=symb)
if(j==choix) {
rect(xleft=i-.5,
xright=i+.5,
ybottom=k-j+1.5,
ytop=k-j+.5,
lwd=4)
text(i,
k-j+1,
round(coeff[j,i],2),
cex=1.2,
font=2)
}
else{
rect(xleft=i-.5,xright=i+.5,ybottom=k-j+1.5,ytop=k-j+.5)
text(i,k-j+1,round(coeff[j,i],2),cex=1.2,font=1)
}
}
axis(3,1:n,noms)
par(mar=c(0.5,0,0,0.5))
plot(0,axes=F,xlab='',ylab='',type='n',xlim=c(0,8),ylim=c(-.2,.8))
cols <- c('green','orange','red','black')
niv <- c('0','0.01','0.05','0.1')
for(i in 0:3){
polygon(c(1+2*i ,1+2*i ,1+2*i-.5 ,1+2*i),
c(.4 ,.7 , .4 , .4),
col=cols[i+1])
text(2*i,0.5,niv[i+1],cex=1.5)
}
text(8,.5,1,cex=1.5)
text(4,0,'p-value',cex=2)
box()
residus <- arimaSelect.out[[3]][[choix]]$res
par(mar=c(1,2,4,1))
acf(residus,main='')
title('acf',line=.5)
par(mar=c(1,2,4,1))
pacf(residus,main='')
title('pacf',line=.5)
par(mar=c(2,2,4,1))
qqnorm(residus,main='')
title('qq-norm',line=.5)
qqline(residus)
residus
}
if (par2 == 0) x <- log(x)
if (par2 != 0) x <- x^par2
(selection <- arimaSelect(x, order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5)))
bitmap(file='test1.png')
resid <- arimaSelectplot(selection)
dev.off()
resid
bitmap(file='test2.png')
acf(resid,length(resid)/2, main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test3.png')
pacf(resid,length(resid)/2, main='Residual Partial Autocorrelation Function')
dev.off()
bitmap(file='test4.png')
cpgram(resid, main='Residual Cumulative Periodogram')
dev.off()
bitmap(file='test5.png')
hist(resid, main='Residual Histogram', xlab='values of Residuals')
dev.off()
bitmap(file='test6.png')
densityplot(~resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test7.png')
qqnorm(resid, main='Residual Normal Q-Q Plot')
qqline(resid)
dev.off()
ncols <- length(selection[[1]][1,])
nrows <- length(selection[[2]][,1])-1
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ARIMA Parameter Estimation and Backward Selection', ncols+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Iteration', header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,names(selection[[3]][[1]]$coef)[i],header=TRUE)
}
a<-table.row.end(a)
for (j in 1:nrows) {
a<-table.row.start(a)
mydum <- 'Estimates ('
mydum <- paste(mydum,j)
mydum <- paste(mydum,')')
a<-table.element(a,mydum, header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,round(selection[[1]][j,i],4))
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(p-val)', header=TRUE)
for (i in 1:ncols) {
mydum <- '('
mydum <- paste(mydum,round(selection[[2]][j,i],4),sep='')
mydum <- paste(mydum,')')
a<-table.element(a,mydum)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated ARIMA Residuals', 1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Value', 1,TRUE)
a<-table.row.end(a)
for (i in (par4*par5+par3):length(resid)) {
a<-table.row.start(a)
a<-table.element(a,resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')