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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Sat, 04 Dec 2010 15:18:46 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/04/t1291475909sy9ucb92yryt3tt.htm/, Retrieved Sun, 05 May 2024 08:34:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105176, Retrieved Sun, 05 May 2024 08:34:02 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

110

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Backward Selection] [Unemployment] [2010-11-29 17:10:28] [b98453cac15ba1066b407e146608df68]
- R PD        [ARIMA Backward Selection] [ws9] [2010-12-04 15:18:46] [0cadca125c925bcc9e6efbdd1941e458] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	82 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 82 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105176&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]82 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105176&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105176&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	82 seconds
R Server	'George Udny Yule' @ 72.249.76.132

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	-0.7167	-0.0635	-0.0488	0.6404	-4e-04	0.0046	-0.03
(p-val)	(0 )	(0.0141 )	(0.0111 )	(1e-04 )	(0.9998 )	(0.9449 )	(0.9861 )
Estimates ( 2 )	-0.7165	-0.0635	-0.0488	0.6402	0	0.0046	-0.0304
(p-val)	(0 )	(0.014 )	(0.011 )	(1e-04 )	(NA )	(0.8028 )	(0.1199 )
Estimates ( 3 )	-0.7502	-0.0662	-0.0477	0.6738	0	0	-0.0291
(p-val)	(0 )	(0.0099 )	(0.0146 )	(0 )	(NA )	(NA )	(0.1331 )
Estimates ( 4 )	-0.7694	-0.0687	-0.0517	0.6929	0	0	0
(p-val)	(0 )	(0.0064 )	(0.0073 )	(0 )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & -0.7167 & -0.0635 & -0.0488 & 0.6404 & -4e-04 & 0.0046 & -0.03 \tabularnewline
(p-val) & (0 ) & (0.0141 ) & (0.0111 ) & (1e-04 ) & (0.9998 ) & (0.9449 ) & (0.9861 ) \tabularnewline
Estimates ( 2 ) & -0.7165 & -0.0635 & -0.0488 & 0.6402 & 0 & 0.0046 & -0.0304 \tabularnewline
(p-val) & (0 ) & (0.014 ) & (0.011 ) & (1e-04 ) & (NA ) & (0.8028 ) & (0.1199 ) \tabularnewline
Estimates ( 3 ) & -0.7502 & -0.0662 & -0.0477 & 0.6738 & 0 & 0 & -0.0291 \tabularnewline
(p-val) & (0 ) & (0.0099 ) & (0.0146 ) & (0 ) & (NA ) & (NA ) & (0.1331 ) \tabularnewline
Estimates ( 4 ) & -0.7694 & -0.0687 & -0.0517 & 0.6929 & 0 & 0 & 0 \tabularnewline
(p-val) & (0 ) & (0.0064 ) & (0.0073 ) & (0 ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105176&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]-0.7167[/C][C]-0.0635[/C][C]-0.0488[/C][C]0.6404[/C][C]-4e-04[/C][C]0.0046[/C][C]-0.03[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.0141 )[/C][C](0.0111 )[/C][C](1e-04 )[/C][C](0.9998 )[/C][C](0.9449 )[/C][C](0.9861 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]-0.7165[/C][C]-0.0635[/C][C]-0.0488[/C][C]0.6402[/C][C]0[/C][C]0.0046[/C][C]-0.0304[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.014 )[/C][C](0.011 )[/C][C](1e-04 )[/C][C](NA )[/C][C](0.8028 )[/C][C](0.1199 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]-0.7502[/C][C]-0.0662[/C][C]-0.0477[/C][C]0.6738[/C][C]0[/C][C]0[/C][C]-0.0291[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.0099 )[/C][C](0.0146 )[/C][C](0 )[/C][C](NA )[/C][C](NA )[/C][C](0.1331 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]-0.7694[/C][C]-0.0687[/C][C]-0.0517[/C][C]0.6929[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.0064 )[/C][C](0.0073 )[/C][C](0 )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105176&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105176&T=1

As an alternative you can also use a QR Code:

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

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	-0.7167	-0.0635	-0.0488	0.6404	-4e-04	0.0046	-0.03
(p-val)	(0 )	(0.0141 )	(0.0111 )	(1e-04 )	(0.9998 )	(0.9449 )	(0.9861 )
Estimates ( 2 )	-0.7165	-0.0635	-0.0488	0.6402	0	0.0046	-0.0304
(p-val)	(0 )	(0.014 )	(0.011 )	(1e-04 )	(NA )	(0.8028 )	(0.1199 )
Estimates ( 3 )	-0.7502	-0.0662	-0.0477	0.6738	0	0	-0.0291
(p-val)	(0 )	(0.0099 )	(0.0146 )	(0 )	(NA )	(NA )	(0.1331 )
Estimates ( 4 )	-0.7694	-0.0687	-0.0517	0.6929	0	0	0
(p-val)	(0 )	(0.0064 )	(0.0073 )	(0 )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
2.75398911825634e-05
0.000156010428590509
-6.64518041283654e-05
-9.9063855450717e-05
-0.000113139152631327
-0.000109510038012853
-0.000106469790138372
0.000296412862311996
8.65964045634425e-05
2.16267239073247e-05
-0.000115400632851519
-1.19613550147907e-05
2.60052554948114e-05
-6.89401932368934e-05
5.32579082721846e-05
3.62477952866236e-05
-3.89938936280570e-05
-2.23535537948484e-05
8.35194053198588e-05
-0.000155612585837468
-0.000105903548727921
-0.000145028090111899
8.87214414778298e-05
-3.45042817195316e-05
-5.79183072844527e-05
-5.93763729364018e-05
0.000113505830849195
1.70160992302482e-05
-2.2241169522462e-05
-5.69243720297267e-05
-7.59357413260409e-05
-4.77020286571062e-06
0.000131855524026842
1.44548656247004e-05
-0.000113118435333568
-0.000205233085213847
-5.74678083590378e-06
4.19056746483563e-05
-1.03418648587962e-05
8.85279982770423e-06
-4.11184609762499e-05
-9.24744744169072e-05
2.57858107907821e-05
-6.31774622871506e-05
-8.36292291295296e-05
-0.000119708743333408
8.63865046600645e-05
-0.000133923832408064
2.93331921062435e-05
9.34516483320734e-05
0.000104946283735377
0.000222290106993948
2.06159338171467e-05
-3.34565697252889e-05
-9.86121149497213e-05
-9.39028793748437e-06
7.31499900273429e-05
-1.16993877864804e-05
8.71616800863367e-07
3.31580027416456e-05
-2.28589799138035e-08
-2.62757046015187e-05
-2.83893886939973e-05
7.14481731627359e-05
-1.26285484309367e-05
6.93783611873527e-06
-8.69394339849498e-05
3.40083432436127e-05
-1.97604711852616e-05
-8.59964330307723e-05
8.74924398044097e-05
-0.000188146559282409
-8.2965456326009e-05
1.76207393794148e-07
-3.12193547397817e-05
6.25031350086624e-05
-3.03165353865258e-05
9.28181886708165e-06
7.41334434120888e-05
8.7919487836291e-06
-0.00010519139987002
-9.1428736175618e-05
-3.76712182504034e-05
7.91147976303072e-06
8.4067926346236e-05
4.66822398413995e-05
0.000184417257239566
3.79079319252351e-05
0.000105930579576353
1.41211113460112e-05
-1.96008390727226e-06
8.05385014532069e-05
3.52723014865851e-05
-3.66126272289824e-05
-6.64088679593923e-05
9.5892379906596e-05
7.8382011923686e-05
-9.25353759128021e-05
-6.36137811034429e-05
2.57783158460027e-05
0.000135955734860527
-8.95588582357776e-05
0.000113137579483183
-0.000141085839979845
-4.29989131111724e-05
0.000189471295098532
0.000177599981031531
0.000172611649481864
4.80419062396063e-05
-5.60907429723104e-05
-7.54650237557407e-05
-4.03423213120625e-05
-1.00715547862451e-05
-6.32444166974895e-05
9.9574600721311e-05
-8.20152259966428e-06
-3.79519218747688e-05
-4.95673863523602e-05
8.23863600282054e-05
2.40329680006278e-05
-4.44816926785212e-05
-0.000118687001995552
-3.07999926247859e-05
-0.000134853276202843
-1.67177065094268e-05
1.89543281432850e-05
0.000261425689308783
-2.77169600728863e-05
-3.02519534972553e-05
-1.73692760771643e-05
3.37967457421304e-05
5.48583670139519e-07
0.000130752461451847
-3.59538932731204e-05
-1.52538954132919e-05
0.000176067508495546
0.000152664467444066
1.09168576954213e-05
0.000110443218812619
6.98550822758465e-05
1.94993259802871e-05
4.37240796924074e-05
-6.60988705837896e-05
1.3049267759066e-06
-1.79286472809514e-05
6.12346315941696e-05
6.22931707672005e-05
3.14746106610288e-05
7.83695271116061e-06
-1.93899879943199e-06
-0.000125159508312309
-0.000240058571489662
9.71425740538268e-06
-0.000109500171391091
-7.12981982243198e-05
9.28501226250787e-05
0.000138536523644737
3.78363696898303e-05
-2.79788403517202e-05
2.58919108862832e-06
-5.24460517298611e-06
-3.73733794239647e-05
3.5329683452507e-05
5.0370086151847e-05
6.66588864692841e-05
8.64019438783191e-05
7.22165492436644e-06
-8.62582073096127e-05
-8.5077577837992e-05
1.83601589776455e-05
-2.60901114530789e-05
-2.77513760571259e-05
-0.000249284917332976
4.62920646852882e-06
1.27475384329480e-05
-1.05845578611576e-05
8.33785211835913e-06
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0.000107347719673544
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2.12021456390647e-05

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
2.75398911825634e-05 \tabularnewline
0.000156010428590509 \tabularnewline
-6.64518041283654e-05 \tabularnewline
-9.9063855450717e-05 \tabularnewline
-0.000113139152631327 \tabularnewline
-0.000109510038012853 \tabularnewline
-0.000106469790138372 \tabularnewline
0.000296412862311996 \tabularnewline
8.65964045634425e-05 \tabularnewline
2.16267239073247e-05 \tabularnewline
-0.000115400632851519 \tabularnewline
-1.19613550147907e-05 \tabularnewline
2.60052554948114e-05 \tabularnewline
-6.89401932368934e-05 \tabularnewline
5.32579082721846e-05 \tabularnewline
3.62477952866236e-05 \tabularnewline
-3.89938936280570e-05 \tabularnewline
-2.23535537948484e-05 \tabularnewline
8.35194053198588e-05 \tabularnewline
-0.000155612585837468 \tabularnewline
-0.000105903548727921 \tabularnewline
-0.000145028090111899 \tabularnewline
8.87214414778298e-05 \tabularnewline
-3.45042817195316e-05 \tabularnewline
-5.79183072844527e-05 \tabularnewline
-5.93763729364018e-05 \tabularnewline
0.000113505830849195 \tabularnewline
1.70160992302482e-05 \tabularnewline
-2.2241169522462e-05 \tabularnewline
-5.69243720297267e-05 \tabularnewline
-7.59357413260409e-05 \tabularnewline
-4.77020286571062e-06 \tabularnewline
0.000131855524026842 \tabularnewline
1.44548656247004e-05 \tabularnewline
-0.000113118435333568 \tabularnewline
-0.000205233085213847 \tabularnewline
-5.74678083590378e-06 \tabularnewline
4.19056746483563e-05 \tabularnewline
-1.03418648587962e-05 \tabularnewline
8.85279982770423e-06 \tabularnewline
-4.11184609762499e-05 \tabularnewline
-9.24744744169072e-05 \tabularnewline
2.57858107907821e-05 \tabularnewline
-6.31774622871506e-05 \tabularnewline
-8.36292291295296e-05 \tabularnewline
-0.000119708743333408 \tabularnewline
8.63865046600645e-05 \tabularnewline
-0.000133923832408064 \tabularnewline
2.93331921062435e-05 \tabularnewline
9.34516483320734e-05 \tabularnewline
0.000104946283735377 \tabularnewline
0.000222290106993948 \tabularnewline
2.06159338171467e-05 \tabularnewline
-3.34565697252889e-05 \tabularnewline
-9.86121149497213e-05 \tabularnewline
-9.39028793748437e-06 \tabularnewline
7.31499900273429e-05 \tabularnewline
-1.16993877864804e-05 \tabularnewline
8.71616800863367e-07 \tabularnewline
3.31580027416456e-05 \tabularnewline
-2.28589799138035e-08 \tabularnewline
-2.62757046015187e-05 \tabularnewline
-2.83893886939973e-05 \tabularnewline
7.14481731627359e-05 \tabularnewline
-1.26285484309367e-05 \tabularnewline
6.93783611873527e-06 \tabularnewline
-8.69394339849498e-05 \tabularnewline
3.40083432436127e-05 \tabularnewline
-1.97604711852616e-05 \tabularnewline
-8.59964330307723e-05 \tabularnewline
8.74924398044097e-05 \tabularnewline
-0.000188146559282409 \tabularnewline
-8.2965456326009e-05 \tabularnewline
1.76207393794148e-07 \tabularnewline
-3.12193547397817e-05 \tabularnewline
6.25031350086624e-05 \tabularnewline
-3.03165353865258e-05 \tabularnewline
9.28181886708165e-06 \tabularnewline
7.41334434120888e-05 \tabularnewline
8.7919487836291e-06 \tabularnewline
-0.00010519139987002 \tabularnewline
-9.1428736175618e-05 \tabularnewline
-3.76712182504034e-05 \tabularnewline
7.91147976303072e-06 \tabularnewline
8.4067926346236e-05 \tabularnewline
4.66822398413995e-05 \tabularnewline
0.000184417257239566 \tabularnewline
3.79079319252351e-05 \tabularnewline
0.000105930579576353 \tabularnewline
1.41211113460112e-05 \tabularnewline
-1.96008390727226e-06 \tabularnewline
8.05385014532069e-05 \tabularnewline
3.52723014865851e-05 \tabularnewline
-3.66126272289824e-05 \tabularnewline
-6.64088679593923e-05 \tabularnewline
9.5892379906596e-05 \tabularnewline
7.8382011923686e-05 \tabularnewline
-9.25353759128021e-05 \tabularnewline
-6.36137811034429e-05 \tabularnewline
2.57783158460027e-05 \tabularnewline
0.000135955734860527 \tabularnewline
-8.95588582357776e-05 \tabularnewline
0.000113137579483183 \tabularnewline
-0.000141085839979845 \tabularnewline
-4.29989131111724e-05 \tabularnewline
0.000189471295098532 \tabularnewline
0.000177599981031531 \tabularnewline
0.000172611649481864 \tabularnewline
4.80419062396063e-05 \tabularnewline
-5.60907429723104e-05 \tabularnewline
-7.54650237557407e-05 \tabularnewline
-4.03423213120625e-05 \tabularnewline
-1.00715547862451e-05 \tabularnewline
-6.32444166974895e-05 \tabularnewline
9.9574600721311e-05 \tabularnewline
-8.20152259966428e-06 \tabularnewline
-3.79519218747688e-05 \tabularnewline
-4.95673863523602e-05 \tabularnewline
8.23863600282054e-05 \tabularnewline
2.40329680006278e-05 \tabularnewline
-4.44816926785212e-05 \tabularnewline
-0.000118687001995552 \tabularnewline
-3.07999926247859e-05 \tabularnewline
-0.000134853276202843 \tabularnewline
-1.67177065094268e-05 \tabularnewline
1.89543281432850e-05 \tabularnewline
0.000261425689308783 \tabularnewline
-2.77169600728863e-05 \tabularnewline
-3.02519534972553e-05 \tabularnewline
-1.73692760771643e-05 \tabularnewline
3.37967457421304e-05 \tabularnewline
5.48583670139519e-07 \tabularnewline
0.000130752461451847 \tabularnewline
-3.59538932731204e-05 \tabularnewline
-1.52538954132919e-05 \tabularnewline
0.000176067508495546 \tabularnewline
0.000152664467444066 \tabularnewline
1.09168576954213e-05 \tabularnewline
0.000110443218812619 \tabularnewline
6.98550822758465e-05 \tabularnewline
1.94993259802871e-05 \tabularnewline
4.37240796924074e-05 \tabularnewline
-6.60988705837896e-05 \tabularnewline
1.3049267759066e-06 \tabularnewline
-1.79286472809514e-05 \tabularnewline
6.12346315941696e-05 \tabularnewline
6.22931707672005e-05 \tabularnewline
3.14746106610288e-05 \tabularnewline
7.83695271116061e-06 \tabularnewline
-1.93899879943199e-06 \tabularnewline
-0.000125159508312309 \tabularnewline
-0.000240058571489662 \tabularnewline
9.71425740538268e-06 \tabularnewline
-0.000109500171391091 \tabularnewline
-7.12981982243198e-05 \tabularnewline
9.28501226250787e-05 \tabularnewline
0.000138536523644737 \tabularnewline
3.78363696898303e-05 \tabularnewline
-2.79788403517202e-05 \tabularnewline
2.58919108862832e-06 \tabularnewline
-5.24460517298611e-06 \tabularnewline
-3.73733794239647e-05 \tabularnewline
3.5329683452507e-05 \tabularnewline
5.0370086151847e-05 \tabularnewline
6.66588864692841e-05 \tabularnewline
8.64019438783191e-05 \tabularnewline
7.22165492436644e-06 \tabularnewline
-8.62582073096127e-05 \tabularnewline
-8.5077577837992e-05 \tabularnewline
1.83601589776455e-05 \tabularnewline
-2.60901114530789e-05 \tabularnewline
-2.77513760571259e-05 \tabularnewline
-0.000249284917332976 \tabularnewline
4.62920646852882e-06 \tabularnewline
1.27475384329480e-05 \tabularnewline
-1.05845578611576e-05 \tabularnewline
8.33785211835913e-06 \tabularnewline
0.000107388978213375 \tabularnewline
1.08040808360355e-05 \tabularnewline
-0.000221740622081558 \tabularnewline
-8.65442406601316e-05 \tabularnewline
-7.01857930888727e-05 \tabularnewline
-0.000192758874173807 \tabularnewline
-0.000718293466411633 \tabularnewline
-0.000847909624656404 \tabularnewline
0.000292867554627495 \tabularnewline
0.000184454856772834 \tabularnewline
-0.000277981869866474 \tabularnewline
-0.000490824680905281 \tabularnewline
2.16981988046573e-05 \tabularnewline
0.000144319875998937 \tabularnewline
-0.000158224787093184 \tabularnewline
0.000133734822411618 \tabularnewline
-0.000187412379546229 \tabularnewline
0.000158772174198903 \tabularnewline
-2.21553844765195e-05 \tabularnewline
0.000259817717694261 \tabularnewline
-1.58309623446672e-05 \tabularnewline
0.000248954482651883 \tabularnewline
-2.95241872103093e-05 \tabularnewline
2.10644072898385e-05 \tabularnewline
2.62168040150654e-05 \tabularnewline
-1.57735456771321e-05 \tabularnewline
0.000190170088156291 \tabularnewline
0.000298862996229578 \tabularnewline
-0.000427135313697848 \tabularnewline
-1.56547776416979e-05 \tabularnewline
0.000248685978919576 \tabularnewline
-4.15300651833081e-06 \tabularnewline
-9.70066056601299e-06 \tabularnewline
-0.000100058292813721 \tabularnewline
0.000146804436978287 \tabularnewline
-0.000106862551253133 \tabularnewline
-5.15661707688915e-05 \tabularnewline
-4.69213991965423e-05 \tabularnewline
-4.24110850421808e-05 \tabularnewline
4.33888425204164e-05 \tabularnewline
-4.75455400895178e-05 \tabularnewline
3.26033238664397e-05 \tabularnewline
-8.7173064647169e-05 \tabularnewline
-2.28966166691200e-05 \tabularnewline
-1.47658816790006e-06 \tabularnewline
-6.1478658850353e-06 \tabularnewline
-0.000244733941426198 \tabularnewline
-2.21695387297681e-05 \tabularnewline
0.000107849392992580 \tabularnewline
5.14732835790212e-05 \tabularnewline
-1.58988448730538e-05 \tabularnewline
5.3081436572084e-05 \tabularnewline
0.000261344857757587 \tabularnewline
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-6.3876429578287e-05 \tabularnewline
-2.24725162219497e-05 \tabularnewline
0.000110400093872098 \tabularnewline
-5.98673549010789e-05 \tabularnewline
-4.37949282850597e-05 \tabularnewline
1.05737865046147e-05 \tabularnewline
-6.8692257326742e-05 \tabularnewline
2.08858466164002e-05 \tabularnewline
-1.81408591678443e-05 \tabularnewline
-1.00482938415088e-05 \tabularnewline
7.46898445375156e-05 \tabularnewline
7.30150333029742e-05 \tabularnewline
8.33941227570169e-05 \tabularnewline
-5.70964297666905e-05 \tabularnewline
-3.92117599024369e-06 \tabularnewline
-4.62429559731498e-05 \tabularnewline
3.16838925849411e-05 \tabularnewline
-4.9836528208242e-05 \tabularnewline
-3.77248587649058e-05 \tabularnewline
3.96693676711635e-05 \tabularnewline
6.5283302310086e-05 \tabularnewline
-0.000136991429578848 \tabularnewline
-0.000145566233814703 \tabularnewline
-0.000114493869740499 \tabularnewline
-2.24984308469130e-05 \tabularnewline
3.23491261107617e-05 \tabularnewline
4.65024629422266e-05 \tabularnewline
2.30482982914171e-05 \tabularnewline
6.9428666108505e-05 \tabularnewline
-2.62681888560344e-05 \tabularnewline
1.64473987538070e-05 \tabularnewline
1.96858727994006e-05 \tabularnewline
-9.23975614980366e-05 \tabularnewline
-0.000192254974131605 \tabularnewline
1.15221787853025e-06 \tabularnewline
0.000182897558329047 \tabularnewline
-0.000171047095045613 \tabularnewline
-0.000157504831921172 \tabularnewline
-5.65475515298657e-05 \tabularnewline
4.62355093808313e-05 \tabularnewline
2.12021456390647e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105176&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]2.75398911825634e-05[/C][/ROW]
[ROW][C]0.000156010428590509[/C][/ROW]
[ROW][C]-6.64518041283654e-05[/C][/ROW]
[ROW][C]-9.9063855450717e-05[/C][/ROW]
[ROW][C]-0.000113139152631327[/C][/ROW]
[ROW][C]-0.000109510038012853[/C][/ROW]
[ROW][C]-0.000106469790138372[/C][/ROW]
[ROW][C]0.000296412862311996[/C][/ROW]
[ROW][C]8.65964045634425e-05[/C][/ROW]
[ROW][C]2.16267239073247e-05[/C][/ROW]
[ROW][C]-0.000115400632851519[/C][/ROW]
[ROW][C]-1.19613550147907e-05[/C][/ROW]
[ROW][C]2.60052554948114e-05[/C][/ROW]
[ROW][C]-6.89401932368934e-05[/C][/ROW]
[ROW][C]5.32579082721846e-05[/C][/ROW]
[ROW][C]3.62477952866236e-05[/C][/ROW]
[ROW][C]-3.89938936280570e-05[/C][/ROW]
[ROW][C]-2.23535537948484e-05[/C][/ROW]
[ROW][C]8.35194053198588e-05[/C][/ROW]
[ROW][C]-0.000155612585837468[/C][/ROW]
[ROW][C]-0.000105903548727921[/C][/ROW]
[ROW][C]-0.000145028090111899[/C][/ROW]
[ROW][C]8.87214414778298e-05[/C][/ROW]
[ROW][C]-3.45042817195316e-05[/C][/ROW]
[ROW][C]-5.79183072844527e-05[/C][/ROW]
[ROW][C]-5.93763729364018e-05[/C][/ROW]
[ROW][C]0.000113505830849195[/C][/ROW]
[ROW][C]1.70160992302482e-05[/C][/ROW]
[ROW][C]-2.2241169522462e-05[/C][/ROW]
[ROW][C]-5.69243720297267e-05[/C][/ROW]
[ROW][C]-7.59357413260409e-05[/C][/ROW]
[ROW][C]-4.77020286571062e-06[/C][/ROW]
[ROW][C]0.000131855524026842[/C][/ROW]
[ROW][C]1.44548656247004e-05[/C][/ROW]
[ROW][C]-0.000113118435333568[/C][/ROW]
[ROW][C]-0.000205233085213847[/C][/ROW]
[ROW][C]-5.74678083590378e-06[/C][/ROW]
[ROW][C]4.19056746483563e-05[/C][/ROW]
[ROW][C]-1.03418648587962e-05[/C][/ROW]
[ROW][C]8.85279982770423e-06[/C][/ROW]
[ROW][C]-4.11184609762499e-05[/C][/ROW]
[ROW][C]-9.24744744169072e-05[/C][/ROW]
[ROW][C]2.57858107907821e-05[/C][/ROW]
[ROW][C]-6.31774622871506e-05[/C][/ROW]
[ROW][C]-8.36292291295296e-05[/C][/ROW]
[ROW][C]-0.000119708743333408[/C][/ROW]
[ROW][C]8.63865046600645e-05[/C][/ROW]
[ROW][C]-0.000133923832408064[/C][/ROW]
[ROW][C]2.93331921062435e-05[/C][/ROW]
[ROW][C]9.34516483320734e-05[/C][/ROW]
[ROW][C]0.000104946283735377[/C][/ROW]
[ROW][C]0.000222290106993948[/C][/ROW]
[ROW][C]2.06159338171467e-05[/C][/ROW]
[ROW][C]-3.34565697252889e-05[/C][/ROW]
[ROW][C]-9.86121149497213e-05[/C][/ROW]
[ROW][C]-9.39028793748437e-06[/C][/ROW]
[ROW][C]7.31499900273429e-05[/C][/ROW]
[ROW][C]-1.16993877864804e-05[/C][/ROW]
[ROW][C]8.71616800863367e-07[/C][/ROW]
[ROW][C]3.31580027416456e-05[/C][/ROW]
[ROW][C]-2.28589799138035e-08[/C][/ROW]
[ROW][C]-2.62757046015187e-05[/C][/ROW]
[ROW][C]-2.83893886939973e-05[/C][/ROW]
[ROW][C]7.14481731627359e-05[/C][/ROW]
[ROW][C]-1.26285484309367e-05[/C][/ROW]
[ROW][C]6.93783611873527e-06[/C][/ROW]
[ROW][C]-8.69394339849498e-05[/C][/ROW]
[ROW][C]3.40083432436127e-05[/C][/ROW]
[ROW][C]-1.97604711852616e-05[/C][/ROW]
[ROW][C]-8.59964330307723e-05[/C][/ROW]
[ROW][C]8.74924398044097e-05[/C][/ROW]
[ROW][C]-0.000188146559282409[/C][/ROW]
[ROW][C]-8.2965456326009e-05[/C][/ROW]
[ROW][C]1.76207393794148e-07[/C][/ROW]
[ROW][C]-3.12193547397817e-05[/C][/ROW]
[ROW][C]6.25031350086624e-05[/C][/ROW]
[ROW][C]-3.03165353865258e-05[/C][/ROW]
[ROW][C]9.28181886708165e-06[/C][/ROW]
[ROW][C]7.41334434120888e-05[/C][/ROW]
[ROW][C]8.7919487836291e-06[/C][/ROW]
[ROW][C]-0.00010519139987002[/C][/ROW]
[ROW][C]-9.1428736175618e-05[/C][/ROW]
[ROW][C]-3.76712182504034e-05[/C][/ROW]
[ROW][C]7.91147976303072e-06[/C][/ROW]
[ROW][C]8.4067926346236e-05[/C][/ROW]
[ROW][C]4.66822398413995e-05[/C][/ROW]
[ROW][C]0.000184417257239566[/C][/ROW]
[ROW][C]3.79079319252351e-05[/C][/ROW]
[ROW][C]0.000105930579576353[/C][/ROW]
[ROW][C]1.41211113460112e-05[/C][/ROW]
[ROW][C]-1.96008390727226e-06[/C][/ROW]
[ROW][C]8.05385014532069e-05[/C][/ROW]
[ROW][C]3.52723014865851e-05[/C][/ROW]
[ROW][C]-3.66126272289824e-05[/C][/ROW]
[ROW][C]-6.64088679593923e-05[/C][/ROW]
[ROW][C]9.5892379906596e-05[/C][/ROW]
[ROW][C]7.8382011923686e-05[/C][/ROW]
[ROW][C]-9.25353759128021e-05[/C][/ROW]
[ROW][C]-6.36137811034429e-05[/C][/ROW]
[ROW][C]2.57783158460027e-05[/C][/ROW]
[ROW][C]0.000135955734860527[/C][/ROW]
[ROW][C]-8.95588582357776e-05[/C][/ROW]
[ROW][C]0.000113137579483183[/C][/ROW]
[ROW][C]-0.000141085839979845[/C][/ROW]
[ROW][C]-4.29989131111724e-05[/C][/ROW]
[ROW][C]0.000189471295098532[/C][/ROW]
[ROW][C]0.000177599981031531[/C][/ROW]
[ROW][C]0.000172611649481864[/C][/ROW]
[ROW][C]4.80419062396063e-05[/C][/ROW]
[ROW][C]-5.60907429723104e-05[/C][/ROW]
[ROW][C]-7.54650237557407e-05[/C][/ROW]
[ROW][C]-4.03423213120625e-05[/C][/ROW]
[ROW][C]-1.00715547862451e-05[/C][/ROW]
[ROW][C]-6.32444166974895e-05[/C][/ROW]
[ROW][C]9.9574600721311e-05[/C][/ROW]
[ROW][C]-8.20152259966428e-06[/C][/ROW]
[ROW][C]-3.79519218747688e-05[/C][/ROW]
[ROW][C]-4.95673863523602e-05[/C][/ROW]
[ROW][C]8.23863600282054e-05[/C][/ROW]
[ROW][C]2.40329680006278e-05[/C][/ROW]
[ROW][C]-4.44816926785212e-05[/C][/ROW]
[ROW][C]-0.000118687001995552[/C][/ROW]
[ROW][C]-3.07999926247859e-05[/C][/ROW]
[ROW][C]-0.000134853276202843[/C][/ROW]
[ROW][C]-1.67177065094268e-05[/C][/ROW]
[ROW][C]1.89543281432850e-05[/C][/ROW]
[ROW][C]0.000261425689308783[/C][/ROW]
[ROW][C]-2.77169600728863e-05[/C][/ROW]
[ROW][C]-3.02519534972553e-05[/C][/ROW]
[ROW][C]-1.73692760771643e-05[/C][/ROW]
[ROW][C]3.37967457421304e-05[/C][/ROW]
[ROW][C]5.48583670139519e-07[/C][/ROW]
[ROW][C]0.000130752461451847[/C][/ROW]
[ROW][C]-3.59538932731204e-05[/C][/ROW]
[ROW][C]-1.52538954132919e-05[/C][/ROW]
[ROW][C]0.000176067508495546[/C][/ROW]
[ROW][C]0.000152664467444066[/C][/ROW]
[ROW][C]1.09168576954213e-05[/C][/ROW]
[ROW][C]0.000110443218812619[/C][/ROW]
[ROW][C]6.98550822758465e-05[/C][/ROW]
[ROW][C]1.94993259802871e-05[/C][/ROW]
[ROW][C]4.37240796924074e-05[/C][/ROW]
[ROW][C]-6.60988705837896e-05[/C][/ROW]
[ROW][C]1.3049267759066e-06[/C][/ROW]
[ROW][C]-1.79286472809514e-05[/C][/ROW]
[ROW][C]6.12346315941696e-05[/C][/ROW]
[ROW][C]6.22931707672005e-05[/C][/ROW]
[ROW][C]3.14746106610288e-05[/C][/ROW]
[ROW][C]7.83695271116061e-06[/C][/ROW]
[ROW][C]-1.93899879943199e-06[/C][/ROW]
[ROW][C]-0.000125159508312309[/C][/ROW]
[ROW][C]-0.000240058571489662[/C][/ROW]
[ROW][C]9.71425740538268e-06[/C][/ROW]
[ROW][C]-0.000109500171391091[/C][/ROW]
[ROW][C]-7.12981982243198e-05[/C][/ROW]
[ROW][C]9.28501226250787e-05[/C][/ROW]
[ROW][C]0.000138536523644737[/C][/ROW]
[ROW][C]3.78363696898303e-05[/C][/ROW]
[ROW][C]-2.79788403517202e-05[/C][/ROW]
[ROW][C]2.58919108862832e-06[/C][/ROW]
[ROW][C]-5.24460517298611e-06[/C][/ROW]
[ROW][C]-3.73733794239647e-05[/C][/ROW]
[ROW][C]3.5329683452507e-05[/C][/ROW]
[ROW][C]5.0370086151847e-05[/C][/ROW]
[ROW][C]6.66588864692841e-05[/C][/ROW]
[ROW][C]8.64019438783191e-05[/C][/ROW]
[ROW][C]7.22165492436644e-06[/C][/ROW]
[ROW][C]-8.62582073096127e-05[/C][/ROW]
[ROW][C]-8.5077577837992e-05[/C][/ROW]
[ROW][C]1.83601589776455e-05[/C][/ROW]
[ROW][C]-2.60901114530789e-05[/C][/ROW]
[ROW][C]-2.77513760571259e-05[/C][/ROW]
[ROW][C]-0.000249284917332976[/C][/ROW]
[ROW][C]4.62920646852882e-06[/C][/ROW]
[ROW][C]1.27475384329480e-05[/C][/ROW]
[ROW][C]-1.05845578611576e-05[/C][/ROW]
[ROW][C]8.33785211835913e-06[/C][/ROW]
[ROW][C]0.000107388978213375[/C][/ROW]
[ROW][C]1.08040808360355e-05[/C][/ROW]
[ROW][C]-0.000221740622081558[/C][/ROW]
[ROW][C]-8.65442406601316e-05[/C][/ROW]
[ROW][C]-7.01857930888727e-05[/C][/ROW]
[ROW][C]-0.000192758874173807[/C][/ROW]
[ROW][C]-0.000718293466411633[/C][/ROW]
[ROW][C]-0.000847909624656404[/C][/ROW]
[ROW][C]0.000292867554627495[/C][/ROW]
[ROW][C]0.000184454856772834[/C][/ROW]
[ROW][C]-0.000277981869866474[/C][/ROW]
[ROW][C]-0.000490824680905281[/C][/ROW]
[ROW][C]2.16981988046573e-05[/C][/ROW]
[ROW][C]0.000144319875998937[/C][/ROW]
[ROW][C]-0.000158224787093184[/C][/ROW]
[ROW][C]0.000133734822411618[/C][/ROW]
[ROW][C]-0.000187412379546229[/C][/ROW]
[ROW][C]0.000158772174198903[/C][/ROW]
[ROW][C]-2.21553844765195e-05[/C][/ROW]
[ROW][C]0.000259817717694261[/C][/ROW]
[ROW][C]-1.58309623446672e-05[/C][/ROW]
[ROW][C]0.000248954482651883[/C][/ROW]
[ROW][C]-2.95241872103093e-05[/C][/ROW]
[ROW][C]2.10644072898385e-05[/C][/ROW]
[ROW][C]2.62168040150654e-05[/C][/ROW]
[ROW][C]-1.57735456771321e-05[/C][/ROW]
[ROW][C]0.000190170088156291[/C][/ROW]
[ROW][C]0.000298862996229578[/C][/ROW]
[ROW][C]-0.000427135313697848[/C][/ROW]
[ROW][C]-1.56547776416979e-05[/C][/ROW]
[ROW][C]0.000248685978919576[/C][/ROW]
[ROW][C]-4.15300651833081e-06[/C][/ROW]
[ROW][C]-9.70066056601299e-06[/C][/ROW]
[ROW][C]-0.000100058292813721[/C][/ROW]
[ROW][C]0.000146804436978287[/C][/ROW]
[ROW][C]-0.000106862551253133[/C][/ROW]
[ROW][C]-5.15661707688915e-05[/C][/ROW]
[ROW][C]-4.69213991965423e-05[/C][/ROW]
[ROW][C]-4.24110850421808e-05[/C][/ROW]
[ROW][C]4.33888425204164e-05[/C][/ROW]
[ROW][C]-4.75455400895178e-05[/C][/ROW]
[ROW][C]3.26033238664397e-05[/C][/ROW]
[ROW][C]-8.7173064647169e-05[/C][/ROW]
[ROW][C]-2.28966166691200e-05[/C][/ROW]
[ROW][C]-1.47658816790006e-06[/C][/ROW]
[ROW][C]-6.1478658850353e-06[/C][/ROW]
[ROW][C]-0.000244733941426198[/C][/ROW]
[ROW][C]-2.21695387297681e-05[/C][/ROW]
[ROW][C]0.000107849392992580[/C][/ROW]
[ROW][C]5.14732835790212e-05[/C][/ROW]
[ROW][C]-1.58988448730538e-05[/C][/ROW]
[ROW][C]5.3081436572084e-05[/C][/ROW]
[ROW][C]0.000261344857757587[/C][/ROW]
[ROW][C]0.000171752413796002[/C][/ROW]
[ROW][C]9.34700588092023e-05[/C][/ROW]
[ROW][C]-0.000115209814495778[/C][/ROW]
[ROW][C]0.000127166934434028[/C][/ROW]
[ROW][C]-3.46951870295355e-05[/C][/ROW]
[ROW][C]-5.14293466367215e-05[/C][/ROW]
[ROW][C]-3.10309684521358e-05[/C][/ROW]
[ROW][C]-6.9326965654419e-06[/C][/ROW]
[ROW][C]5.70700221847256e-06[/C][/ROW]
[ROW][C]2.21177180326528e-05[/C][/ROW]
[ROW][C]-0.000194722434799489[/C][/ROW]
[ROW][C]-3.18029109770551e-05[/C][/ROW]
[ROW][C]-8.79031877643495e-05[/C][/ROW]
[ROW][C]1.16635577812017e-05[/C][/ROW]
[ROW][C]6.4510523334442e-06[/C][/ROW]
[ROW][C]-6.46634485982137e-06[/C][/ROW]
[ROW][C]-3.6824319015135e-05[/C][/ROW]
[ROW][C]-0.000109970858694745[/C][/ROW]
[ROW][C]-6.33280690632079e-06[/C][/ROW]
[ROW][C]-7.4085289682585e-06[/C][/ROW]
[ROW][C]0.000456803320356119[/C][/ROW]
[ROW][C]0.000170789679007490[/C][/ROW]
[ROW][C]6.1275096579546e-05[/C][/ROW]
[ROW][C]-9.78695466174566e-05[/C][/ROW]
[ROW][C]-7.8377776710662e-05[/C][/ROW]
[ROW][C]7.40592508429762e-05[/C][/ROW]
[ROW][C]-4.19650944590358e-06[/C][/ROW]
[ROW][C]3.62086044434010e-06[/C][/ROW]
[ROW][C]-0.000129185985891848[/C][/ROW]
[ROW][C]-0.000196550167865232[/C][/ROW]
[ROW][C]-0.000104261573321923[/C][/ROW]
[ROW][C]-4.46963100556898e-05[/C][/ROW]
[ROW][C]-5.12878476712289e-06[/C][/ROW]
[ROW][C]8.32609506127117e-05[/C][/ROW]
[ROW][C]-9.21106045728877e-05[/C][/ROW]
[ROW][C]-9.3959985774779e-05[/C][/ROW]
[ROW][C]0.000129343376083422[/C][/ROW]
[ROW][C]-9.77793234467755e-05[/C][/ROW]
[ROW][C]-0.000102307269062171[/C][/ROW]
[ROW][C]9.26634759244524e-06[/C][/ROW]
[ROW][C]-0.000128575004976983[/C][/ROW]
[ROW][C]3.08668806908233e-05[/C][/ROW]
[ROW][C]-5.64306389681246e-05[/C][/ROW]
[ROW][C]7.6974800833806e-05[/C][/ROW]
[ROW][C]-0.00101252142253998[/C][/ROW]
[ROW][C]0.000394199656460221[/C][/ROW]
[ROW][C]2.77119751655383e-06[/C][/ROW]
[ROW][C]-0.000252998911452133[/C][/ROW]
[ROW][C]-0.000150901148581083[/C][/ROW]
[ROW][C]0.00025506511292955[/C][/ROW]
[ROW][C]-3.83849592440130e-05[/C][/ROW]
[ROW][C]0.000192723374445737[/C][/ROW]
[ROW][C]-2.58370936863858e-05[/C][/ROW]
[ROW][C]6.9170408715305e-05[/C][/ROW]
[ROW][C]1.95191394944394e-05[/C][/ROW]
[ROW][C]-2.02620661228156e-05[/C][/ROW]
[ROW][C]0.000125557085973088[/C][/ROW]
[ROW][C]-3.31458837667803e-06[/C][/ROW]
[ROW][C]1.39253778257305e-05[/C][/ROW]
[ROW][C]-1.40194307428759e-05[/C][/ROW]
[ROW][C]1.40978892115735e-05[/C][/ROW]
[ROW][C]-3.76971148423576e-05[/C][/ROW]
[ROW][C]0.000180335002098898[/C][/ROW]
[ROW][C]-4.82938275349655e-05[/C][/ROW]
[ROW][C]8.41229897391438e-06[/C][/ROW]
[ROW][C]-3.05973279174677e-05[/C][/ROW]
[ROW][C]-0.000192912850672650[/C][/ROW]
[ROW][C]0.000173514457474985[/C][/ROW]
[ROW][C]-4.80226863453018e-05[/C][/ROW]
[ROW][C]0.000119243008603484[/C][/ROW]
[ROW][C]-8.89920284574998e-05[/C][/ROW]
[ROW][C]6.41710278486765e-05[/C][/ROW]
[ROW][C]6.67710647720282e-05[/C][/ROW]
[ROW][C]6.86520294921854e-05[/C][/ROW]
[ROW][C]8.94532817576864e-05[/C][/ROW]
[ROW][C]-1.29701448738327e-05[/C][/ROW]
[ROW][C]-0.000243226269918413[/C][/ROW]
[ROW][C]9.5181456592451e-05[/C][/ROW]
[ROW][C]0.000154931556635686[/C][/ROW]
[ROW][C]7.3015123311572e-05[/C][/ROW]
[ROW][C]6.14739864160836e-05[/C][/ROW]
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[ROW][C]2.12021456390647e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105176&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105176&T=2

As an alternative you can also use a QR Code:

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

Estimated ARIMA Residuals
Value
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3.62477952866236e-05
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1.44548656247004e-05
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4.19056746483563e-05
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Figure 1

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Postscript link

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Parameters (Session):

par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ;

Parameters (R input):

par1 = FALSE ; par2 = -0.4 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code