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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Sat, 12 Dec 2009 05:11:40 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/12/t12606202053ujwttcys60ldlr.htm/, Retrieved Mon, 29 Apr 2024 10:45:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66921, Retrieved Mon, 29 Apr 2024 10:45:29 +0000

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User-defined keywords

Estimated Impact

146

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   [ARIMA Backward Selection] [] [2009-11-27 14:53:14] [b98453cac15ba1066b407e146608df68]
-   PD    [ARIMA Backward Selection] [ws9 tabel] [2009-12-04 14:44:54] [626f1d98f4a7f05bcb9f17666b672c60]
- R PD        [ARIMA Backward Selection] [Paper ARS] [2009-12-12 12:11:40] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
-    D          [ARIMA Backward Selection] [ARIMA backward se...] [2010-12-19 14:59:42] [8d09066a9d3795298da6860e7d4a4400] 
- R               [ARIMA Backward Selection] [ARIMA backward se...] [2010-12-19 16:10:01] [8d09066a9d3795298da6860e7d4a4400] 
-   P               [ARIMA Backward Selection] [ARIMA backward se...] [2010-12-24 10:51:31] [18a20458ff88c9ba38344d123a9464bc] 
- RM D            [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-19 16:30:13] [8d09066a9d3795298da6860e7d4a4400] 
-   P               [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-24 10:55:57] [18a20458ff88c9ba38344d123a9464bc] 

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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	60 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 & 60 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66921&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]60 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=66921&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66921&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	60 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	ma2	ma3	sar1	sar2	sma1
Estimates ( 1 )	-0.1887	0.0284	0.9145	0.3285	0.1609	-0.7663	0.3597	0.0369	-0.8519
(p-val)	(1e-04 )	(0.5888 )	(0 )	(0 )	(0.052 )	(0 )	(1e-04 )	(0.6064 )	(0 )
Estimates ( 2 )	-0.1978	0.0182	0.9062	0.3428	0.1753	-0.7527	0.3529	0	-0.8344
(p-val)	(1e-04 )	(0.7354 )	(0 )	(0 )	(0.0385 )	(0 )	(1e-04 )	(NA )	(0 )
Estimates ( 3 )	-0.1083	0	0.8926	0.2397	0.2103	-0.7768	0.3405	0	-0.8199
(p-val)	(0 )	(NA )	(0 )	(0 )	(0 )	(0 )	(1e-04 )	(NA )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 14 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 15 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 16 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 17 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & ma2 & ma3 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & -0.1887 & 0.0284 & 0.9145 & 0.3285 & 0.1609 & -0.7663 & 0.3597 & 0.0369 & -0.8519 \tabularnewline
(p-val) & (1e-04 ) & (0.5888 ) & (0 ) & (0 ) & (0.052 ) & (0 ) & (1e-04 ) & (0.6064 ) & (0 ) \tabularnewline
Estimates ( 2 ) & -0.1978 & 0.0182 & 0.9062 & 0.3428 & 0.1753 & -0.7527 & 0.3529 & 0 & -0.8344 \tabularnewline
(p-val) & (1e-04 ) & (0.7354 ) & (0 ) & (0 ) & (0.0385 ) & (0 ) & (1e-04 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 3 ) & -0.1083 & 0 & 0.8926 & 0.2397 & 0.2103 & -0.7768 & 0.3405 & 0 & -0.8199 \tabularnewline
(p-val) & (0 ) & (NA ) & (0 ) & (0 ) & (0 ) & (0 ) & (1e-04 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 14 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 15 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 16 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 17 ) & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66921&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][C]sar1[/C][C]sar2[/C][C]sma1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]-0.1887[/C][C]0.0284[/C][C]0.9145[/C][C]0.3285[/C][C]0.1609[/C][C]-0.7663[/C][C]0.3597[/C][C]0.0369[/C][C]-0.8519[/C][/ROW]
[ROW][C](p-val)[/C][C](1e-04 )[/C][C](0.5888 )[/C][C](0 )[/C][C](0 )[/C][C](0.052 )[/C][C](0 )[/C][C](1e-04 )[/C][C](0.6064 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]-0.1978[/C][C]0.0182[/C][C]0.9062[/C][C]0.3428[/C][C]0.1753[/C][C]-0.7527[/C][C]0.3529[/C][C]0[/C][C]-0.8344[/C][/ROW]
[ROW][C](p-val)[/C][C](1e-04 )[/C][C](0.7354 )[/C][C](0 )[/C][C](0 )[/C][C](0.0385 )[/C][C](0 )[/C][C](1e-04 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]-0.1083[/C][C]0[/C][C]0.8926[/C][C]0.2397[/C][C]0.2103[/C][C]-0.7768[/C][C]0.3405[/C][C]0[/C][C]-0.8199[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][C](0 )[/C][C](0 )[/C][C](0 )[/C][C](1e-04 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][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][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][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][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][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][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][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][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][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][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][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][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][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][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][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][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][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][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][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][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 14 )[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 15 )[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 16 )[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 17 )[/C][C]NA[/C][C]NA[/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][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66921&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66921&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	ma2	ma3	sar1	sar2	sma1
Estimates ( 1 )	-0.1887	0.0284	0.9145	0.3285	0.1609	-0.7663	0.3597	0.0369	-0.8519
(p-val)	(1e-04 )	(0.5888 )	(0 )	(0 )	(0.052 )	(0 )	(1e-04 )	(0.6064 )	(0 )
Estimates ( 2 )	-0.1978	0.0182	0.9062	0.3428	0.1753	-0.7527	0.3529	0	-0.8344
(p-val)	(1e-04 )	(0.7354 )	(0 )	(0 )	(0.0385 )	(0 )	(1e-04 )	(NA )	(0 )
Estimates ( 3 )	-0.1083	0	0.8926	0.2397	0.2103	-0.7768	0.3405	0	-0.8199
(p-val)	(0 )	(NA )	(0 )	(0 )	(0 )	(0 )	(1e-04 )	(NA )	(0 )
Estimates ( 4 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 5 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 14 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 15 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 16 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 17 )	NA	NA	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-1.05389947172549
8.4416022879863
0.264809227269645
3.61402647545751
2.35089967630583
3.52769728890782
-2.36177429977434
-2.65651876096212
-3.4283485942069
-2.99884785553649
1.99258765783025
2.28027601222431
4.37153301272526
3.2891912398501
-4.30465796011704
-7.56205660616637
-3.96472569389475
-1.32683160618236
1.15344273317683
-1.21036276521473
-0.103393269600576
2.86226847700442
3.19201503137537
-0.484346036524424
-2.23734272045455
-1.67193083282762
-3.72628235308536
-1.1997435889455
-4.51552147586442
0.782361843337378
-1.6079816139996
6.66144507437813
0.115615097015846
-3.14096477472873
-11.9554357704287
-9.60458651471003
-0.565730541013051
-2.59593660150408
-2.29858759052585
-6.90851594198716
5.7558335371874
-2.00548827985797
2.57422580096239
10.2722338405722
-7.04761284912167
-3.09340157945066
3.94489631072717
-8.00055683371443
16.8979740128494
-12.2954413780262
-12.3729171716218
-10.8559610399445
-6.60553080633236
-12.7056286407012
-6.7403618009817
-3.28999071619384
4.25421478298725
-0.390700042346132
-1.28505319333245
12.0533780060711
-7.21238785187422
1.76793712361490
4.57202059577267
4.10948518214669
5.14909984653437
8.04290388282365
-10.5188719921736
-7.67152468863669
3.20253937398167
17.16265889193
-7.80963644246112
6.44209467186323
-2.56850146035081
-7.96053252053479
0.442918372643544
0.902400902718005
-3.13747965267471
0.0586115500217112
-0.594363204386132
-9.83263587475384
-2.06944538960645
-2.96354673048204
1.49895087018255
-4.73215337193649
0.420318403856962
1.74523389325738
-3.81206784432846
0.810447426617338
-1.78307109450322
0.163214499466636
2.67433073911937
-4.57723527521646
-8.67907940828837
-1.77255966119988
2.06381114805042
2.23071928055821
-1.39811757394171
1.98375072571723
9.37247395930867
-6.74227766888264
-0.715024887450298
2.14203936798073
-4.08093041248461
3.64296045336104
-7.74732385740661
0.755516796141954
1.17881917306037
2.78180428905239
0.665601360838618
-0.0364235602931105
-0.389504457830173
4.8262131876641
-0.302478492950054
6.1732455939182
0.0993924835551327
-5.79052464599116
5.84989928285716
1.63802666538586
1.34506841848302
5.97158098164758
-0.858159643541342
7.89732766143513
-1.49602389557607
1.26033518648678
-1.47904386296764
2.82889295128891
-3.62945239257948
2.6800891256584
-1.42101132661476
2.16036331591487
0.298099666278185
3.4583888216932
-0.747319630243315
-2.08623509187243
4.64177875007438
3.38181815673068
-1.80327781664126
6.33815307000637
-4.91188075348182
2.5871367419019
-0.857148528507152
-2.00415871714141
5.12696172890453
8.35189503100999
1.45523114514816
8.25198215678349
-1.39009835835298
0.521510137549863
2.85955775357443
1.17713696587334
2.08223526709373
3.94730038555576
2.30209207232646
-10.2204425177615
2.26988280576407
-4.33510774462436
-2.75959339560696
-1.08375312766277
-4.65657126458126
-2.43276121142529
0.310539400796128
-3.01600836416012
-8.64256680644585
6.00185099616093
-3.18960658784065
-4.22561345270917
-5.37141272177894
1.18741444744113
1.75712465429544
3.93977951240657
-3.77134959542952
2.65125462626012
-1.89989574702174
1.18374453467759
3.50710639907773
5.77573710302503
0.608262579498656
2.05816885861869
-6.29327210861513
0.898792841791191
4.4518149400203
-8.01541706005978
-6.12640390341727
0.888963362094796
-6.9354774459447
-8.81890475846638
5.2409852263649
4.02361696956346
-9.12615720537498
-9.3333700427019
3.24809064701777
-2.06229812947806
0.0292789946023568
9.48582980321639
4.84442772392704
1.79904157643567
-0.045866502215208
8.67895504738705
-6.78878050664347
-1.11683523555325
-0.66130246943713
-7.9836903597607
-5.44139285218807
2.1944481846405
-2.53506676859463
2.63226705644079
0.326889627644759
-2.77381840644999
-1.43884133016045
-6.10645393640706
2.08020999583957
12.106615103282
-8.02775422556687
-13.3939755139849
-4.59863355065739
5.11875368220678
5.48532446616882
-2.08437210885651
3.392706040891
-1.48493248366128
2.70026695182974
1.84814665788656
-1.67866482077488
3.24709996727309
-8.48435405937905
-0.915914780845507
-4.57656328288288
-0.809525063645757
1.34854004655264
-0.311163437842765
-3.17812027344872
7.76253192299654
-3.57505148119773
1.73526471570766
-1.76129779799427
9.91930725016443
-6.38044799914943
-0.0927649213110234
-5.17046591677725
-4.34801338264625
6.63853034434849
5.54078016201049
4.06113912444872
0.443619152117213
6.35528726455257
-4.26389615760859
0.571020932025585
-1.17826872848335
16.5109581253798
0.964963159468123
-17.4071839919191
-0.522791412377851
0.835531276998813
8.5031318202778
5.7355289404567
-4.06144368788898
2.79137616821308
2.11604172514896
7.20331712589241
-18.7714140835119
0.585507839187224
8.97803171466246
12.4920066744206
-2.40392575957367
1.87695973399627
1.25438410518603
-1.46293052161354
6.72871131739579
-1.99220013159346
3.09877181914469
4.1582661600124
-7.45859851214467
0.053321192990512
-4.41071328984103
-5.7184912450394
4.61799934272152
3.58961153220946
2.52747349919649
1.30446220990521
-5.81881391304613
0.811845327841342
2.86751837618379
-5.71751886020892
-0.123780313822417
6.52739153590004
11.2885579472426
-4.33411208739956
-5.8723950678609
-8.15122283905666
1.07783271226473
4.57433096261199
-0.592770433482863
0.411365331134307
-0.149933001584183
0.206222228581196
-12.1907499967954
3.72839107758182
-7.10628259662316
-0.508924801394239
3.30403981260061
-1.76792038730655
0.4810722515175
0.561913067646686
4.88308987912015
5.06547426939577
-0.0142817041629347
-6.71006157054785
-8.38938781207838
0.704364827602098
-17.56025835431
-2.88442777435588
-4.75130653934548
8.6155726079912
-5.89752723606562
-1.5604059970912
3.53749491284865
-8.11860712937344
-6.85424970452308
8.84042979403381
1.29888334418643
-14.0967619469544
9.48883828306574
5.36986019608196
9.77164681377232
-1.81963419747215
0.583058745629914
-0.848389732198407
2.32268639016988
-8.64597651446204
16.2317200162606
-7.10023505565231
-5.88936251888072
-1.20391877890568
2.65476422162358
14.4993442735723
9.47757739311795
5.2678308701691
9.95388372773352
10.6380864211721
-0.813023914066638
-2.48362281747688
2.81638569930519
-5.75612039362401
-2.63274456116255
-7.3073934090228
-5.3570041988903
4.85353129641589

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-1.05389947172549 \tabularnewline
8.4416022879863 \tabularnewline
0.264809227269645 \tabularnewline
3.61402647545751 \tabularnewline
2.35089967630583 \tabularnewline
3.52769728890782 \tabularnewline
-2.36177429977434 \tabularnewline
-2.65651876096212 \tabularnewline
-3.4283485942069 \tabularnewline
-2.99884785553649 \tabularnewline
1.99258765783025 \tabularnewline
2.28027601222431 \tabularnewline
4.37153301272526 \tabularnewline
3.2891912398501 \tabularnewline
-4.30465796011704 \tabularnewline
-7.56205660616637 \tabularnewline
-3.96472569389475 \tabularnewline
-1.32683160618236 \tabularnewline
1.15344273317683 \tabularnewline
-1.21036276521473 \tabularnewline
-0.103393269600576 \tabularnewline
2.86226847700442 \tabularnewline
3.19201503137537 \tabularnewline
-0.484346036524424 \tabularnewline
-2.23734272045455 \tabularnewline
-1.67193083282762 \tabularnewline
-3.72628235308536 \tabularnewline
-1.1997435889455 \tabularnewline
-4.51552147586442 \tabularnewline
0.782361843337378 \tabularnewline
-1.6079816139996 \tabularnewline
6.66144507437813 \tabularnewline
0.115615097015846 \tabularnewline
-3.14096477472873 \tabularnewline
-11.9554357704287 \tabularnewline
-9.60458651471003 \tabularnewline
-0.565730541013051 \tabularnewline
-2.59593660150408 \tabularnewline
-2.29858759052585 \tabularnewline
-6.90851594198716 \tabularnewline
5.7558335371874 \tabularnewline
-2.00548827985797 \tabularnewline
2.57422580096239 \tabularnewline
10.2722338405722 \tabularnewline
-7.04761284912167 \tabularnewline
-3.09340157945066 \tabularnewline
3.94489631072717 \tabularnewline
-8.00055683371443 \tabularnewline
16.8979740128494 \tabularnewline
-12.2954413780262 \tabularnewline
-12.3729171716218 \tabularnewline
-10.8559610399445 \tabularnewline
-6.60553080633236 \tabularnewline
-12.7056286407012 \tabularnewline
-6.7403618009817 \tabularnewline
-3.28999071619384 \tabularnewline
4.25421478298725 \tabularnewline
-0.390700042346132 \tabularnewline
-1.28505319333245 \tabularnewline
12.0533780060711 \tabularnewline
-7.21238785187422 \tabularnewline
1.76793712361490 \tabularnewline
4.57202059577267 \tabularnewline
4.10948518214669 \tabularnewline
5.14909984653437 \tabularnewline
8.04290388282365 \tabularnewline
-10.5188719921736 \tabularnewline
-7.67152468863669 \tabularnewline
3.20253937398167 \tabularnewline
17.16265889193 \tabularnewline
-7.80963644246112 \tabularnewline
6.44209467186323 \tabularnewline
-2.56850146035081 \tabularnewline
-7.96053252053479 \tabularnewline
0.442918372643544 \tabularnewline
0.902400902718005 \tabularnewline
-3.13747965267471 \tabularnewline
0.0586115500217112 \tabularnewline
-0.594363204386132 \tabularnewline
-9.83263587475384 \tabularnewline
-2.06944538960645 \tabularnewline
-2.96354673048204 \tabularnewline
1.49895087018255 \tabularnewline
-4.73215337193649 \tabularnewline
0.420318403856962 \tabularnewline
1.74523389325738 \tabularnewline
-3.81206784432846 \tabularnewline
0.810447426617338 \tabularnewline
-1.78307109450322 \tabularnewline
0.163214499466636 \tabularnewline
2.67433073911937 \tabularnewline
-4.57723527521646 \tabularnewline
-8.67907940828837 \tabularnewline
-1.77255966119988 \tabularnewline
2.06381114805042 \tabularnewline
2.23071928055821 \tabularnewline
-1.39811757394171 \tabularnewline
1.98375072571723 \tabularnewline
9.37247395930867 \tabularnewline
-6.74227766888264 \tabularnewline
-0.715024887450298 \tabularnewline
2.14203936798073 \tabularnewline
-4.08093041248461 \tabularnewline
3.64296045336104 \tabularnewline
-7.74732385740661 \tabularnewline
0.755516796141954 \tabularnewline
1.17881917306037 \tabularnewline
2.78180428905239 \tabularnewline
0.665601360838618 \tabularnewline
-0.0364235602931105 \tabularnewline
-0.389504457830173 \tabularnewline
4.8262131876641 \tabularnewline
-0.302478492950054 \tabularnewline
6.1732455939182 \tabularnewline
0.0993924835551327 \tabularnewline
-5.79052464599116 \tabularnewline
5.84989928285716 \tabularnewline
1.63802666538586 \tabularnewline
1.34506841848302 \tabularnewline
5.97158098164758 \tabularnewline
-0.858159643541342 \tabularnewline
7.89732766143513 \tabularnewline
-1.49602389557607 \tabularnewline
1.26033518648678 \tabularnewline
-1.47904386296764 \tabularnewline
2.82889295128891 \tabularnewline
-3.62945239257948 \tabularnewline
2.6800891256584 \tabularnewline
-1.42101132661476 \tabularnewline
2.16036331591487 \tabularnewline
0.298099666278185 \tabularnewline
3.4583888216932 \tabularnewline
-0.747319630243315 \tabularnewline
-2.08623509187243 \tabularnewline
4.64177875007438 \tabularnewline
3.38181815673068 \tabularnewline
-1.80327781664126 \tabularnewline
6.33815307000637 \tabularnewline
-4.91188075348182 \tabularnewline
2.5871367419019 \tabularnewline
-0.857148528507152 \tabularnewline
-2.00415871714141 \tabularnewline
5.12696172890453 \tabularnewline
8.35189503100999 \tabularnewline
1.45523114514816 \tabularnewline
8.25198215678349 \tabularnewline
-1.39009835835298 \tabularnewline
0.521510137549863 \tabularnewline
2.85955775357443 \tabularnewline
1.17713696587334 \tabularnewline
2.08223526709373 \tabularnewline
3.94730038555576 \tabularnewline
2.30209207232646 \tabularnewline
-10.2204425177615 \tabularnewline
2.26988280576407 \tabularnewline
-4.33510774462436 \tabularnewline
-2.75959339560696 \tabularnewline
-1.08375312766277 \tabularnewline
-4.65657126458126 \tabularnewline
-2.43276121142529 \tabularnewline
0.310539400796128 \tabularnewline
-3.01600836416012 \tabularnewline
-8.64256680644585 \tabularnewline
6.00185099616093 \tabularnewline
-3.18960658784065 \tabularnewline
-4.22561345270917 \tabularnewline
-5.37141272177894 \tabularnewline
1.18741444744113 \tabularnewline
1.75712465429544 \tabularnewline
3.93977951240657 \tabularnewline
-3.77134959542952 \tabularnewline
2.65125462626012 \tabularnewline
-1.89989574702174 \tabularnewline
1.18374453467759 \tabularnewline
3.50710639907773 \tabularnewline
5.77573710302503 \tabularnewline
0.608262579498656 \tabularnewline
2.05816885861869 \tabularnewline
-6.29327210861513 \tabularnewline
0.898792841791191 \tabularnewline
4.4518149400203 \tabularnewline
-8.01541706005978 \tabularnewline
-6.12640390341727 \tabularnewline
0.888963362094796 \tabularnewline
-6.9354774459447 \tabularnewline
-8.81890475846638 \tabularnewline
5.2409852263649 \tabularnewline
4.02361696956346 \tabularnewline
-9.12615720537498 \tabularnewline
-9.3333700427019 \tabularnewline
3.24809064701777 \tabularnewline
-2.06229812947806 \tabularnewline
0.0292789946023568 \tabularnewline
9.48582980321639 \tabularnewline
4.84442772392704 \tabularnewline
1.79904157643567 \tabularnewline
-0.045866502215208 \tabularnewline
8.67895504738705 \tabularnewline
-6.78878050664347 \tabularnewline
-1.11683523555325 \tabularnewline
-0.66130246943713 \tabularnewline
-7.9836903597607 \tabularnewline
-5.44139285218807 \tabularnewline
2.1944481846405 \tabularnewline
-2.53506676859463 \tabularnewline
2.63226705644079 \tabularnewline
0.326889627644759 \tabularnewline
-2.77381840644999 \tabularnewline
-1.43884133016045 \tabularnewline
-6.10645393640706 \tabularnewline
2.08020999583957 \tabularnewline
12.106615103282 \tabularnewline
-8.02775422556687 \tabularnewline
-13.3939755139849 \tabularnewline
-4.59863355065739 \tabularnewline
5.11875368220678 \tabularnewline
5.48532446616882 \tabularnewline
-2.08437210885651 \tabularnewline
3.392706040891 \tabularnewline
-1.48493248366128 \tabularnewline
2.70026695182974 \tabularnewline
1.84814665788656 \tabularnewline
-1.67866482077488 \tabularnewline
3.24709996727309 \tabularnewline
-8.48435405937905 \tabularnewline
-0.915914780845507 \tabularnewline
-4.57656328288288 \tabularnewline
-0.809525063645757 \tabularnewline
1.34854004655264 \tabularnewline
-0.311163437842765 \tabularnewline
-3.17812027344872 \tabularnewline
7.76253192299654 \tabularnewline
-3.57505148119773 \tabularnewline
1.73526471570766 \tabularnewline
-1.76129779799427 \tabularnewline
9.91930725016443 \tabularnewline
-6.38044799914943 \tabularnewline
-0.0927649213110234 \tabularnewline
-5.17046591677725 \tabularnewline
-4.34801338264625 \tabularnewline
6.63853034434849 \tabularnewline
5.54078016201049 \tabularnewline
4.06113912444872 \tabularnewline
0.443619152117213 \tabularnewline
6.35528726455257 \tabularnewline
-4.26389615760859 \tabularnewline
0.571020932025585 \tabularnewline
-1.17826872848335 \tabularnewline
16.5109581253798 \tabularnewline
0.964963159468123 \tabularnewline
-17.4071839919191 \tabularnewline
-0.522791412377851 \tabularnewline
0.835531276998813 \tabularnewline
8.5031318202778 \tabularnewline
5.7355289404567 \tabularnewline
-4.06144368788898 \tabularnewline
2.79137616821308 \tabularnewline
2.11604172514896 \tabularnewline
7.20331712589241 \tabularnewline
-18.7714140835119 \tabularnewline
0.585507839187224 \tabularnewline
8.97803171466246 \tabularnewline
12.4920066744206 \tabularnewline
-2.40392575957367 \tabularnewline
1.87695973399627 \tabularnewline
1.25438410518603 \tabularnewline
-1.46293052161354 \tabularnewline
6.72871131739579 \tabularnewline
-1.99220013159346 \tabularnewline
3.09877181914469 \tabularnewline
4.1582661600124 \tabularnewline
-7.45859851214467 \tabularnewline
0.053321192990512 \tabularnewline
-4.41071328984103 \tabularnewline
-5.7184912450394 \tabularnewline
4.61799934272152 \tabularnewline
3.58961153220946 \tabularnewline
2.52747349919649 \tabularnewline
1.30446220990521 \tabularnewline
-5.81881391304613 \tabularnewline
0.811845327841342 \tabularnewline
2.86751837618379 \tabularnewline
-5.71751886020892 \tabularnewline
-0.123780313822417 \tabularnewline
6.52739153590004 \tabularnewline
11.2885579472426 \tabularnewline
-4.33411208739956 \tabularnewline
-5.8723950678609 \tabularnewline
-8.15122283905666 \tabularnewline
1.07783271226473 \tabularnewline
4.57433096261199 \tabularnewline
-0.592770433482863 \tabularnewline
0.411365331134307 \tabularnewline
-0.149933001584183 \tabularnewline
0.206222228581196 \tabularnewline
-12.1907499967954 \tabularnewline
3.72839107758182 \tabularnewline
-7.10628259662316 \tabularnewline
-0.508924801394239 \tabularnewline
3.30403981260061 \tabularnewline
-1.76792038730655 \tabularnewline
0.4810722515175 \tabularnewline
0.561913067646686 \tabularnewline
4.88308987912015 \tabularnewline
5.06547426939577 \tabularnewline
-0.0142817041629347 \tabularnewline
-6.71006157054785 \tabularnewline
-8.38938781207838 \tabularnewline
0.704364827602098 \tabularnewline
-17.56025835431 \tabularnewline
-2.88442777435588 \tabularnewline
-4.75130653934548 \tabularnewline
8.6155726079912 \tabularnewline
-5.89752723606562 \tabularnewline
-1.5604059970912 \tabularnewline
3.53749491284865 \tabularnewline
-8.11860712937344 \tabularnewline
-6.85424970452308 \tabularnewline
8.84042979403381 \tabularnewline
1.29888334418643 \tabularnewline
-14.0967619469544 \tabularnewline
9.48883828306574 \tabularnewline
5.36986019608196 \tabularnewline
9.77164681377232 \tabularnewline
-1.81963419747215 \tabularnewline
0.583058745629914 \tabularnewline
-0.848389732198407 \tabularnewline
2.32268639016988 \tabularnewline
-8.64597651446204 \tabularnewline
16.2317200162606 \tabularnewline
-7.10023505565231 \tabularnewline
-5.88936251888072 \tabularnewline
-1.20391877890568 \tabularnewline
2.65476422162358 \tabularnewline
14.4993442735723 \tabularnewline
9.47757739311795 \tabularnewline
5.2678308701691 \tabularnewline
9.95388372773352 \tabularnewline
10.6380864211721 \tabularnewline
-0.813023914066638 \tabularnewline
-2.48362281747688 \tabularnewline
2.81638569930519 \tabularnewline
-5.75612039362401 \tabularnewline
-2.63274456116255 \tabularnewline
-7.3073934090228 \tabularnewline
-5.3570041988903 \tabularnewline
4.85353129641589 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66921&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-1.05389947172549[/C][/ROW]
[ROW][C]8.4416022879863[/C][/ROW]
[ROW][C]0.264809227269645[/C][/ROW]
[ROW][C]3.61402647545751[/C][/ROW]
[ROW][C]2.35089967630583[/C][/ROW]
[ROW][C]3.52769728890782[/C][/ROW]
[ROW][C]-2.36177429977434[/C][/ROW]
[ROW][C]-2.65651876096212[/C][/ROW]
[ROW][C]-3.4283485942069[/C][/ROW]
[ROW][C]-2.99884785553649[/C][/ROW]
[ROW][C]1.99258765783025[/C][/ROW]
[ROW][C]2.28027601222431[/C][/ROW]
[ROW][C]4.37153301272526[/C][/ROW]
[ROW][C]3.2891912398501[/C][/ROW]
[ROW][C]-4.30465796011704[/C][/ROW]
[ROW][C]-7.56205660616637[/C][/ROW]
[ROW][C]-3.96472569389475[/C][/ROW]
[ROW][C]-1.32683160618236[/C][/ROW]
[ROW][C]1.15344273317683[/C][/ROW]
[ROW][C]-1.21036276521473[/C][/ROW]
[ROW][C]-0.103393269600576[/C][/ROW]
[ROW][C]2.86226847700442[/C][/ROW]
[ROW][C]3.19201503137537[/C][/ROW]
[ROW][C]-0.484346036524424[/C][/ROW]
[ROW][C]-2.23734272045455[/C][/ROW]
[ROW][C]-1.67193083282762[/C][/ROW]
[ROW][C]-3.72628235308536[/C][/ROW]
[ROW][C]-1.1997435889455[/C][/ROW]
[ROW][C]-4.51552147586442[/C][/ROW]
[ROW][C]0.782361843337378[/C][/ROW]
[ROW][C]-1.6079816139996[/C][/ROW]
[ROW][C]6.66144507437813[/C][/ROW]
[ROW][C]0.115615097015846[/C][/ROW]
[ROW][C]-3.14096477472873[/C][/ROW]
[ROW][C]-11.9554357704287[/C][/ROW]
[ROW][C]-9.60458651471003[/C][/ROW]
[ROW][C]-0.565730541013051[/C][/ROW]
[ROW][C]-2.59593660150408[/C][/ROW]
[ROW][C]-2.29858759052585[/C][/ROW]
[ROW][C]-6.90851594198716[/C][/ROW]
[ROW][C]5.7558335371874[/C][/ROW]
[ROW][C]-2.00548827985797[/C][/ROW]
[ROW][C]2.57422580096239[/C][/ROW]
[ROW][C]10.2722338405722[/C][/ROW]
[ROW][C]-7.04761284912167[/C][/ROW]
[ROW][C]-3.09340157945066[/C][/ROW]
[ROW][C]3.94489631072717[/C][/ROW]
[ROW][C]-8.00055683371443[/C][/ROW]
[ROW][C]16.8979740128494[/C][/ROW]
[ROW][C]-12.2954413780262[/C][/ROW]
[ROW][C]-12.3729171716218[/C][/ROW]
[ROW][C]-10.8559610399445[/C][/ROW]
[ROW][C]-6.60553080633236[/C][/ROW]
[ROW][C]-12.7056286407012[/C][/ROW]
[ROW][C]-6.7403618009817[/C][/ROW]
[ROW][C]-3.28999071619384[/C][/ROW]
[ROW][C]4.25421478298725[/C][/ROW]
[ROW][C]-0.390700042346132[/C][/ROW]
[ROW][C]-1.28505319333245[/C][/ROW]
[ROW][C]12.0533780060711[/C][/ROW]
[ROW][C]-7.21238785187422[/C][/ROW]
[ROW][C]1.76793712361490[/C][/ROW]
[ROW][C]4.57202059577267[/C][/ROW]
[ROW][C]4.10948518214669[/C][/ROW]
[ROW][C]5.14909984653437[/C][/ROW]
[ROW][C]8.04290388282365[/C][/ROW]
[ROW][C]-10.5188719921736[/C][/ROW]
[ROW][C]-7.67152468863669[/C][/ROW]
[ROW][C]3.20253937398167[/C][/ROW]
[ROW][C]17.16265889193[/C][/ROW]
[ROW][C]-7.80963644246112[/C][/ROW]
[ROW][C]6.44209467186323[/C][/ROW]
[ROW][C]-2.56850146035081[/C][/ROW]
[ROW][C]-7.96053252053479[/C][/ROW]
[ROW][C]0.442918372643544[/C][/ROW]
[ROW][C]0.902400902718005[/C][/ROW]
[ROW][C]-3.13747965267471[/C][/ROW]
[ROW][C]0.0586115500217112[/C][/ROW]
[ROW][C]-0.594363204386132[/C][/ROW]
[ROW][C]-9.83263587475384[/C][/ROW]
[ROW][C]-2.06944538960645[/C][/ROW]
[ROW][C]-2.96354673048204[/C][/ROW]
[ROW][C]1.49895087018255[/C][/ROW]
[ROW][C]-4.73215337193649[/C][/ROW]
[ROW][C]0.420318403856962[/C][/ROW]
[ROW][C]1.74523389325738[/C][/ROW]
[ROW][C]-3.81206784432846[/C][/ROW]
[ROW][C]0.810447426617338[/C][/ROW]
[ROW][C]-1.78307109450322[/C][/ROW]
[ROW][C]0.163214499466636[/C][/ROW]
[ROW][C]2.67433073911937[/C][/ROW]
[ROW][C]-4.57723527521646[/C][/ROW]
[ROW][C]-8.67907940828837[/C][/ROW]
[ROW][C]-1.77255966119988[/C][/ROW]
[ROW][C]2.06381114805042[/C][/ROW]
[ROW][C]2.23071928055821[/C][/ROW]
[ROW][C]-1.39811757394171[/C][/ROW]
[ROW][C]1.98375072571723[/C][/ROW]
[ROW][C]9.37247395930867[/C][/ROW]
[ROW][C]-6.74227766888264[/C][/ROW]
[ROW][C]-0.715024887450298[/C][/ROW]
[ROW][C]2.14203936798073[/C][/ROW]
[ROW][C]-4.08093041248461[/C][/ROW]
[ROW][C]3.64296045336104[/C][/ROW]
[ROW][C]-7.74732385740661[/C][/ROW]
[ROW][C]0.755516796141954[/C][/ROW]
[ROW][C]1.17881917306037[/C][/ROW]
[ROW][C]2.78180428905239[/C][/ROW]
[ROW][C]0.665601360838618[/C][/ROW]
[ROW][C]-0.0364235602931105[/C][/ROW]
[ROW][C]-0.389504457830173[/C][/ROW]
[ROW][C]4.8262131876641[/C][/ROW]
[ROW][C]-0.302478492950054[/C][/ROW]
[ROW][C]6.1732455939182[/C][/ROW]
[ROW][C]0.0993924835551327[/C][/ROW]
[ROW][C]-5.79052464599116[/C][/ROW]
[ROW][C]5.84989928285716[/C][/ROW]
[ROW][C]1.63802666538586[/C][/ROW]
[ROW][C]1.34506841848302[/C][/ROW]
[ROW][C]5.97158098164758[/C][/ROW]
[ROW][C]-0.858159643541342[/C][/ROW]
[ROW][C]7.89732766143513[/C][/ROW]
[ROW][C]-1.49602389557607[/C][/ROW]
[ROW][C]1.26033518648678[/C][/ROW]
[ROW][C]-1.47904386296764[/C][/ROW]
[ROW][C]2.82889295128891[/C][/ROW]
[ROW][C]-3.62945239257948[/C][/ROW]
[ROW][C]2.6800891256584[/C][/ROW]
[ROW][C]-1.42101132661476[/C][/ROW]
[ROW][C]2.16036331591487[/C][/ROW]
[ROW][C]0.298099666278185[/C][/ROW]
[ROW][C]3.4583888216932[/C][/ROW]
[ROW][C]-0.747319630243315[/C][/ROW]
[ROW][C]-2.08623509187243[/C][/ROW]
[ROW][C]4.64177875007438[/C][/ROW]
[ROW][C]3.38181815673068[/C][/ROW]
[ROW][C]-1.80327781664126[/C][/ROW]
[ROW][C]6.33815307000637[/C][/ROW]
[ROW][C]-4.91188075348182[/C][/ROW]
[ROW][C]2.5871367419019[/C][/ROW]
[ROW][C]-0.857148528507152[/C][/ROW]
[ROW][C]-2.00415871714141[/C][/ROW]
[ROW][C]5.12696172890453[/C][/ROW]
[ROW][C]8.35189503100999[/C][/ROW]
[ROW][C]1.45523114514816[/C][/ROW]
[ROW][C]8.25198215678349[/C][/ROW]
[ROW][C]-1.39009835835298[/C][/ROW]
[ROW][C]0.521510137549863[/C][/ROW]
[ROW][C]2.85955775357443[/C][/ROW]
[ROW][C]1.17713696587334[/C][/ROW]
[ROW][C]2.08223526709373[/C][/ROW]
[ROW][C]3.94730038555576[/C][/ROW]
[ROW][C]2.30209207232646[/C][/ROW]
[ROW][C]-10.2204425177615[/C][/ROW]
[ROW][C]2.26988280576407[/C][/ROW]
[ROW][C]-4.33510774462436[/C][/ROW]
[ROW][C]-2.75959339560696[/C][/ROW]
[ROW][C]-1.08375312766277[/C][/ROW]
[ROW][C]-4.65657126458126[/C][/ROW]
[ROW][C]-2.43276121142529[/C][/ROW]
[ROW][C]0.310539400796128[/C][/ROW]
[ROW][C]-3.01600836416012[/C][/ROW]
[ROW][C]-8.64256680644585[/C][/ROW]
[ROW][C]6.00185099616093[/C][/ROW]
[ROW][C]-3.18960658784065[/C][/ROW]
[ROW][C]-4.22561345270917[/C][/ROW]
[ROW][C]-5.37141272177894[/C][/ROW]
[ROW][C]1.18741444744113[/C][/ROW]
[ROW][C]1.75712465429544[/C][/ROW]
[ROW][C]3.93977951240657[/C][/ROW]
[ROW][C]-3.77134959542952[/C][/ROW]
[ROW][C]2.65125462626012[/C][/ROW]
[ROW][C]-1.89989574702174[/C][/ROW]
[ROW][C]1.18374453467759[/C][/ROW]
[ROW][C]3.50710639907773[/C][/ROW]
[ROW][C]5.77573710302503[/C][/ROW]
[ROW][C]0.608262579498656[/C][/ROW]
[ROW][C]2.05816885861869[/C][/ROW]
[ROW][C]-6.29327210861513[/C][/ROW]
[ROW][C]0.898792841791191[/C][/ROW]
[ROW][C]4.4518149400203[/C][/ROW]
[ROW][C]-8.01541706005978[/C][/ROW]
[ROW][C]-6.12640390341727[/C][/ROW]
[ROW][C]0.888963362094796[/C][/ROW]
[ROW][C]-6.9354774459447[/C][/ROW]
[ROW][C]-8.81890475846638[/C][/ROW]
[ROW][C]5.2409852263649[/C][/ROW]
[ROW][C]4.02361696956346[/C][/ROW]
[ROW][C]-9.12615720537498[/C][/ROW]
[ROW][C]-9.3333700427019[/C][/ROW]
[ROW][C]3.24809064701777[/C][/ROW]
[ROW][C]-2.06229812947806[/C][/ROW]
[ROW][C]0.0292789946023568[/C][/ROW]
[ROW][C]9.48582980321639[/C][/ROW]
[ROW][C]4.84442772392704[/C][/ROW]
[ROW][C]1.79904157643567[/C][/ROW]
[ROW][C]-0.045866502215208[/C][/ROW]
[ROW][C]8.67895504738705[/C][/ROW]
[ROW][C]-6.78878050664347[/C][/ROW]
[ROW][C]-1.11683523555325[/C][/ROW]
[ROW][C]-0.66130246943713[/C][/ROW]
[ROW][C]-7.9836903597607[/C][/ROW]
[ROW][C]-5.44139285218807[/C][/ROW]
[ROW][C]2.1944481846405[/C][/ROW]
[ROW][C]-2.53506676859463[/C][/ROW]
[ROW][C]2.63226705644079[/C][/ROW]
[ROW][C]0.326889627644759[/C][/ROW]
[ROW][C]-2.77381840644999[/C][/ROW]
[ROW][C]-1.43884133016045[/C][/ROW]
[ROW][C]-6.10645393640706[/C][/ROW]
[ROW][C]2.08020999583957[/C][/ROW]
[ROW][C]12.106615103282[/C][/ROW]
[ROW][C]-8.02775422556687[/C][/ROW]
[ROW][C]-13.3939755139849[/C][/ROW]
[ROW][C]-4.59863355065739[/C][/ROW]
[ROW][C]5.11875368220678[/C][/ROW]
[ROW][C]5.48532446616882[/C][/ROW]
[ROW][C]-2.08437210885651[/C][/ROW]
[ROW][C]3.392706040891[/C][/ROW]
[ROW][C]-1.48493248366128[/C][/ROW]
[ROW][C]2.70026695182974[/C][/ROW]
[ROW][C]1.84814665788656[/C][/ROW]
[ROW][C]-1.67866482077488[/C][/ROW]
[ROW][C]3.24709996727309[/C][/ROW]
[ROW][C]-8.48435405937905[/C][/ROW]
[ROW][C]-0.915914780845507[/C][/ROW]
[ROW][C]-4.57656328288288[/C][/ROW]
[ROW][C]-0.809525063645757[/C][/ROW]
[ROW][C]1.34854004655264[/C][/ROW]
[ROW][C]-0.311163437842765[/C][/ROW]
[ROW][C]-3.17812027344872[/C][/ROW]
[ROW][C]7.76253192299654[/C][/ROW]
[ROW][C]-3.57505148119773[/C][/ROW]
[ROW][C]1.73526471570766[/C][/ROW]
[ROW][C]-1.76129779799427[/C][/ROW]
[ROW][C]9.91930725016443[/C][/ROW]
[ROW][C]-6.38044799914943[/C][/ROW]
[ROW][C]-0.0927649213110234[/C][/ROW]
[ROW][C]-5.17046591677725[/C][/ROW]
[ROW][C]-4.34801338264625[/C][/ROW]
[ROW][C]6.63853034434849[/C][/ROW]
[ROW][C]5.54078016201049[/C][/ROW]
[ROW][C]4.06113912444872[/C][/ROW]
[ROW][C]0.443619152117213[/C][/ROW]
[ROW][C]6.35528726455257[/C][/ROW]
[ROW][C]-4.26389615760859[/C][/ROW]
[ROW][C]0.571020932025585[/C][/ROW]
[ROW][C]-1.17826872848335[/C][/ROW]
[ROW][C]16.5109581253798[/C][/ROW]
[ROW][C]0.964963159468123[/C][/ROW]
[ROW][C]-17.4071839919191[/C][/ROW]
[ROW][C]-0.522791412377851[/C][/ROW]
[ROW][C]0.835531276998813[/C][/ROW]
[ROW][C]8.5031318202778[/C][/ROW]
[ROW][C]5.7355289404567[/C][/ROW]
[ROW][C]-4.06144368788898[/C][/ROW]
[ROW][C]2.79137616821308[/C][/ROW]
[ROW][C]2.11604172514896[/C][/ROW]
[ROW][C]7.20331712589241[/C][/ROW]
[ROW][C]-18.7714140835119[/C][/ROW]
[ROW][C]0.585507839187224[/C][/ROW]
[ROW][C]8.97803171466246[/C][/ROW]
[ROW][C]12.4920066744206[/C][/ROW]
[ROW][C]-2.40392575957367[/C][/ROW]
[ROW][C]1.87695973399627[/C][/ROW]
[ROW][C]1.25438410518603[/C][/ROW]
[ROW][C]-1.46293052161354[/C][/ROW]
[ROW][C]6.72871131739579[/C][/ROW]
[ROW][C]-1.99220013159346[/C][/ROW]
[ROW][C]3.09877181914469[/C][/ROW]
[ROW][C]4.1582661600124[/C][/ROW]
[ROW][C]-7.45859851214467[/C][/ROW]
[ROW][C]0.053321192990512[/C][/ROW]
[ROW][C]-4.41071328984103[/C][/ROW]
[ROW][C]-5.7184912450394[/C][/ROW]
[ROW][C]4.61799934272152[/C][/ROW]
[ROW][C]3.58961153220946[/C][/ROW]
[ROW][C]2.52747349919649[/C][/ROW]
[ROW][C]1.30446220990521[/C][/ROW]
[ROW][C]-5.81881391304613[/C][/ROW]
[ROW][C]0.811845327841342[/C][/ROW]
[ROW][C]2.86751837618379[/C][/ROW]
[ROW][C]-5.71751886020892[/C][/ROW]
[ROW][C]-0.123780313822417[/C][/ROW]
[ROW][C]6.52739153590004[/C][/ROW]
[ROW][C]11.2885579472426[/C][/ROW]
[ROW][C]-4.33411208739956[/C][/ROW]
[ROW][C]-5.8723950678609[/C][/ROW]
[ROW][C]-8.15122283905666[/C][/ROW]
[ROW][C]1.07783271226473[/C][/ROW]
[ROW][C]4.57433096261199[/C][/ROW]
[ROW][C]-0.592770433482863[/C][/ROW]
[ROW][C]0.411365331134307[/C][/ROW]
[ROW][C]-0.149933001584183[/C][/ROW]
[ROW][C]0.206222228581196[/C][/ROW]
[ROW][C]-12.1907499967954[/C][/ROW]
[ROW][C]3.72839107758182[/C][/ROW]
[ROW][C]-7.10628259662316[/C][/ROW]
[ROW][C]-0.508924801394239[/C][/ROW]
[ROW][C]3.30403981260061[/C][/ROW]
[ROW][C]-1.76792038730655[/C][/ROW]
[ROW][C]0.4810722515175[/C][/ROW]
[ROW][C]0.561913067646686[/C][/ROW]
[ROW][C]4.88308987912015[/C][/ROW]
[ROW][C]5.06547426939577[/C][/ROW]
[ROW][C]-0.0142817041629347[/C][/ROW]
[ROW][C]-6.71006157054785[/C][/ROW]
[ROW][C]-8.38938781207838[/C][/ROW]
[ROW][C]0.704364827602098[/C][/ROW]
[ROW][C]-17.56025835431[/C][/ROW]
[ROW][C]-2.88442777435588[/C][/ROW]
[ROW][C]-4.75130653934548[/C][/ROW]
[ROW][C]8.6155726079912[/C][/ROW]
[ROW][C]-5.89752723606562[/C][/ROW]
[ROW][C]-1.5604059970912[/C][/ROW]
[ROW][C]3.53749491284865[/C][/ROW]
[ROW][C]-8.11860712937344[/C][/ROW]
[ROW][C]-6.85424970452308[/C][/ROW]
[ROW][C]8.84042979403381[/C][/ROW]
[ROW][C]1.29888334418643[/C][/ROW]
[ROW][C]-14.0967619469544[/C][/ROW]
[ROW][C]9.48883828306574[/C][/ROW]
[ROW][C]5.36986019608196[/C][/ROW]
[ROW][C]9.77164681377232[/C][/ROW]
[ROW][C]-1.81963419747215[/C][/ROW]
[ROW][C]0.583058745629914[/C][/ROW]
[ROW][C]-0.848389732198407[/C][/ROW]
[ROW][C]2.32268639016988[/C][/ROW]
[ROW][C]-8.64597651446204[/C][/ROW]
[ROW][C]16.2317200162606[/C][/ROW]
[ROW][C]-7.10023505565231[/C][/ROW]
[ROW][C]-5.88936251888072[/C][/ROW]
[ROW][C]-1.20391877890568[/C][/ROW]
[ROW][C]2.65476422162358[/C][/ROW]
[ROW][C]14.4993442735723[/C][/ROW]
[ROW][C]9.47757739311795[/C][/ROW]
[ROW][C]5.2678308701691[/C][/ROW]
[ROW][C]9.95388372773352[/C][/ROW]
[ROW][C]10.6380864211721[/C][/ROW]
[ROW][C]-0.813023914066638[/C][/ROW]
[ROW][C]-2.48362281747688[/C][/ROW]
[ROW][C]2.81638569930519[/C][/ROW]
[ROW][C]-5.75612039362401[/C][/ROW]
[ROW][C]-2.63274456116255[/C][/ROW]
[ROW][C]-7.3073934090228[/C][/ROW]
[ROW][C]-5.3570041988903[/C][/ROW]
[ROW][C]4.85353129641589[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66921&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66921&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
-1.05389947172549
8.4416022879863
0.264809227269645
3.61402647545751
2.35089967630583
3.52769728890782
-2.36177429977434
-2.65651876096212
-3.4283485942069
-2.99884785553649
1.99258765783025
2.28027601222431
4.37153301272526
3.2891912398501
-4.30465796011704
-7.56205660616637
-3.96472569389475
-1.32683160618236
1.15344273317683
-1.21036276521473
-0.103393269600576
2.86226847700442
3.19201503137537
-0.484346036524424
-2.23734272045455
-1.67193083282762
-3.72628235308536
-1.1997435889455
-4.51552147586442
0.782361843337378
-1.6079816139996
6.66144507437813
0.115615097015846
-3.14096477472873
-11.9554357704287
-9.60458651471003
-0.565730541013051
-2.59593660150408
-2.29858759052585
-6.90851594198716
5.7558335371874
-2.00548827985797
2.57422580096239
10.2722338405722
-7.04761284912167
-3.09340157945066
3.94489631072717
-8.00055683371443
16.8979740128494
-12.2954413780262
-12.3729171716218
-10.8559610399445
-6.60553080633236
-12.7056286407012
-6.7403618009817
-3.28999071619384
4.25421478298725
-0.390700042346132
-1.28505319333245
12.0533780060711
-7.21238785187422
1.76793712361490
4.57202059577267
4.10948518214669
5.14909984653437
8.04290388282365
-10.5188719921736
-7.67152468863669
3.20253937398167
17.16265889193
-7.80963644246112
6.44209467186323
-2.56850146035081
-7.96053252053479
0.442918372643544
0.902400902718005
-3.13747965267471
0.0586115500217112
-0.594363204386132
-9.83263587475384
-2.06944538960645
-2.96354673048204
1.49895087018255
-4.73215337193649
0.420318403856962
1.74523389325738
-3.81206784432846
0.810447426617338
-1.78307109450322
0.163214499466636
2.67433073911937
-4.57723527521646
-8.67907940828837
-1.77255966119988
2.06381114805042
2.23071928055821
-1.39811757394171
1.98375072571723
9.37247395930867
-6.74227766888264
-0.715024887450298
2.14203936798073
-4.08093041248461
3.64296045336104
-7.74732385740661
0.755516796141954
1.17881917306037
2.78180428905239
0.665601360838618
-0.0364235602931105
-0.389504457830173
4.8262131876641
-0.302478492950054
6.1732455939182
0.0993924835551327
-5.79052464599116
5.84989928285716
1.63802666538586
1.34506841848302
5.97158098164758
-0.858159643541342
7.89732766143513
-1.49602389557607
1.26033518648678
-1.47904386296764
2.82889295128891
-3.62945239257948
2.6800891256584
-1.42101132661476
2.16036331591487
0.298099666278185
3.4583888216932
-0.747319630243315
-2.08623509187243
4.64177875007438
3.38181815673068
-1.80327781664126
6.33815307000637
-4.91188075348182
2.5871367419019
-0.857148528507152
-2.00415871714141
5.12696172890453
8.35189503100999
1.45523114514816
8.25198215678349
-1.39009835835298
0.521510137549863
2.85955775357443
1.17713696587334
2.08223526709373
3.94730038555576
2.30209207232646
-10.2204425177615
2.26988280576407
-4.33510774462436
-2.75959339560696
-1.08375312766277
-4.65657126458126
-2.43276121142529
0.310539400796128
-3.01600836416012
-8.64256680644585
6.00185099616093
-3.18960658784065
-4.22561345270917
-5.37141272177894
1.18741444744113
1.75712465429544
3.93977951240657
-3.77134959542952
2.65125462626012
-1.89989574702174
1.18374453467759
3.50710639907773
5.77573710302503
0.608262579498656
2.05816885861869
-6.29327210861513
0.898792841791191
4.4518149400203
-8.01541706005978
-6.12640390341727
0.888963362094796
-6.9354774459447
-8.81890475846638
5.2409852263649
4.02361696956346
-9.12615720537498
-9.3333700427019
3.24809064701777
-2.06229812947806
0.0292789946023568
9.48582980321639
4.84442772392704
1.79904157643567
-0.045866502215208
8.67895504738705
-6.78878050664347
-1.11683523555325
-0.66130246943713
-7.9836903597607
-5.44139285218807
2.1944481846405
-2.53506676859463
2.63226705644079
0.326889627644759
-2.77381840644999
-1.43884133016045
-6.10645393640706
2.08020999583957
12.106615103282
-8.02775422556687
-13.3939755139849
-4.59863355065739
5.11875368220678
5.48532446616882
-2.08437210885651
3.392706040891
-1.48493248366128
2.70026695182974
1.84814665788656
-1.67866482077488
3.24709996727309
-8.48435405937905
-0.915914780845507
-4.57656328288288
-0.809525063645757
1.34854004655264
-0.311163437842765
-3.17812027344872
7.76253192299654
-3.57505148119773
1.73526471570766
-1.76129779799427
9.91930725016443
-6.38044799914943
-0.0927649213110234
-5.17046591677725
-4.34801338264625
6.63853034434849
5.54078016201049
4.06113912444872
0.443619152117213
6.35528726455257
-4.26389615760859
0.571020932025585
-1.17826872848335
16.5109581253798
0.964963159468123
-17.4071839919191
-0.522791412377851
0.835531276998813
8.5031318202778
5.7355289404567
-4.06144368788898
2.79137616821308
2.11604172514896
7.20331712589241
-18.7714140835119
0.585507839187224
8.97803171466246
12.4920066744206
-2.40392575957367
1.87695973399627
1.25438410518603
-1.46293052161354
6.72871131739579
-1.99220013159346
3.09877181914469
4.1582661600124
-7.45859851214467
0.053321192990512
-4.41071328984103
-5.7184912450394
4.61799934272152
3.58961153220946
2.52747349919649
1.30446220990521
-5.81881391304613
0.811845327841342
2.86751837618379
-5.71751886020892
-0.123780313822417
6.52739153590004
11.2885579472426
-4.33411208739956
-5.8723950678609
-8.15122283905666
1.07783271226473
4.57433096261199
-0.592770433482863
0.411365331134307
-0.149933001584183
0.206222228581196
-12.1907499967954
3.72839107758182
-7.10628259662316
-0.508924801394239
3.30403981260061
-1.76792038730655
0.4810722515175
0.561913067646686
4.88308987912015
5.06547426939577
-0.0142817041629347
-6.71006157054785
-8.38938781207838
0.704364827602098
-17.56025835431
-2.88442777435588
-4.75130653934548
8.6155726079912
-5.89752723606562
-1.5604059970912
3.53749491284865
-8.11860712937344
-6.85424970452308
8.84042979403381
1.29888334418643
-14.0967619469544
9.48883828306574
5.36986019608196
9.77164681377232
-1.81963419747215
0.583058745629914
-0.848389732198407
2.32268639016988
-8.64597651446204
16.2317200162606
-7.10023505565231
-5.88936251888072
-1.20391877890568
2.65476422162358
14.4993442735723
9.47757739311795
5.2678308701691
9.95388372773352
10.6380864211721
-0.813023914066638
-2.48362281747688
2.81638569930519
-5.75612039362401
-2.63274456116255
-7.3073934090228
-5.3570041988903
4.85353129641589

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

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Figure 3

PNG link

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Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

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Figure 7

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 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 <- 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code