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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_arimabackwardselection.wasp
Title produced by softwareARIMA Backward Selection
Date of computationTue, 28 Dec 2010 09:23:51 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t1293528208l5j92ip1gv02kzx.htm/, Retrieved Sun, 05 May 2024 00:51:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116246, Retrieved Sun, 05 May 2024 00:51:26 +0000
QR Codes:

Original text written by user:We hebben hier volgende parameters ingesteld: lambda= 1 d = 1 D = 0 p = 3 (maximum waarde) q = 1 (maximum waarde) P = 2 (maximum waarde) Q = 1 (maximum waarde)
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

Tree of Dependent Computations

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]
F   PD      [ARIMA Backward Selection] [Workshop 6 'Aanta...] [2010-12-14 18:47:02] [40c8b935cbad1b0be3c22a481f9723f7]
- R P         [ARIMA Backward Selection] [ARIMA backward se...] [2010-12-17 15:45:37] [75b8170d590d2aca2c97c1862bb2167f]
-   PD          [ARIMA Backward Selection] [ARIMA BACKWARD Se...] [2010-12-26 13:20:22] [c895532cb7349383dee5125244983cc8]
-                   [ARIMA Backward Selection] [ARIMA backward se...] [2010-12-28 09:23:51] [a4848c79f7a98c5639a543e143e21e11] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10
10
10
10
10
9.94
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
10.06
9.94
9.94
9.94
9.94
9.94
9.94
10.06
10.06
9.94
10.06
10.06
10.06
10.18
10.28
10.28
10.18
10.28
10.28
10.28
10.18
10.28
10.28
10.18
10.18
10.18
10.28
10.28
10.18
10.18
10.18
10.18
10.18
10.18
10.28
10.28
10.28
10.18
10.18
10.18
10.28
10.18
10.18
10.28
10.18
10.18
10.18
10.28
10.28
10.28
10.28
10.28
10.28
10.18
10.18
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10.18
10.18
10.18
10.18
10.18
10.18
10.28
10.28
10.28
10.28
10.28
10.28
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10.28
10.18
10.28
10.28
10.28
10.28
10.18
10.28
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10.28
10.18
10.18
10.28
10.28
10.28
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10.28
10.18
10.28
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10.28
10.42
10.42
10.42
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10.42
10.42
10.42
10.42
10.42
10.42
10.34
10.34
10.34
10.42
10.42
10.42
10.42
10.34
10.42
10.42
10.42
10.42
10.42
10.42
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10.34
10.34
10.34
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10.42
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10.34
10.34
10.34
10.42
10.42
10.42
10.34
10.34
10.34
10.34
10.34
10.42
10.42
10.42
10.34
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.34
10.34
10.34
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.42
10.34
10.34
10.42
10.42
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.49
10.49
10.55
10.55
10.55
10.55
10.55
10.55
10.49
10.55
10.55
10.55
10.55
10.55
10.55
10.49
10.49
10.55
10.55
10.55
10.49
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.55
10.49
10.49
10.49
10.55
10.55
10.55
10.49
10.55
10.55
10.55
10.63
10.63
10.63
10.63
10.63
10.57
10.63
10.63
10.63
10.63
10.57
10.57
10.57
10.63
10.63
10.63
10.63
10.57
10.63
10.63
10.57
10.63
10.63
10.63
10.63
10.57
10.63
10.6
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.6
10.6
10.6
10.6
10.7
10.7
10.6
10.7
10.7
10.7
10.7
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10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.7
10.8
10.8
10.8
10.8
10.7
10.7
10.7
10.85
10.75
10.75
10.75
10.75
10.75
10.75
10.75
10.75
10.75
10.75
10.75
10.85
10.85
10.85
10.85
10.85
10.85
10.85
10.85
10.85
10.85
10.75
10.75
10.85
10.85
10.85
10.85
10.75
10.75
10.75
10.75
10.75

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time30 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 & 30 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116246&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]30 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=116246&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116246&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time30 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2ar3ma1sar1sar2sma1
Estimates ( 1 )0.5683-0.00410.0453-0.84990.0590.0683-0.0392
(p-val)(0 )(0.9515 )(0.5008 )(0 )(0.9257 )(0.231 )(0.9504 )
Estimates ( 2 )0.565800.0432-0.85010.01310.06890.0069
(p-val)(0 )(NA )(0.5163 )(0 )(0.983 )(0.218 )(0.991 )
Estimates ( 3 )0.568600.0445-0.85180.02030.06890
(p-val)(0 )(NA )(0.5 )(0 )(0.7207 )(0.211 )(NA )
Estimates ( 4 )0.556800.0406-0.842900.06860
(p-val)(0 )(NA )(0.5435 )(0 )(NA )(0.2137 )(NA )
Estimates ( 5 )0.511400-0.798100.06840
(p-val)(0 )(NA )(NA )(0 )(NA )(0.2157 )(NA )
Estimates ( 6 )0.490400-0.7819000
(p-val)(0 )(NA )(NA )(0 )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 12 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 13 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & 0.5683 & -0.0041 & 0.0453 & -0.8499 & 0.059 & 0.0683 & -0.0392 \tabularnewline
(p-val) & (0 ) & (0.9515 ) & (0.5008 ) & (0 ) & (0.9257 ) & (0.231 ) & (0.9504 ) \tabularnewline
Estimates ( 2 ) & 0.5658 & 0 & 0.0432 & -0.8501 & 0.0131 & 0.0689 & 0.0069 \tabularnewline
(p-val) & (0 ) & (NA ) & (0.5163 ) & (0 ) & (0.983 ) & (0.218 ) & (0.991 ) \tabularnewline
Estimates ( 3 ) & 0.5686 & 0 & 0.0445 & -0.8518 & 0.0203 & 0.0689 & 0 \tabularnewline
(p-val) & (0 ) & (NA ) & (0.5 ) & (0 ) & (0.7207 ) & (0.211 ) & (NA ) \tabularnewline
Estimates ( 4 ) & 0.5568 & 0 & 0.0406 & -0.8429 & 0 & 0.0686 & 0 \tabularnewline
(p-val) & (0 ) & (NA ) & (0.5435 ) & (0 ) & (NA ) & (0.2137 ) & (NA ) \tabularnewline
Estimates ( 5 ) & 0.5114 & 0 & 0 & -0.7981 & 0 & 0.0684 & 0 \tabularnewline
(p-val) & (0 ) & (NA ) & (NA ) & (0 ) & (NA ) & (0.2157 ) & (NA ) \tabularnewline
Estimates ( 6 ) & 0.4904 & 0 & 0 & -0.7819 & 0 & 0 & 0 \tabularnewline
(p-val) & (0 ) & (NA ) & (NA ) & (0 ) & (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=116246&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]0.5683[/C][C]-0.0041[/C][C]0.0453[/C][C]-0.8499[/C][C]0.059[/C][C]0.0683[/C][C]-0.0392[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.9515 )[/C][C](0.5008 )[/C][C](0 )[/C][C](0.9257 )[/C][C](0.231 )[/C][C](0.9504 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.5658[/C][C]0[/C][C]0.0432[/C][C]-0.8501[/C][C]0.0131[/C][C]0.0689[/C][C]0.0069[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](0.5163 )[/C][C](0 )[/C][C](0.983 )[/C][C](0.218 )[/C][C](0.991 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0.5686[/C][C]0[/C][C]0.0445[/C][C]-0.8518[/C][C]0.0203[/C][C]0.0689[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](0.5 )[/C][C](0 )[/C][C](0.7207 )[/C][C](0.211 )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0.5568[/C][C]0[/C][C]0.0406[/C][C]-0.8429[/C][C]0[/C][C]0.0686[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](0.5435 )[/C][C](0 )[/C][C](NA )[/C][C](0.2137 )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]0.5114[/C][C]0[/C][C]0[/C][C]-0.7981[/C][C]0[/C][C]0.0684[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][C](NA )[/C][C](0.2157 )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]0.4904[/C][C]0[/C][C]0[/C][C]-0.7819[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/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=116246&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116246&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2ar3ma1sar1sar2sma1
Estimates ( 1 )0.5683-0.00410.0453-0.84990.0590.0683-0.0392
(p-val)(0 )(0.9515 )(0.5008 )(0 )(0.9257 )(0.231 )(0.9504 )
Estimates ( 2 )0.565800.0432-0.85010.01310.06890.0069
(p-val)(0 )(NA )(0.5163 )(0 )(0.983 )(0.218 )(0.991 )
Estimates ( 3 )0.568600.0445-0.85180.02030.06890
(p-val)(0 )(NA )(0.5 )(0 )(0.7207 )(0.211 )(NA )
Estimates ( 4 )0.556800.0406-0.842900.06860
(p-val)(0 )(NA )(0.5435 )(0 )(NA )(0.2137 )(NA )
Estimates ( 5 )0.511400-0.798100.06840
(p-val)(0 )(NA )(NA )(0 )(NA )(0.2157 )(NA )
Estimates ( 6 )0.490400-0.7819000
(p-val)(0 )(NA )(NA )(0 )(NA )(NA )(NA )
Estimates ( 7 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 8 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 9 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 10 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 11 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 12 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 13 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )






Estimated ARIMA Residuals
Value
0.00999999441741765
2.18466871311649e-06
1.60358108020423e-06
1.21778698489518e-06
9.42865414664583e-07
-0.0594269157011813
0.102776269776958
0.0203675520303013
0.0161785913104872
0.0128733066649317
0.0102544613006946
0.00817403703887163
0.00651858798917304
0.00519993732323023
0.00414892600253484
0.00331101649987624
0.00264310127126963
0.00211115500282611
0.00168853928987249
0.00135489182465135
-0.118624009464853
-0.033422881169734
-0.0266276879964830
-0.0211632890860420
-0.0167279226306115
-0.0134365812118422
0.109266277486939
0.0258233304433997
-0.099387927663909
0.106155140151518
0.0130380310071018
0.0146044036050458
0.131654351925100
0.143700837259228
0.0635436470079612
-0.0492872241937609
0.111805056625835
0.0380888968968041
0.0303979002778869
-0.0757400700794453
0.0906936645616727
0.0212404649160439
-0.083048431858437
-0.0151389782796319
-0.00387057511315093
0.0927115859236417
0.0228509404526591
-0.0817631497113515
-0.0141132274718329
-0.0112634667413033
-0.0172006541993972
-0.00952808793501963
0.00060735645576289
0.0880738088323331
0.0233490194617765
0.0186343560932779
-0.0933398373893489
-0.025995882012764
-0.0172472704183547
0.0930782541741359
-0.0871988520419995
-0.0149518561670927
0.088067241422673
-0.074012676230925
-0.0182701644668412
-0.0110815394727555
0.097998992979995
0.0235712190738143
0.0188116888914163
0.0081702749517715
0.0100200131850174
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\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.00999999441741765 \tabularnewline
2.18466871311649e-06 \tabularnewline
1.60358108020423e-06 \tabularnewline
1.21778698489518e-06 \tabularnewline
9.42865414664583e-07 \tabularnewline
-0.0594269157011813 \tabularnewline
0.102776269776958 \tabularnewline
0.0203675520303013 \tabularnewline
0.0161785913104872 \tabularnewline
0.0128733066649317 \tabularnewline
0.0102544613006946 \tabularnewline
0.00817403703887163 \tabularnewline
0.00651858798917304 \tabularnewline
0.00519993732323023 \tabularnewline
0.00414892600253484 \tabularnewline
0.00331101649987624 \tabularnewline
0.00264310127126963 \tabularnewline
0.00211115500282611 \tabularnewline
0.00168853928987249 \tabularnewline
0.00135489182465135 \tabularnewline
-0.118624009464853 \tabularnewline
-0.033422881169734 \tabularnewline
-0.0266276879964830 \tabularnewline
-0.0211632890860420 \tabularnewline
-0.0167279226306115 \tabularnewline
-0.0134365812118422 \tabularnewline
0.109266277486939 \tabularnewline
0.0258233304433997 \tabularnewline
-0.099387927663909 \tabularnewline
0.106155140151518 \tabularnewline
0.0130380310071018 \tabularnewline
0.0146044036050458 \tabularnewline
0.131654351925100 \tabularnewline
0.143700837259228 \tabularnewline
0.0635436470079612 \tabularnewline
-0.0492872241937609 \tabularnewline
0.111805056625835 \tabularnewline
0.0380888968968041 \tabularnewline
0.0303979002778869 \tabularnewline
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0.0906936645616727 \tabularnewline
0.0212404649160439 \tabularnewline
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0.0186343560932779 \tabularnewline
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0.00105493966346692 \tabularnewline
0.0973424344998113 \tabularnewline
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0.0217896207784722 \tabularnewline
0.0138903427423767 \tabularnewline
0.00424265320286565 \tabularnewline
0.0137283958303485 \tabularnewline
0.00745685046803857 \tabularnewline
-0.0940488461510824 \tabularnewline
0.0692388846474081 \tabularnewline
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0.00485172827766078 \tabularnewline
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0.0150977768722011 \tabularnewline
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0.00883856333806143 \tabularnewline
0.00705386951953102 \tabularnewline
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0.00253110905303977 \tabularnewline
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0.144506421143099 \tabularnewline
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0.0229724863277170 \tabularnewline
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0.0174247272858530 \tabularnewline
0.01390630445092 \tabularnewline
0.0179412600511828 \tabularnewline
0.00397611377618467 \tabularnewline
0.00667274230570669 \tabularnewline
-0.0746746262077202 \tabularnewline
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0.0628222267873788 \tabularnewline
0.0127244112960749 \tabularnewline
0.0101550821736893 \tabularnewline
0.00810455521711795 \tabularnewline
-0.0735319267590473 \tabularnewline
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0.00323380959770780 \tabularnewline
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-0.0228238636483073 \tabularnewline
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0.0676970989595222 \tabularnewline
0.0131154527310873 \tabularnewline
-0.0640584887101525 \tabularnewline
-0.0184854948325697 \tabularnewline
-0.0119532881446389 \tabularnewline
0.0704603348217745 \tabularnewline
0.0153207325348852 \tabularnewline
0.0122271509646072 \tabularnewline
-0.0702417707266374 \tabularnewline
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-0.00964712876409024 \tabularnewline
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0.0738554573617609 \tabularnewline
0.0180303076642225 \tabularnewline
0.0143896052781276 \tabularnewline
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0.0662310301577324 \tabularnewline
0.0119454143844759 \tabularnewline
0.0095333812976115 \tabularnewline
0.0130827362225734 \tabularnewline
0.00764146134397236 \tabularnewline
0.0060984878647421 \tabularnewline
0.0048670735298213 \tabularnewline
-0.00159003933402069 \tabularnewline
0.00153061574351909 \tabularnewline
0.006695899147946 \tabularnewline
0.00254426243915518 \tabularnewline
0.00203052176952312 \tabularnewline
-0.00385383099757952 \tabularnewline
-0.0802760682619432 \tabularnewline
-0.0231544607412886 \tabularnewline
-0.0130047356660441 \tabularnewline
0.0668216045687977 \tabularnewline
0.0124167392681578 \tabularnewline
0.00990953566836516 \tabularnewline
0.00790858977078024 \tabularnewline
0.000837330124641156 \tabularnewline
0.00346784771009467 \tabularnewline
0.00276761554168736 \tabularnewline
0.00768312239206814 \tabularnewline
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0.00212815101265029 \tabularnewline
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-0.0181540991555362 \tabularnewline
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0.0456651625467526 \tabularnewline
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0.0471282434909632 \tabularnewline
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0.00135120707401093 \tabularnewline
0.00107836964327745 \tabularnewline
0.00086062388948882 \tabularnewline
0.000686845631992838 \tabularnewline
0.0005481568986756 \tabularnewline
0.00043747236870928 \tabularnewline
0.100349137398156 \tabularnewline
0.0289463097981226 \tabularnewline
0.0231014345406795 \tabularnewline
0.0252796979157352 \tabularnewline
-0.0833243008826425 \tabularnewline
-0.0153591496705658 \tabularnewline
-0.0122578108639644 \tabularnewline
0.133374367638682 \tabularnewline
-0.066767567363744 \tabularnewline
0.00469736147982758 \tabularnewline
-0.00659356014920931 \tabularnewline
-0.00176268977550542 \tabularnewline
-0.00140676524048722 \tabularnewline
-0.00112270943494508 \tabularnewline
-0.000896010534692237 \tabularnewline
-0.0007150869613195 \tabularnewline
-0.000570695703288493 \tabularnewline
-0.000455460109565209 \tabularnewline
-0.000363493031768414 \tabularnewline
0.099709903938086 \tabularnewline
0.0284361511617703 \tabularnewline
0.0226942877774068 \tabularnewline
0.0181118286646384 \tabularnewline
0.0144546654556734 \tabularnewline
0.00469302716458841 \tabularnewline
0.00724489564162667 \tabularnewline
0.0057819972074622 \tabularnewline
0.00461448906386153 \tabularnewline
0.0105256597060865 \tabularnewline
-0.0950991851524492 \tabularnewline
-0.0247564345086051 \tabularnewline
0.0699780147530475 \tabularnewline
0.0167999321166601 \tabularnewline
0.00990817828676249 \tabularnewline
0.00790750647337823 \tabularnewline
-0.0936891871727781 \tabularnewline
-0.0236311450932334 \tabularnewline
-0.0188595145737036 \tabularnewline
-0.0150513776862056 \tabularnewline
-0.0120121845855277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116246&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.00999999441741765[/C][/ROW]
[ROW][C]2.18466871311649e-06[/C][/ROW]
[ROW][C]1.60358108020423e-06[/C][/ROW]
[ROW][C]1.21778698489518e-06[/C][/ROW]
[ROW][C]9.42865414664583e-07[/C][/ROW]
[ROW][C]-0.0594269157011813[/C][/ROW]
[ROW][C]0.102776269776958[/C][/ROW]
[ROW][C]0.0203675520303013[/C][/ROW]
[ROW][C]0.0161785913104872[/C][/ROW]
[ROW][C]0.0128733066649317[/C][/ROW]
[ROW][C]0.0102544613006946[/C][/ROW]
[ROW][C]0.00817403703887163[/C][/ROW]
[ROW][C]0.00651858798917304[/C][/ROW]
[ROW][C]0.00519993732323023[/C][/ROW]
[ROW][C]0.00414892600253484[/C][/ROW]
[ROW][C]0.00331101649987624[/C][/ROW]
[ROW][C]0.00264310127126963[/C][/ROW]
[ROW][C]0.00211115500282611[/C][/ROW]
[ROW][C]0.00168853928987249[/C][/ROW]
[ROW][C]0.00135489182465135[/C][/ROW]
[ROW][C]-0.118624009464853[/C][/ROW]
[ROW][C]-0.033422881169734[/C][/ROW]
[ROW][C]-0.0266276879964830[/C][/ROW]
[ROW][C]-0.0211632890860420[/C][/ROW]
[ROW][C]-0.0167279226306115[/C][/ROW]
[ROW][C]-0.0134365812118422[/C][/ROW]
[ROW][C]0.109266277486939[/C][/ROW]
[ROW][C]0.0258233304433997[/C][/ROW]
[ROW][C]-0.099387927663909[/C][/ROW]
[ROW][C]0.106155140151518[/C][/ROW]
[ROW][C]0.0130380310071018[/C][/ROW]
[ROW][C]0.0146044036050458[/C][/ROW]
[ROW][C]0.131654351925100[/C][/ROW]
[ROW][C]0.143700837259228[/C][/ROW]
[ROW][C]0.0635436470079612[/C][/ROW]
[ROW][C]-0.0492872241937609[/C][/ROW]
[ROW][C]0.111805056625835[/C][/ROW]
[ROW][C]0.0380888968968041[/C][/ROW]
[ROW][C]0.0303979002778869[/C][/ROW]
[ROW][C]-0.0757400700794453[/C][/ROW]
[ROW][C]0.0906936645616727[/C][/ROW]
[ROW][C]0.0212404649160439[/C][/ROW]
[ROW][C]-0.083048431858437[/C][/ROW]
[ROW][C]-0.0151389782796319[/C][/ROW]
[ROW][C]-0.00387057511315093[/C][/ROW]
[ROW][C]0.0927115859236417[/C][/ROW]
[ROW][C]0.0228509404526591[/C][/ROW]
[ROW][C]-0.0817631497113515[/C][/ROW]
[ROW][C]-0.0141132274718329[/C][/ROW]
[ROW][C]-0.0112634667413033[/C][/ROW]
[ROW][C]-0.0172006541993972[/C][/ROW]
[ROW][C]-0.00952808793501963[/C][/ROW]
[ROW][C]0.00060735645576289[/C][/ROW]
[ROW][C]0.0880738088323331[/C][/ROW]
[ROW][C]0.0233490194617765[/C][/ROW]
[ROW][C]0.0186343560932779[/C][/ROW]
[ROW][C]-0.0933398373893489[/C][/ROW]
[ROW][C]-0.025995882012764[/C][/ROW]
[ROW][C]-0.0172472704183547[/C][/ROW]
[ROW][C]0.0930782541741359[/C][/ROW]
[ROW][C]-0.0871988520419995[/C][/ROW]
[ROW][C]-0.0149518561670927[/C][/ROW]
[ROW][C]0.088067241422673[/C][/ROW]
[ROW][C]-0.074012676230925[/C][/ROW]
[ROW][C]-0.0182701644668412[/C][/ROW]
[ROW][C]-0.0110815394727555[/C][/ROW]
[ROW][C]0.097998992979995[/C][/ROW]
[ROW][C]0.0235712190738143[/C][/ROW]
[ROW][C]0.0188116888914163[/C][/ROW]
[ROW][C]0.0081702749517715[/C][/ROW]
[ROW][C]0.0100200131850174[/C][/ROW]
[ROW][C]0.0148396936024177[/C][/ROW]
[ROW][C]-0.0916562464028246[/C][/ROW]
[ROW][C]-0.0220086982787698[/C][/ROW]
[ROW][C]-0.0175646742592913[/C][/ROW]
[ROW][C]-0.0140179931555796[/C][/ROW]
[ROW][C]-0.0111874623582009[/C][/ROW]
[ROW][C]-0.0157714099711741[/C][/ROW]
[ROW][C]-0.00908733662565624[/C][/ROW]
[ROW][C]-0.00725241019220842[/C][/ROW]
[ROW][C]0.00105493966346692[/C][/ROW]
[ROW][C]0.0973424344998113[/C][/ROW]
[ROW][C]0.0265467241281758[/C][/ROW]
[ROW][C]0.0143434421512687[/C][/ROW]
[ROW][C]0.0217896207784722[/C][/ROW]
[ROW][C]0.0138903427423767[/C][/ROW]
[ROW][C]0.00424265320286565[/C][/ROW]
[ROW][C]0.0137283958303485[/C][/ROW]
[ROW][C]0.00745685046803857[/C][/ROW]
[ROW][C]-0.0940488461510824[/C][/ROW]
[ROW][C]0.0692388846474081[/C][/ROW]
[ROW][C]0.00761736880654062[/C][/ROW]
[ROW][C]0.0060792601227515[/C][/ROW]
[ROW][C]0.00485172827766078[/C][/ROW]
[ROW][C]-0.0961279387943658[/C][/ROW]
[ROW][C]0.0744225390779078[/C][/ROW]
[ROW][C]0.0150977768722011[/C][/ROW]
[ROW][C]0.00854972436872714[/C][/ROW]
[ROW][C]-0.0931766467220694[/C][/ROW]
[ROW][C]-0.0232220974545516[/C][/ROW]
[ROW][C]0.081466937651637[/C][/ROW]
[ROW][C]0.0138768275577110[/C][/ROW]
[ROW][C]0.0110748010952868[/C][/ROW]
[ROW][C]0.00883856333806143[/C][/ROW]
[ROW][C]0.00705386951953102[/C][/ROW]
[ROW][C]-0.00121339075396953[/C][/ROW]
[ROW][C]0.00253110905303977[/C][/ROW]
[ROW][C]-0.0979799756683341[/C][/ROW]
[ROW][C]0.0729444678173827[/C][/ROW]
[ROW][C]0.00707522554439599[/C][/ROW]
[ROW][C]0.00564658710952592[/C][/ROW]
[ROW][C]0.144506421143099[/C][/ROW]
[ROW][C]0.0437312178488352[/C][/ROW]
[ROW][C]0.0417438894484565[/C][/ROW]
[ROW][C]0.0229724863277170[/C][/ROW]
[ROW][C]0.0218333434348388[/C][/ROW]
[ROW][C]0.0174247272858530[/C][/ROW]
[ROW][C]0.01390630445092[/C][/ROW]
[ROW][C]0.0179412600511828[/C][/ROW]
[ROW][C]0.00397611377618467[/C][/ROW]
[ROW][C]0.00667274230570669[/C][/ROW]
[ROW][C]-0.0746746262077202[/C][/ROW]
[ROW][C]-0.0118411348331691[/C][/ROW]
[ROW][C]-0.0129496484252147[/C][/ROW]
[ROW][C]0.0628222267873788[/C][/ROW]
[ROW][C]0.0127244112960749[/C][/ROW]
[ROW][C]0.0101550821736893[/C][/ROW]
[ROW][C]0.00810455521711795[/C][/ROW]
[ROW][C]-0.0735319267590473[/C][/ROW]
[ROW][C]0.0622278952325423[/C][/ROW]
[ROW][C]0.00875059749497353[/C][/ROW]
[ROW][C]0.0138265999240588[/C][/ROW]
[ROW][C]0.00069229099370105[/C][/ROW]
[ROW][C]0.00405199314694293[/C][/ROW]
[ROW][C]0.00323380959770780[/C][/ROW]
[ROW][C]-0.00699927300449765[/C][/ROW]
[ROW][C]-0.00068668441277353[/C][/ROW]
[ROW][C]-0.000548028233042785[/C][/ROW]
[ROW][C]-0.000437369683403688[/C][/ROW]
[ROW][C]-0.000349055447195212[/C][/ROW]
[ROW][C]-0.000278573732565235[/C][/ROW]
[ROW][C]-0.000222323774341504[/C][/ROW]
[ROW][C]-0.000177431878384482[/C][/ROW]
[ROW][C]-0.000141604610485402[/C][/ROW]
[ROW][C]-0.000113011629551352[/C][/ROW]
[ROW][C]0.00538415507994294[/C][/ROW]
[ROW][C]-0.0785026126178874[/C][/ROW]
[ROW][C]-0.0217391034899599[/C][/ROW]
[ROW][C]-0.0228238636483073[/C][/ROW]
[ROW][C]-0.0154156480761483[/C][/ROW]
[ROW][C]0.0676970989595222[/C][/ROW]
[ROW][C]0.0131154527310873[/C][/ROW]
[ROW][C]-0.0640584887101525[/C][/ROW]
[ROW][C]-0.0184854948325697[/C][/ROW]
[ROW][C]-0.0119532881446389[/C][/ROW]
[ROW][C]0.0704603348217745[/C][/ROW]
[ROW][C]0.0153207325348852[/C][/ROW]
[ROW][C]0.0122271509646072[/C][/ROW]
[ROW][C]-0.0702417707266374[/C][/ROW]
[ROW][C]-0.0151463011765536[/C][/ROW]
[ROW][C]-0.0120879410053956[/C][/ROW]
[ROW][C]-0.00964712876409024[/C][/ROW]
[ROW][C]-0.00769916839843887[/C][/ROW]
[ROW][C]0.0738554573617609[/C][/ROW]
[ROW][C]0.0180303076642225[/C][/ROW]
[ROW][C]0.0143896052781276[/C][/ROW]
[ROW][C]-0.0685159619061206[/C][/ROW]
[ROW][C]0.0662310301577324[/C][/ROW]
[ROW][C]0.0119454143844759[/C][/ROW]
[ROW][C]0.0095333812976115[/C][/ROW]
[ROW][C]0.0130827362225734[/C][/ROW]
[ROW][C]0.00764146134397236[/C][/ROW]
[ROW][C]0.0060984878647421[/C][/ROW]
[ROW][C]0.0048670735298213[/C][/ROW]
[ROW][C]-0.00159003933402069[/C][/ROW]
[ROW][C]0.00153061574351909[/C][/ROW]
[ROW][C]0.006695899147946[/C][/ROW]
[ROW][C]0.00254426243915518[/C][/ROW]
[ROW][C]0.00203052176952312[/C][/ROW]
[ROW][C]-0.00385383099757952[/C][/ROW]
[ROW][C]-0.0802760682619432[/C][/ROW]
[ROW][C]-0.0231544607412886[/C][/ROW]
[ROW][C]-0.0130047356660441[/C][/ROW]
[ROW][C]0.0668216045687977[/C][/ROW]
[ROW][C]0.0124167392681578[/C][/ROW]
[ROW][C]0.00990953566836516[/C][/ROW]
[ROW][C]0.00790858977078024[/C][/ROW]
[ROW][C]0.000837330124641156[/C][/ROW]
[ROW][C]0.00346784771009467[/C][/ROW]
[ROW][C]0.00276761554168736[/C][/ROW]
[ROW][C]0.00768312239206814[/C][/ROW]
[ROW][C]-0.00214220293424105[/C][/ROW]
[ROW][C]0.00108994571147747[/C][/ROW]
[ROW][C]0.000869862503448004[/C][/ROW]
[ROW][C]0.00069421877340936[/C][/ROW]
[ROW][C]0.000554041246109804[/C][/ROW]
[ROW][C]0.000442168541313848[/C][/ROW]
[ROW][C]-0.0796471146863151[/C][/ROW]
[ROW][C]-0.0226525062621903[/C][/ROW]
[ROW][C]0.0619215162745092[/C][/ROW]
[ROW][C]0.00850608296123845[/C][/ROW]
[ROW][C]0.136788523998296[/C][/ROW]
[ROW][C]0.0426857485608814[/C][/ROW]
[ROW][C]0.0340665885591793[/C][/ROW]
[ROW][C]0.0326621674377669[/C][/ROW]
[ROW][C]0.0232673891985442[/C][/ROW]
[ROW][C]0.0185692087264808[/C][/ROW]
[ROW][C]0.00934534350133198[/C][/ROW]
[ROW][C]0.0102579123319284[/C][/ROW]
[ROW][C]0.00818662178055795[/C][/ROW]
[ROW][C]0.00653356882075329[/C][/ROW]
[ROW][C]-0.0547856976076648[/C][/ROW]
[ROW][C]-0.0130391784979942[/C][/ROW]
[ROW][C]0.0495937088134397[/C][/ROW]
[ROW][C]0.00889556260697866[/C][/ROW]
[ROW][C]0.00709935942442641[/C][/ROW]
[ROW][C]0.00566584784616531[/C][/ROW]
[ROW][C]0.00452179272758713[/C][/ROW]
[ROW][C]0.00360874665653199[/C][/ROW]
[ROW][C]-0.0571199360042378[/C][/ROW]
[ROW][C]0.0450979154564042[/C][/ROW]
[ROW][C]0.0107819127546307[/C][/ROW]
[ROW][C]0.00580522304261244[/C][/ROW]
[ROW][C]-0.000841322150025192[/C][/ROW]
[ROW][C]0.00212815101265029[/C][/ROW]
[ROW][C]-0.00719738221094346[/C][/ROW]
[ROW][C]-0.0611947402013317[/C][/ROW]
[ROW][C]-0.0181540991555362[/C][/ROW]
[ROW][C]0.0455115993640813[/C][/ROW]
[ROW][C]0.00563771782849365[/C][/ROW]
[ROW][C]0.00449934275844122[/C][/ROW]
[ROW][C]-0.0564091701866278[/C][/ROW]
[ROW][C]0.0456651625467526[/C][/ROW]
[ROW][C]0.00576027334030371[/C][/ROW]
[ROW][C]0.00459715170726405[/C][/ROW]
[ROW][C]0.00777464950071938[/C][/ROW]
[ROW][C]0.00410508824896816[/C][/ROW]
[ROW][C]-0.000829576774410867[/C][/ROW]
[ROW][C]0.00143762666308866[/C][/ROW]
[ROW][C]0.00114733928030475[/C][/ROW]
[ROW][C]0.000915667090719552[/C][/ROW]
[ROW][C]-0.0592692255591522[/C][/ROW]
[ROW][C]-0.0166173868501112[/C][/ROW]
[ROW][C]-0.0091562227663129[/C][/ROW]
[ROW][C]0.0464871585463289[/C][/ROW]
[ROW][C]0.00851598512697293[/C][/ROW]
[ROW][C]0.00679642670627878[/C][/ROW]
[ROW][C]-0.0545759163167734[/C][/ROW]
[ROW][C]0.0471282434909632[/C][/ROW]
[ROW][C]0.00692792714129453[/C][/ROW]
[ROW][C]0.00963479182952653[/C][/ROW]
[ROW][C]0.0855896283007063[/C][/ROW]
[ROW][C]0.02328933961393[/C][/ROW]
[ROW][C]0.0206864211389064[/C][/ROW]
[ROW][C]0.016509392981499[/C][/ROW]
[ROW][C]0.017281556044205[/C][/ROW]
[ROW][C]-0.0524134121705728[/C][/ROW]
[ROW][C]0.0509537863343876[/C][/ROW]
[ROW][C]0.00998101156539732[/C][/ROW]
[ROW][C]0.00796563316484544[/C][/ROW]
[ROW][C]0.00635720250408767[/C][/ROW]
[ROW][C]-0.0549264518159909[/C][/ROW]
[ROW][C]-0.0131515114396592[/C][/ROW]
[ROW][C]-0.0104959417194514[/C][/ROW]
[ROW][C]0.0516234120250303[/C][/ROW]
[ROW][C]0.0146211860393315[/C][/ROW]
[ROW][C]0.00956916352420123[/C][/ROW]
[ROW][C]0.00763694599778475[/C][/ROW]
[ROW][C]-0.058010876181477[/C][/ROW]
[ROW][C]0.0464865692920942[/C][/ROW]
[ROW][C]0.00641582060318946[/C][/ROW]
[ROW][C]-0.0507739095127313[/C][/ROW]
[ROW][C]0.0439570896054295[/C][/ROW]
[ROW][C]0.00649679088669686[/C][/ROW]
[ROW][C]0.00518495070495106[/C][/ROW]
[ROW][C]-0.00133634831763629[/C][/ROW]
[ROW][C]-0.058266918848993[/C][/ROW]
[ROW][C]0.0441825328293213[/C][/ROW]
[ROW][C]-0.0254229819210483[/C][/ROW]
[ROW][C]0.095052519636864[/C][/ROW]
[ROW][C]0.0288249521969881[/C][/ROW]
[ROW][C]0.0167991269219918[/C][/ROW]
[ROW][C]0.0155067203513592[/C][/ROW]
[ROW][C]0.0123755838874082[/C][/ROW]
[ROW][C]0.00987669043382588[/C][/ROW]
[ROW][C]0.0119881371316897[/C][/ROW]
[ROW][C]0.00746778316150376[/C][/ROW]
[ROW][C]0.00595987899917638[/C][/ROW]
[ROW][C]0.000650692296202848[/C][/ROW]
[ROW][C]-0.097381002057606[/C][/ROW]
[ROW][C]-0.0265775040762257[/C][/ROW]
[ROW][C]-0.0212109410475332[/C][/ROW]
[ROW][C]-0.0128222407264911[/C][/ROW]
[ROW][C]0.0835613875405361[/C][/ROW]
[ROW][C]0.0176480577450047[/C][/ROW]
[ROW][C]-0.0818096998125384[/C][/ROW]
[ROW][C]0.0796441665508265[/C][/ROW]
[ROW][C]0.0145218069411452[/C][/ROW]
[ROW][C]0.0115895454309349[/C][/ROW]
[ROW][C]0.00924936985046543[/C][/ROW]
[ROW][C]0.0114874859090097[/C][/ROW]
[ROW][C]0.00296246361857477[/C][/ROW]
[ROW][C]0.00651685371586019[/C][/ROW]
[ROW][C]-0.00269181877783176[/C][/ROW]
[ROW][C]0.00135120707401093[/C][/ROW]
[ROW][C]0.00107836964327745[/C][/ROW]
[ROW][C]0.00086062388948882[/C][/ROW]
[ROW][C]0.000686845631992838[/C][/ROW]
[ROW][C]0.0005481568986756[/C][/ROW]
[ROW][C]0.00043747236870928[/C][/ROW]
[ROW][C]0.100349137398156[/C][/ROW]
[ROW][C]0.0289463097981226[/C][/ROW]
[ROW][C]0.0231014345406795[/C][/ROW]
[ROW][C]0.0252796979157352[/C][/ROW]
[ROW][C]-0.0833243008826425[/C][/ROW]
[ROW][C]-0.0153591496705658[/C][/ROW]
[ROW][C]-0.0122578108639644[/C][/ROW]
[ROW][C]0.133374367638682[/C][/ROW]
[ROW][C]-0.066767567363744[/C][/ROW]
[ROW][C]0.00469736147982758[/C][/ROW]
[ROW][C]-0.00659356014920931[/C][/ROW]
[ROW][C]-0.00176268977550542[/C][/ROW]
[ROW][C]-0.00140676524048722[/C][/ROW]
[ROW][C]-0.00112270943494508[/C][/ROW]
[ROW][C]-0.000896010534692237[/C][/ROW]
[ROW][C]-0.0007150869613195[/C][/ROW]
[ROW][C]-0.000570695703288493[/C][/ROW]
[ROW][C]-0.000455460109565209[/C][/ROW]
[ROW][C]-0.000363493031768414[/C][/ROW]
[ROW][C]0.099709903938086[/C][/ROW]
[ROW][C]0.0284361511617703[/C][/ROW]
[ROW][C]0.0226942877774068[/C][/ROW]
[ROW][C]0.0181118286646384[/C][/ROW]
[ROW][C]0.0144546654556734[/C][/ROW]
[ROW][C]0.00469302716458841[/C][/ROW]
[ROW][C]0.00724489564162667[/C][/ROW]
[ROW][C]0.0057819972074622[/C][/ROW]
[ROW][C]0.00461448906386153[/C][/ROW]
[ROW][C]0.0105256597060865[/C][/ROW]
[ROW][C]-0.0950991851524492[/C][/ROW]
[ROW][C]-0.0247564345086051[/C][/ROW]
[ROW][C]0.0699780147530475[/C][/ROW]
[ROW][C]0.0167999321166601[/C][/ROW]
[ROW][C]0.00990817828676249[/C][/ROW]
[ROW][C]0.00790750647337823[/C][/ROW]
[ROW][C]-0.0936891871727781[/C][/ROW]
[ROW][C]-0.0236311450932334[/C][/ROW]
[ROW][C]-0.0188595145737036[/C][/ROW]
[ROW][C]-0.0150513776862056[/C][/ROW]
[ROW][C]-0.0120121845855277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116246&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116246&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Estimated ARIMA Residuals
Value
0.00999999441741765
2.18466871311649e-06
1.60358108020423e-06
1.21778698489518e-06
9.42865414664583e-07
-0.0594269157011813
0.102776269776958
0.0203675520303013
0.0161785913104872
0.0128733066649317
0.0102544613006946
0.00817403703887163
0.00651858798917304
0.00519993732323023
0.00414892600253484
0.00331101649987624
0.00264310127126963
0.00211115500282611
0.00168853928987249
0.00135489182465135
-0.118624009464853
-0.033422881169734
-0.0266276879964830
-0.0211632890860420
-0.0167279226306115
-0.0134365812118422
0.109266277486939
0.0258233304433997
-0.099387927663909
0.106155140151518
0.0130380310071018
0.0146044036050458
0.131654351925100
0.143700837259228
0.0635436470079612
-0.0492872241937609
0.111805056625835
0.0380888968968041
0.0303979002778869
-0.0757400700794453
0.0906936645616727
0.0212404649160439
-0.083048431858437
-0.0151389782796319
-0.00387057511315093
0.0927115859236417
0.0228509404526591
-0.0817631497113515
-0.0141132274718329
-0.0112634667413033
-0.0172006541993972
-0.00952808793501963
0.00060735645576289
0.0880738088323331
0.0233490194617765
0.0186343560932779
-0.0933398373893489
-0.025995882012764
-0.0172472704183547
0.0930782541741359
-0.0871988520419995
-0.0149518561670927
0.088067241422673
-0.074012676230925
-0.0182701644668412
-0.0110815394727555
0.097998992979995
0.0235712190738143
0.0188116888914163
0.0081702749517715
0.0100200131850174
0.0148396936024177
-0.0916562464028246
-0.0220086982787698
-0.0175646742592913
-0.0140179931555796
-0.0111874623582009
-0.0157714099711741
-0.00908733662565624
-0.00725241019220842
0.00105493966346692
0.0973424344998113
0.0265467241281758
0.0143434421512687
0.0217896207784722
0.0138903427423767
0.00424265320286565
0.0137283958303485
0.00745685046803857
-0.0940488461510824
0.0692388846474081
0.00761736880654062
0.0060792601227515
0.00485172827766078
-0.0961279387943658
0.0744225390779078
0.0150977768722011
0.00854972436872714
-0.0931766467220694
-0.0232220974545516
0.081466937651637
0.0138768275577110
0.0110748010952868
0.00883856333806143
0.00705386951953102
-0.00121339075396953
0.00253110905303977
-0.0979799756683341
0.0729444678173827
0.00707522554439599
0.00564658710952592
0.144506421143099
0.0437312178488352
0.0417438894484565
0.0229724863277170
0.0218333434348388
0.0174247272858530
0.01390630445092
0.0179412600511828
0.00397611377618467
0.00667274230570669
-0.0746746262077202
-0.0118411348331691
-0.0129496484252147
0.0628222267873788
0.0127244112960749
0.0101550821736893
0.00810455521711795
-0.0735319267590473
0.0622278952325423
0.00875059749497353
0.0138265999240588
0.00069229099370105
0.00405199314694293
0.00323380959770780
-0.00699927300449765
-0.00068668441277353
-0.000548028233042785
-0.000437369683403688
-0.000349055447195212
-0.000278573732565235
-0.000222323774341504
-0.000177431878384482
-0.000141604610485402
-0.000113011629551352
0.00538415507994294
-0.0785026126178874
-0.0217391034899599
-0.0228238636483073
-0.0154156480761483
0.0676970989595222
0.0131154527310873
-0.0640584887101525
-0.0184854948325697
-0.0119532881446389
0.0704603348217745
0.0153207325348852
0.0122271509646072
-0.0702417707266374
-0.0151463011765536
-0.0120879410053956
-0.00964712876409024
-0.00769916839843887
0.0738554573617609
0.0180303076642225
0.0143896052781276
-0.0685159619061206
0.0662310301577324
0.0119454143844759
0.0095333812976115
0.0130827362225734
0.00764146134397236
0.0060984878647421
0.0048670735298213
-0.00159003933402069
0.00153061574351909
0.006695899147946
0.00254426243915518
0.00203052176952312
-0.00385383099757952
-0.0802760682619432
-0.0231544607412886
-0.0130047356660441
0.0668216045687977
0.0124167392681578
0.00990953566836516
0.00790858977078024
0.000837330124641156
0.00346784771009467
0.00276761554168736
0.00768312239206814
-0.00214220293424105
0.00108994571147747
0.000869862503448004
0.00069421877340936
0.000554041246109804
0.000442168541313848
-0.0796471146863151
-0.0226525062621903
0.0619215162745092
0.00850608296123845
0.136788523998296
0.0426857485608814
0.0340665885591793
0.0326621674377669
0.0232673891985442
0.0185692087264808
0.00934534350133198
0.0102579123319284
0.00818662178055795
0.00653356882075329
-0.0547856976076648
-0.0130391784979942
0.0495937088134397
0.00889556260697866
0.00709935942442641
0.00566584784616531
0.00452179272758713
0.00360874665653199
-0.0571199360042378
0.0450979154564042
0.0107819127546307
0.00580522304261244
-0.000841322150025192
0.00212815101265029
-0.00719738221094346
-0.0611947402013317
-0.0181540991555362
0.0455115993640813
0.00563771782849365
0.00449934275844122
-0.0564091701866278
0.0456651625467526
0.00576027334030371
0.00459715170726405
0.00777464950071938
0.00410508824896816
-0.000829576774410867
0.00143762666308866
0.00114733928030475
0.000915667090719552
-0.0592692255591522
-0.0166173868501112
-0.0091562227663129
0.0464871585463289
0.00851598512697293
0.00679642670627878
-0.0545759163167734
0.0471282434909632
0.00692792714129453
0.00963479182952653
0.0855896283007063
0.02328933961393
0.0206864211389064
0.016509392981499
0.017281556044205
-0.0524134121705728
0.0509537863343876
0.00998101156539732
0.00796563316484544
0.00635720250408767
-0.0549264518159909
-0.0131515114396592
-0.0104959417194514
0.0516234120250303
0.0146211860393315
0.00956916352420123
0.00763694599778475
-0.058010876181477
0.0464865692920942
0.00641582060318946
-0.0507739095127313
0.0439570896054295
0.00649679088669686
0.00518495070495106
-0.00133634831763629
-0.058266918848993
0.0441825328293213
-0.0254229819210483
0.095052519636864
0.0288249521969881
0.0167991269219918
0.0155067203513592
0.0123755838874082
0.00987669043382588
0.0119881371316897
0.00746778316150376
0.00595987899917638
0.000650692296202848
-0.097381002057606
-0.0265775040762257
-0.0212109410475332
-0.0128222407264911
0.0835613875405361
0.0176480577450047
-0.0818096998125384
0.0796441665508265
0.0145218069411452
0.0115895454309349
0.00924936985046543
0.0114874859090097
0.00296246361857477
0.00651685371586019
-0.00269181877783176
0.00135120707401093
0.00107836964327745
0.00086062388948882
0.000686845631992838
0.0005481568986756
0.00043747236870928
0.100349137398156
0.0289463097981226
0.0231014345406795
0.0252796979157352
-0.0833243008826425
-0.0153591496705658
-0.0122578108639644
0.133374367638682
-0.066767567363744
0.00469736147982758
-0.00659356014920931
-0.00176268977550542
-0.00140676524048722
-0.00112270943494508
-0.000896010534692237
-0.0007150869613195
-0.000570695703288493
-0.000455460109565209
-0.000363493031768414
0.099709903938086
0.0284361511617703
0.0226942877774068
0.0181118286646384
0.0144546654556734
0.00469302716458841
0.00724489564162667
0.0057819972074622
0.00461448906386153
0.0105256597060865
-0.0950991851524492
-0.0247564345086051
0.0699780147530475
0.0167999321166601
0.00990817828676249
0.00790750647337823
-0.0936891871727781
-0.0236311450932334
-0.0188595145737036
-0.0150513776862056
-0.0120121845855277


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- as.numeric(par5) #seasonal period
par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial
par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial
armaGR <- function(arima.out, names, n){
try1 <- arima.out$coef
try2 <- sqrt(diag(arima.out$var.coef))
try.data.frame  <- data.frame(matrix(NA,ncol=4,nrow=length(names)))
dimnames(try.data.frame) <- list(names,c('coef','std','tstat','pv'))
try.data.frame[,1] <- try1
for(i in 1:length(try2)) try.data.frame[which(rownames(try.data.frame)==names(try2)[i]),2] <- try2[i]
try.data.frame[,3] <- try.data.frame[,1] / try.data.frame[,2]
try.data.frame[,4] <- round((1-pt(abs(try.data.frame[,3]),df=n-(length(try2)+1)))*2,5)
vector <- rep(NA,length(names))
vector[is.na(try.data.frame[,4])] <- 0
maxi <- which.max(try.data.frame[,4])
continue <- max(try.data.frame[,4],na.rm=TRUE) > .05
vector[maxi] <- 0
list(summary=try.data.frame,next.vector=vector,continue=continue)
}
arimaSelect <- function(series, order=c(13,0,0), seasonal=list(order=c(2,0,0),period=12), include.mean=F){
nrc <- order[1]+order[3]+seasonal$order[1]+seasonal$order[3]
coeff <- matrix(NA, nrow=nrc*2, ncol=nrc)
pval <- matrix(NA, nrow=nrc*2, ncol=nrc)
mylist <- rep(list(NULL), nrc)
names  <- NULL
if(order[1] > 0) names <- paste('ar',1:order[1],sep='')
if(order[3] > 0) names <- c( names , paste('ma',1:order[3],sep='') )
if(seasonal$order[1] > 0) names <- c(names, paste('sar',1:seasonal$order[1],sep=''))
if(seasonal$order[3] > 0) names <- c(names, paste('sma',1:seasonal$order[3],sep=''))
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML')
mylist[[1]] <- arima.out
last.arma <- armaGR(arima.out, names, length(series))
mystop <- FALSE
i <- 1
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- 2
aic <- arima.out$aic
while(!mystop){
mylist[[i]] <- arima.out
arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML', fixed=last.arma$next.vector)
aic <- c(aic, arima.out$aic)
last.arma <- armaGR(arima.out, names, length(series))
mystop <- !last.arma$continue
coeff[i,] <- last.arma[[1]][,1]
pval [i,] <- last.arma[[1]][,4]
i <- i+1
}
list(coeff, pval, mylist, aic=aic)
}
arimaSelectplot <- function(arimaSelect.out,noms,choix){
noms <- names(arimaSelect.out[[3]][[1]]$coef)
coeff <- arimaSelect.out[[1]]
k <- min(which(is.na(coeff[,1])))-1
coeff <- coeff[1:k,]
pval  <- arimaSelect.out[[2]][1:k,]
aic   <- arimaSelect.out$aic[1:k]
coeff[coeff==0] <- NA
n <- ncol(coeff)
if(missing(choix)) choix <- k
layout(matrix(c(1,1,1,2,
3,3,3,2,
3,3,3,4,
5,6,7,7),nr=4),
widths=c(10,35,45,15),
heights=c(30,30,15,15))
couleurs <- rainbow(75)[1:50]#(50)
ticks <- pretty(coeff)
par(mar=c(1,1,3,1))
plot(aic,k:1-.5,type='o',pch=21,bg='blue',cex=2,axes=F,lty=2,xpd=NA)
points(aic[choix],k-choix+.5,pch=21,cex=4,bg=2,xpd=NA)
title('aic',line=2)
par(mar=c(3,0,0,0))
plot(0,axes=F,xlab='',ylab='',xlim=range(ticks),ylim=c(.1,1))
rect(xleft  = min(ticks) + (0:49)/50*(max(ticks)-min(ticks)),
xright = min(ticks) + (1:50)/50*(max(ticks)-min(ticks)),
ytop   = rep(1,50),
ybottom= rep(0,50),col=couleurs,border=NA)
axis(1,ticks)
rect(xleft=min(ticks),xright=max(ticks),ytop=1,ybottom=0)
text(mean(coeff,na.rm=T),.5,'coefficients',cex=2,font=2)
par(mar=c(1,1,3,1))
image(1:n,1:k,t(coeff[k:1,]),axes=F,col=couleurs,zlim=range(ticks))
for(i in 1:n) for(j in 1:k) if(!is.na(coeff[j,i])) {
if(pval[j,i]<.01)                            symb = 'green'
else if( (pval[j,i]<.05) & (pval[j,i]>=.01)) symb = 'orange'
else if( (pval[j,i]<.1)  & (pval[j,i]>=.05)) symb = 'red'
else                                         symb = 'black'
polygon(c(i+.5   ,i+.2   ,i+.5   ,i+.5),
c(k-j+0.5,k-j+0.5,k-j+0.8,k-j+0.5),
col=symb)
if(j==choix)  {
rect(xleft=i-.5,
xright=i+.5,
ybottom=k-j+1.5,
ytop=k-j+.5,
lwd=4)
text(i,
k-j+1,
round(coeff[j,i],2),
cex=1.2,
font=2)
}
else{
rect(xleft=i-.5,xright=i+.5,ybottom=k-j+1.5,ytop=k-j+.5)
text(i,k-j+1,round(coeff[j,i],2),cex=1.2,font=1)
}
}
axis(3,1:n,noms)
par(mar=c(0.5,0,0,0.5))
plot(0,axes=F,xlab='',ylab='',type='n',xlim=c(0,8),ylim=c(-.2,.8))
cols <- c('green','orange','red','black')
niv  <- c('0','0.01','0.05','0.1')
for(i in 0:3){
polygon(c(1+2*i   ,1+2*i   ,1+2*i-.5   ,1+2*i),
c(.4      ,.7      , .4        , .4),
col=cols[i+1])
text(2*i,0.5,niv[i+1],cex=1.5)
}
text(8,.5,1,cex=1.5)
text(4,0,'p-value',cex=2)
box()
residus <- arimaSelect.out[[3]][[choix]]$res
par(mar=c(1,2,4,1))
acf(residus,main='')
title('acf',line=.5)
par(mar=c(1,2,4,1))
pacf(residus,main='')
title('pacf',line=.5)
par(mar=c(2,2,4,1))
qqnorm(residus,main='')
title('qq-norm',line=.5)
qqline(residus)
residus
}
if (par2 == 0) x <- log(x)
if (par2 != 0) x <- x^par2
(selection <- arimaSelect(x, order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5)))
bitmap(file='test1.png')
resid <- arimaSelectplot(selection)
dev.off()
resid
bitmap(file='test2.png')
acf(resid,length(resid)/2, main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test3.png')
pacf(resid,length(resid)/2, main='Residual Partial Autocorrelation Function')
dev.off()
bitmap(file='test4.png')
cpgram(resid, main='Residual Cumulative Periodogram')
dev.off()
bitmap(file='test5.png')
hist(resid, main='Residual Histogram', xlab='values of Residuals')
dev.off()
bitmap(file='test6.png')
densityplot(~resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test7.png')
qqnorm(resid, main='Residual Normal Q-Q Plot')
qqline(resid)
dev.off()
ncols <- length(selection[[1]][1,])
nrows <- length(selection[[2]][,1])-1
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ARIMA Parameter Estimation and Backward Selection', ncols+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Iteration', header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,names(selection[[3]][[1]]$coef)[i],header=TRUE)
}
a<-table.row.end(a)
for (j in 1:nrows) {
a<-table.row.start(a)
mydum <- 'Estimates ('
mydum <- paste(mydum,j)
mydum <- paste(mydum,')')
a<-table.element(a,mydum, header=TRUE)
for (i in 1:ncols) {
a<-table.element(a,round(selection[[1]][j,i],4))
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(p-val)', header=TRUE)
for (i in 1:ncols) {
mydum <- '('
mydum <- paste(mydum,round(selection[[2]][j,i],4),sep='')
mydum <- paste(mydum,')')
a<-table.element(a,mydum)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated ARIMA Residuals', 1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Value', 1,TRUE)
a<-table.row.end(a)
for (i in (par4*par5+par3):length(resid)) {
a<-table.row.start(a)
a<-table.element(a,resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')