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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Wed, 02 Dec 2009 10:38:59 -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/02/t1259775630a81qnel897sw6wc.htm/, Retrieved Sun, 28 Apr 2024 08:49:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62483, Retrieved Sun, 28 Apr 2024 08:49:27 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

164

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]
-    D      [ARIMA Backward Selection] [backwards arima s...] [2009-12-02 17:38:59] [f0f26816ac6124f58333f11f6c174000] [Current]
-   P         [ARIMA Backward Selection] [backward arma  es...] [2009-12-03 13:27:44] [8b1aef4e7013bd33fbc2a5833375c5f5] 
-    D          [ARIMA Backward Selection] [Workshop9] [2009-12-04 09:45:33] [34b80aeb109c116fd63bf2eb7493a276] 
- RMPD            [Harrell-Davis Quantiles] [Review ws10] [2009-12-09 00:11:18] [f924a0adda9c1905a1ba8f1c751261ff] 
-   PD            [ARIMA Backward Selection] [ARIMA] [2009-12-12 12:00:09] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD              [ARIMA Backward Selection] [ARIMA] [2009-12-14 09:23:59] [34b80aeb109c116fd63bf2eb7493a276] 
- RMPD          [Univariate Data Series] [Paper: Werklooshe...] [2009-12-04 11:23:56] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD            [Univariate Data Series] [Paper: Werklooshe...] [2009-12-04 11:37:55] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD            [Univariate Data Series] [Paper: Inflatie B...] [2009-12-04 11:37:55] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD              [Univariate Data Series] [Inflatie Belgi�] [2009-12-04 11:57:12] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD              [Univariate Data Series] [Industri�le produ...] [2009-12-04 12:03:38] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD            [Univariate Data Series] [Inflatie Belgi�] [2009-12-04 22:48:22] [34b80aeb109c116fd63bf2eb7493a276] 
-   PD            [Univariate Data Series] [Werkloosheid Belgi�] [2009-12-04 22:54:39] [34b80aeb109c116fd63bf2eb7493a276] 
-               [ARIMA Backward Selection] [] [2009-12-04 14:27:54] [08fc5c07292c885b941f0cb515ce13f3] 
-               [ARIMA Backward Selection] [] [2009-12-04 14:27:54] [08fc5c07292c885b941f0cb515ce13f3] 
- R PD          [ARIMA Backward Selection] [ws9 6] [2009-12-04 14:58:37] [55b7a497389226c9339ee8d75ebc3b97] 
-   PD          [ARIMA Backward Selection] [WS9] [2009-12-04 18:38:48] [af2352cd9a951bedd08ebe247d0de1a2] 
-   PD            [ARIMA Backward Selection] [WS10] [2009-12-09 17:42:08] [af2352cd9a951bedd08ebe247d0de1a2] 
-   PD            [ARIMA Backward Selection] [] [2009-12-11 11:12:05] [09f192433169b2c787c4a71fde86e883] 

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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	12 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 & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62483&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]12 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=62483&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62483&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	12 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	0.018	0.179	-0.1364	0.1296	-0.1213	0.0817	-0.7555
(p-val)	(0.9677 )	(0.0389 )	(0.1754 )	(0.7733 )	(0.3084 )	(0.4542 )	(0 )
Estimates ( 2 )	0	0.1811	-0.1334	0.1476	-0.1215	0.0821	-0.7553
(p-val)	(NA )	(0.0085 )	(0.0545 )	(0.034 )	(0.3077 )	(0.4508 )	(0 )
Estimates ( 3 )	0	0.1803	-0.1336	0.1519	-0.1836	0	-0.6964
(p-val)	(NA )	(0.0088 )	(0.0538 )	(0.0286 )	(0.0614 )	(NA )	(0 )
Estimates ( 4 )	0	0.1881	-0.129	0.1517	0	0	-1.2642
(p-val)	(NA )	(0.0061 )	(0.0638 )	(0.0284 )	(NA )	(NA )	(0 )
Estimates ( 5 )	0	0.1906	0	0.1541	0	0	-1.2788
(p-val)	(NA )	(0.0074 )	(NA )	(0.025 )	(NA )	(NA )	(0 )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & ar3 & ma1 & sar1 & sar2 & sma1 \tabularnewline
Estimates ( 1 ) & 0.018 & 0.179 & -0.1364 & 0.1296 & -0.1213 & 0.0817 & -0.7555 \tabularnewline
(p-val) & (0.9677 ) & (0.0389 ) & (0.1754 ) & (0.7733 ) & (0.3084 ) & (0.4542 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0 & 0.1811 & -0.1334 & 0.1476 & -0.1215 & 0.0821 & -0.7553 \tabularnewline
(p-val) & (NA ) & (0.0085 ) & (0.0545 ) & (0.034 ) & (0.3077 ) & (0.4508 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0 & 0.1803 & -0.1336 & 0.1519 & -0.1836 & 0 & -0.6964 \tabularnewline
(p-val) & (NA ) & (0.0088 ) & (0.0538 ) & (0.0286 ) & (0.0614 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0 & 0.1881 & -0.129 & 0.1517 & 0 & 0 & -1.2642 \tabularnewline
(p-val) & (NA ) & (0.0061 ) & (0.0638 ) & (0.0284 ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 5 ) & 0 & 0.1906 & 0 & 0.1541 & 0 & 0 & -1.2788 \tabularnewline
(p-val) & (NA ) & (0.0074 ) & (NA ) & (0.025 ) & (NA ) & (NA ) & (0 ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62483&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]0.018[/C][C]0.179[/C][C]-0.1364[/C][C]0.1296[/C][C]-0.1213[/C][C]0.0817[/C][C]-0.7555[/C][/ROW]
[ROW][C](p-val)[/C][C](0.9677 )[/C][C](0.0389 )[/C][C](0.1754 )[/C][C](0.7733 )[/C][C](0.3084 )[/C][C](0.4542 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0[/C][C]0.1811[/C][C]-0.1334[/C][C]0.1476[/C][C]-0.1215[/C][C]0.0821[/C][C]-0.7553[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0085 )[/C][C](0.0545 )[/C][C](0.034 )[/C][C](0.3077 )[/C][C](0.4508 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0[/C][C]0.1803[/C][C]-0.1336[/C][C]0.1519[/C][C]-0.1836[/C][C]0[/C][C]-0.6964[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0088 )[/C][C](0.0538 )[/C][C](0.0286 )[/C][C](0.0614 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0[/C][C]0.1881[/C][C]-0.129[/C][C]0.1517[/C][C]0[/C][C]0[/C][C]-1.2642[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0061 )[/C][C](0.0638 )[/C][C](0.0284 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]0[/C][C]0.1906[/C][C]0[/C][C]0.1541[/C][C]0[/C][C]0[/C][C]-1.2788[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0074 )[/C][C](NA )[/C][C](0.025 )[/C][C](NA )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62483&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62483&T=1

As an alternative you can also use a QR Code:

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

ARIMA Parameter Estimation and Backward Selection
Iteration	ar1	ar2	ar3	ma1	sar1	sar2	sma1
Estimates ( 1 )	0.018	0.179	-0.1364	0.1296	-0.1213	0.0817	-0.7555
(p-val)	(0.9677 )	(0.0389 )	(0.1754 )	(0.7733 )	(0.3084 )	(0.4542 )	(0 )
Estimates ( 2 )	0	0.1811	-0.1334	0.1476	-0.1215	0.0821	-0.7553
(p-val)	(NA )	(0.0085 )	(0.0545 )	(0.034 )	(0.3077 )	(0.4508 )	(0 )
Estimates ( 3 )	0	0.1803	-0.1336	0.1519	-0.1836	0	-0.6964
(p-val)	(NA )	(0.0088 )	(0.0538 )	(0.0286 )	(0.0614 )	(NA )	(0 )
Estimates ( 4 )	0	0.1881	-0.129	0.1517	0	0	-1.2642
(p-val)	(NA )	(0.0061 )	(0.0638 )	(0.0284 )	(NA )	(NA )	(0 )
Estimates ( 5 )	0	0.1906	0	0.1541	0	0	-1.2788
(p-val)	(NA )	(0.0074 )	(NA )	(0.025 )	(NA )	(NA )	(0 )
Estimates ( 6 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 7 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 8 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 9 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 10 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 11 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 12 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )
Estimates ( 13 )	NA	NA	NA	NA	NA	NA	NA
(p-val)	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )	(NA )

Estimated ARIMA Residuals
Value
-0.0428218125170796
-0.0100326993013991
0.0106918718216985
-0.0270254228728889
0.00331295567691715
-0.00172922886482726
0.00366757515519101
-0.00415526854787519
0.0104271549130312
0.00427641309877716
-0.0126496967383851
-0.00390689047203263
-0.0101206960011753
-0.00468772961407567
-0.0150740304292764
-1.33428110902740e-05
0.0119188075076894
0.00572283197168028
0.00665070278331704
0.00090205406909518
-0.0162622053844042
-0.00296756232063624
-0.00135456295251316
-0.0042209026627126
-0.00691408156016935
-0.00912632470708239
-0.00363510844058383
-0.00306970191559634
-0.00780541568564299
-0.006868812991491
-0.000257167935027653
0.0049273580740412
-0.000471880075575950
0.00317403516926835
-0.00343539003636517
-0.00551097799029973
-0.00331882804059151
-0.00361129923103662
-0.00652485052709214
-0.00534106241603319
-0.00135927919983362
-0.0343214228787846
0.0177594984616496
0.00364339425842831
-0.00121175380858133
-0.0327812777406239
-0.00148506143608297
0.00654626504510931
-0.008351643395982
0.0203907579605412
0.000568475381496058
-0.00942604815258168
0.00113916206615276
0.0043092472157751
-0.00301159386164524
-0.00906169822472322
-0.0136304198479953
-0.00212936574530797
0.0068318098515847
0.000150216886319774
-0.00737963781697722
-0.00153897632601257
0.000841643815183354
-0.0132092570518280
0.00292140455998971
0.0129145072578084
0.00606074015887007
-0.00658945299795582
-0.0115849184572875
-0.000552060264397507
0.00248265055500265
0.00334878283923914
-0.00269702618853409
0.0115526199006686
0.00118595439052892
-0.00135637686316826
0.00215929077771191
-0.000482170078572539
-0.00387224935612852
0.00351301275870692
-0.00927814778277982
-0.0029904541530031
-0.00274095220266759
-0.00249636536060637
-0.00311171252457146
-0.00805853653701809
0.000265678489948079
0.0273268578244866
0.00697830979820947
0.00496746078085009
0.00859756339461414
0.00301817383550722
-0.00234812076011175
0.0147587387471635
-0.00544202527272388
-0.00677778505404914
0.0004550798404177
-0.0122394292493475
-0.00234804851701877
-0.0256177580063547
-0.00464405104943095
-2.70057488568111e-05
-0.00989528047657607
0.0165312207375463
0.0080040365882147
-0.00521646931112789
0.00322664055997624
0.00551614198148039
-0.00100617891676795
-0.00205682092387900
-0.00258556303479596
0.00934819608973077
0.0179703269504516
0.0103451559754469
0.00649502857332097
-0.0121013907012526
0.00364835716496857
-0.00298182402789843
0.000479097204803333
0.00207952137945619
0.00431246556704327
-0.0187863854547659
0.00172520467637257
-0.0035514491910531
-0.000874163230723674
-0.000488392516677418
0.0098104397277384
-0.0039659160977418
-0.000399503211136772
-0.00258411728185081
0.00655686668097407
-0.00210834440504175
0.0110432610023186
-0.0203220167411467
-0.0135046593294898
-0.0177584958286347
0.0142621829665637
0.0100204291181164
-0.00940830173673466
0.00149121114491802
-0.0058067759318511
-0.000446298372889234
0.00944580002621718
0.00691718794043605
-0.00100117509695559
-0.0108963720487612
-0.00312829444661124
-0.00648819967032455
-0.00660213243724198
0.0172106693358473
0.000921999931238851
0.00158697851318715
-0.00200308563212723
0.00156258277386819
0.00452390423245766
-0.00242752057423049
0.00653782319365939
-0.00864260317110358
-0.00193393493475223
0.0113212678526945
-0.000295818101161019
-0.0113715935595373
0.0128823719922788
-0.00363190185691193
-0.00783993650577952
0.00462815396898063
0.00240904978361227
-0.00213947676937367
-0.000228613739743290
0.00182324954083881
0.0165147809111417
-0.0147601210657752
-0.00185723008076251
0.00501477614625141
-0.00984433525296626
0.00615059973608415
-0.000979322360050031
0.00448393353602957
-0.00043571402871413
0.000581224621625873
-0.00466808730426968
-0.0067302162881713
-0.00817181013794204
-0.0155557665617804
-0.00274249112106238
-0.000108175829954355
-0.0046207976104667
-0.00631784437519178
-0.00256610172319716
0.00864858976183008
-0.00462861129435498
0.0106395707414771
-0.00183307313881890
0.0127941062754136
0.0406957999993953
-0.00243510460817833
0.00769886703923425
-0.00181980046600172
-0.00166617365407226
0.0128619317223768
0.00716448453613985
-0.007637802225223
0.0159149478080651
-0.00403452114642185
-0.00180503183014593
-0.00850380070981158
-0.0112341066169573
-0.00616891274001468
0.00920188897733349
0.00796423400336723
-0.0068821032663446
0.00806738315921829

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.0428218125170796 \tabularnewline
-0.0100326993013991 \tabularnewline
0.0106918718216985 \tabularnewline
-0.0270254228728889 \tabularnewline
0.00331295567691715 \tabularnewline
-0.00172922886482726 \tabularnewline
0.00366757515519101 \tabularnewline
-0.00415526854787519 \tabularnewline
0.0104271549130312 \tabularnewline
0.00427641309877716 \tabularnewline
-0.0126496967383851 \tabularnewline
-0.00390689047203263 \tabularnewline
-0.0101206960011753 \tabularnewline
-0.00468772961407567 \tabularnewline
-0.0150740304292764 \tabularnewline
-1.33428110902740e-05 \tabularnewline
0.0119188075076894 \tabularnewline
0.00572283197168028 \tabularnewline
0.00665070278331704 \tabularnewline
0.00090205406909518 \tabularnewline
-0.0162622053844042 \tabularnewline
-0.00296756232063624 \tabularnewline
-0.00135456295251316 \tabularnewline
-0.0042209026627126 \tabularnewline
-0.00691408156016935 \tabularnewline
-0.00912632470708239 \tabularnewline
-0.00363510844058383 \tabularnewline
-0.00306970191559634 \tabularnewline
-0.00780541568564299 \tabularnewline
-0.006868812991491 \tabularnewline
-0.000257167935027653 \tabularnewline
0.0049273580740412 \tabularnewline
-0.000471880075575950 \tabularnewline
0.00317403516926835 \tabularnewline
-0.00343539003636517 \tabularnewline
-0.00551097799029973 \tabularnewline
-0.00331882804059151 \tabularnewline
-0.00361129923103662 \tabularnewline
-0.00652485052709214 \tabularnewline
-0.00534106241603319 \tabularnewline
-0.00135927919983362 \tabularnewline
-0.0343214228787846 \tabularnewline
0.0177594984616496 \tabularnewline
0.00364339425842831 \tabularnewline
-0.00121175380858133 \tabularnewline
-0.0327812777406239 \tabularnewline
-0.00148506143608297 \tabularnewline
0.00654626504510931 \tabularnewline
-0.008351643395982 \tabularnewline
0.0203907579605412 \tabularnewline
0.000568475381496058 \tabularnewline
-0.00942604815258168 \tabularnewline
0.00113916206615276 \tabularnewline
0.0043092472157751 \tabularnewline
-0.00301159386164524 \tabularnewline
-0.00906169822472322 \tabularnewline
-0.0136304198479953 \tabularnewline
-0.00212936574530797 \tabularnewline
0.0068318098515847 \tabularnewline
0.000150216886319774 \tabularnewline
-0.00737963781697722 \tabularnewline
-0.00153897632601257 \tabularnewline
0.000841643815183354 \tabularnewline
-0.0132092570518280 \tabularnewline
0.00292140455998971 \tabularnewline
0.0129145072578084 \tabularnewline
0.00606074015887007 \tabularnewline
-0.00658945299795582 \tabularnewline
-0.0115849184572875 \tabularnewline
-0.000552060264397507 \tabularnewline
0.00248265055500265 \tabularnewline
0.00334878283923914 \tabularnewline
-0.00269702618853409 \tabularnewline
0.0115526199006686 \tabularnewline
0.00118595439052892 \tabularnewline
-0.00135637686316826 \tabularnewline
0.00215929077771191 \tabularnewline
-0.000482170078572539 \tabularnewline
-0.00387224935612852 \tabularnewline
0.00351301275870692 \tabularnewline
-0.00927814778277982 \tabularnewline
-0.0029904541530031 \tabularnewline
-0.00274095220266759 \tabularnewline
-0.00249636536060637 \tabularnewline
-0.00311171252457146 \tabularnewline
-0.00805853653701809 \tabularnewline
0.000265678489948079 \tabularnewline
0.0273268578244866 \tabularnewline
0.00697830979820947 \tabularnewline
0.00496746078085009 \tabularnewline
0.00859756339461414 \tabularnewline
0.00301817383550722 \tabularnewline
-0.00234812076011175 \tabularnewline
0.0147587387471635 \tabularnewline
-0.00544202527272388 \tabularnewline
-0.00677778505404914 \tabularnewline
0.0004550798404177 \tabularnewline
-0.0122394292493475 \tabularnewline
-0.00234804851701877 \tabularnewline
-0.0256177580063547 \tabularnewline
-0.00464405104943095 \tabularnewline
-2.70057488568111e-05 \tabularnewline
-0.00989528047657607 \tabularnewline
0.0165312207375463 \tabularnewline
0.0080040365882147 \tabularnewline
-0.00521646931112789 \tabularnewline
0.00322664055997624 \tabularnewline
0.00551614198148039 \tabularnewline
-0.00100617891676795 \tabularnewline
-0.00205682092387900 \tabularnewline
-0.00258556303479596 \tabularnewline
0.00934819608973077 \tabularnewline
0.0179703269504516 \tabularnewline
0.0103451559754469 \tabularnewline
0.00649502857332097 \tabularnewline
-0.0121013907012526 \tabularnewline
0.00364835716496857 \tabularnewline
-0.00298182402789843 \tabularnewline
0.000479097204803333 \tabularnewline
0.00207952137945619 \tabularnewline
0.00431246556704327 \tabularnewline
-0.0187863854547659 \tabularnewline
0.00172520467637257 \tabularnewline
-0.0035514491910531 \tabularnewline
-0.000874163230723674 \tabularnewline
-0.000488392516677418 \tabularnewline
0.0098104397277384 \tabularnewline
-0.0039659160977418 \tabularnewline
-0.000399503211136772 \tabularnewline
-0.00258411728185081 \tabularnewline
0.00655686668097407 \tabularnewline
-0.00210834440504175 \tabularnewline
0.0110432610023186 \tabularnewline
-0.0203220167411467 \tabularnewline
-0.0135046593294898 \tabularnewline
-0.0177584958286347 \tabularnewline
0.0142621829665637 \tabularnewline
0.0100204291181164 \tabularnewline
-0.00940830173673466 \tabularnewline
0.00149121114491802 \tabularnewline
-0.0058067759318511 \tabularnewline
-0.000446298372889234 \tabularnewline
0.00944580002621718 \tabularnewline
0.00691718794043605 \tabularnewline
-0.00100117509695559 \tabularnewline
-0.0108963720487612 \tabularnewline
-0.00312829444661124 \tabularnewline
-0.00648819967032455 \tabularnewline
-0.00660213243724198 \tabularnewline
0.0172106693358473 \tabularnewline
0.000921999931238851 \tabularnewline
0.00158697851318715 \tabularnewline
-0.00200308563212723 \tabularnewline
0.00156258277386819 \tabularnewline
0.00452390423245766 \tabularnewline
-0.00242752057423049 \tabularnewline
0.00653782319365939 \tabularnewline
-0.00864260317110358 \tabularnewline
-0.00193393493475223 \tabularnewline
0.0113212678526945 \tabularnewline
-0.000295818101161019 \tabularnewline
-0.0113715935595373 \tabularnewline
0.0128823719922788 \tabularnewline
-0.00363190185691193 \tabularnewline
-0.00783993650577952 \tabularnewline
0.00462815396898063 \tabularnewline
0.00240904978361227 \tabularnewline
-0.00213947676937367 \tabularnewline
-0.000228613739743290 \tabularnewline
0.00182324954083881 \tabularnewline
0.0165147809111417 \tabularnewline
-0.0147601210657752 \tabularnewline
-0.00185723008076251 \tabularnewline
0.00501477614625141 \tabularnewline
-0.00984433525296626 \tabularnewline
0.00615059973608415 \tabularnewline
-0.000979322360050031 \tabularnewline
0.00448393353602957 \tabularnewline
-0.00043571402871413 \tabularnewline
0.000581224621625873 \tabularnewline
-0.00466808730426968 \tabularnewline
-0.0067302162881713 \tabularnewline
-0.00817181013794204 \tabularnewline
-0.0155557665617804 \tabularnewline
-0.00274249112106238 \tabularnewline
-0.000108175829954355 \tabularnewline
-0.0046207976104667 \tabularnewline
-0.00631784437519178 \tabularnewline
-0.00256610172319716 \tabularnewline
0.00864858976183008 \tabularnewline
-0.00462861129435498 \tabularnewline
0.0106395707414771 \tabularnewline
-0.00183307313881890 \tabularnewline
0.0127941062754136 \tabularnewline
0.0406957999993953 \tabularnewline
-0.00243510460817833 \tabularnewline
0.00769886703923425 \tabularnewline
-0.00181980046600172 \tabularnewline
-0.00166617365407226 \tabularnewline
0.0128619317223768 \tabularnewline
0.00716448453613985 \tabularnewline
-0.007637802225223 \tabularnewline
0.0159149478080651 \tabularnewline
-0.00403452114642185 \tabularnewline
-0.00180503183014593 \tabularnewline
-0.00850380070981158 \tabularnewline
-0.0112341066169573 \tabularnewline
-0.00616891274001468 \tabularnewline
0.00920188897733349 \tabularnewline
0.00796423400336723 \tabularnewline
-0.0068821032663446 \tabularnewline
0.00806738315921829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62483&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.0428218125170796[/C][/ROW]
[ROW][C]-0.0100326993013991[/C][/ROW]
[ROW][C]0.0106918718216985[/C][/ROW]
[ROW][C]-0.0270254228728889[/C][/ROW]
[ROW][C]0.00331295567691715[/C][/ROW]
[ROW][C]-0.00172922886482726[/C][/ROW]
[ROW][C]0.00366757515519101[/C][/ROW]
[ROW][C]-0.00415526854787519[/C][/ROW]
[ROW][C]0.0104271549130312[/C][/ROW]
[ROW][C]0.00427641309877716[/C][/ROW]
[ROW][C]-0.0126496967383851[/C][/ROW]
[ROW][C]-0.00390689047203263[/C][/ROW]
[ROW][C]-0.0101206960011753[/C][/ROW]
[ROW][C]-0.00468772961407567[/C][/ROW]
[ROW][C]-0.0150740304292764[/C][/ROW]
[ROW][C]-1.33428110902740e-05[/C][/ROW]
[ROW][C]0.0119188075076894[/C][/ROW]
[ROW][C]0.00572283197168028[/C][/ROW]
[ROW][C]0.00665070278331704[/C][/ROW]
[ROW][C]0.00090205406909518[/C][/ROW]
[ROW][C]-0.0162622053844042[/C][/ROW]
[ROW][C]-0.00296756232063624[/C][/ROW]
[ROW][C]-0.00135456295251316[/C][/ROW]
[ROW][C]-0.0042209026627126[/C][/ROW]
[ROW][C]-0.00691408156016935[/C][/ROW]
[ROW][C]-0.00912632470708239[/C][/ROW]
[ROW][C]-0.00363510844058383[/C][/ROW]
[ROW][C]-0.00306970191559634[/C][/ROW]
[ROW][C]-0.00780541568564299[/C][/ROW]
[ROW][C]-0.006868812991491[/C][/ROW]
[ROW][C]-0.000257167935027653[/C][/ROW]
[ROW][C]0.0049273580740412[/C][/ROW]
[ROW][C]-0.000471880075575950[/C][/ROW]
[ROW][C]0.00317403516926835[/C][/ROW]
[ROW][C]-0.00343539003636517[/C][/ROW]
[ROW][C]-0.00551097799029973[/C][/ROW]
[ROW][C]-0.00331882804059151[/C][/ROW]
[ROW][C]-0.00361129923103662[/C][/ROW]
[ROW][C]-0.00652485052709214[/C][/ROW]
[ROW][C]-0.00534106241603319[/C][/ROW]
[ROW][C]-0.00135927919983362[/C][/ROW]
[ROW][C]-0.0343214228787846[/C][/ROW]
[ROW][C]0.0177594984616496[/C][/ROW]
[ROW][C]0.00364339425842831[/C][/ROW]
[ROW][C]-0.00121175380858133[/C][/ROW]
[ROW][C]-0.0327812777406239[/C][/ROW]
[ROW][C]-0.00148506143608297[/C][/ROW]
[ROW][C]0.00654626504510931[/C][/ROW]
[ROW][C]-0.008351643395982[/C][/ROW]
[ROW][C]0.0203907579605412[/C][/ROW]
[ROW][C]0.000568475381496058[/C][/ROW]
[ROW][C]-0.00942604815258168[/C][/ROW]
[ROW][C]0.00113916206615276[/C][/ROW]
[ROW][C]0.0043092472157751[/C][/ROW]
[ROW][C]-0.00301159386164524[/C][/ROW]
[ROW][C]-0.00906169822472322[/C][/ROW]
[ROW][C]-0.0136304198479953[/C][/ROW]
[ROW][C]-0.00212936574530797[/C][/ROW]
[ROW][C]0.0068318098515847[/C][/ROW]
[ROW][C]0.000150216886319774[/C][/ROW]
[ROW][C]-0.00737963781697722[/C][/ROW]
[ROW][C]-0.00153897632601257[/C][/ROW]
[ROW][C]0.000841643815183354[/C][/ROW]
[ROW][C]-0.0132092570518280[/C][/ROW]
[ROW][C]0.00292140455998971[/C][/ROW]
[ROW][C]0.0129145072578084[/C][/ROW]
[ROW][C]0.00606074015887007[/C][/ROW]
[ROW][C]-0.00658945299795582[/C][/ROW]
[ROW][C]-0.0115849184572875[/C][/ROW]
[ROW][C]-0.000552060264397507[/C][/ROW]
[ROW][C]0.00248265055500265[/C][/ROW]
[ROW][C]0.00334878283923914[/C][/ROW]
[ROW][C]-0.00269702618853409[/C][/ROW]
[ROW][C]0.0115526199006686[/C][/ROW]
[ROW][C]0.00118595439052892[/C][/ROW]
[ROW][C]-0.00135637686316826[/C][/ROW]
[ROW][C]0.00215929077771191[/C][/ROW]
[ROW][C]-0.000482170078572539[/C][/ROW]
[ROW][C]-0.00387224935612852[/C][/ROW]
[ROW][C]0.00351301275870692[/C][/ROW]
[ROW][C]-0.00927814778277982[/C][/ROW]
[ROW][C]-0.0029904541530031[/C][/ROW]
[ROW][C]-0.00274095220266759[/C][/ROW]
[ROW][C]-0.00249636536060637[/C][/ROW]
[ROW][C]-0.00311171252457146[/C][/ROW]
[ROW][C]-0.00805853653701809[/C][/ROW]
[ROW][C]0.000265678489948079[/C][/ROW]
[ROW][C]0.0273268578244866[/C][/ROW]
[ROW][C]0.00697830979820947[/C][/ROW]
[ROW][C]0.00496746078085009[/C][/ROW]
[ROW][C]0.00859756339461414[/C][/ROW]
[ROW][C]0.00301817383550722[/C][/ROW]
[ROW][C]-0.00234812076011175[/C][/ROW]
[ROW][C]0.0147587387471635[/C][/ROW]
[ROW][C]-0.00544202527272388[/C][/ROW]
[ROW][C]-0.00677778505404914[/C][/ROW]
[ROW][C]0.0004550798404177[/C][/ROW]
[ROW][C]-0.0122394292493475[/C][/ROW]
[ROW][C]-0.00234804851701877[/C][/ROW]
[ROW][C]-0.0256177580063547[/C][/ROW]
[ROW][C]-0.00464405104943095[/C][/ROW]
[ROW][C]-2.70057488568111e-05[/C][/ROW]
[ROW][C]-0.00989528047657607[/C][/ROW]
[ROW][C]0.0165312207375463[/C][/ROW]
[ROW][C]0.0080040365882147[/C][/ROW]
[ROW][C]-0.00521646931112789[/C][/ROW]
[ROW][C]0.00322664055997624[/C][/ROW]
[ROW][C]0.00551614198148039[/C][/ROW]
[ROW][C]-0.00100617891676795[/C][/ROW]
[ROW][C]-0.00205682092387900[/C][/ROW]
[ROW][C]-0.00258556303479596[/C][/ROW]
[ROW][C]0.00934819608973077[/C][/ROW]
[ROW][C]0.0179703269504516[/C][/ROW]
[ROW][C]0.0103451559754469[/C][/ROW]
[ROW][C]0.00649502857332097[/C][/ROW]
[ROW][C]-0.0121013907012526[/C][/ROW]
[ROW][C]0.00364835716496857[/C][/ROW]
[ROW][C]-0.00298182402789843[/C][/ROW]
[ROW][C]0.000479097204803333[/C][/ROW]
[ROW][C]0.00207952137945619[/C][/ROW]
[ROW][C]0.00431246556704327[/C][/ROW]
[ROW][C]-0.0187863854547659[/C][/ROW]
[ROW][C]0.00172520467637257[/C][/ROW]
[ROW][C]-0.0035514491910531[/C][/ROW]
[ROW][C]-0.000874163230723674[/C][/ROW]
[ROW][C]-0.000488392516677418[/C][/ROW]
[ROW][C]0.0098104397277384[/C][/ROW]
[ROW][C]-0.0039659160977418[/C][/ROW]
[ROW][C]-0.000399503211136772[/C][/ROW]
[ROW][C]-0.00258411728185081[/C][/ROW]
[ROW][C]0.00655686668097407[/C][/ROW]
[ROW][C]-0.00210834440504175[/C][/ROW]
[ROW][C]0.0110432610023186[/C][/ROW]
[ROW][C]-0.0203220167411467[/C][/ROW]
[ROW][C]-0.0135046593294898[/C][/ROW]
[ROW][C]-0.0177584958286347[/C][/ROW]
[ROW][C]0.0142621829665637[/C][/ROW]
[ROW][C]0.0100204291181164[/C][/ROW]
[ROW][C]-0.00940830173673466[/C][/ROW]
[ROW][C]0.00149121114491802[/C][/ROW]
[ROW][C]-0.0058067759318511[/C][/ROW]
[ROW][C]-0.000446298372889234[/C][/ROW]
[ROW][C]0.00944580002621718[/C][/ROW]
[ROW][C]0.00691718794043605[/C][/ROW]
[ROW][C]-0.00100117509695559[/C][/ROW]
[ROW][C]-0.0108963720487612[/C][/ROW]
[ROW][C]-0.00312829444661124[/C][/ROW]
[ROW][C]-0.00648819967032455[/C][/ROW]
[ROW][C]-0.00660213243724198[/C][/ROW]
[ROW][C]0.0172106693358473[/C][/ROW]
[ROW][C]0.000921999931238851[/C][/ROW]
[ROW][C]0.00158697851318715[/C][/ROW]
[ROW][C]-0.00200308563212723[/C][/ROW]
[ROW][C]0.00156258277386819[/C][/ROW]
[ROW][C]0.00452390423245766[/C][/ROW]
[ROW][C]-0.00242752057423049[/C][/ROW]
[ROW][C]0.00653782319365939[/C][/ROW]
[ROW][C]-0.00864260317110358[/C][/ROW]
[ROW][C]-0.00193393493475223[/C][/ROW]
[ROW][C]0.0113212678526945[/C][/ROW]
[ROW][C]-0.000295818101161019[/C][/ROW]
[ROW][C]-0.0113715935595373[/C][/ROW]
[ROW][C]0.0128823719922788[/C][/ROW]
[ROW][C]-0.00363190185691193[/C][/ROW]
[ROW][C]-0.00783993650577952[/C][/ROW]
[ROW][C]0.00462815396898063[/C][/ROW]
[ROW][C]0.00240904978361227[/C][/ROW]
[ROW][C]-0.00213947676937367[/C][/ROW]
[ROW][C]-0.000228613739743290[/C][/ROW]
[ROW][C]0.00182324954083881[/C][/ROW]
[ROW][C]0.0165147809111417[/C][/ROW]
[ROW][C]-0.0147601210657752[/C][/ROW]
[ROW][C]-0.00185723008076251[/C][/ROW]
[ROW][C]0.00501477614625141[/C][/ROW]
[ROW][C]-0.00984433525296626[/C][/ROW]
[ROW][C]0.00615059973608415[/C][/ROW]
[ROW][C]-0.000979322360050031[/C][/ROW]
[ROW][C]0.00448393353602957[/C][/ROW]
[ROW][C]-0.00043571402871413[/C][/ROW]
[ROW][C]0.000581224621625873[/C][/ROW]
[ROW][C]-0.00466808730426968[/C][/ROW]
[ROW][C]-0.0067302162881713[/C][/ROW]
[ROW][C]-0.00817181013794204[/C][/ROW]
[ROW][C]-0.0155557665617804[/C][/ROW]
[ROW][C]-0.00274249112106238[/C][/ROW]
[ROW][C]-0.000108175829954355[/C][/ROW]
[ROW][C]-0.0046207976104667[/C][/ROW]
[ROW][C]-0.00631784437519178[/C][/ROW]
[ROW][C]-0.00256610172319716[/C][/ROW]
[ROW][C]0.00864858976183008[/C][/ROW]
[ROW][C]-0.00462861129435498[/C][/ROW]
[ROW][C]0.0106395707414771[/C][/ROW]
[ROW][C]-0.00183307313881890[/C][/ROW]
[ROW][C]0.0127941062754136[/C][/ROW]
[ROW][C]0.0406957999993953[/C][/ROW]
[ROW][C]-0.00243510460817833[/C][/ROW]
[ROW][C]0.00769886703923425[/C][/ROW]
[ROW][C]-0.00181980046600172[/C][/ROW]
[ROW][C]-0.00166617365407226[/C][/ROW]
[ROW][C]0.0128619317223768[/C][/ROW]
[ROW][C]0.00716448453613985[/C][/ROW]
[ROW][C]-0.007637802225223[/C][/ROW]
[ROW][C]0.0159149478080651[/C][/ROW]
[ROW][C]-0.00403452114642185[/C][/ROW]
[ROW][C]-0.00180503183014593[/C][/ROW]
[ROW][C]-0.00850380070981158[/C][/ROW]
[ROW][C]-0.0112341066169573[/C][/ROW]
[ROW][C]-0.00616891274001468[/C][/ROW]
[ROW][C]0.00920188897733349[/C][/ROW]
[ROW][C]0.00796423400336723[/C][/ROW]
[ROW][C]-0.0068821032663446[/C][/ROW]
[ROW][C]0.00806738315921829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62483&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62483&T=2

As an alternative you can also use a QR Code:

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

Estimated ARIMA Residuals
Value
-0.0428218125170796
-0.0100326993013991
0.0106918718216985
-0.0270254228728889
0.00331295567691715
-0.00172922886482726
0.00366757515519101
-0.00415526854787519
0.0104271549130312
0.00427641309877716
-0.0126496967383851
-0.00390689047203263
-0.0101206960011753
-0.00468772961407567
-0.0150740304292764
-1.33428110902740e-05
0.0119188075076894
0.00572283197168028
0.00665070278331704
0.00090205406909518
-0.0162622053844042
-0.00296756232063624
-0.00135456295251316
-0.0042209026627126
-0.00691408156016935
-0.00912632470708239
-0.00363510844058383
-0.00306970191559634
-0.00780541568564299
-0.006868812991491
-0.000257167935027653
0.0049273580740412
-0.000471880075575950
0.00317403516926835
-0.00343539003636517
-0.00551097799029973
-0.00331882804059151
-0.00361129923103662
-0.00652485052709214
-0.00534106241603319
-0.00135927919983362
-0.0343214228787846
0.0177594984616496
0.00364339425842831
-0.00121175380858133
-0.0327812777406239
-0.00148506143608297
0.00654626504510931
-0.008351643395982
0.0203907579605412
0.000568475381496058
-0.00942604815258168
0.00113916206615276
0.0043092472157751
-0.00301159386164524
-0.00906169822472322
-0.0136304198479953
-0.00212936574530797
0.0068318098515847
0.000150216886319774
-0.00737963781697722
-0.00153897632601257
0.000841643815183354
-0.0132092570518280
0.00292140455998971
0.0129145072578084
0.00606074015887007
-0.00658945299795582
-0.0115849184572875
-0.000552060264397507
0.00248265055500265
0.00334878283923914
-0.00269702618853409
0.0115526199006686
0.00118595439052892
-0.00135637686316826
0.00215929077771191
-0.000482170078572539
-0.00387224935612852
0.00351301275870692
-0.00927814778277982
-0.0029904541530031
-0.00274095220266759
-0.00249636536060637
-0.00311171252457146
-0.00805853653701809
0.000265678489948079
0.0273268578244866
0.00697830979820947
0.00496746078085009
0.00859756339461414
0.00301817383550722
-0.00234812076011175
0.0147587387471635
-0.00544202527272388
-0.00677778505404914
0.0004550798404177
-0.0122394292493475
-0.00234804851701877
-0.0256177580063547
-0.00464405104943095
-2.70057488568111e-05
-0.00989528047657607
0.0165312207375463
0.0080040365882147
-0.00521646931112789
0.00322664055997624
0.00551614198148039
-0.00100617891676795
-0.00205682092387900
-0.00258556303479596
0.00934819608973077
0.0179703269504516
0.0103451559754469
0.00649502857332097
-0.0121013907012526
0.00364835716496857
-0.00298182402789843
0.000479097204803333
0.00207952137945619
0.00431246556704327
-0.0187863854547659
0.00172520467637257
-0.0035514491910531
-0.000874163230723674
-0.000488392516677418
0.0098104397277384
-0.0039659160977418
-0.000399503211136772
-0.00258411728185081
0.00655686668097407
-0.00210834440504175
0.0110432610023186
-0.0203220167411467
-0.0135046593294898
-0.0177584958286347
0.0142621829665637
0.0100204291181164
-0.00940830173673466
0.00149121114491802
-0.0058067759318511
-0.000446298372889234
0.00944580002621718
0.00691718794043605
-0.00100117509695559
-0.0108963720487612
-0.00312829444661124
-0.00648819967032455
-0.00660213243724198
0.0172106693358473
0.000921999931238851
0.00158697851318715
-0.00200308563212723
0.00156258277386819
0.00452390423245766
-0.00242752057423049
0.00653782319365939
-0.00864260317110358
-0.00193393493475223
0.0113212678526945
-0.000295818101161019
-0.0113715935595373
0.0128823719922788
-0.00363190185691193
-0.00783993650577952
0.00462815396898063
0.00240904978361227
-0.00213947676937367
-0.000228613739743290
0.00182324954083881
0.0165147809111417
-0.0147601210657752
-0.00185723008076251
0.00501477614625141
-0.00984433525296626
0.00615059973608415
-0.000979322360050031
0.00448393353602957
-0.00043571402871413
0.000581224621625873
-0.00466808730426968
-0.0067302162881713
-0.00817181013794204
-0.0155557665617804
-0.00274249112106238
-0.000108175829954355
-0.0046207976104667
-0.00631784437519178
-0.00256610172319716
0.00864858976183008
-0.00462861129435498
0.0106395707414771
-0.00183307313881890
0.0127941062754136
0.0406957999993953
-0.00243510460817833
0.00769886703923425
-0.00181980046600172
-0.00166617365407226
0.0128619317223768
0.00716448453613985
-0.007637802225223
0.0159149478080651
-0.00403452114642185
-0.00180503183014593
-0.00850380070981158
-0.0112341066169573
-0.00616891274001468
0.00920188897733349
0.00796423400336723
-0.0068821032663446
0.00806738315921829

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

Parameters (R input):

par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code