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R Software Module

rwasp_arimabackwardselection.wasp

Title produced by software

ARIMA Backward Selection

Date of computation

Thu, 03 Dec 2009 06:27:44 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259846994qti27k467prf495.htm/, Retrieved Thu, 25 Apr 2024 00:56:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62729, Retrieved Thu, 25 Apr 2024 00:56:56 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

187

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] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   P         [ARIMA Backward Selection] [backward arma  es...] [2009-12-03 13:27:44] [f0f26816ac6124f58333f11f6c174000] [Current]
-    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=62729&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=62729&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62729&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 )	0.0417	0.1746	-0.1224	0.1065	-0.1204	0.0914	-0.7716
(p-val)	(0.9322 )	(0.0568 )	(0.2366 )	(0.8292 )	(0.3048 )	(0.4036 )	(0 )
Estimates ( 2 )	0	0.1797	-0.1157	0.1482	-0.1204	0.0925	-0.7713
(p-val)	(NA )	(0.0091 )	(0.0936 )	(0.0335 )	(0.3056 )	(0.3958 )	(0 )
Estimates ( 3 )	0	0.1776	-0.1174	0.1531	-0.1896	0	-0.7056
(p-val)	(NA )	(0.0099 )	(0.0884 )	(0.0274 )	(0.0536 )	(NA )	(0 )
Estimates ( 4 )	0	0.18	0	0.1533	-0.1812	0	-0.7043
(p-val)	(NA )	(0.0114 )	(NA )	(0.0261 )	(0.0653 )	(NA )	(0 )
Estimates ( 5 )	0	0.1867	0	0.1571	0	0	-1.2543
(p-val)	(NA )	(0.0084 )	(NA )	(0.0222 )	(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 ) & 0.0417 & 0.1746 & -0.1224 & 0.1065 & -0.1204 & 0.0914 & -0.7716 \tabularnewline
(p-val) & (0.9322 ) & (0.0568 ) & (0.2366 ) & (0.8292 ) & (0.3048 ) & (0.4036 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0 & 0.1797 & -0.1157 & 0.1482 & -0.1204 & 0.0925 & -0.7713 \tabularnewline
(p-val) & (NA ) & (0.0091 ) & (0.0936 ) & (0.0335 ) & (0.3056 ) & (0.3958 ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0 & 0.1776 & -0.1174 & 0.1531 & -0.1896 & 0 & -0.7056 \tabularnewline
(p-val) & (NA ) & (0.0099 ) & (0.0884 ) & (0.0274 ) & (0.0536 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0 & 0.18 & 0 & 0.1533 & -0.1812 & 0 & -0.7043 \tabularnewline
(p-val) & (NA ) & (0.0114 ) & (NA ) & (0.0261 ) & (0.0653 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 5 ) & 0 & 0.1867 & 0 & 0.1571 & 0 & 0 & -1.2543 \tabularnewline
(p-val) & (NA ) & (0.0084 ) & (NA ) & (0.0222 ) & (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=62729&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]0.0417[/C][C]0.1746[/C][C]-0.1224[/C][C]0.1065[/C][C]-0.1204[/C][C]0.0914[/C][C]-0.7716[/C][/ROW]
[ROW][C](p-val)[/C][C](0.9322 )[/C][C](0.0568 )[/C][C](0.2366 )[/C][C](0.8292 )[/C][C](0.3048 )[/C][C](0.4036 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0[/C][C]0.1797[/C][C]-0.1157[/C][C]0.1482[/C][C]-0.1204[/C][C]0.0925[/C][C]-0.7713[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0091 )[/C][C](0.0936 )[/C][C](0.0335 )[/C][C](0.3056 )[/C][C](0.3958 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0[/C][C]0.1776[/C][C]-0.1174[/C][C]0.1531[/C][C]-0.1896[/C][C]0[/C][C]-0.7056[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0099 )[/C][C](0.0884 )[/C][C](0.0274 )[/C][C](0.0536 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0[/C][C]0.18[/C][C]0[/C][C]0.1533[/C][C]-0.1812[/C][C]0[/C][C]-0.7043[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0114 )[/C][C](NA )[/C][C](0.0261 )[/C][C](0.0653 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]0[/C][C]0.1867[/C][C]0[/C][C]0.1571[/C][C]0[/C][C]0[/C][C]-1.2543[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.0084 )[/C][C](NA )[/C][C](0.0222 )[/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=62729&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62729&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 )	0.0417	0.1746	-0.1224	0.1065	-0.1204	0.0914	-0.7716
(p-val)	(0.9322 )	(0.0568 )	(0.2366 )	(0.8292 )	(0.3048 )	(0.4036 )	(0 )
Estimates ( 2 )	0	0.1797	-0.1157	0.1482	-0.1204	0.0925	-0.7713
(p-val)	(NA )	(0.0091 )	(0.0936 )	(0.0335 )	(0.3056 )	(0.3958 )	(0 )
Estimates ( 3 )	0	0.1776	-0.1174	0.1531	-0.1896	0	-0.7056
(p-val)	(NA )	(0.0099 )	(0.0884 )	(0.0274 )	(0.0536 )	(NA )	(0 )
Estimates ( 4 )	0	0.18	0	0.1533	-0.1812	0	-0.7043
(p-val)	(NA )	(0.0114 )	(NA )	(0.0261 )	(0.0653 )	(NA )	(0 )
Estimates ( 5 )	0	0.1867	0	0.1571	0	0	-1.2543
(p-val)	(NA )	(0.0084 )	(NA )	(0.0222 )	(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
-0.52374480397648
-0.288361715303982
0.345483732026524
-0.816905506263942
0.145034188744529
-0.099401539884145
0.223502798390389
-0.145276377483508
0.352369551994772
0.114222563819357
-0.381596315834949
-0.149274079374981
-0.364506463466575
-0.131497048871967
-0.428928897957025
-0.0128029445731647
0.417547580819552
0.253567809001675
0.237899815412068
-0.0136767235765247
-0.525393295813975
-0.106285788912696
-0.109709083824742
-0.0779139906509786
-0.276618297718814
-0.255097319502197
-0.167453241941011
0.0033271972235008
-0.183243797051705
-0.168630989911728
0.0189100323389874
0.211950610566072
-0.0648135188510749
0.107025348222725
-0.138322204494206
-0.178522727757717
-0.154390446352741
-0.0930828394745394
-0.185887464297410
-0.113283903040525
-0.0829781677262606
-1.16540295867325
0.60920181880751
0.160757523234962
0.142372143826710
-1.16421021167506
-0.0484899660961531
0.174606377147616
-0.130754518326490
0.735513692367742
0.02873973769248
-0.265108225849052
-0.0602546402983856
0.0180017038742341
-0.0180923837366958
-0.284436409099758
-0.44436460698603
-0.195822494605576
0.272672297656948
0.108489887826107
-0.235168565685108
0.0587534134213678
0.0613075600251907
-0.407444998261471
0.100129136178290
0.523400942946945
0.217166038043875
-0.27346058527365
-0.48173870852231
0.0086946833692491
0.144438297793334
0.177084520218175
-0.0890208191408817
0.398869073021547
0.0548822037071899
-0.0122097583692534
0.0315803665719613
0.0647857171065976
-0.131952243873601
0.114010842802942
-0.324872329366068
-0.0348883988715922
-0.110274402880525
-0.0249891770234306
-0.081718654322768
-0.193232000126616
0.0439594282300216
1.05354070143321
0.273574898212201
0.177320466942412
0.142402012912143
0.117920576129720
-0.0929376290161563
0.529608127868264
-0.234523879622836
-0.237465235947183
-0.0353078922529346
-0.423297789916321
-0.0398114675724483
-0.728950589060202
-0.0882887590535755
0.016905908843429
-0.215737013021926
0.62612454718676
0.364266172837773
-0.0598636007940919
0.0227812067894789
0.13832751484115
-0.0077164398165806
-0.087510844881476
-0.0963734147998768
0.241809202827894
0.616466521859784
0.374566597138869
0.159450456202993
-0.444107324982977
0.172825571278153
-0.170808387285465
0.0949355461621432
0.0886391824848962
0.207429699689407
-0.631581829567683
0.0802945024987532
-0.0549242238104122
0.113633307290431
-0.0061867462491774
0.422956175260977
-0.238091449285586
0.0364373730488438
-0.153323002409131
0.278396092587863
-0.0816392733211193
0.468294608492834
-0.781560717256575
-0.434163960688174
-0.698414659989165
0.577281587759107
0.371075879542926
-0.197286798037801
-0.0111944344049922
-0.229578327168158
0.00664372513288023
0.368679927857223
0.279885889981472
0.00785452638088507
-0.406002915906195
-0.174266375425880
-0.268313066291987
-0.174937936173617
0.673768944725947
0.0202950067121689
0.118771704546288
-0.158404820896165
0.0830328512616531
0.15752149674081
-0.0360228406351563
0.20164488636655
-0.238804044531652
-0.0199280729380379
0.461223303429214
-0.056133915696854
-0.402453851621938
0.450557249291248
-0.112790608474864
-0.223838008190007
0.141286494695174
0.0948556876353299
-0.0805240925513677
-0.0100328284360783
0.164912185218094
0.682482831092595
-0.427247122528398
-0.0991204216994101
-0.0128278411212124
-0.261600157301203
0.227060102277355
-0.0245420821445065
0.234879271165509
-0.0686901897667455
0.0280645423923847
-0.23830001916173
-0.112041737720483
-0.214994102426051
-0.576858533068063
-0.106447262177217
0.0277723778955199
-0.159338833737699
-0.181329243183862
-0.0452735377680643
0.368164583940315
-0.182844023786306
0.433977629768653
-0.146317419525741
0.588171838001187
1.47174492794147
-0.0437192223165927
0.220558651331199
-0.278086295912511
-0.0679383492549549
0.414285631873695
0.345630680998224
-0.275424852206537
0.548354542075289
-0.156962707914349
-0.0367355412491467
-0.274017462894157
-0.234934345311429
-0.154977478547228
0.445242923221808
0.323484904801379
-0.214187104038128
0.339258439245050

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
-0.52374480397648 \tabularnewline
-0.288361715303982 \tabularnewline
0.345483732026524 \tabularnewline
-0.816905506263942 \tabularnewline
0.145034188744529 \tabularnewline
-0.099401539884145 \tabularnewline
0.223502798390389 \tabularnewline
-0.145276377483508 \tabularnewline
0.352369551994772 \tabularnewline
0.114222563819357 \tabularnewline
-0.381596315834949 \tabularnewline
-0.149274079374981 \tabularnewline
-0.364506463466575 \tabularnewline
-0.131497048871967 \tabularnewline
-0.428928897957025 \tabularnewline
-0.0128029445731647 \tabularnewline
0.417547580819552 \tabularnewline
0.253567809001675 \tabularnewline
0.237899815412068 \tabularnewline
-0.0136767235765247 \tabularnewline
-0.525393295813975 \tabularnewline
-0.106285788912696 \tabularnewline
-0.109709083824742 \tabularnewline
-0.0779139906509786 \tabularnewline
-0.276618297718814 \tabularnewline
-0.255097319502197 \tabularnewline
-0.167453241941011 \tabularnewline
0.0033271972235008 \tabularnewline
-0.183243797051705 \tabularnewline
-0.168630989911728 \tabularnewline
0.0189100323389874 \tabularnewline
0.211950610566072 \tabularnewline
-0.0648135188510749 \tabularnewline
0.107025348222725 \tabularnewline
-0.138322204494206 \tabularnewline
-0.178522727757717 \tabularnewline
-0.154390446352741 \tabularnewline
-0.0930828394745394 \tabularnewline
-0.185887464297410 \tabularnewline
-0.113283903040525 \tabularnewline
-0.0829781677262606 \tabularnewline
-1.16540295867325 \tabularnewline
0.60920181880751 \tabularnewline
0.160757523234962 \tabularnewline
0.142372143826710 \tabularnewline
-1.16421021167506 \tabularnewline
-0.0484899660961531 \tabularnewline
0.174606377147616 \tabularnewline
-0.130754518326490 \tabularnewline
0.735513692367742 \tabularnewline
0.02873973769248 \tabularnewline
-0.265108225849052 \tabularnewline
-0.0602546402983856 \tabularnewline
0.0180017038742341 \tabularnewline
-0.0180923837366958 \tabularnewline
-0.284436409099758 \tabularnewline
-0.44436460698603 \tabularnewline
-0.195822494605576 \tabularnewline
0.272672297656948 \tabularnewline
0.108489887826107 \tabularnewline
-0.235168565685108 \tabularnewline
0.0587534134213678 \tabularnewline
0.0613075600251907 \tabularnewline
-0.407444998261471 \tabularnewline
0.100129136178290 \tabularnewline
0.523400942946945 \tabularnewline
0.217166038043875 \tabularnewline
-0.27346058527365 \tabularnewline
-0.48173870852231 \tabularnewline
0.0086946833692491 \tabularnewline
0.144438297793334 \tabularnewline
0.177084520218175 \tabularnewline
-0.0890208191408817 \tabularnewline
0.398869073021547 \tabularnewline
0.0548822037071899 \tabularnewline
-0.0122097583692534 \tabularnewline
0.0315803665719613 \tabularnewline
0.0647857171065976 \tabularnewline
-0.131952243873601 \tabularnewline
0.114010842802942 \tabularnewline
-0.324872329366068 \tabularnewline
-0.0348883988715922 \tabularnewline
-0.110274402880525 \tabularnewline
-0.0249891770234306 \tabularnewline
-0.081718654322768 \tabularnewline
-0.193232000126616 \tabularnewline
0.0439594282300216 \tabularnewline
1.05354070143321 \tabularnewline
0.273574898212201 \tabularnewline
0.177320466942412 \tabularnewline
0.142402012912143 \tabularnewline
0.117920576129720 \tabularnewline
-0.0929376290161563 \tabularnewline
0.529608127868264 \tabularnewline
-0.234523879622836 \tabularnewline
-0.237465235947183 \tabularnewline
-0.0353078922529346 \tabularnewline
-0.423297789916321 \tabularnewline
-0.0398114675724483 \tabularnewline
-0.728950589060202 \tabularnewline
-0.0882887590535755 \tabularnewline
0.016905908843429 \tabularnewline
-0.215737013021926 \tabularnewline
0.62612454718676 \tabularnewline
0.364266172837773 \tabularnewline
-0.0598636007940919 \tabularnewline
0.0227812067894789 \tabularnewline
0.13832751484115 \tabularnewline
-0.0077164398165806 \tabularnewline
-0.087510844881476 \tabularnewline
-0.0963734147998768 \tabularnewline
0.241809202827894 \tabularnewline
0.616466521859784 \tabularnewline
0.374566597138869 \tabularnewline
0.159450456202993 \tabularnewline
-0.444107324982977 \tabularnewline
0.172825571278153 \tabularnewline
-0.170808387285465 \tabularnewline
0.0949355461621432 \tabularnewline
0.0886391824848962 \tabularnewline
0.207429699689407 \tabularnewline
-0.631581829567683 \tabularnewline
0.0802945024987532 \tabularnewline
-0.0549242238104122 \tabularnewline
0.113633307290431 \tabularnewline
-0.0061867462491774 \tabularnewline
0.422956175260977 \tabularnewline
-0.238091449285586 \tabularnewline
0.0364373730488438 \tabularnewline
-0.153323002409131 \tabularnewline
0.278396092587863 \tabularnewline
-0.0816392733211193 \tabularnewline
0.468294608492834 \tabularnewline
-0.781560717256575 \tabularnewline
-0.434163960688174 \tabularnewline
-0.698414659989165 \tabularnewline
0.577281587759107 \tabularnewline
0.371075879542926 \tabularnewline
-0.197286798037801 \tabularnewline
-0.0111944344049922 \tabularnewline
-0.229578327168158 \tabularnewline
0.00664372513288023 \tabularnewline
0.368679927857223 \tabularnewline
0.279885889981472 \tabularnewline
0.00785452638088507 \tabularnewline
-0.406002915906195 \tabularnewline
-0.174266375425880 \tabularnewline
-0.268313066291987 \tabularnewline
-0.174937936173617 \tabularnewline
0.673768944725947 \tabularnewline
0.0202950067121689 \tabularnewline
0.118771704546288 \tabularnewline
-0.158404820896165 \tabularnewline
0.0830328512616531 \tabularnewline
0.15752149674081 \tabularnewline
-0.0360228406351563 \tabularnewline
0.20164488636655 \tabularnewline
-0.238804044531652 \tabularnewline
-0.0199280729380379 \tabularnewline
0.461223303429214 \tabularnewline
-0.056133915696854 \tabularnewline
-0.402453851621938 \tabularnewline
0.450557249291248 \tabularnewline
-0.112790608474864 \tabularnewline
-0.223838008190007 \tabularnewline
0.141286494695174 \tabularnewline
0.0948556876353299 \tabularnewline
-0.0805240925513677 \tabularnewline
-0.0100328284360783 \tabularnewline
0.164912185218094 \tabularnewline
0.682482831092595 \tabularnewline
-0.427247122528398 \tabularnewline
-0.0991204216994101 \tabularnewline
-0.0128278411212124 \tabularnewline
-0.261600157301203 \tabularnewline
0.227060102277355 \tabularnewline
-0.0245420821445065 \tabularnewline
0.234879271165509 \tabularnewline
-0.0686901897667455 \tabularnewline
0.0280645423923847 \tabularnewline
-0.23830001916173 \tabularnewline
-0.112041737720483 \tabularnewline
-0.214994102426051 \tabularnewline
-0.576858533068063 \tabularnewline
-0.106447262177217 \tabularnewline
0.0277723778955199 \tabularnewline
-0.159338833737699 \tabularnewline
-0.181329243183862 \tabularnewline
-0.0452735377680643 \tabularnewline
0.368164583940315 \tabularnewline
-0.182844023786306 \tabularnewline
0.433977629768653 \tabularnewline
-0.146317419525741 \tabularnewline
0.588171838001187 \tabularnewline
1.47174492794147 \tabularnewline
-0.0437192223165927 \tabularnewline
0.220558651331199 \tabularnewline
-0.278086295912511 \tabularnewline
-0.0679383492549549 \tabularnewline
0.414285631873695 \tabularnewline
0.345630680998224 \tabularnewline
-0.275424852206537 \tabularnewline
0.548354542075289 \tabularnewline
-0.156962707914349 \tabularnewline
-0.0367355412491467 \tabularnewline
-0.274017462894157 \tabularnewline
-0.234934345311429 \tabularnewline
-0.154977478547228 \tabularnewline
0.445242923221808 \tabularnewline
0.323484904801379 \tabularnewline
-0.214187104038128 \tabularnewline
0.339258439245050 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62729&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]-0.52374480397648[/C][/ROW]
[ROW][C]-0.288361715303982[/C][/ROW]
[ROW][C]0.345483732026524[/C][/ROW]
[ROW][C]-0.816905506263942[/C][/ROW]
[ROW][C]0.145034188744529[/C][/ROW]
[ROW][C]-0.099401539884145[/C][/ROW]
[ROW][C]0.223502798390389[/C][/ROW]
[ROW][C]-0.145276377483508[/C][/ROW]
[ROW][C]0.352369551994772[/C][/ROW]
[ROW][C]0.114222563819357[/C][/ROW]
[ROW][C]-0.381596315834949[/C][/ROW]
[ROW][C]-0.149274079374981[/C][/ROW]
[ROW][C]-0.364506463466575[/C][/ROW]
[ROW][C]-0.131497048871967[/C][/ROW]
[ROW][C]-0.428928897957025[/C][/ROW]
[ROW][C]-0.0128029445731647[/C][/ROW]
[ROW][C]0.417547580819552[/C][/ROW]
[ROW][C]0.253567809001675[/C][/ROW]
[ROW][C]0.237899815412068[/C][/ROW]
[ROW][C]-0.0136767235765247[/C][/ROW]
[ROW][C]-0.525393295813975[/C][/ROW]
[ROW][C]-0.106285788912696[/C][/ROW]
[ROW][C]-0.109709083824742[/C][/ROW]
[ROW][C]-0.0779139906509786[/C][/ROW]
[ROW][C]-0.276618297718814[/C][/ROW]
[ROW][C]-0.255097319502197[/C][/ROW]
[ROW][C]-0.167453241941011[/C][/ROW]
[ROW][C]0.0033271972235008[/C][/ROW]
[ROW][C]-0.183243797051705[/C][/ROW]
[ROW][C]-0.168630989911728[/C][/ROW]
[ROW][C]0.0189100323389874[/C][/ROW]
[ROW][C]0.211950610566072[/C][/ROW]
[ROW][C]-0.0648135188510749[/C][/ROW]
[ROW][C]0.107025348222725[/C][/ROW]
[ROW][C]-0.138322204494206[/C][/ROW]
[ROW][C]-0.178522727757717[/C][/ROW]
[ROW][C]-0.154390446352741[/C][/ROW]
[ROW][C]-0.0930828394745394[/C][/ROW]
[ROW][C]-0.185887464297410[/C][/ROW]
[ROW][C]-0.113283903040525[/C][/ROW]
[ROW][C]-0.0829781677262606[/C][/ROW]
[ROW][C]-1.16540295867325[/C][/ROW]
[ROW][C]0.60920181880751[/C][/ROW]
[ROW][C]0.160757523234962[/C][/ROW]
[ROW][C]0.142372143826710[/C][/ROW]
[ROW][C]-1.16421021167506[/C][/ROW]
[ROW][C]-0.0484899660961531[/C][/ROW]
[ROW][C]0.174606377147616[/C][/ROW]
[ROW][C]-0.130754518326490[/C][/ROW]
[ROW][C]0.735513692367742[/C][/ROW]
[ROW][C]0.02873973769248[/C][/ROW]
[ROW][C]-0.265108225849052[/C][/ROW]
[ROW][C]-0.0602546402983856[/C][/ROW]
[ROW][C]0.0180017038742341[/C][/ROW]
[ROW][C]-0.0180923837366958[/C][/ROW]
[ROW][C]-0.284436409099758[/C][/ROW]
[ROW][C]-0.44436460698603[/C][/ROW]
[ROW][C]-0.195822494605576[/C][/ROW]
[ROW][C]0.272672297656948[/C][/ROW]
[ROW][C]0.108489887826107[/C][/ROW]
[ROW][C]-0.235168565685108[/C][/ROW]
[ROW][C]0.0587534134213678[/C][/ROW]
[ROW][C]0.0613075600251907[/C][/ROW]
[ROW][C]-0.407444998261471[/C][/ROW]
[ROW][C]0.100129136178290[/C][/ROW]
[ROW][C]0.523400942946945[/C][/ROW]
[ROW][C]0.217166038043875[/C][/ROW]
[ROW][C]-0.27346058527365[/C][/ROW]
[ROW][C]-0.48173870852231[/C][/ROW]
[ROW][C]0.0086946833692491[/C][/ROW]
[ROW][C]0.144438297793334[/C][/ROW]
[ROW][C]0.177084520218175[/C][/ROW]
[ROW][C]-0.0890208191408817[/C][/ROW]
[ROW][C]0.398869073021547[/C][/ROW]
[ROW][C]0.0548822037071899[/C][/ROW]
[ROW][C]-0.0122097583692534[/C][/ROW]
[ROW][C]0.0315803665719613[/C][/ROW]
[ROW][C]0.0647857171065976[/C][/ROW]
[ROW][C]-0.131952243873601[/C][/ROW]
[ROW][C]0.114010842802942[/C][/ROW]
[ROW][C]-0.324872329366068[/C][/ROW]
[ROW][C]-0.0348883988715922[/C][/ROW]
[ROW][C]-0.110274402880525[/C][/ROW]
[ROW][C]-0.0249891770234306[/C][/ROW]
[ROW][C]-0.081718654322768[/C][/ROW]
[ROW][C]-0.193232000126616[/C][/ROW]
[ROW][C]0.0439594282300216[/C][/ROW]
[ROW][C]1.05354070143321[/C][/ROW]
[ROW][C]0.273574898212201[/C][/ROW]
[ROW][C]0.177320466942412[/C][/ROW]
[ROW][C]0.142402012912143[/C][/ROW]
[ROW][C]0.117920576129720[/C][/ROW]
[ROW][C]-0.0929376290161563[/C][/ROW]
[ROW][C]0.529608127868264[/C][/ROW]
[ROW][C]-0.234523879622836[/C][/ROW]
[ROW][C]-0.237465235947183[/C][/ROW]
[ROW][C]-0.0353078922529346[/C][/ROW]
[ROW][C]-0.423297789916321[/C][/ROW]
[ROW][C]-0.0398114675724483[/C][/ROW]
[ROW][C]-0.728950589060202[/C][/ROW]
[ROW][C]-0.0882887590535755[/C][/ROW]
[ROW][C]0.016905908843429[/C][/ROW]
[ROW][C]-0.215737013021926[/C][/ROW]
[ROW][C]0.62612454718676[/C][/ROW]
[ROW][C]0.364266172837773[/C][/ROW]
[ROW][C]-0.0598636007940919[/C][/ROW]
[ROW][C]0.0227812067894789[/C][/ROW]
[ROW][C]0.13832751484115[/C][/ROW]
[ROW][C]-0.0077164398165806[/C][/ROW]
[ROW][C]-0.087510844881476[/C][/ROW]
[ROW][C]-0.0963734147998768[/C][/ROW]
[ROW][C]0.241809202827894[/C][/ROW]
[ROW][C]0.616466521859784[/C][/ROW]
[ROW][C]0.374566597138869[/C][/ROW]
[ROW][C]0.159450456202993[/C][/ROW]
[ROW][C]-0.444107324982977[/C][/ROW]
[ROW][C]0.172825571278153[/C][/ROW]
[ROW][C]-0.170808387285465[/C][/ROW]
[ROW][C]0.0949355461621432[/C][/ROW]
[ROW][C]0.0886391824848962[/C][/ROW]
[ROW][C]0.207429699689407[/C][/ROW]
[ROW][C]-0.631581829567683[/C][/ROW]
[ROW][C]0.0802945024987532[/C][/ROW]
[ROW][C]-0.0549242238104122[/C][/ROW]
[ROW][C]0.113633307290431[/C][/ROW]
[ROW][C]-0.0061867462491774[/C][/ROW]
[ROW][C]0.422956175260977[/C][/ROW]
[ROW][C]-0.238091449285586[/C][/ROW]
[ROW][C]0.0364373730488438[/C][/ROW]
[ROW][C]-0.153323002409131[/C][/ROW]
[ROW][C]0.278396092587863[/C][/ROW]
[ROW][C]-0.0816392733211193[/C][/ROW]
[ROW][C]0.468294608492834[/C][/ROW]
[ROW][C]-0.781560717256575[/C][/ROW]
[ROW][C]-0.434163960688174[/C][/ROW]
[ROW][C]-0.698414659989165[/C][/ROW]
[ROW][C]0.577281587759107[/C][/ROW]
[ROW][C]0.371075879542926[/C][/ROW]
[ROW][C]-0.197286798037801[/C][/ROW]
[ROW][C]-0.0111944344049922[/C][/ROW]
[ROW][C]-0.229578327168158[/C][/ROW]
[ROW][C]0.00664372513288023[/C][/ROW]
[ROW][C]0.368679927857223[/C][/ROW]
[ROW][C]0.279885889981472[/C][/ROW]
[ROW][C]0.00785452638088507[/C][/ROW]
[ROW][C]-0.406002915906195[/C][/ROW]
[ROW][C]-0.174266375425880[/C][/ROW]
[ROW][C]-0.268313066291987[/C][/ROW]
[ROW][C]-0.174937936173617[/C][/ROW]
[ROW][C]0.673768944725947[/C][/ROW]
[ROW][C]0.0202950067121689[/C][/ROW]
[ROW][C]0.118771704546288[/C][/ROW]
[ROW][C]-0.158404820896165[/C][/ROW]
[ROW][C]0.0830328512616531[/C][/ROW]
[ROW][C]0.15752149674081[/C][/ROW]
[ROW][C]-0.0360228406351563[/C][/ROW]
[ROW][C]0.20164488636655[/C][/ROW]
[ROW][C]-0.238804044531652[/C][/ROW]
[ROW][C]-0.0199280729380379[/C][/ROW]
[ROW][C]0.461223303429214[/C][/ROW]
[ROW][C]-0.056133915696854[/C][/ROW]
[ROW][C]-0.402453851621938[/C][/ROW]
[ROW][C]0.450557249291248[/C][/ROW]
[ROW][C]-0.112790608474864[/C][/ROW]
[ROW][C]-0.223838008190007[/C][/ROW]
[ROW][C]0.141286494695174[/C][/ROW]
[ROW][C]0.0948556876353299[/C][/ROW]
[ROW][C]-0.0805240925513677[/C][/ROW]
[ROW][C]-0.0100328284360783[/C][/ROW]
[ROW][C]0.164912185218094[/C][/ROW]
[ROW][C]0.682482831092595[/C][/ROW]
[ROW][C]-0.427247122528398[/C][/ROW]
[ROW][C]-0.0991204216994101[/C][/ROW]
[ROW][C]-0.0128278411212124[/C][/ROW]
[ROW][C]-0.261600157301203[/C][/ROW]
[ROW][C]0.227060102277355[/C][/ROW]
[ROW][C]-0.0245420821445065[/C][/ROW]
[ROW][C]0.234879271165509[/C][/ROW]
[ROW][C]-0.0686901897667455[/C][/ROW]
[ROW][C]0.0280645423923847[/C][/ROW]
[ROW][C]-0.23830001916173[/C][/ROW]
[ROW][C]-0.112041737720483[/C][/ROW]
[ROW][C]-0.214994102426051[/C][/ROW]
[ROW][C]-0.576858533068063[/C][/ROW]
[ROW][C]-0.106447262177217[/C][/ROW]
[ROW][C]0.0277723778955199[/C][/ROW]
[ROW][C]-0.159338833737699[/C][/ROW]
[ROW][C]-0.181329243183862[/C][/ROW]
[ROW][C]-0.0452735377680643[/C][/ROW]
[ROW][C]0.368164583940315[/C][/ROW]
[ROW][C]-0.182844023786306[/C][/ROW]
[ROW][C]0.433977629768653[/C][/ROW]
[ROW][C]-0.146317419525741[/C][/ROW]
[ROW][C]0.588171838001187[/C][/ROW]
[ROW][C]1.47174492794147[/C][/ROW]
[ROW][C]-0.0437192223165927[/C][/ROW]
[ROW][C]0.220558651331199[/C][/ROW]
[ROW][C]-0.278086295912511[/C][/ROW]
[ROW][C]-0.0679383492549549[/C][/ROW]
[ROW][C]0.414285631873695[/C][/ROW]
[ROW][C]0.345630680998224[/C][/ROW]
[ROW][C]-0.275424852206537[/C][/ROW]
[ROW][C]0.548354542075289[/C][/ROW]
[ROW][C]-0.156962707914349[/C][/ROW]
[ROW][C]-0.0367355412491467[/C][/ROW]
[ROW][C]-0.274017462894157[/C][/ROW]
[ROW][C]-0.234934345311429[/C][/ROW]
[ROW][C]-0.154977478547228[/C][/ROW]
[ROW][C]0.445242923221808[/C][/ROW]
[ROW][C]0.323484904801379[/C][/ROW]
[ROW][C]-0.214187104038128[/C][/ROW]
[ROW][C]0.339258439245050[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62729&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62729&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
-0.52374480397648
-0.288361715303982
0.345483732026524
-0.816905506263942
0.145034188744529
-0.099401539884145
0.223502798390389
-0.145276377483508
0.352369551994772
0.114222563819357
-0.381596315834949
-0.149274079374981
-0.364506463466575
-0.131497048871967
-0.428928897957025
-0.0128029445731647
0.417547580819552
0.253567809001675
0.237899815412068
-0.0136767235765247
-0.525393295813975
-0.106285788912696
-0.109709083824742
-0.0779139906509786
-0.276618297718814
-0.255097319502197
-0.167453241941011
0.0033271972235008
-0.183243797051705
-0.168630989911728
0.0189100323389874
0.211950610566072
-0.0648135188510749
0.107025348222725
-0.138322204494206
-0.178522727757717
-0.154390446352741
-0.0930828394745394
-0.185887464297410
-0.113283903040525
-0.0829781677262606
-1.16540295867325
0.60920181880751
0.160757523234962
0.142372143826710
-1.16421021167506
-0.0484899660961531
0.174606377147616
-0.130754518326490
0.735513692367742
0.02873973769248
-0.265108225849052
-0.0602546402983856
0.0180017038742341
-0.0180923837366958
-0.284436409099758
-0.44436460698603
-0.195822494605576
0.272672297656948
0.108489887826107
-0.235168565685108
0.0587534134213678
0.0613075600251907
-0.407444998261471
0.100129136178290
0.523400942946945
0.217166038043875
-0.27346058527365
-0.48173870852231
0.0086946833692491
0.144438297793334
0.177084520218175
-0.0890208191408817
0.398869073021547
0.0548822037071899
-0.0122097583692534
0.0315803665719613
0.0647857171065976
-0.131952243873601
0.114010842802942
-0.324872329366068
-0.0348883988715922
-0.110274402880525
-0.0249891770234306
-0.081718654322768
-0.193232000126616
0.0439594282300216
1.05354070143321
0.273574898212201
0.177320466942412
0.142402012912143
0.117920576129720
-0.0929376290161563
0.529608127868264
-0.234523879622836
-0.237465235947183
-0.0353078922529346
-0.423297789916321
-0.0398114675724483
-0.728950589060202
-0.0882887590535755
0.016905908843429
-0.215737013021926
0.62612454718676
0.364266172837773
-0.0598636007940919
0.0227812067894789
0.13832751484115
-0.0077164398165806
-0.087510844881476
-0.0963734147998768
0.241809202827894
0.616466521859784
0.374566597138869
0.159450456202993
-0.444107324982977
0.172825571278153
-0.170808387285465
0.0949355461621432
0.0886391824848962
0.207429699689407
-0.631581829567683
0.0802945024987532
-0.0549242238104122
0.113633307290431
-0.0061867462491774
0.422956175260977
-0.238091449285586
0.0364373730488438
-0.153323002409131
0.278396092587863
-0.0816392733211193
0.468294608492834
-0.781560717256575
-0.434163960688174
-0.698414659989165
0.577281587759107
0.371075879542926
-0.197286798037801
-0.0111944344049922
-0.229578327168158
0.00664372513288023
0.368679927857223
0.279885889981472
0.00785452638088507
-0.406002915906195
-0.174266375425880
-0.268313066291987
-0.174937936173617
0.673768944725947
0.0202950067121689
0.118771704546288
-0.158404820896165
0.0830328512616531
0.15752149674081
-0.0360228406351563
0.20164488636655
-0.238804044531652
-0.0199280729380379
0.461223303429214
-0.056133915696854
-0.402453851621938
0.450557249291248
-0.112790608474864
-0.223838008190007
0.141286494695174
0.0948556876353299
-0.0805240925513677
-0.0100328284360783
0.164912185218094
0.682482831092595
-0.427247122528398
-0.0991204216994101
-0.0128278411212124
-0.261600157301203
0.227060102277355
-0.0245420821445065
0.234879271165509
-0.0686901897667455
0.0280645423923847
-0.23830001916173
-0.112041737720483
-0.214994102426051
-0.576858533068063
-0.106447262177217
0.0277723778955199
-0.159338833737699
-0.181329243183862
-0.0452735377680643
0.368164583940315
-0.182844023786306
0.433977629768653
-0.146317419525741
0.588171838001187
1.47174492794147
-0.0437192223165927
0.220558651331199
-0.278086295912511
-0.0679383492549549
0.414285631873695
0.345630680998224
-0.275424852206537
0.548354542075289
-0.156962707914349
-0.0367355412491467
-0.274017462894157
-0.234934345311429
-0.154977478547228
0.445242923221808
0.323484904801379
-0.214187104038128
0.339258439245050

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

Parameters (R input):

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

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

library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- as.numeric(par5) #seasonal period
par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
par7 <- 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