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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 computationSat, 04 Dec 2010 12:17:27 +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/04/t129146495385yhitvjjp01si8.htm/, Retrieved Sun, 05 May 2024 03:57:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105111, Retrieved Sun, 05 May 2024 03:57:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Standard Deviation-Mean Plot] [Births] [2010-11-29 10:52:49] [b98453cac15ba1066b407e146608df68]
- RMP           [ARIMA Backward Selection] [Births] [2010-11-29 17:42:52] [b98453cac15ba1066b407e146608df68]
-   PD              [ARIMA Backward Selection] [Model 1: CPI] [2010-12-04 12:17:27] [b6992a7b26e556359948e164e4227eba] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
115,65
116,00
115,92
116,10
116,44
116,65
117,45
117,58
117,43
117,24
117,25
117,29
117,83
118,22
118,11
118,23
118,15
118,23
119,03
119,38
118,97
118,78
118,97
118,94
119,86
120,09
120,13
120,15
119,90
120,00
120,84
121,17
120,81
121,00
121,12
121,29
122,09
121,88
121,31
121,33
121,45
121,67
122,78
122,84
122,34
122,37
122,72
122,68
122,78
123,08
122,92
123,51
124,18
124,05
124,36
123,87
123,84
123,85
123,83
123,84
124,27
124,56
124,57
124,87
125,08
124,86
124,89
124,58
124,83
124,97
125,19
125,42
125,74
126,07
126,35
126,69
126,85
127,12
127,43
127,49
128,05
127,85
128,35
128,29
128,38
128,80
129,18
130,14
130,77
131,19
131,32
131,41
131,61
131,69
131,94
131,70
132,54
132,74
133,02
132,76
133,05
132,74
133,16
133,10
133,37
133,15
133,18
133,29
133,76
134,51
134,82
134,71
134,52
134,86
135,11
135,28
135,61
135,22
135,47
135,42
135,85
136,27
136,30
136,85
137,05
137,03
137,45
137,49
137,55
138,04
138,03
137,75
138,27
138,99
139,74
139,70
139,97
140,21
140,78
140,80
140,64
140,42
140,85
140,96
141,04
141,71
141,60
142,11
142,59
142,56
143,00
143,18
143,15
143,10
143,45
143,59
143,92
144,66
144,34
144,82
144,49
144,41
144,99
144,95
145,00
145,66
146,68
147,38
147,94
149,12
149,95
150,19
151,16
151,74
152,56
152,09
152,46
152,66
152,38
152,59
152,88
153,29
152,35
152,49
152,20
151,57
151,55
151,79
151,52
151,76
151,92
152,20
152,75
153,49
153,78
154,10
154,62
154,65
154,81
154,92
155,40
155,63
155,76

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time27 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 & 27 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105111&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]27 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=105111&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105111&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 time27 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2ar3ma1sar1sar2sma1
Estimates ( 1 )0.8738-0.09860.0427-0.70680.92170.0377-0.7744
(p-val)(0 )(0.3306 )(0.57 )(4e-04 )(0 )(0.774 )(0 )
Estimates ( 2 )0.8634-0.09160.0401-0.6970.96870-0.8106
(p-val)(1e-04 )(0.3516 )(0.5926 )(5e-04 )(0 )(NA )(0 )
Estimates ( 3 )0.9044-0.06840-0.74030.96880-0.81
(p-val)(0 )(0.4412 )(NA )(1e-04 )(0 )(NA )(0 )
Estimates ( 4 )0.774900-0.64570.96640-0.8016
(p-val)(0 )(NA )(NA )(0.0021 )(0 )(NA )(0 )
Estimates ( 5 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(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 ) & 0.8738 & -0.0986 & 0.0427 & -0.7068 & 0.9217 & 0.0377 & -0.7744 \tabularnewline
(p-val) & (0 ) & (0.3306 ) & (0.57 ) & (4e-04 ) & (0 ) & (0.774 ) & (0 ) \tabularnewline
Estimates ( 2 ) & 0.8634 & -0.0916 & 0.0401 & -0.697 & 0.9687 & 0 & -0.8106 \tabularnewline
(p-val) & (1e-04 ) & (0.3516 ) & (0.5926 ) & (5e-04 ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 3 ) & 0.9044 & -0.0684 & 0 & -0.7403 & 0.9688 & 0 & -0.81 \tabularnewline
(p-val) & (0 ) & (0.4412 ) & (NA ) & (1e-04 ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 4 ) & 0.7749 & 0 & 0 & -0.6457 & 0.9664 & 0 & -0.8016 \tabularnewline
(p-val) & (0 ) & (NA ) & (NA ) & (0.0021 ) & (0 ) & (NA ) & (0 ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 6 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 7 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 8 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 9 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 10 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 11 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 12 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 13 ) & NA & NA & NA & NA & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105111&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]0.8738[/C][C]-0.0986[/C][C]0.0427[/C][C]-0.7068[/C][C]0.9217[/C][C]0.0377[/C][C]-0.7744[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.3306 )[/C][C](0.57 )[/C][C](4e-04 )[/C][C](0 )[/C][C](0.774 )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0.8634[/C][C]-0.0916[/C][C]0.0401[/C][C]-0.697[/C][C]0.9687[/C][C]0[/C][C]-0.8106[/C][/ROW]
[ROW][C](p-val)[/C][C](1e-04 )[/C][C](0.3516 )[/C][C](0.5926 )[/C][C](5e-04 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0.9044[/C][C]-0.0684[/C][C]0[/C][C]-0.7403[/C][C]0.9688[/C][C]0[/C][C]-0.81[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](0.4412 )[/C][C](NA )[/C][C](1e-04 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/C][C]0.7749[/C][C]0[/C][C]0[/C][C]-0.6457[/C][C]0.9664[/C][C]0[/C][C]-0.8016[/C][/ROW]
[ROW][C](p-val)[/C][C](0 )[/C][C](NA )[/C][C](NA )[/C][C](0.0021 )[/C][C](0 )[/C][C](NA )[/C][C](0 )[/C][/ROW]
[ROW][C]Estimates ( 5 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 6 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 7 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 8 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 9 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 10 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 11 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 12 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[ROW][C]Estimates ( 13 )[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][C](NA )[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105111&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105111&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 )0.8738-0.09860.0427-0.70680.92170.0377-0.7744
(p-val)(0 )(0.3306 )(0.57 )(4e-04 )(0 )(0.774 )(0 )
Estimates ( 2 )0.8634-0.09160.0401-0.6970.96870-0.8106
(p-val)(1e-04 )(0.3516 )(0.5926 )(5e-04 )(0 )(NA )(0 )
Estimates ( 3 )0.9044-0.06840-0.74030.96880-0.81
(p-val)(0 )(0.4412 )(NA )(1e-04 )(0 )(NA )(0 )
Estimates ( 4 )0.774900-0.64570.96640-0.8016
(p-val)(0 )(NA )(NA )(0.0021 )(0 )(NA )(0 )
Estimates ( 5 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(NA )(NA )(NA )
Estimates ( 6 )NANANANANANANA
(p-val)(NA )(NA )(NA )(NA )(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
0.00475056485124056
0.00247504793411891
-0.00106194350030167
0.00121505334849092
0.00211935984463230
0.00092752027248238
0.0052081627192718
-0.000346879257137005
-0.00180539253689171
-0.00169300870269297
-6.00523363523245e-05
3.13380687917076e-05
0.00352264681824106
0.00131895033717696
-0.00115428178780621
0.000188282742784928
-0.00192097066181708
7.94903499236243e-05
0.0036737576061425
0.00164335166815458
-0.00330823797550335
-0.000757803344470652
0.00146251209650006
-0.000656899524533367
0.00528429234036723
-0.000717666050761922
0.000430499881704567
-0.000868062978718721
-0.00267166461815923
0.000426611447526902
0.00304325309378902
0.00101160332389794
-0.00197611962153723
0.00238584454433812
5.42723328775363e-06
0.00102565628284530
0.00253318201189295
-0.00399723676257157
-0.00402893197019578
0.000291275786838034
0.00127970584043858
0.00107907567085112
0.00441138685832337
-0.00172587229588192
-0.00243392502173615
0.00073998690162352
0.00210889883066612
-0.00106221484138316
-0.00325971251248695
0.00191338777752094
-0.000243454830383293
0.00428699702675089
0.00447395627042045
-0.00297456229930305
-0.00281648966398898
-0.00486804212760008
0.00264595239499945
0.000178270406972129
-0.00114898301939344
0.000105006238111238
0.000253014006367018
0.00115980024949635
0.00109069626449593
0.000909002036861653
0.000261980845369229
-0.00244929651960932
-0.00402156001750216
-0.00194353895378591
0.00433847675093676
0.000933382417981402
0.000797500926038066
0.00143688135272116
-0.00103816133060778
0.00120550483636709
0.00282104292534209
0.000626918121061133
-0.000400283988088099
0.00175937086042091
-0.00172833697603232
0.000681220294795203
0.0050813140909742
-0.00267093749625112
0.00283313502823658
-0.00161141550021103
-0.00245020420763068
0.00191436217244747
0.00297909811006697
0.00514588592829155
0.00244132336740685
0.00167392160915974
-0.00333329917549936
0.00063891447754157
0.00112301645048264
0.000266679062839042
7.51517419149655e-05
-0.00243016757132318
0.00394978322346537
-0.000943549792870616
0.00169144124309149
-0.00492493855251241
0.000945219232961752
-0.00320070906301309
0.00088253012198922
-0.00031526382846575
0.00199461703853426
-0.00178406982842898
-0.00096940395169011
0.00116685812991443
0.000406920759502193
0.00387070681289998
0.00114313276726965
-0.00300694019352198
-0.0030010220053399
0.00266501766047088
-0.00117085545828032
0.00146032173575359
0.00173710977277532
-0.00293038785233396
0.00092732212120324
-0.000518903585650646
0.000175245903807454
0.000820469349048455
-0.000702137342047436
0.00283736497050179
-0.000189595808297198
-0.00100863400574725
0.000513566003004405
1.22857174850386e-05
-0.000458885812881207
0.00426864086456223
-0.00206237011715001
-0.00205550068670909
0.00100934758941353
0.00276323887422298
0.00420773927892034
-0.0028751326123077
0.000673251592790075
0.000897248924739407
0.00113360321135822
-0.000458068000943603
-0.00207456487113373
-0.00141763082954970
0.00227569144616662
0.000834503304850766
-0.00268572509260798
0.0023233885826124
-0.00246403101966315
0.00259547796779457
0.00177845327186514
-0.00132223856394053
0.000345445917432854
0.000965519637197693
-0.000868040590295883
-0.000110069358050079
0.00109492920450789
0.000891096995588172
-0.000500824176488164
0.00209137231875589
-0.00366572658013643
0.00205844790027419
-0.0040902327989501
-0.000508789230086955
0.00165466887491901
-0.000643285871851185
0.000211684090005044
0.00486812757501941
0.00479156629769871
0.00359122813521209
0.000152960278062861
0.00392432417233458
0.00379469461480864
-0.00169930171409849
0.00483106319763837
0.00205124870917911
0.00131217711944221
-0.00442191208577143
0.00202957055724382
0.000141072970312991
-0.00459215557432748
0.000963038884209305
-0.000752722907005557
-0.00110488403086444
-0.00720765566409188
0.000464363832536138
-0.00308259719781095
-0.00405587853708399
-0.00197281441120705
0.003046806927848
-0.00208392663037710
0.00171853484537252
-0.000264118312605648
0.00130425348656972
0.00128120677274489
0.00117920102643447
0.00164111409541065
0.000158065137854410
0.00201595954535217
-0.000364874226793661
-0.00172732691183730
0.00078594073288945
0.00270888243144978
0.000178569270360085
-0.000919279224580164

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.00475056485124056 \tabularnewline
0.00247504793411891 \tabularnewline
-0.00106194350030167 \tabularnewline
0.00121505334849092 \tabularnewline
0.00211935984463230 \tabularnewline
0.00092752027248238 \tabularnewline
0.0052081627192718 \tabularnewline
-0.000346879257137005 \tabularnewline
-0.00180539253689171 \tabularnewline
-0.00169300870269297 \tabularnewline
-6.00523363523245e-05 \tabularnewline
3.13380687917076e-05 \tabularnewline
0.00352264681824106 \tabularnewline
0.00131895033717696 \tabularnewline
-0.00115428178780621 \tabularnewline
0.000188282742784928 \tabularnewline
-0.00192097066181708 \tabularnewline
7.94903499236243e-05 \tabularnewline
0.0036737576061425 \tabularnewline
0.00164335166815458 \tabularnewline
-0.00330823797550335 \tabularnewline
-0.000757803344470652 \tabularnewline
0.00146251209650006 \tabularnewline
-0.000656899524533367 \tabularnewline
0.00528429234036723 \tabularnewline
-0.000717666050761922 \tabularnewline
0.000430499881704567 \tabularnewline
-0.000868062978718721 \tabularnewline
-0.00267166461815923 \tabularnewline
0.000426611447526902 \tabularnewline
0.00304325309378902 \tabularnewline
0.00101160332389794 \tabularnewline
-0.00197611962153723 \tabularnewline
0.00238584454433812 \tabularnewline
5.42723328775363e-06 \tabularnewline
0.00102565628284530 \tabularnewline
0.00253318201189295 \tabularnewline
-0.00399723676257157 \tabularnewline
-0.00402893197019578 \tabularnewline
0.000291275786838034 \tabularnewline
0.00127970584043858 \tabularnewline
0.00107907567085112 \tabularnewline
0.00441138685832337 \tabularnewline
-0.00172587229588192 \tabularnewline
-0.00243392502173615 \tabularnewline
0.00073998690162352 \tabularnewline
0.00210889883066612 \tabularnewline
-0.00106221484138316 \tabularnewline
-0.00325971251248695 \tabularnewline
0.00191338777752094 \tabularnewline
-0.000243454830383293 \tabularnewline
0.00428699702675089 \tabularnewline
0.00447395627042045 \tabularnewline
-0.00297456229930305 \tabularnewline
-0.00281648966398898 \tabularnewline
-0.00486804212760008 \tabularnewline
0.00264595239499945 \tabularnewline
0.000178270406972129 \tabularnewline
-0.00114898301939344 \tabularnewline
0.000105006238111238 \tabularnewline
0.000253014006367018 \tabularnewline
0.00115980024949635 \tabularnewline
0.00109069626449593 \tabularnewline
0.000909002036861653 \tabularnewline
0.000261980845369229 \tabularnewline
-0.00244929651960932 \tabularnewline
-0.00402156001750216 \tabularnewline
-0.00194353895378591 \tabularnewline
0.00433847675093676 \tabularnewline
0.000933382417981402 \tabularnewline
0.000797500926038066 \tabularnewline
0.00143688135272116 \tabularnewline
-0.00103816133060778 \tabularnewline
0.00120550483636709 \tabularnewline
0.00282104292534209 \tabularnewline
0.000626918121061133 \tabularnewline
-0.000400283988088099 \tabularnewline
0.00175937086042091 \tabularnewline
-0.00172833697603232 \tabularnewline
0.000681220294795203 \tabularnewline
0.0050813140909742 \tabularnewline
-0.00267093749625112 \tabularnewline
0.00283313502823658 \tabularnewline
-0.00161141550021103 \tabularnewline
-0.00245020420763068 \tabularnewline
0.00191436217244747 \tabularnewline
0.00297909811006697 \tabularnewline
0.00514588592829155 \tabularnewline
0.00244132336740685 \tabularnewline
0.00167392160915974 \tabularnewline
-0.00333329917549936 \tabularnewline
0.00063891447754157 \tabularnewline
0.00112301645048264 \tabularnewline
0.000266679062839042 \tabularnewline
7.51517419149655e-05 \tabularnewline
-0.00243016757132318 \tabularnewline
0.00394978322346537 \tabularnewline
-0.000943549792870616 \tabularnewline
0.00169144124309149 \tabularnewline
-0.00492493855251241 \tabularnewline
0.000945219232961752 \tabularnewline
-0.00320070906301309 \tabularnewline
0.00088253012198922 \tabularnewline
-0.00031526382846575 \tabularnewline
0.00199461703853426 \tabularnewline
-0.00178406982842898 \tabularnewline
-0.00096940395169011 \tabularnewline
0.00116685812991443 \tabularnewline
0.000406920759502193 \tabularnewline
0.00387070681289998 \tabularnewline
0.00114313276726965 \tabularnewline
-0.00300694019352198 \tabularnewline
-0.0030010220053399 \tabularnewline
0.00266501766047088 \tabularnewline
-0.00117085545828032 \tabularnewline
0.00146032173575359 \tabularnewline
0.00173710977277532 \tabularnewline
-0.00293038785233396 \tabularnewline
0.00092732212120324 \tabularnewline
-0.000518903585650646 \tabularnewline
0.000175245903807454 \tabularnewline
0.000820469349048455 \tabularnewline
-0.000702137342047436 \tabularnewline
0.00283736497050179 \tabularnewline
-0.000189595808297198 \tabularnewline
-0.00100863400574725 \tabularnewline
0.000513566003004405 \tabularnewline
1.22857174850386e-05 \tabularnewline
-0.000458885812881207 \tabularnewline
0.00426864086456223 \tabularnewline
-0.00206237011715001 \tabularnewline
-0.00205550068670909 \tabularnewline
0.00100934758941353 \tabularnewline
0.00276323887422298 \tabularnewline
0.00420773927892034 \tabularnewline
-0.0028751326123077 \tabularnewline
0.000673251592790075 \tabularnewline
0.000897248924739407 \tabularnewline
0.00113360321135822 \tabularnewline
-0.000458068000943603 \tabularnewline
-0.00207456487113373 \tabularnewline
-0.00141763082954970 \tabularnewline
0.00227569144616662 \tabularnewline
0.000834503304850766 \tabularnewline
-0.00268572509260798 \tabularnewline
0.0023233885826124 \tabularnewline
-0.00246403101966315 \tabularnewline
0.00259547796779457 \tabularnewline
0.00177845327186514 \tabularnewline
-0.00132223856394053 \tabularnewline
0.000345445917432854 \tabularnewline
0.000965519637197693 \tabularnewline
-0.000868040590295883 \tabularnewline
-0.000110069358050079 \tabularnewline
0.00109492920450789 \tabularnewline
0.000891096995588172 \tabularnewline
-0.000500824176488164 \tabularnewline
0.00209137231875589 \tabularnewline
-0.00366572658013643 \tabularnewline
0.00205844790027419 \tabularnewline
-0.0040902327989501 \tabularnewline
-0.000508789230086955 \tabularnewline
0.00165466887491901 \tabularnewline
-0.000643285871851185 \tabularnewline
0.000211684090005044 \tabularnewline
0.00486812757501941 \tabularnewline
0.00479156629769871 \tabularnewline
0.00359122813521209 \tabularnewline
0.000152960278062861 \tabularnewline
0.00392432417233458 \tabularnewline
0.00379469461480864 \tabularnewline
-0.00169930171409849 \tabularnewline
0.00483106319763837 \tabularnewline
0.00205124870917911 \tabularnewline
0.00131217711944221 \tabularnewline
-0.00442191208577143 \tabularnewline
0.00202957055724382 \tabularnewline
0.000141072970312991 \tabularnewline
-0.00459215557432748 \tabularnewline
0.000963038884209305 \tabularnewline
-0.000752722907005557 \tabularnewline
-0.00110488403086444 \tabularnewline
-0.00720765566409188 \tabularnewline
0.000464363832536138 \tabularnewline
-0.00308259719781095 \tabularnewline
-0.00405587853708399 \tabularnewline
-0.00197281441120705 \tabularnewline
0.003046806927848 \tabularnewline
-0.00208392663037710 \tabularnewline
0.00171853484537252 \tabularnewline
-0.000264118312605648 \tabularnewline
0.00130425348656972 \tabularnewline
0.00128120677274489 \tabularnewline
0.00117920102643447 \tabularnewline
0.00164111409541065 \tabularnewline
0.000158065137854410 \tabularnewline
0.00201595954535217 \tabularnewline
-0.000364874226793661 \tabularnewline
-0.00172732691183730 \tabularnewline
0.00078594073288945 \tabularnewline
0.00270888243144978 \tabularnewline
0.000178569270360085 \tabularnewline
-0.000919279224580164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105111&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.00475056485124056[/C][/ROW]
[ROW][C]0.00247504793411891[/C][/ROW]
[ROW][C]-0.00106194350030167[/C][/ROW]
[ROW][C]0.00121505334849092[/C][/ROW]
[ROW][C]0.00211935984463230[/C][/ROW]
[ROW][C]0.00092752027248238[/C][/ROW]
[ROW][C]0.0052081627192718[/C][/ROW]
[ROW][C]-0.000346879257137005[/C][/ROW]
[ROW][C]-0.00180539253689171[/C][/ROW]
[ROW][C]-0.00169300870269297[/C][/ROW]
[ROW][C]-6.00523363523245e-05[/C][/ROW]
[ROW][C]3.13380687917076e-05[/C][/ROW]
[ROW][C]0.00352264681824106[/C][/ROW]
[ROW][C]0.00131895033717696[/C][/ROW]
[ROW][C]-0.00115428178780621[/C][/ROW]
[ROW][C]0.000188282742784928[/C][/ROW]
[ROW][C]-0.00192097066181708[/C][/ROW]
[ROW][C]7.94903499236243e-05[/C][/ROW]
[ROW][C]0.0036737576061425[/C][/ROW]
[ROW][C]0.00164335166815458[/C][/ROW]
[ROW][C]-0.00330823797550335[/C][/ROW]
[ROW][C]-0.000757803344470652[/C][/ROW]
[ROW][C]0.00146251209650006[/C][/ROW]
[ROW][C]-0.000656899524533367[/C][/ROW]
[ROW][C]0.00528429234036723[/C][/ROW]
[ROW][C]-0.000717666050761922[/C][/ROW]
[ROW][C]0.000430499881704567[/C][/ROW]
[ROW][C]-0.000868062978718721[/C][/ROW]
[ROW][C]-0.00267166461815923[/C][/ROW]
[ROW][C]0.000426611447526902[/C][/ROW]
[ROW][C]0.00304325309378902[/C][/ROW]
[ROW][C]0.00101160332389794[/C][/ROW]
[ROW][C]-0.00197611962153723[/C][/ROW]
[ROW][C]0.00238584454433812[/C][/ROW]
[ROW][C]5.42723328775363e-06[/C][/ROW]
[ROW][C]0.00102565628284530[/C][/ROW]
[ROW][C]0.00253318201189295[/C][/ROW]
[ROW][C]-0.00399723676257157[/C][/ROW]
[ROW][C]-0.00402893197019578[/C][/ROW]
[ROW][C]0.000291275786838034[/C][/ROW]
[ROW][C]0.00127970584043858[/C][/ROW]
[ROW][C]0.00107907567085112[/C][/ROW]
[ROW][C]0.00441138685832337[/C][/ROW]
[ROW][C]-0.00172587229588192[/C][/ROW]
[ROW][C]-0.00243392502173615[/C][/ROW]
[ROW][C]0.00073998690162352[/C][/ROW]
[ROW][C]0.00210889883066612[/C][/ROW]
[ROW][C]-0.00106221484138316[/C][/ROW]
[ROW][C]-0.00325971251248695[/C][/ROW]
[ROW][C]0.00191338777752094[/C][/ROW]
[ROW][C]-0.000243454830383293[/C][/ROW]
[ROW][C]0.00428699702675089[/C][/ROW]
[ROW][C]0.00447395627042045[/C][/ROW]
[ROW][C]-0.00297456229930305[/C][/ROW]
[ROW][C]-0.00281648966398898[/C][/ROW]
[ROW][C]-0.00486804212760008[/C][/ROW]
[ROW][C]0.00264595239499945[/C][/ROW]
[ROW][C]0.000178270406972129[/C][/ROW]
[ROW][C]-0.00114898301939344[/C][/ROW]
[ROW][C]0.000105006238111238[/C][/ROW]
[ROW][C]0.000253014006367018[/C][/ROW]
[ROW][C]0.00115980024949635[/C][/ROW]
[ROW][C]0.00109069626449593[/C][/ROW]
[ROW][C]0.000909002036861653[/C][/ROW]
[ROW][C]0.000261980845369229[/C][/ROW]
[ROW][C]-0.00244929651960932[/C][/ROW]
[ROW][C]-0.00402156001750216[/C][/ROW]
[ROW][C]-0.00194353895378591[/C][/ROW]
[ROW][C]0.00433847675093676[/C][/ROW]
[ROW][C]0.000933382417981402[/C][/ROW]
[ROW][C]0.000797500926038066[/C][/ROW]
[ROW][C]0.00143688135272116[/C][/ROW]
[ROW][C]-0.00103816133060778[/C][/ROW]
[ROW][C]0.00120550483636709[/C][/ROW]
[ROW][C]0.00282104292534209[/C][/ROW]
[ROW][C]0.000626918121061133[/C][/ROW]
[ROW][C]-0.000400283988088099[/C][/ROW]
[ROW][C]0.00175937086042091[/C][/ROW]
[ROW][C]-0.00172833697603232[/C][/ROW]
[ROW][C]0.000681220294795203[/C][/ROW]
[ROW][C]0.0050813140909742[/C][/ROW]
[ROW][C]-0.00267093749625112[/C][/ROW]
[ROW][C]0.00283313502823658[/C][/ROW]
[ROW][C]-0.00161141550021103[/C][/ROW]
[ROW][C]-0.00245020420763068[/C][/ROW]
[ROW][C]0.00191436217244747[/C][/ROW]
[ROW][C]0.00297909811006697[/C][/ROW]
[ROW][C]0.00514588592829155[/C][/ROW]
[ROW][C]0.00244132336740685[/C][/ROW]
[ROW][C]0.00167392160915974[/C][/ROW]
[ROW][C]-0.00333329917549936[/C][/ROW]
[ROW][C]0.00063891447754157[/C][/ROW]
[ROW][C]0.00112301645048264[/C][/ROW]
[ROW][C]0.000266679062839042[/C][/ROW]
[ROW][C]7.51517419149655e-05[/C][/ROW]
[ROW][C]-0.00243016757132318[/C][/ROW]
[ROW][C]0.00394978322346537[/C][/ROW]
[ROW][C]-0.000943549792870616[/C][/ROW]
[ROW][C]0.00169144124309149[/C][/ROW]
[ROW][C]-0.00492493855251241[/C][/ROW]
[ROW][C]0.000945219232961752[/C][/ROW]
[ROW][C]-0.00320070906301309[/C][/ROW]
[ROW][C]0.00088253012198922[/C][/ROW]
[ROW][C]-0.00031526382846575[/C][/ROW]
[ROW][C]0.00199461703853426[/C][/ROW]
[ROW][C]-0.00178406982842898[/C][/ROW]
[ROW][C]-0.00096940395169011[/C][/ROW]
[ROW][C]0.00116685812991443[/C][/ROW]
[ROW][C]0.000406920759502193[/C][/ROW]
[ROW][C]0.00387070681289998[/C][/ROW]
[ROW][C]0.00114313276726965[/C][/ROW]
[ROW][C]-0.00300694019352198[/C][/ROW]
[ROW][C]-0.0030010220053399[/C][/ROW]
[ROW][C]0.00266501766047088[/C][/ROW]
[ROW][C]-0.00117085545828032[/C][/ROW]
[ROW][C]0.00146032173575359[/C][/ROW]
[ROW][C]0.00173710977277532[/C][/ROW]
[ROW][C]-0.00293038785233396[/C][/ROW]
[ROW][C]0.00092732212120324[/C][/ROW]
[ROW][C]-0.000518903585650646[/C][/ROW]
[ROW][C]0.000175245903807454[/C][/ROW]
[ROW][C]0.000820469349048455[/C][/ROW]
[ROW][C]-0.000702137342047436[/C][/ROW]
[ROW][C]0.00283736497050179[/C][/ROW]
[ROW][C]-0.000189595808297198[/C][/ROW]
[ROW][C]-0.00100863400574725[/C][/ROW]
[ROW][C]0.000513566003004405[/C][/ROW]
[ROW][C]1.22857174850386e-05[/C][/ROW]
[ROW][C]-0.000458885812881207[/C][/ROW]
[ROW][C]0.00426864086456223[/C][/ROW]
[ROW][C]-0.00206237011715001[/C][/ROW]
[ROW][C]-0.00205550068670909[/C][/ROW]
[ROW][C]0.00100934758941353[/C][/ROW]
[ROW][C]0.00276323887422298[/C][/ROW]
[ROW][C]0.00420773927892034[/C][/ROW]
[ROW][C]-0.0028751326123077[/C][/ROW]
[ROW][C]0.000673251592790075[/C][/ROW]
[ROW][C]0.000897248924739407[/C][/ROW]
[ROW][C]0.00113360321135822[/C][/ROW]
[ROW][C]-0.000458068000943603[/C][/ROW]
[ROW][C]-0.00207456487113373[/C][/ROW]
[ROW][C]-0.00141763082954970[/C][/ROW]
[ROW][C]0.00227569144616662[/C][/ROW]
[ROW][C]0.000834503304850766[/C][/ROW]
[ROW][C]-0.00268572509260798[/C][/ROW]
[ROW][C]0.0023233885826124[/C][/ROW]
[ROW][C]-0.00246403101966315[/C][/ROW]
[ROW][C]0.00259547796779457[/C][/ROW]
[ROW][C]0.00177845327186514[/C][/ROW]
[ROW][C]-0.00132223856394053[/C][/ROW]
[ROW][C]0.000345445917432854[/C][/ROW]
[ROW][C]0.000965519637197693[/C][/ROW]
[ROW][C]-0.000868040590295883[/C][/ROW]
[ROW][C]-0.000110069358050079[/C][/ROW]
[ROW][C]0.00109492920450789[/C][/ROW]
[ROW][C]0.000891096995588172[/C][/ROW]
[ROW][C]-0.000500824176488164[/C][/ROW]
[ROW][C]0.00209137231875589[/C][/ROW]
[ROW][C]-0.00366572658013643[/C][/ROW]
[ROW][C]0.00205844790027419[/C][/ROW]
[ROW][C]-0.0040902327989501[/C][/ROW]
[ROW][C]-0.000508789230086955[/C][/ROW]
[ROW][C]0.00165466887491901[/C][/ROW]
[ROW][C]-0.000643285871851185[/C][/ROW]
[ROW][C]0.000211684090005044[/C][/ROW]
[ROW][C]0.00486812757501941[/C][/ROW]
[ROW][C]0.00479156629769871[/C][/ROW]
[ROW][C]0.00359122813521209[/C][/ROW]
[ROW][C]0.000152960278062861[/C][/ROW]
[ROW][C]0.00392432417233458[/C][/ROW]
[ROW][C]0.00379469461480864[/C][/ROW]
[ROW][C]-0.00169930171409849[/C][/ROW]
[ROW][C]0.00483106319763837[/C][/ROW]
[ROW][C]0.00205124870917911[/C][/ROW]
[ROW][C]0.00131217711944221[/C][/ROW]
[ROW][C]-0.00442191208577143[/C][/ROW]
[ROW][C]0.00202957055724382[/C][/ROW]
[ROW][C]0.000141072970312991[/C][/ROW]
[ROW][C]-0.00459215557432748[/C][/ROW]
[ROW][C]0.000963038884209305[/C][/ROW]
[ROW][C]-0.000752722907005557[/C][/ROW]
[ROW][C]-0.00110488403086444[/C][/ROW]
[ROW][C]-0.00720765566409188[/C][/ROW]
[ROW][C]0.000464363832536138[/C][/ROW]
[ROW][C]-0.00308259719781095[/C][/ROW]
[ROW][C]-0.00405587853708399[/C][/ROW]
[ROW][C]-0.00197281441120705[/C][/ROW]
[ROW][C]0.003046806927848[/C][/ROW]
[ROW][C]-0.00208392663037710[/C][/ROW]
[ROW][C]0.00171853484537252[/C][/ROW]
[ROW][C]-0.000264118312605648[/C][/ROW]
[ROW][C]0.00130425348656972[/C][/ROW]
[ROW][C]0.00128120677274489[/C][/ROW]
[ROW][C]0.00117920102643447[/C][/ROW]
[ROW][C]0.00164111409541065[/C][/ROW]
[ROW][C]0.000158065137854410[/C][/ROW]
[ROW][C]0.00201595954535217[/C][/ROW]
[ROW][C]-0.000364874226793661[/C][/ROW]
[ROW][C]-0.00172732691183730[/C][/ROW]
[ROW][C]0.00078594073288945[/C][/ROW]
[ROW][C]0.00270888243144978[/C][/ROW]
[ROW][C]0.000178569270360085[/C][/ROW]
[ROW][C]-0.000919279224580164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105111&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105111&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
0.00475056485124056
0.00247504793411891
-0.00106194350030167
0.00121505334849092
0.00211935984463230
0.00092752027248238
0.0052081627192718
-0.000346879257137005
-0.00180539253689171
-0.00169300870269297
-6.00523363523245e-05
3.13380687917076e-05
0.00352264681824106
0.00131895033717696
-0.00115428178780621
0.000188282742784928
-0.00192097066181708
7.94903499236243e-05
0.0036737576061425
0.00164335166815458
-0.00330823797550335
-0.000757803344470652
0.00146251209650006
-0.000656899524533367
0.00528429234036723
-0.000717666050761922
0.000430499881704567
-0.000868062978718721
-0.00267166461815923
0.000426611447526902
0.00304325309378902
0.00101160332389794
-0.00197611962153723
0.00238584454433812
5.42723328775363e-06
0.00102565628284530
0.00253318201189295
-0.00399723676257157
-0.00402893197019578
0.000291275786838034
0.00127970584043858
0.00107907567085112
0.00441138685832337
-0.00172587229588192
-0.00243392502173615
0.00073998690162352
0.00210889883066612
-0.00106221484138316
-0.00325971251248695
0.00191338777752094
-0.000243454830383293
0.00428699702675089
0.00447395627042045
-0.00297456229930305
-0.00281648966398898
-0.00486804212760008
0.00264595239499945
0.000178270406972129
-0.00114898301939344
0.000105006238111238
0.000253014006367018
0.00115980024949635
0.00109069626449593
0.000909002036861653
0.000261980845369229
-0.00244929651960932
-0.00402156001750216
-0.00194353895378591
0.00433847675093676
0.000933382417981402
0.000797500926038066
0.00143688135272116
-0.00103816133060778
0.00120550483636709
0.00282104292534209
0.000626918121061133
-0.000400283988088099
0.00175937086042091
-0.00172833697603232
0.000681220294795203
0.0050813140909742
-0.00267093749625112
0.00283313502823658
-0.00161141550021103
-0.00245020420763068
0.00191436217244747
0.00297909811006697
0.00514588592829155
0.00244132336740685
0.00167392160915974
-0.00333329917549936
0.00063891447754157
0.00112301645048264
0.000266679062839042
7.51517419149655e-05
-0.00243016757132318
0.00394978322346537
-0.000943549792870616
0.00169144124309149
-0.00492493855251241
0.000945219232961752
-0.00320070906301309
0.00088253012198922
-0.00031526382846575
0.00199461703853426
-0.00178406982842898
-0.00096940395169011
0.00116685812991443
0.000406920759502193
0.00387070681289998
0.00114313276726965
-0.00300694019352198
-0.0030010220053399
0.00266501766047088
-0.00117085545828032
0.00146032173575359
0.00173710977277532
-0.00293038785233396
0.00092732212120324
-0.000518903585650646
0.000175245903807454
0.000820469349048455
-0.000702137342047436
0.00283736497050179
-0.000189595808297198
-0.00100863400574725
0.000513566003004405
1.22857174850386e-05
-0.000458885812881207
0.00426864086456223
-0.00206237011715001
-0.00205550068670909
0.00100934758941353
0.00276323887422298
0.00420773927892034
-0.0028751326123077
0.000673251592790075
0.000897248924739407
0.00113360321135822
-0.000458068000943603
-0.00207456487113373
-0.00141763082954970
0.00227569144616662
0.000834503304850766
-0.00268572509260798
0.0023233885826124
-0.00246403101966315
0.00259547796779457
0.00177845327186514
-0.00132223856394053
0.000345445917432854
0.000965519637197693
-0.000868040590295883
-0.000110069358050079
0.00109492920450789
0.000891096995588172
-0.000500824176488164
0.00209137231875589
-0.00366572658013643
0.00205844790027419
-0.0040902327989501
-0.000508789230086955
0.00165466887491901
-0.000643285871851185
0.000211684090005044
0.00486812757501941
0.00479156629769871
0.00359122813521209
0.000152960278062861
0.00392432417233458
0.00379469461480864
-0.00169930171409849
0.00483106319763837
0.00205124870917911
0.00131217711944221
-0.00442191208577143
0.00202957055724382
0.000141072970312991
-0.00459215557432748
0.000963038884209305
-0.000752722907005557
-0.00110488403086444
-0.00720765566409188
0.000464363832536138
-0.00308259719781095
-0.00405587853708399
-0.00197281441120705
0.003046806927848
-0.00208392663037710
0.00171853484537252
-0.000264118312605648
0.00130425348656972
0.00128120677274489
0.00117920102643447
0.00164111409541065
0.000158065137854410
0.00201595954535217
-0.000364874226793661
-0.00172732691183730
0.00078594073288945
0.00270888243144978
0.000178569270360085
-0.000919279224580164


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = FALSE ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
R code (references can be found in the software module):
library(lattice)
if (par1 == 'TRUE') par1 <- TRUE
if (par1 == 'FALSE') par1 <- FALSE
par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
par3 <- as.numeric(par3) #degree of non-seasonal differencing
par4 <- as.numeric(par4) #degree of seasonal differencing
par5 <- 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')