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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 computationFri, 23 Dec 2011 09:03:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/23/t1324649053xzmf7etohnbv5zk.htm/, Retrieved Mon, 29 Apr 2024 19:36:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160421, Retrieved Mon, 29 Apr 2024 19:36:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Backward Selection] [Unemployment] [2010-11-29 17:10:28] [b98453cac15ba1066b407e146608df68]
-           [ARIMA Backward Selection] [ws9 error] [2011-12-05 18:13:45] [8501ca4b76170905b8a207a77f626994]
- R P         [ARIMA Backward Selection] [ws9 arima] [2011-12-06 21:08:38] [8501ca4b76170905b8a207a77f626994]
-               [ARIMA Backward Selection] [Paper Deel 2 Arim...] [2011-12-22 14:22:54] [8501ca4b76170905b8a207a77f626994]
-   PD              [ARIMA Backward Selection] [Paper: ARIMA Back...] [2011-12-23 14:03:19] [3e64eea457df40fcb7af8f28e1ee6256] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
24.90
25.06
25.10
24.92
25.46
25.89
25.39
25.38
25.25
24.88
25.00
25.00
24.07
23.60
23.18
23.25
23.04
22.77
22.25
22.41
22.50
22.91
22.88
21.69
21.19
21.56
22.00
22.13
22.27
22.30
21.94
22.40
22.77
22.90
23.03
23.05
22.41
22.26
21.90
22.01
22.62
22.76
23.40
23.63
24.05
23.82
23.71
23.95
23.61
23.98
23.56
23.99
24.33
24.48
24.31
24.38
24.63
25.54
25.75
25.73
25.85
25.78
25.86
26.86
27.36
27.38
26.58
27.65
27.73
27.18
27.32
27.30
26.90
26.70
26.75
26.41
26.29
27.51
27.91
27.70
27.28
28.25
27.62
27.30
25.94
24.99
25.50
24.42
26.58
25.84
26.76
26.74
26.68
25.55
26.40
25.19
23.94
24.20
24.20
23.07
24.07
25.02
24.65
24.68
24.63
24.49
25.05
24.31
23.90
23.68
24.50
25.22
25.48
26.00
26.07
26.06
26.22
26.70
27.20
26.77
26.11
25.43
24.99
25.51
24.00
23.86
22.96
23.41
23.17
24.12
23.87
24.27
24.40
24.16
25.15
25.09
24.60
24.33
24.14
24.36
25.40
26.15
26.77
26.94
26.33
26.24
26.23
25.88
27.00
26.91
27.15
27.78
28.73
28.83
28.68
27.56
27.15
27.41
27.47
28.76
28.47
27.94
27.23
27.01
26.15
26.11
27.20
27.36
27.33
27.43
28.92
29.45
29.01
29.25
29.14
29.64
30.40
30.62
31.25
31.75
31.30
30.70
31.03
31.46
31.28
31.03
30.95
31.17
31.29
31.91
32.10
31.71
31.90
32.02
32.65
33.77
33.51
34.26
34.21
34.13
34.73
34.73
34.57
34.80
33.98
34.40
34.21
34.61
35.25
35.23
35.00
34.52
33.82
34.35
34.81
34.96
36.69
36.42
36.44
37.41
36.40
36.15
35.78
36.95
36.14
36.36
37.31
37.58
38.00
37.23
37.00
37.87
37.70
36.17
36.56
37.70
38.77
39.02
39.88
39.56
38.52
37.20
38.58
39.41
39.08
38.81
38.73
38.70
39.23
39.82
39.97
40.37
39.54
39.21
39.07
39.78
39.40
38.92

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160421&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160421&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 time3 seconds
R Server'AstonUniversity' @ aston.wessa.net






ARIMA Parameter Estimation and Backward Selection
Iterationar1ar2sar1
Estimates ( 1 )-0.01720.02230.1287
(p-val)(0.786 )(0.7216 )(0.0411 )
Estimates ( 2 )00.02230.1258
(p-val)(NA )(0.7208 )(0.0429 )
Estimates ( 3 )000.1239
(p-val)(NA )(NA )(0.0453 )
Estimates ( 4 )NANANA
(p-val)(NA )(NA )(NA )
Estimates ( 5 )NANANA
(p-val)(NA )(NA )(NA )

\begin{tabular}{lllllllll}
\hline
ARIMA Parameter Estimation and Backward Selection \tabularnewline
Iteration & ar1 & ar2 & sar1 \tabularnewline
Estimates ( 1 ) & -0.0172 & 0.0223 & 0.1287 \tabularnewline
(p-val) & (0.786 ) & (0.7216 ) & (0.0411 ) \tabularnewline
Estimates ( 2 ) & 0 & 0.0223 & 0.1258 \tabularnewline
(p-val) & (NA ) & (0.7208 ) & (0.0429 ) \tabularnewline
Estimates ( 3 ) & 0 & 0 & 0.1239 \tabularnewline
(p-val) & (NA ) & (NA ) & (0.0453 ) \tabularnewline
Estimates ( 4 ) & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) \tabularnewline
Estimates ( 5 ) & NA & NA & NA \tabularnewline
(p-val) & (NA ) & (NA ) & (NA ) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160421&T=1

[TABLE]
[ROW][C]ARIMA Parameter Estimation and Backward Selection[/C][/ROW]
[ROW][C]Iteration[/C][C]ar1[/C][C]ar2[/C][C]sar1[/C][/ROW]
[ROW][C]Estimates ( 1 )[/C][C]-0.0172[/C][C]0.0223[/C][C]0.1287[/C][/ROW]
[ROW][C](p-val)[/C][C](0.786 )[/C][C](0.7216 )[/C][C](0.0411 )[/C][/ROW]
[ROW][C]Estimates ( 2 )[/C][C]0[/C][C]0.0223[/C][C]0.1258[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](0.7208 )[/C][C](0.0429 )[/C][/ROW]
[ROW][C]Estimates ( 3 )[/C][C]0[/C][C]0[/C][C]0.1239[/C][/ROW]
[ROW][C](p-val)[/C][C](NA )[/C][C](NA )[/C][C](0.0453 )[/C][/ROW]
[ROW][C]Estimates ( 4 )[/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][/ROW]
[ROW][C]Estimates ( 5 )[/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][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160421&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160421&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
Iterationar1ar2sar1
Estimates ( 1 )-0.01720.02230.1287
(p-val)(0.786 )(0.7216 )(0.0411 )
Estimates ( 2 )00.02230.1258
(p-val)(NA )(0.7208 )(0.0429 )
Estimates ( 3 )000.1239
(p-val)(NA )(NA )(0.0453 )
Estimates ( 4 )NANANA
(p-val)(NA )(NA )(NA )
Estimates ( 5 )NANANA
(p-val)(NA )(NA )(NA )






Estimated ARIMA Residuals
Value
0.00321486616938156
0.00635268854201554
0.00158176224292197
-0.00728190928055009
0.0212322918846433
0.0167746476139755
-0.0198215128598677
-0.000761906266485178
-0.00466242640691158
-0.0146363127304741
0.00488701710228592
0.000309237856741927
-0.0377200880360597
-0.0205247320657338
-0.0173240076586746
0.00437900666494617
-0.0113643146461864
-0.0139821862992827
-0.0203860210629919
0.00752516023291124
0.00511514796922667
0.0197538656096163
-0.00201949404637883
-0.0538566345666434
-0.0185107284671553
0.020983718512475
0.0228757903696535
0.00507040452999372
0.00694594267206939
0.00270582315044909
-0.0135357026216257
0.0197850389677095
0.0161773726343427
0.00297828700473966
0.0054709771941518
0.00751002398657796
-0.0253550514795195
-0.009062760581585
-0.0182825109123385
0.00446780180637193
0.026965251060176
0.00590545756088409
0.0291857297986564
0.00703707501980973
0.0148920942626869
-0.0104856916579368
-0.00568816872662893
0.0101928518707152
-0.0106367866170735
0.0161720585354502
-0.0153786771667276
0.0170903392912223
0.0109832749938495
0.00498030897836837
-0.0106943698880915
0.00152508684384619
0.00821957584918115
0.0374526163031148
0.00859262682253593
-0.0028811393073025
0.00625554345619307
-0.00462188082548218
0.00517687363415715
0.0357700340520172
0.0165548833044287
-0.000838962657226227
-0.0291496154830362
0.0391059482858703
0.00224859236396429
-0.0254703901346132
0.00407173755425148
-8.52346475854562e-05
-0.0154374297445959
-0.00710746973912443
0.00182391911649746
-0.0174050594925484
-0.00690712817517445
0.0456613088230593
0.0183189890919394
-0.0135279986118039
-0.0160477061042965
0.0377390848029247
-0.0228501869919558
-0.0123979716339994
-0.0487257384704988
-0.0361135213004145
0.0210672165092541
-0.0408546316956701
0.084883456203317
-0.033010468714535
0.0312630009080394
0.000960400782011633
-0.00106535073719615
-0.0476762909089525
0.0355708013777278
-0.0443863675154798
-0.0452630267988256
0.0165101419203807
-0.0015480002617593
-0.0427221822424283
0.0318288614354148
0.0432072807307505
-0.0200087395652214
0.000366466095043467
-0.00131439311350743
-0.000286038262189873
0.0185314253834188
-0.0240788775205749
-0.011020366998374
-0.0100684467037505
0.034279217952988
0.0352160666665448
0.00415873895426238
0.0145524341629925
0.00445284017289998
-0.00087911886705239
0.00627409018093109
0.0188700880959196
0.0155671438825596
-0.0125845207358521
-0.0231748287063334
-0.0249539285987421
-0.0212260700284032
0.0175149373589692
-0.0618213514746822
-0.00877020855688114
-0.0373964458098009
0.0196453908792444
-0.010208545115948
0.0374665785649998
-0.0125053127094837
0.0177764659966942
0.00876695884008688
-0.00698138960594941
0.0421655026517971
-0.00483240707890766
-0.012993934098054
-0.0101891893499407
-0.0027344562961438
0.00686083900040388
0.0431700172897673
0.0238975133695183
0.0237805232430346
0.00370290370361753
-0.0241277817334609
-0.0022753562374175
-0.00490607979969384
-0.0130841790842614
0.0449685711768396
-0.00165738907047713
0.00886358233872071
0.0218417124922883
0.0281465565198036
-0.000672547736432361
-0.00879752702326364
-0.0406266782052846
-0.0119251912762987
0.0108690232728445
0.00250495149447204
0.0473582514152284
-0.0155135798629654
-0.0194342599102774
-0.0265115247013308
-0.0105872279802588
-0.0359877153885506
-0.00172223847637768
0.0423719124258156
0.0109196469049415
-0.000139889658389308
0.00221056506297855
0.0526034484945333
0.0123333296805171
-0.0149537992930109
0.0103259797793409
-0.000222333504361218
0.0177965761240893
0.0293997826657046
0.0070005662346758
0.0145652055998906
0.0149702571456381
-0.0144765975189818
-0.0201528938739596
0.00435404457556901
0.0119206619105734
-0.00393470073239699
-0.00931713205046564
-0.00202168608685327
0.00514548939650375
0.000704944356502894
0.0186034747465066
0.00336016879648003
-0.0146385309468463
0.00769407376897128
0.00650692481575547
0.0179657539386284
0.0318586424277529
-0.0074123156545105
0.0224293057079873
-0.000979281171639932
-0.00374909018321216
0.016969148212662
-0.00239581587551559
-0.00574277639963853
0.008223838468136
-0.0244768876562691
0.0116297202193972
-0.00744001507068773
0.0071183782697277
0.0194734915429982
-0.00351660611554459
-0.00679716970838818
-0.0134398444213737
-0.022536397530477
0.0158515201639834
0.014390024023166
0.0031184593011752
0.0509889737593141
-0.00900876477301251
9.99225660551601e-05
0.0250082506998601
-0.0297018304718999
-0.00737453165491915
-0.00880123403514181
0.0340658851493796
-0.0193770987590839
0.00335562989904984
0.0245563449445541
0.00657788819359133
0.00450012424150035
-0.0196911719991439
-0.00637857031687555
0.0203733111974522
-0.000916564806809762
-0.0410084434487924
0.0120423532475484
0.0275639908244012
0.0305062851865836
0.00506880327946204
0.01786901841283
-0.00908992913399778
-0.0284533590060965
-0.0320936604801024
0.0378309671004017
0.0190834510694514
-0.00867379178398282
-0.00213173027385685
-0.003237287820608
-0.00459870230812346
0.0101580848899194
0.0142226160778352
0.000792518605555397
0.0106557954401084
-0.0174458289456836
-0.00424007510529581
-0.00776950561932123
0.0154211928140162
-0.00835854425796005
-0.0117279418091893

\begin{tabular}{lllllllll}
\hline
Estimated ARIMA Residuals \tabularnewline
Value \tabularnewline
0.00321486616938156 \tabularnewline
0.00635268854201554 \tabularnewline
0.00158176224292197 \tabularnewline
-0.00728190928055009 \tabularnewline
0.0212322918846433 \tabularnewline
0.0167746476139755 \tabularnewline
-0.0198215128598677 \tabularnewline
-0.000761906266485178 \tabularnewline
-0.00466242640691158 \tabularnewline
-0.0146363127304741 \tabularnewline
0.00488701710228592 \tabularnewline
0.000309237856741927 \tabularnewline
-0.0377200880360597 \tabularnewline
-0.0205247320657338 \tabularnewline
-0.0173240076586746 \tabularnewline
0.00437900666494617 \tabularnewline
-0.0113643146461864 \tabularnewline
-0.0139821862992827 \tabularnewline
-0.0203860210629919 \tabularnewline
0.00752516023291124 \tabularnewline
0.00511514796922667 \tabularnewline
0.0197538656096163 \tabularnewline
-0.00201949404637883 \tabularnewline
-0.0538566345666434 \tabularnewline
-0.0185107284671553 \tabularnewline
0.020983718512475 \tabularnewline
0.0228757903696535 \tabularnewline
0.00507040452999372 \tabularnewline
0.00694594267206939 \tabularnewline
0.00270582315044909 \tabularnewline
-0.0135357026216257 \tabularnewline
0.0197850389677095 \tabularnewline
0.0161773726343427 \tabularnewline
0.00297828700473966 \tabularnewline
0.0054709771941518 \tabularnewline
0.00751002398657796 \tabularnewline
-0.0253550514795195 \tabularnewline
-0.009062760581585 \tabularnewline
-0.0182825109123385 \tabularnewline
0.00446780180637193 \tabularnewline
0.026965251060176 \tabularnewline
0.00590545756088409 \tabularnewline
0.0291857297986564 \tabularnewline
0.00703707501980973 \tabularnewline
0.0148920942626869 \tabularnewline
-0.0104856916579368 \tabularnewline
-0.00568816872662893 \tabularnewline
0.0101928518707152 \tabularnewline
-0.0106367866170735 \tabularnewline
0.0161720585354502 \tabularnewline
-0.0153786771667276 \tabularnewline
0.0170903392912223 \tabularnewline
0.0109832749938495 \tabularnewline
0.00498030897836837 \tabularnewline
-0.0106943698880915 \tabularnewline
0.00152508684384619 \tabularnewline
0.00821957584918115 \tabularnewline
0.0374526163031148 \tabularnewline
0.00859262682253593 \tabularnewline
-0.0028811393073025 \tabularnewline
0.00625554345619307 \tabularnewline
-0.00462188082548218 \tabularnewline
0.00517687363415715 \tabularnewline
0.0357700340520172 \tabularnewline
0.0165548833044287 \tabularnewline
-0.000838962657226227 \tabularnewline
-0.0291496154830362 \tabularnewline
0.0391059482858703 \tabularnewline
0.00224859236396429 \tabularnewline
-0.0254703901346132 \tabularnewline
0.00407173755425148 \tabularnewline
-8.52346475854562e-05 \tabularnewline
-0.0154374297445959 \tabularnewline
-0.00710746973912443 \tabularnewline
0.00182391911649746 \tabularnewline
-0.0174050594925484 \tabularnewline
-0.00690712817517445 \tabularnewline
0.0456613088230593 \tabularnewline
0.0183189890919394 \tabularnewline
-0.0135279986118039 \tabularnewline
-0.0160477061042965 \tabularnewline
0.0377390848029247 \tabularnewline
-0.0228501869919558 \tabularnewline
-0.0123979716339994 \tabularnewline
-0.0487257384704988 \tabularnewline
-0.0361135213004145 \tabularnewline
0.0210672165092541 \tabularnewline
-0.0408546316956701 \tabularnewline
0.084883456203317 \tabularnewline
-0.033010468714535 \tabularnewline
0.0312630009080394 \tabularnewline
0.000960400782011633 \tabularnewline
-0.00106535073719615 \tabularnewline
-0.0476762909089525 \tabularnewline
0.0355708013777278 \tabularnewline
-0.0443863675154798 \tabularnewline
-0.0452630267988256 \tabularnewline
0.0165101419203807 \tabularnewline
-0.0015480002617593 \tabularnewline
-0.0427221822424283 \tabularnewline
0.0318288614354148 \tabularnewline
0.0432072807307505 \tabularnewline
-0.0200087395652214 \tabularnewline
0.000366466095043467 \tabularnewline
-0.00131439311350743 \tabularnewline
-0.000286038262189873 \tabularnewline
0.0185314253834188 \tabularnewline
-0.0240788775205749 \tabularnewline
-0.011020366998374 \tabularnewline
-0.0100684467037505 \tabularnewline
0.034279217952988 \tabularnewline
0.0352160666665448 \tabularnewline
0.00415873895426238 \tabularnewline
0.0145524341629925 \tabularnewline
0.00445284017289998 \tabularnewline
-0.00087911886705239 \tabularnewline
0.00627409018093109 \tabularnewline
0.0188700880959196 \tabularnewline
0.0155671438825596 \tabularnewline
-0.0125845207358521 \tabularnewline
-0.0231748287063334 \tabularnewline
-0.0249539285987421 \tabularnewline
-0.0212260700284032 \tabularnewline
0.0175149373589692 \tabularnewline
-0.0618213514746822 \tabularnewline
-0.00877020855688114 \tabularnewline
-0.0373964458098009 \tabularnewline
0.0196453908792444 \tabularnewline
-0.010208545115948 \tabularnewline
0.0374665785649998 \tabularnewline
-0.0125053127094837 \tabularnewline
0.0177764659966942 \tabularnewline
0.00876695884008688 \tabularnewline
-0.00698138960594941 \tabularnewline
0.0421655026517971 \tabularnewline
-0.00483240707890766 \tabularnewline
-0.012993934098054 \tabularnewline
-0.0101891893499407 \tabularnewline
-0.0027344562961438 \tabularnewline
0.00686083900040388 \tabularnewline
0.0431700172897673 \tabularnewline
0.0238975133695183 \tabularnewline
0.0237805232430346 \tabularnewline
0.00370290370361753 \tabularnewline
-0.0241277817334609 \tabularnewline
-0.0022753562374175 \tabularnewline
-0.00490607979969384 \tabularnewline
-0.0130841790842614 \tabularnewline
0.0449685711768396 \tabularnewline
-0.00165738907047713 \tabularnewline
0.00886358233872071 \tabularnewline
0.0218417124922883 \tabularnewline
0.0281465565198036 \tabularnewline
-0.000672547736432361 \tabularnewline
-0.00879752702326364 \tabularnewline
-0.0406266782052846 \tabularnewline
-0.0119251912762987 \tabularnewline
0.0108690232728445 \tabularnewline
0.00250495149447204 \tabularnewline
0.0473582514152284 \tabularnewline
-0.0155135798629654 \tabularnewline
-0.0194342599102774 \tabularnewline
-0.0265115247013308 \tabularnewline
-0.0105872279802588 \tabularnewline
-0.0359877153885506 \tabularnewline
-0.00172223847637768 \tabularnewline
0.0423719124258156 \tabularnewline
0.0109196469049415 \tabularnewline
-0.000139889658389308 \tabularnewline
0.00221056506297855 \tabularnewline
0.0526034484945333 \tabularnewline
0.0123333296805171 \tabularnewline
-0.0149537992930109 \tabularnewline
0.0103259797793409 \tabularnewline
-0.000222333504361218 \tabularnewline
0.0177965761240893 \tabularnewline
0.0293997826657046 \tabularnewline
0.0070005662346758 \tabularnewline
0.0145652055998906 \tabularnewline
0.0149702571456381 \tabularnewline
-0.0144765975189818 \tabularnewline
-0.0201528938739596 \tabularnewline
0.00435404457556901 \tabularnewline
0.0119206619105734 \tabularnewline
-0.00393470073239699 \tabularnewline
-0.00931713205046564 \tabularnewline
-0.00202168608685327 \tabularnewline
0.00514548939650375 \tabularnewline
0.000704944356502894 \tabularnewline
0.0186034747465066 \tabularnewline
0.00336016879648003 \tabularnewline
-0.0146385309468463 \tabularnewline
0.00769407376897128 \tabularnewline
0.00650692481575547 \tabularnewline
0.0179657539386284 \tabularnewline
0.0318586424277529 \tabularnewline
-0.0074123156545105 \tabularnewline
0.0224293057079873 \tabularnewline
-0.000979281171639932 \tabularnewline
-0.00374909018321216 \tabularnewline
0.016969148212662 \tabularnewline
-0.00239581587551559 \tabularnewline
-0.00574277639963853 \tabularnewline
0.008223838468136 \tabularnewline
-0.0244768876562691 \tabularnewline
0.0116297202193972 \tabularnewline
-0.00744001507068773 \tabularnewline
0.0071183782697277 \tabularnewline
0.0194734915429982 \tabularnewline
-0.00351660611554459 \tabularnewline
-0.00679716970838818 \tabularnewline
-0.0134398444213737 \tabularnewline
-0.022536397530477 \tabularnewline
0.0158515201639834 \tabularnewline
0.014390024023166 \tabularnewline
0.0031184593011752 \tabularnewline
0.0509889737593141 \tabularnewline
-0.00900876477301251 \tabularnewline
9.99225660551601e-05 \tabularnewline
0.0250082506998601 \tabularnewline
-0.0297018304718999 \tabularnewline
-0.00737453165491915 \tabularnewline
-0.00880123403514181 \tabularnewline
0.0340658851493796 \tabularnewline
-0.0193770987590839 \tabularnewline
0.00335562989904984 \tabularnewline
0.0245563449445541 \tabularnewline
0.00657788819359133 \tabularnewline
0.00450012424150035 \tabularnewline
-0.0196911719991439 \tabularnewline
-0.00637857031687555 \tabularnewline
0.0203733111974522 \tabularnewline
-0.000916564806809762 \tabularnewline
-0.0410084434487924 \tabularnewline
0.0120423532475484 \tabularnewline
0.0275639908244012 \tabularnewline
0.0305062851865836 \tabularnewline
0.00506880327946204 \tabularnewline
0.01786901841283 \tabularnewline
-0.00908992913399778 \tabularnewline
-0.0284533590060965 \tabularnewline
-0.0320936604801024 \tabularnewline
0.0378309671004017 \tabularnewline
0.0190834510694514 \tabularnewline
-0.00867379178398282 \tabularnewline
-0.00213173027385685 \tabularnewline
-0.003237287820608 \tabularnewline
-0.00459870230812346 \tabularnewline
0.0101580848899194 \tabularnewline
0.0142226160778352 \tabularnewline
0.000792518605555397 \tabularnewline
0.0106557954401084 \tabularnewline
-0.0174458289456836 \tabularnewline
-0.00424007510529581 \tabularnewline
-0.00776950561932123 \tabularnewline
0.0154211928140162 \tabularnewline
-0.00835854425796005 \tabularnewline
-0.0117279418091893 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160421&T=2

[TABLE]
[ROW][C]Estimated ARIMA Residuals[/C][/ROW]
[ROW][C]Value[/C][/ROW]
[ROW][C]0.00321486616938156[/C][/ROW]
[ROW][C]0.00635268854201554[/C][/ROW]
[ROW][C]0.00158176224292197[/C][/ROW]
[ROW][C]-0.00728190928055009[/C][/ROW]
[ROW][C]0.0212322918846433[/C][/ROW]
[ROW][C]0.0167746476139755[/C][/ROW]
[ROW][C]-0.0198215128598677[/C][/ROW]
[ROW][C]-0.000761906266485178[/C][/ROW]
[ROW][C]-0.00466242640691158[/C][/ROW]
[ROW][C]-0.0146363127304741[/C][/ROW]
[ROW][C]0.00488701710228592[/C][/ROW]
[ROW][C]0.000309237856741927[/C][/ROW]
[ROW][C]-0.0377200880360597[/C][/ROW]
[ROW][C]-0.0205247320657338[/C][/ROW]
[ROW][C]-0.0173240076586746[/C][/ROW]
[ROW][C]0.00437900666494617[/C][/ROW]
[ROW][C]-0.0113643146461864[/C][/ROW]
[ROW][C]-0.0139821862992827[/C][/ROW]
[ROW][C]-0.0203860210629919[/C][/ROW]
[ROW][C]0.00752516023291124[/C][/ROW]
[ROW][C]0.00511514796922667[/C][/ROW]
[ROW][C]0.0197538656096163[/C][/ROW]
[ROW][C]-0.00201949404637883[/C][/ROW]
[ROW][C]-0.0538566345666434[/C][/ROW]
[ROW][C]-0.0185107284671553[/C][/ROW]
[ROW][C]0.020983718512475[/C][/ROW]
[ROW][C]0.0228757903696535[/C][/ROW]
[ROW][C]0.00507040452999372[/C][/ROW]
[ROW][C]0.00694594267206939[/C][/ROW]
[ROW][C]0.00270582315044909[/C][/ROW]
[ROW][C]-0.0135357026216257[/C][/ROW]
[ROW][C]0.0197850389677095[/C][/ROW]
[ROW][C]0.0161773726343427[/C][/ROW]
[ROW][C]0.00297828700473966[/C][/ROW]
[ROW][C]0.0054709771941518[/C][/ROW]
[ROW][C]0.00751002398657796[/C][/ROW]
[ROW][C]-0.0253550514795195[/C][/ROW]
[ROW][C]-0.009062760581585[/C][/ROW]
[ROW][C]-0.0182825109123385[/C][/ROW]
[ROW][C]0.00446780180637193[/C][/ROW]
[ROW][C]0.026965251060176[/C][/ROW]
[ROW][C]0.00590545756088409[/C][/ROW]
[ROW][C]0.0291857297986564[/C][/ROW]
[ROW][C]0.00703707501980973[/C][/ROW]
[ROW][C]0.0148920942626869[/C][/ROW]
[ROW][C]-0.0104856916579368[/C][/ROW]
[ROW][C]-0.00568816872662893[/C][/ROW]
[ROW][C]0.0101928518707152[/C][/ROW]
[ROW][C]-0.0106367866170735[/C][/ROW]
[ROW][C]0.0161720585354502[/C][/ROW]
[ROW][C]-0.0153786771667276[/C][/ROW]
[ROW][C]0.0170903392912223[/C][/ROW]
[ROW][C]0.0109832749938495[/C][/ROW]
[ROW][C]0.00498030897836837[/C][/ROW]
[ROW][C]-0.0106943698880915[/C][/ROW]
[ROW][C]0.00152508684384619[/C][/ROW]
[ROW][C]0.00821957584918115[/C][/ROW]
[ROW][C]0.0374526163031148[/C][/ROW]
[ROW][C]0.00859262682253593[/C][/ROW]
[ROW][C]-0.0028811393073025[/C][/ROW]
[ROW][C]0.00625554345619307[/C][/ROW]
[ROW][C]-0.00462188082548218[/C][/ROW]
[ROW][C]0.00517687363415715[/C][/ROW]
[ROW][C]0.0357700340520172[/C][/ROW]
[ROW][C]0.0165548833044287[/C][/ROW]
[ROW][C]-0.000838962657226227[/C][/ROW]
[ROW][C]-0.0291496154830362[/C][/ROW]
[ROW][C]0.0391059482858703[/C][/ROW]
[ROW][C]0.00224859236396429[/C][/ROW]
[ROW][C]-0.0254703901346132[/C][/ROW]
[ROW][C]0.00407173755425148[/C][/ROW]
[ROW][C]-8.52346475854562e-05[/C][/ROW]
[ROW][C]-0.0154374297445959[/C][/ROW]
[ROW][C]-0.00710746973912443[/C][/ROW]
[ROW][C]0.00182391911649746[/C][/ROW]
[ROW][C]-0.0174050594925484[/C][/ROW]
[ROW][C]-0.00690712817517445[/C][/ROW]
[ROW][C]0.0456613088230593[/C][/ROW]
[ROW][C]0.0183189890919394[/C][/ROW]
[ROW][C]-0.0135279986118039[/C][/ROW]
[ROW][C]-0.0160477061042965[/C][/ROW]
[ROW][C]0.0377390848029247[/C][/ROW]
[ROW][C]-0.0228501869919558[/C][/ROW]
[ROW][C]-0.0123979716339994[/C][/ROW]
[ROW][C]-0.0487257384704988[/C][/ROW]
[ROW][C]-0.0361135213004145[/C][/ROW]
[ROW][C]0.0210672165092541[/C][/ROW]
[ROW][C]-0.0408546316956701[/C][/ROW]
[ROW][C]0.084883456203317[/C][/ROW]
[ROW][C]-0.033010468714535[/C][/ROW]
[ROW][C]0.0312630009080394[/C][/ROW]
[ROW][C]0.000960400782011633[/C][/ROW]
[ROW][C]-0.00106535073719615[/C][/ROW]
[ROW][C]-0.0476762909089525[/C][/ROW]
[ROW][C]0.0355708013777278[/C][/ROW]
[ROW][C]-0.0443863675154798[/C][/ROW]
[ROW][C]-0.0452630267988256[/C][/ROW]
[ROW][C]0.0165101419203807[/C][/ROW]
[ROW][C]-0.0015480002617593[/C][/ROW]
[ROW][C]-0.0427221822424283[/C][/ROW]
[ROW][C]0.0318288614354148[/C][/ROW]
[ROW][C]0.0432072807307505[/C][/ROW]
[ROW][C]-0.0200087395652214[/C][/ROW]
[ROW][C]0.000366466095043467[/C][/ROW]
[ROW][C]-0.00131439311350743[/C][/ROW]
[ROW][C]-0.000286038262189873[/C][/ROW]
[ROW][C]0.0185314253834188[/C][/ROW]
[ROW][C]-0.0240788775205749[/C][/ROW]
[ROW][C]-0.011020366998374[/C][/ROW]
[ROW][C]-0.0100684467037505[/C][/ROW]
[ROW][C]0.034279217952988[/C][/ROW]
[ROW][C]0.0352160666665448[/C][/ROW]
[ROW][C]0.00415873895426238[/C][/ROW]
[ROW][C]0.0145524341629925[/C][/ROW]
[ROW][C]0.00445284017289998[/C][/ROW]
[ROW][C]-0.00087911886705239[/C][/ROW]
[ROW][C]0.00627409018093109[/C][/ROW]
[ROW][C]0.0188700880959196[/C][/ROW]
[ROW][C]0.0155671438825596[/C][/ROW]
[ROW][C]-0.0125845207358521[/C][/ROW]
[ROW][C]-0.0231748287063334[/C][/ROW]
[ROW][C]-0.0249539285987421[/C][/ROW]
[ROW][C]-0.0212260700284032[/C][/ROW]
[ROW][C]0.0175149373589692[/C][/ROW]
[ROW][C]-0.0618213514746822[/C][/ROW]
[ROW][C]-0.00877020855688114[/C][/ROW]
[ROW][C]-0.0373964458098009[/C][/ROW]
[ROW][C]0.0196453908792444[/C][/ROW]
[ROW][C]-0.010208545115948[/C][/ROW]
[ROW][C]0.0374665785649998[/C][/ROW]
[ROW][C]-0.0125053127094837[/C][/ROW]
[ROW][C]0.0177764659966942[/C][/ROW]
[ROW][C]0.00876695884008688[/C][/ROW]
[ROW][C]-0.00698138960594941[/C][/ROW]
[ROW][C]0.0421655026517971[/C][/ROW]
[ROW][C]-0.00483240707890766[/C][/ROW]
[ROW][C]-0.012993934098054[/C][/ROW]
[ROW][C]-0.0101891893499407[/C][/ROW]
[ROW][C]-0.0027344562961438[/C][/ROW]
[ROW][C]0.00686083900040388[/C][/ROW]
[ROW][C]0.0431700172897673[/C][/ROW]
[ROW][C]0.0238975133695183[/C][/ROW]
[ROW][C]0.0237805232430346[/C][/ROW]
[ROW][C]0.00370290370361753[/C][/ROW]
[ROW][C]-0.0241277817334609[/C][/ROW]
[ROW][C]-0.0022753562374175[/C][/ROW]
[ROW][C]-0.00490607979969384[/C][/ROW]
[ROW][C]-0.0130841790842614[/C][/ROW]
[ROW][C]0.0449685711768396[/C][/ROW]
[ROW][C]-0.00165738907047713[/C][/ROW]
[ROW][C]0.00886358233872071[/C][/ROW]
[ROW][C]0.0218417124922883[/C][/ROW]
[ROW][C]0.0281465565198036[/C][/ROW]
[ROW][C]-0.000672547736432361[/C][/ROW]
[ROW][C]-0.00879752702326364[/C][/ROW]
[ROW][C]-0.0406266782052846[/C][/ROW]
[ROW][C]-0.0119251912762987[/C][/ROW]
[ROW][C]0.0108690232728445[/C][/ROW]
[ROW][C]0.00250495149447204[/C][/ROW]
[ROW][C]0.0473582514152284[/C][/ROW]
[ROW][C]-0.0155135798629654[/C][/ROW]
[ROW][C]-0.0194342599102774[/C][/ROW]
[ROW][C]-0.0265115247013308[/C][/ROW]
[ROW][C]-0.0105872279802588[/C][/ROW]
[ROW][C]-0.0359877153885506[/C][/ROW]
[ROW][C]-0.00172223847637768[/C][/ROW]
[ROW][C]0.0423719124258156[/C][/ROW]
[ROW][C]0.0109196469049415[/C][/ROW]
[ROW][C]-0.000139889658389308[/C][/ROW]
[ROW][C]0.00221056506297855[/C][/ROW]
[ROW][C]0.0526034484945333[/C][/ROW]
[ROW][C]0.0123333296805171[/C][/ROW]
[ROW][C]-0.0149537992930109[/C][/ROW]
[ROW][C]0.0103259797793409[/C][/ROW]
[ROW][C]-0.000222333504361218[/C][/ROW]
[ROW][C]0.0177965761240893[/C][/ROW]
[ROW][C]0.0293997826657046[/C][/ROW]
[ROW][C]0.0070005662346758[/C][/ROW]
[ROW][C]0.0145652055998906[/C][/ROW]
[ROW][C]0.0149702571456381[/C][/ROW]
[ROW][C]-0.0144765975189818[/C][/ROW]
[ROW][C]-0.0201528938739596[/C][/ROW]
[ROW][C]0.00435404457556901[/C][/ROW]
[ROW][C]0.0119206619105734[/C][/ROW]
[ROW][C]-0.00393470073239699[/C][/ROW]
[ROW][C]-0.00931713205046564[/C][/ROW]
[ROW][C]-0.00202168608685327[/C][/ROW]
[ROW][C]0.00514548939650375[/C][/ROW]
[ROW][C]0.000704944356502894[/C][/ROW]
[ROW][C]0.0186034747465066[/C][/ROW]
[ROW][C]0.00336016879648003[/C][/ROW]
[ROW][C]-0.0146385309468463[/C][/ROW]
[ROW][C]0.00769407376897128[/C][/ROW]
[ROW][C]0.00650692481575547[/C][/ROW]
[ROW][C]0.0179657539386284[/C][/ROW]
[ROW][C]0.0318586424277529[/C][/ROW]
[ROW][C]-0.0074123156545105[/C][/ROW]
[ROW][C]0.0224293057079873[/C][/ROW]
[ROW][C]-0.000979281171639932[/C][/ROW]
[ROW][C]-0.00374909018321216[/C][/ROW]
[ROW][C]0.016969148212662[/C][/ROW]
[ROW][C]-0.00239581587551559[/C][/ROW]
[ROW][C]-0.00574277639963853[/C][/ROW]
[ROW][C]0.008223838468136[/C][/ROW]
[ROW][C]-0.0244768876562691[/C][/ROW]
[ROW][C]0.0116297202193972[/C][/ROW]
[ROW][C]-0.00744001507068773[/C][/ROW]
[ROW][C]0.0071183782697277[/C][/ROW]
[ROW][C]0.0194734915429982[/C][/ROW]
[ROW][C]-0.00351660611554459[/C][/ROW]
[ROW][C]-0.00679716970838818[/C][/ROW]
[ROW][C]-0.0134398444213737[/C][/ROW]
[ROW][C]-0.022536397530477[/C][/ROW]
[ROW][C]0.0158515201639834[/C][/ROW]
[ROW][C]0.014390024023166[/C][/ROW]
[ROW][C]0.0031184593011752[/C][/ROW]
[ROW][C]0.0509889737593141[/C][/ROW]
[ROW][C]-0.00900876477301251[/C][/ROW]
[ROW][C]9.99225660551601e-05[/C][/ROW]
[ROW][C]0.0250082506998601[/C][/ROW]
[ROW][C]-0.0297018304718999[/C][/ROW]
[ROW][C]-0.00737453165491915[/C][/ROW]
[ROW][C]-0.00880123403514181[/C][/ROW]
[ROW][C]0.0340658851493796[/C][/ROW]
[ROW][C]-0.0193770987590839[/C][/ROW]
[ROW][C]0.00335562989904984[/C][/ROW]
[ROW][C]0.0245563449445541[/C][/ROW]
[ROW][C]0.00657788819359133[/C][/ROW]
[ROW][C]0.00450012424150035[/C][/ROW]
[ROW][C]-0.0196911719991439[/C][/ROW]
[ROW][C]-0.00637857031687555[/C][/ROW]
[ROW][C]0.0203733111974522[/C][/ROW]
[ROW][C]-0.000916564806809762[/C][/ROW]
[ROW][C]-0.0410084434487924[/C][/ROW]
[ROW][C]0.0120423532475484[/C][/ROW]
[ROW][C]0.0275639908244012[/C][/ROW]
[ROW][C]0.0305062851865836[/C][/ROW]
[ROW][C]0.00506880327946204[/C][/ROW]
[ROW][C]0.01786901841283[/C][/ROW]
[ROW][C]-0.00908992913399778[/C][/ROW]
[ROW][C]-0.0284533590060965[/C][/ROW]
[ROW][C]-0.0320936604801024[/C][/ROW]
[ROW][C]0.0378309671004017[/C][/ROW]
[ROW][C]0.0190834510694514[/C][/ROW]
[ROW][C]-0.00867379178398282[/C][/ROW]
[ROW][C]-0.00213173027385685[/C][/ROW]
[ROW][C]-0.003237287820608[/C][/ROW]
[ROW][C]-0.00459870230812346[/C][/ROW]
[ROW][C]0.0101580848899194[/C][/ROW]
[ROW][C]0.0142226160778352[/C][/ROW]
[ROW][C]0.000792518605555397[/C][/ROW]
[ROW][C]0.0106557954401084[/C][/ROW]
[ROW][C]-0.0174458289456836[/C][/ROW]
[ROW][C]-0.00424007510529581[/C][/ROW]
[ROW][C]-0.00776950561932123[/C][/ROW]
[ROW][C]0.0154211928140162[/C][/ROW]
[ROW][C]-0.00835854425796005[/C][/ROW]
[ROW][C]-0.0117279418091893[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160421&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160421&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
0.00321486616938156
0.00635268854201554
0.00158176224292197
-0.00728190928055009
0.0212322918846433
0.0167746476139755
-0.0198215128598677
-0.000761906266485178
-0.00466242640691158
-0.0146363127304741
0.00488701710228592
0.000309237856741927
-0.0377200880360597
-0.0205247320657338
-0.0173240076586746
0.00437900666494617
-0.0113643146461864
-0.0139821862992827
-0.0203860210629919
0.00752516023291124
0.00511514796922667
0.0197538656096163
-0.00201949404637883
-0.0538566345666434
-0.0185107284671553
0.020983718512475
0.0228757903696535
0.00507040452999372
0.00694594267206939
0.00270582315044909
-0.0135357026216257
0.0197850389677095
0.0161773726343427
0.00297828700473966
0.0054709771941518
0.00751002398657796
-0.0253550514795195
-0.009062760581585
-0.0182825109123385
0.00446780180637193
0.026965251060176
0.00590545756088409
0.0291857297986564
0.00703707501980973
0.0148920942626869
-0.0104856916579368
-0.00568816872662893
0.0101928518707152
-0.0106367866170735
0.0161720585354502
-0.0153786771667276
0.0170903392912223
0.0109832749938495
0.00498030897836837
-0.0106943698880915
0.00152508684384619
0.00821957584918115
0.0374526163031148
0.00859262682253593
-0.0028811393073025
0.00625554345619307
-0.00462188082548218
0.00517687363415715
0.0357700340520172
0.0165548833044287
-0.000838962657226227
-0.0291496154830362
0.0391059482858703
0.00224859236396429
-0.0254703901346132
0.00407173755425148
-8.52346475854562e-05
-0.0154374297445959
-0.00710746973912443
0.00182391911649746
-0.0174050594925484
-0.00690712817517445
0.0456613088230593
0.0183189890919394
-0.0135279986118039
-0.0160477061042965
0.0377390848029247
-0.0228501869919558
-0.0123979716339994
-0.0487257384704988
-0.0361135213004145
0.0210672165092541
-0.0408546316956701
0.084883456203317
-0.033010468714535
0.0312630009080394
0.000960400782011633
-0.00106535073719615
-0.0476762909089525
0.0355708013777278
-0.0443863675154798
-0.0452630267988256
0.0165101419203807
-0.0015480002617593
-0.0427221822424283
0.0318288614354148
0.0432072807307505
-0.0200087395652214
0.000366466095043467
-0.00131439311350743
-0.000286038262189873
0.0185314253834188
-0.0240788775205749
-0.011020366998374
-0.0100684467037505
0.034279217952988
0.0352160666665448
0.00415873895426238
0.0145524341629925
0.00445284017289998
-0.00087911886705239
0.00627409018093109
0.0188700880959196
0.0155671438825596
-0.0125845207358521
-0.0231748287063334
-0.0249539285987421
-0.0212260700284032
0.0175149373589692
-0.0618213514746822
-0.00877020855688114
-0.0373964458098009
0.0196453908792444
-0.010208545115948
0.0374665785649998
-0.0125053127094837
0.0177764659966942
0.00876695884008688
-0.00698138960594941
0.0421655026517971
-0.00483240707890766
-0.012993934098054
-0.0101891893499407
-0.0027344562961438
0.00686083900040388
0.0431700172897673
0.0238975133695183
0.0237805232430346
0.00370290370361753
-0.0241277817334609
-0.0022753562374175
-0.00490607979969384
-0.0130841790842614
0.0449685711768396
-0.00165738907047713
0.00886358233872071
0.0218417124922883
0.0281465565198036
-0.000672547736432361
-0.00879752702326364
-0.0406266782052846
-0.0119251912762987
0.0108690232728445
0.00250495149447204
0.0473582514152284
-0.0155135798629654
-0.0194342599102774
-0.0265115247013308
-0.0105872279802588
-0.0359877153885506
-0.00172223847637768
0.0423719124258156
0.0109196469049415
-0.000139889658389308
0.00221056506297855
0.0526034484945333
0.0123333296805171
-0.0149537992930109
0.0103259797793409
-0.000222333504361218
0.0177965761240893
0.0293997826657046
0.0070005662346758
0.0145652055998906
0.0149702571456381
-0.0144765975189818
-0.0201528938739596
0.00435404457556901
0.0119206619105734
-0.00393470073239699
-0.00931713205046564
-0.00202168608685327
0.00514548939650375
0.000704944356502894
0.0186034747465066
0.00336016879648003
-0.0146385309468463
0.00769407376897128
0.00650692481575547
0.0179657539386284
0.0318586424277529
-0.0074123156545105
0.0224293057079873
-0.000979281171639932
-0.00374909018321216
0.016969148212662
-0.00239581587551559
-0.00574277639963853
0.008223838468136
-0.0244768876562691
0.0116297202193972
-0.00744001507068773
0.0071183782697277
0.0194734915429982
-0.00351660611554459
-0.00679716970838818
-0.0134398444213737
-0.022536397530477
0.0158515201639834
0.014390024023166
0.0031184593011752
0.0509889737593141
-0.00900876477301251
9.99225660551601e-05
0.0250082506998601
-0.0297018304718999
-0.00737453165491915
-0.00880123403514181
0.0340658851493796
-0.0193770987590839
0.00335562989904984
0.0245563449445541
0.00657788819359133
0.00450012424150035
-0.0196911719991439
-0.00637857031687555
0.0203733111974522
-0.000916564806809762
-0.0410084434487924
0.0120423532475484
0.0275639908244012
0.0305062851865836
0.00506880327946204
0.01786901841283
-0.00908992913399778
-0.0284533590060965
-0.0320936604801024
0.0378309671004017
0.0190834510694514
-0.00867379178398282
-0.00213173027385685
-0.003237287820608
-0.00459870230812346
0.0101580848899194
0.0142226160778352
0.000792518605555397
0.0106557954401084
-0.0174458289456836
-0.00424007510529581
-0.00776950561932123
0.0154211928140162
-0.00835854425796005
-0.0117279418091893


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Valutakoersen Eur-Dollar ; par4 = 12 ;
Parameters (R input):
par1 = FALSE ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 2 ; par7 = 0 ; par8 = 1 ; par9 = 0 ;
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')