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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationSat, 13 Dec 2014 15:03:41 +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/2014/Dec/13/t1418483762b319pp9ks98jpx1.htm/, Retrieved Fri, 01 Nov 2024 00:00:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267148, Retrieved Fri, 01 Nov 2024 00:00:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [Time series man CD] [2014-12-13 13:57:12] [bb1b6762b7e5624d262776d3f7139d34]
- RMP   [Spectral Analysis] [KUL paper spectra...] [2014-12-13 15:00:40] [bb1b6762b7e5624d262776d3f7139d34]
- R         [Spectral Analysis] [KUL paper spectra...] [2014-12-13 15:03:41] [8568a324fefbb8dbb43f697bfa8d1be6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
NA
6
NA
1
1
5.5
NA
6.5
4.5
2
5
0.5
5
NA
NA
NA
5.5
NA
3
NA
0.5
6.5
NA
7.5
5.5
4
7.5
NA
4
NA
NA
NA
3.5
2.5
4.5
4.5
NA
6
2.5
NA
0
5
6.5
5
6
NA
5.5
1
NA
6
5
1
5
6.5
7
4.5
NA
8.5
NA
7.5
3.5
NA
NA
9
NA
3.5
NA
6.5
7.5
NA
NA
NA
NA
7.5
NA
NA
6.5
NA
NA
1.5
NA
NA
NA
0
NA
5.5
5
NA
NA
NA
7
0
4.5
NA
1.5
NA
2.5
5.5
8
1
5
NA
3
3
8
NA
NA
NA
NA
NA
NA
5.5
0.5
7.5
9
9.5
NA
7
8
NA
7
NA
NA
9.5
4
6
8
5.5
9.5
7.5
7
NA
8
7
7
6
10
2.5
NA
8
6
8.5
6
9
NA
NA
5.5
NA
NA
9
NA
8.5
9
NA
9
7.5
10
NA
NA
NA
NA
8.5
NA
10
NA
6.5
NA
8.5
NA
NA
8
NA
7
7.5
7.5
9.5
6
NA
7
NA
NA
NA
10
NA
3.5
NA
NA
NA
NA
6.5
6.5
8.5
4
NA
NA
8.5
NA
NA
NA
NA
10
8
NA
NA
5
NA
4.5
8.5
NA
8.5
7.5
7.5
NA
NA
NA
5.5
8.5
9.5
7
NA
NA
NA
6.5
6.5
NA
NA
NA
10
10
NA
NA
NA
7.5
4.5
4.5
0.5
NA
4.5
5.5
5
NA
NA
8
NA
6.5
8
NA
5.5
NA
5
3.5
NA
9
NA
5
NA
3
NA
NA
0.5
6.5
NA
4.5
8
NA
7.5
NA
NA
9.5
6.5
NA
6
NA
NA
8
NA
NA

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267148&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267148&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267148&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)0
Seasonal Period (s)1
Frequency (Period)Spectrum
0.0062 (160)36.466556
0.0125 (80)28.038163
0.0188 (53.3333)0.307862
0.025 (40)13.368561
0.0312 (32)12.892815
0.0375 (26.6667)25.555898
0.0438 (22.8571)0.812044
0.05 (20)0.598829
0.0562 (17.7778)0.246193
0.0625 (16)3.138071
0.0688 (14.5455)6.264499
0.075 (13.3333)0.788784
0.0813 (12.3077)13.062205
0.0875 (11.4286)6.652219
0.0938 (10.6667)4.07355
0.1 (10)2.821615
0.1062 (9.4118)1.346977
0.1125 (8.8889)3.177893
0.1188 (8.4211)3.253712
0.125 (8)5.163022
0.1312 (7.619)6.808318
0.1375 (7.2727)8.359098
0.1438 (6.9565)0.15557
0.15 (6.6667)1.54603
0.1563 (6.4)0.071293
0.1625 (6.1538)11.825417
0.1688 (5.9259)9.073464
0.175 (5.7143)4.474348
0.1813 (5.5172)1.849542
0.1875 (5.3333)8.311986
0.1938 (5.1613)3.915754
0.2 (5)7.126988
0.2062 (4.8485)7.598652
0.2125 (4.7059)11.638064
0.2188 (4.5714)1.961835
0.225 (4.4444)8.607045
0.2312 (4.3243)1.175702
0.2375 (4.2105)0.595753
0.2438 (4.1026)14.426893
0.25 (4)0.76571
0.2562 (3.9024)1.19668
0.2625 (3.8095)2.873135
0.2688 (3.7209)0.067038
0.275 (3.6364)10.659045
0.2812 (3.5556)2.064037
0.2875 (3.4783)4.383496
0.2938 (3.4043)5.420694
0.3 (3.3333)5.450227
0.3062 (3.2653)0.150474
0.3125 (3.2)8.794855
0.3188 (3.1373)9.152083
0.325 (3.0769)8.447264
0.3312 (3.0189)5.525352
0.3375 (2.963)4.997737
0.3438 (2.9091)2.54772
0.35 (2.8571)4.035443
0.3562 (2.807)8.234471
0.3625 (2.7586)0.015296
0.3688 (2.7119)3.44942
0.375 (2.6667)1.585905
0.3812 (2.623)3.073501
0.3875 (2.5806)0.73576
0.3938 (2.5397)3.755375
0.4 (2.5)2.850228
0.4062 (2.4615)4.881471
0.4125 (2.4242)0.435094
0.4188 (2.3881)3.206335
0.425 (2.3529)3.764755
0.4312 (2.3188)4.520412
0.4375 (2.2857)8.854976
0.4438 (2.2535)3.949317
0.45 (2.2222)3.197797
0.4562 (2.1918)2.841337
0.4625 (2.1622)2.723415
0.4688 (2.1333)4.794971
0.475 (2.1053)6.779181
0.4812 (2.0779)0.665477
0.4875 (2.0513)3.738442
0.4938 (2.0253)16.851455
0.5 (2)1.589475

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 0 \tabularnewline
Degree of seasonal differencing (D) & 0 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0062 (160) & 36.466556 \tabularnewline
0.0125 (80) & 28.038163 \tabularnewline
0.0188 (53.3333) & 0.307862 \tabularnewline
0.025 (40) & 13.368561 \tabularnewline
0.0312 (32) & 12.892815 \tabularnewline
0.0375 (26.6667) & 25.555898 \tabularnewline
0.0438 (22.8571) & 0.812044 \tabularnewline
0.05 (20) & 0.598829 \tabularnewline
0.0562 (17.7778) & 0.246193 \tabularnewline
0.0625 (16) & 3.138071 \tabularnewline
0.0688 (14.5455) & 6.264499 \tabularnewline
0.075 (13.3333) & 0.788784 \tabularnewline
0.0813 (12.3077) & 13.062205 \tabularnewline
0.0875 (11.4286) & 6.652219 \tabularnewline
0.0938 (10.6667) & 4.07355 \tabularnewline
0.1 (10) & 2.821615 \tabularnewline
0.1062 (9.4118) & 1.346977 \tabularnewline
0.1125 (8.8889) & 3.177893 \tabularnewline
0.1188 (8.4211) & 3.253712 \tabularnewline
0.125 (8) & 5.163022 \tabularnewline
0.1312 (7.619) & 6.808318 \tabularnewline
0.1375 (7.2727) & 8.359098 \tabularnewline
0.1438 (6.9565) & 0.15557 \tabularnewline
0.15 (6.6667) & 1.54603 \tabularnewline
0.1563 (6.4) & 0.071293 \tabularnewline
0.1625 (6.1538) & 11.825417 \tabularnewline
0.1688 (5.9259) & 9.073464 \tabularnewline
0.175 (5.7143) & 4.474348 \tabularnewline
0.1813 (5.5172) & 1.849542 \tabularnewline
0.1875 (5.3333) & 8.311986 \tabularnewline
0.1938 (5.1613) & 3.915754 \tabularnewline
0.2 (5) & 7.126988 \tabularnewline
0.2062 (4.8485) & 7.598652 \tabularnewline
0.2125 (4.7059) & 11.638064 \tabularnewline
0.2188 (4.5714) & 1.961835 \tabularnewline
0.225 (4.4444) & 8.607045 \tabularnewline
0.2312 (4.3243) & 1.175702 \tabularnewline
0.2375 (4.2105) & 0.595753 \tabularnewline
0.2438 (4.1026) & 14.426893 \tabularnewline
0.25 (4) & 0.76571 \tabularnewline
0.2562 (3.9024) & 1.19668 \tabularnewline
0.2625 (3.8095) & 2.873135 \tabularnewline
0.2688 (3.7209) & 0.067038 \tabularnewline
0.275 (3.6364) & 10.659045 \tabularnewline
0.2812 (3.5556) & 2.064037 \tabularnewline
0.2875 (3.4783) & 4.383496 \tabularnewline
0.2938 (3.4043) & 5.420694 \tabularnewline
0.3 (3.3333) & 5.450227 \tabularnewline
0.3062 (3.2653) & 0.150474 \tabularnewline
0.3125 (3.2) & 8.794855 \tabularnewline
0.3188 (3.1373) & 9.152083 \tabularnewline
0.325 (3.0769) & 8.447264 \tabularnewline
0.3312 (3.0189) & 5.525352 \tabularnewline
0.3375 (2.963) & 4.997737 \tabularnewline
0.3438 (2.9091) & 2.54772 \tabularnewline
0.35 (2.8571) & 4.035443 \tabularnewline
0.3562 (2.807) & 8.234471 \tabularnewline
0.3625 (2.7586) & 0.015296 \tabularnewline
0.3688 (2.7119) & 3.44942 \tabularnewline
0.375 (2.6667) & 1.585905 \tabularnewline
0.3812 (2.623) & 3.073501 \tabularnewline
0.3875 (2.5806) & 0.73576 \tabularnewline
0.3938 (2.5397) & 3.755375 \tabularnewline
0.4 (2.5) & 2.850228 \tabularnewline
0.4062 (2.4615) & 4.881471 \tabularnewline
0.4125 (2.4242) & 0.435094 \tabularnewline
0.4188 (2.3881) & 3.206335 \tabularnewline
0.425 (2.3529) & 3.764755 \tabularnewline
0.4312 (2.3188) & 4.520412 \tabularnewline
0.4375 (2.2857) & 8.854976 \tabularnewline
0.4438 (2.2535) & 3.949317 \tabularnewline
0.45 (2.2222) & 3.197797 \tabularnewline
0.4562 (2.1918) & 2.841337 \tabularnewline
0.4625 (2.1622) & 2.723415 \tabularnewline
0.4688 (2.1333) & 4.794971 \tabularnewline
0.475 (2.1053) & 6.779181 \tabularnewline
0.4812 (2.0779) & 0.665477 \tabularnewline
0.4875 (2.0513) & 3.738442 \tabularnewline
0.4938 (2.0253) & 16.851455 \tabularnewline
0.5 (2) & 1.589475 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267148&T=1

[TABLE]
[ROW][C]Raw Periodogram[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda)[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d)[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D)[/C][C]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0062 (160)[/C][C]36.466556[/C][/ROW]
[ROW][C]0.0125 (80)[/C][C]28.038163[/C][/ROW]
[ROW][C]0.0188 (53.3333)[/C][C]0.307862[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]13.368561[/C][/ROW]
[ROW][C]0.0312 (32)[/C][C]12.892815[/C][/ROW]
[ROW][C]0.0375 (26.6667)[/C][C]25.555898[/C][/ROW]
[ROW][C]0.0438 (22.8571)[/C][C]0.812044[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]0.598829[/C][/ROW]
[ROW][C]0.0562 (17.7778)[/C][C]0.246193[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]3.138071[/C][/ROW]
[ROW][C]0.0688 (14.5455)[/C][C]6.264499[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]0.788784[/C][/ROW]
[ROW][C]0.0813 (12.3077)[/C][C]13.062205[/C][/ROW]
[ROW][C]0.0875 (11.4286)[/C][C]6.652219[/C][/ROW]
[ROW][C]0.0938 (10.6667)[/C][C]4.07355[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]2.821615[/C][/ROW]
[ROW][C]0.1062 (9.4118)[/C][C]1.346977[/C][/ROW]
[ROW][C]0.1125 (8.8889)[/C][C]3.177893[/C][/ROW]
[ROW][C]0.1188 (8.4211)[/C][C]3.253712[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]5.163022[/C][/ROW]
[ROW][C]0.1312 (7.619)[/C][C]6.808318[/C][/ROW]
[ROW][C]0.1375 (7.2727)[/C][C]8.359098[/C][/ROW]
[ROW][C]0.1438 (6.9565)[/C][C]0.15557[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]1.54603[/C][/ROW]
[ROW][C]0.1563 (6.4)[/C][C]0.071293[/C][/ROW]
[ROW][C]0.1625 (6.1538)[/C][C]11.825417[/C][/ROW]
[ROW][C]0.1688 (5.9259)[/C][C]9.073464[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]4.474348[/C][/ROW]
[ROW][C]0.1813 (5.5172)[/C][C]1.849542[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]8.311986[/C][/ROW]
[ROW][C]0.1938 (5.1613)[/C][C]3.915754[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]7.126988[/C][/ROW]
[ROW][C]0.2062 (4.8485)[/C][C]7.598652[/C][/ROW]
[ROW][C]0.2125 (4.7059)[/C][C]11.638064[/C][/ROW]
[ROW][C]0.2188 (4.5714)[/C][C]1.961835[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]8.607045[/C][/ROW]
[ROW][C]0.2312 (4.3243)[/C][C]1.175702[/C][/ROW]
[ROW][C]0.2375 (4.2105)[/C][C]0.595753[/C][/ROW]
[ROW][C]0.2438 (4.1026)[/C][C]14.426893[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.76571[/C][/ROW]
[ROW][C]0.2562 (3.9024)[/C][C]1.19668[/C][/ROW]
[ROW][C]0.2625 (3.8095)[/C][C]2.873135[/C][/ROW]
[ROW][C]0.2688 (3.7209)[/C][C]0.067038[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]10.659045[/C][/ROW]
[ROW][C]0.2812 (3.5556)[/C][C]2.064037[/C][/ROW]
[ROW][C]0.2875 (3.4783)[/C][C]4.383496[/C][/ROW]
[ROW][C]0.2938 (3.4043)[/C][C]5.420694[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]5.450227[/C][/ROW]
[ROW][C]0.3062 (3.2653)[/C][C]0.150474[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]8.794855[/C][/ROW]
[ROW][C]0.3188 (3.1373)[/C][C]9.152083[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]8.447264[/C][/ROW]
[ROW][C]0.3312 (3.0189)[/C][C]5.525352[/C][/ROW]
[ROW][C]0.3375 (2.963)[/C][C]4.997737[/C][/ROW]
[ROW][C]0.3438 (2.9091)[/C][C]2.54772[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]4.035443[/C][/ROW]
[ROW][C]0.3562 (2.807)[/C][C]8.234471[/C][/ROW]
[ROW][C]0.3625 (2.7586)[/C][C]0.015296[/C][/ROW]
[ROW][C]0.3688 (2.7119)[/C][C]3.44942[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]1.585905[/C][/ROW]
[ROW][C]0.3812 (2.623)[/C][C]3.073501[/C][/ROW]
[ROW][C]0.3875 (2.5806)[/C][C]0.73576[/C][/ROW]
[ROW][C]0.3938 (2.5397)[/C][C]3.755375[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]2.850228[/C][/ROW]
[ROW][C]0.4062 (2.4615)[/C][C]4.881471[/C][/ROW]
[ROW][C]0.4125 (2.4242)[/C][C]0.435094[/C][/ROW]
[ROW][C]0.4188 (2.3881)[/C][C]3.206335[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]3.764755[/C][/ROW]
[ROW][C]0.4312 (2.3188)[/C][C]4.520412[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]8.854976[/C][/ROW]
[ROW][C]0.4438 (2.2535)[/C][C]3.949317[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]3.197797[/C][/ROW]
[ROW][C]0.4562 (2.1918)[/C][C]2.841337[/C][/ROW]
[ROW][C]0.4625 (2.1622)[/C][C]2.723415[/C][/ROW]
[ROW][C]0.4688 (2.1333)[/C][C]4.794971[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]6.779181[/C][/ROW]
[ROW][C]0.4812 (2.0779)[/C][C]0.665477[/C][/ROW]
[ROW][C]0.4875 (2.0513)[/C][C]3.738442[/C][/ROW]
[ROW][C]0.4938 (2.0253)[/C][C]16.851455[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]1.589475[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267148&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267148&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:

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)0
Seasonal Period (s)1
Frequency (Period)Spectrum
0.0062 (160)36.466556
0.0125 (80)28.038163
0.0188 (53.3333)0.307862
0.025 (40)13.368561
0.0312 (32)12.892815
0.0375 (26.6667)25.555898
0.0438 (22.8571)0.812044
0.05 (20)0.598829
0.0562 (17.7778)0.246193
0.0625 (16)3.138071
0.0688 (14.5455)6.264499
0.075 (13.3333)0.788784
0.0813 (12.3077)13.062205
0.0875 (11.4286)6.652219
0.0938 (10.6667)4.07355
0.1 (10)2.821615
0.1062 (9.4118)1.346977
0.1125 (8.8889)3.177893
0.1188 (8.4211)3.253712
0.125 (8)5.163022
0.1312 (7.619)6.808318
0.1375 (7.2727)8.359098
0.1438 (6.9565)0.15557
0.15 (6.6667)1.54603
0.1563 (6.4)0.071293
0.1625 (6.1538)11.825417
0.1688 (5.9259)9.073464
0.175 (5.7143)4.474348
0.1813 (5.5172)1.849542
0.1875 (5.3333)8.311986
0.1938 (5.1613)3.915754
0.2 (5)7.126988
0.2062 (4.8485)7.598652
0.2125 (4.7059)11.638064
0.2188 (4.5714)1.961835
0.225 (4.4444)8.607045
0.2312 (4.3243)1.175702
0.2375 (4.2105)0.595753
0.2438 (4.1026)14.426893
0.25 (4)0.76571
0.2562 (3.9024)1.19668
0.2625 (3.8095)2.873135
0.2688 (3.7209)0.067038
0.275 (3.6364)10.659045
0.2812 (3.5556)2.064037
0.2875 (3.4783)4.383496
0.2938 (3.4043)5.420694
0.3 (3.3333)5.450227
0.3062 (3.2653)0.150474
0.3125 (3.2)8.794855
0.3188 (3.1373)9.152083
0.325 (3.0769)8.447264
0.3312 (3.0189)5.525352
0.3375 (2.963)4.997737
0.3438 (2.9091)2.54772
0.35 (2.8571)4.035443
0.3562 (2.807)8.234471
0.3625 (2.7586)0.015296
0.3688 (2.7119)3.44942
0.375 (2.6667)1.585905
0.3812 (2.623)3.073501
0.3875 (2.5806)0.73576
0.3938 (2.5397)3.755375
0.4 (2.5)2.850228
0.4062 (2.4615)4.881471
0.4125 (2.4242)0.435094
0.4188 (2.3881)3.206335
0.425 (2.3529)3.764755
0.4312 (2.3188)4.520412
0.4375 (2.2857)8.854976
0.4438 (2.2535)3.949317
0.45 (2.2222)3.197797
0.4562 (2.1918)2.841337
0.4625 (2.1622)2.723415
0.4688 (2.1333)4.794971
0.475 (2.1053)6.779181
0.4812 (2.0779)0.665477
0.4875 (2.0513)3.738442
0.4938 (2.0253)16.851455
0.5 (2)1.589475


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ;
R code (references can be found in the software module):
x<-na.omit(x)
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
bitmap(file='test1.png')
r <- spectrum(x,main='Raw Periodogram')
dev.off()
bitmap(file='test2.png')
cpgram(x,main='Cumulative Periodogram')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Raw Periodogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda)',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d)',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D)',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Frequency (Period)',header=TRUE)
a<-table.element(a,'Spectrum',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(r$freq)) {
a<-table.row.start(a)
mylab <- round(r$freq[i],4)
mylab <- paste(mylab,' (',sep='')
mylab <- paste(mylab,round(1/r$freq[i],4),sep='')
mylab <- paste(mylab,')',sep='')
a<-table.element(a,mylab,header=TRUE)
a<-table.element(a,round(r$spec[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')