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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationWed, 21 Dec 2016 14:20:15 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/21/t1482326433xkjzzktzov5tg1d.htm/, Retrieved Tue, 07 May 2024 01:11:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302265, Retrieved Tue, 07 May 2024 01:11:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsN1910
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ML Fitting and QQ Plot- Normal Distribution] [Normal distribution] [2016-12-15 09:27:42] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chisquared simula...] [2016-12-15 10:38:18] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 13:20:15] [9a9519454d094169f95f881e5b6f16f7] [Current]
- RMPD        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [a] [2017-01-22 21:09:42] [29aab2222b4b721088e78b64014cd237]
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Dataseries X:
4738.4
4687.2
5930.8
5532
5429.8
6107.4
5960.8
5541.8
5362.2
5237
4827
4781.6
4983.2
4718.4
5523.8
5286.6
5389
5810.4
5057.4
5604.4
5285
5215.2
4625.4
4270.4
4685.4
4233.8
5278.4
4978.8
5333.4
5451
5224
5790.2
5079.4
4705.8
4139.6
3720.8
4594
4638.8
4969.4
4764.4
5010.8
5267.8
5312.2
5723.2
4579.6
5015.2
4282.4
3834.2
4523.4
3884.2
3897.8
4845.6
4929
4955.4
5198.4
5122.2
4643.2
4789.8
3950.8
3824.4
4511.8
4262.4
4616.6
5139.6
4972.8
5222
5242
4979.8
4691.8
4821.6
4123.6
4027.4
4365.2
4333.6
4930
5053
5031.4
5342
5191.4
4852.2
4675.6
4689.2
3809.4
4054.2
4409.6
4210.2
4566.4
4907
5021.8
5215.2
4933.6
5197.8
4734.6
4681.8
4172
4037.8
4462.6
4282.6
4962.4
4969.2
5214.6
5416.8
4764.2
5326.2
4545.4
4797.2
4259
4117
4469.2
4203.2
5033.8
4883
5361.6
5044.6
5005.6
5382
4565.4
4825
4290.2
3933.6
4177.6
3949.4
4492.6
4894.2
5224.4
5071




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302265&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302265&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302265&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0083 (120)174490.296951
0.0167 (60)29127.557662
0.025 (40)131698.144207
0.0333 (30)310688.148317
0.0417 (24)55411.864917
0.05 (20)26119.89756
0.0583 (17.1429)195705.032958
0.0667 (15)68727.062414
0.075 (13.3333)30621.009432
0.0833 (12)3298.411505
0.0917 (10.9091)65698.946544
0.1 (10)7635.662695
0.1083 (9.2308)32376.613079
0.1167 (8.5714)214348.824154
0.125 (8)305182.281592
0.1333 (7.5)134645.476069
0.1417 (7.0588)815.184575
0.15 (6.6667)3140.829377
0.1583 (6.3158)340.411298
0.1667 (6)4160.311881
0.175 (5.7143)36977.300742
0.1833 (5.4545)119638.500043
0.1917 (5.2174)275730.918992
0.2 (5)155616.384083
0.2083 (4.8)75238.396786
0.2167 (4.6154)97857.415697
0.225 (4.4444)55171.091452
0.2333 (4.2857)1563.122208
0.2417 (4.1379)12546.990004
0.25 (4)3846.614798
0.2583 (3.871)72.111559
0.2667 (3.75)21591.068234
0.275 (3.6364)51705.359302
0.2833 (3.5294)119880.145978
0.2917 (3.4286)6271.615736
0.3 (3.3333)52987.080806
0.3083 (3.2432)37331.841231
0.3167 (3.1579)7785.852188
0.325 (3.0769)4539.682528
0.3333 (3)23868.011242
0.3417 (2.9268)192703.84066
0.35 (2.8571)260724.469527
0.3583 (2.7907)74541.221211
0.3667 (2.7273)34338.887558
0.375 (2.6667)38858.971048
0.3833 (2.6087)2778.763637
0.3917 (2.5532)2258.119513
0.4 (2.5)36988.135076
0.4083 (2.449)38785.298159
0.4167 (2.4)7455.79768
0.425 (2.3529)33877.031392
0.4333 (2.3077)46125.439529
0.4417 (2.2642)89687.151417
0.45 (2.2222)64239.516938
0.4583 (2.1818)19551.377586
0.4667 (2.1429)60227.031445
0.475 (2.1053)44621.837465
0.4833 (2.069)4202.065495
0.4917 (2.0339)8559.419917
0.5 (2)2.50226

\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) & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0083 (120) & 174490.296951 \tabularnewline
0.0167 (60) & 29127.557662 \tabularnewline
0.025 (40) & 131698.144207 \tabularnewline
0.0333 (30) & 310688.148317 \tabularnewline
0.0417 (24) & 55411.864917 \tabularnewline
0.05 (20) & 26119.89756 \tabularnewline
0.0583 (17.1429) & 195705.032958 \tabularnewline
0.0667 (15) & 68727.062414 \tabularnewline
0.075 (13.3333) & 30621.009432 \tabularnewline
0.0833 (12) & 3298.411505 \tabularnewline
0.0917 (10.9091) & 65698.946544 \tabularnewline
0.1 (10) & 7635.662695 \tabularnewline
0.1083 (9.2308) & 32376.613079 \tabularnewline
0.1167 (8.5714) & 214348.824154 \tabularnewline
0.125 (8) & 305182.281592 \tabularnewline
0.1333 (7.5) & 134645.476069 \tabularnewline
0.1417 (7.0588) & 815.184575 \tabularnewline
0.15 (6.6667) & 3140.829377 \tabularnewline
0.1583 (6.3158) & 340.411298 \tabularnewline
0.1667 (6) & 4160.311881 \tabularnewline
0.175 (5.7143) & 36977.300742 \tabularnewline
0.1833 (5.4545) & 119638.500043 \tabularnewline
0.1917 (5.2174) & 275730.918992 \tabularnewline
0.2 (5) & 155616.384083 \tabularnewline
0.2083 (4.8) & 75238.396786 \tabularnewline
0.2167 (4.6154) & 97857.415697 \tabularnewline
0.225 (4.4444) & 55171.091452 \tabularnewline
0.2333 (4.2857) & 1563.122208 \tabularnewline
0.2417 (4.1379) & 12546.990004 \tabularnewline
0.25 (4) & 3846.614798 \tabularnewline
0.2583 (3.871) & 72.111559 \tabularnewline
0.2667 (3.75) & 21591.068234 \tabularnewline
0.275 (3.6364) & 51705.359302 \tabularnewline
0.2833 (3.5294) & 119880.145978 \tabularnewline
0.2917 (3.4286) & 6271.615736 \tabularnewline
0.3 (3.3333) & 52987.080806 \tabularnewline
0.3083 (3.2432) & 37331.841231 \tabularnewline
0.3167 (3.1579) & 7785.852188 \tabularnewline
0.325 (3.0769) & 4539.682528 \tabularnewline
0.3333 (3) & 23868.011242 \tabularnewline
0.3417 (2.9268) & 192703.84066 \tabularnewline
0.35 (2.8571) & 260724.469527 \tabularnewline
0.3583 (2.7907) & 74541.221211 \tabularnewline
0.3667 (2.7273) & 34338.887558 \tabularnewline
0.375 (2.6667) & 38858.971048 \tabularnewline
0.3833 (2.6087) & 2778.763637 \tabularnewline
0.3917 (2.5532) & 2258.119513 \tabularnewline
0.4 (2.5) & 36988.135076 \tabularnewline
0.4083 (2.449) & 38785.298159 \tabularnewline
0.4167 (2.4) & 7455.79768 \tabularnewline
0.425 (2.3529) & 33877.031392 \tabularnewline
0.4333 (2.3077) & 46125.439529 \tabularnewline
0.4417 (2.2642) & 89687.151417 \tabularnewline
0.45 (2.2222) & 64239.516938 \tabularnewline
0.4583 (2.1818) & 19551.377586 \tabularnewline
0.4667 (2.1429) & 60227.031445 \tabularnewline
0.475 (2.1053) & 44621.837465 \tabularnewline
0.4833 (2.069) & 4202.065495 \tabularnewline
0.4917 (2.0339) & 8559.419917 \tabularnewline
0.5 (2) & 2.50226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302265&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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0083 (120)[/C][C]174490.296951[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]29127.557662[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]131698.144207[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]310688.148317[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]55411.864917[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]26119.89756[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]195705.032958[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]68727.062414[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]30621.009432[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]3298.411505[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]65698.946544[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]7635.662695[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]32376.613079[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]214348.824154[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]305182.281592[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]134645.476069[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]815.184575[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]3140.829377[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]340.411298[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]4160.311881[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]36977.300742[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]119638.500043[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]275730.918992[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]155616.384083[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]75238.396786[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]97857.415697[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]55171.091452[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]1563.122208[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]12546.990004[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]3846.614798[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]72.111559[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]21591.068234[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]51705.359302[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]119880.145978[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]6271.615736[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]52987.080806[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]37331.841231[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]7785.852188[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]4539.682528[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]23868.011242[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]192703.84066[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]260724.469527[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]74541.221211[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]34338.887558[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]38858.971048[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]2778.763637[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]2258.119513[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]36988.135076[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]38785.298159[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]7455.79768[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]33877.031392[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]46125.439529[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]89687.151417[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]64239.516938[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]19551.377586[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]60227.031445[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]44621.837465[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]4202.065495[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]8559.419917[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]2.50226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302265&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302265&T=1

As an alternative you can also use a 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)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0083 (120)174490.296951
0.0167 (60)29127.557662
0.025 (40)131698.144207
0.0333 (30)310688.148317
0.0417 (24)55411.864917
0.05 (20)26119.89756
0.0583 (17.1429)195705.032958
0.0667 (15)68727.062414
0.075 (13.3333)30621.009432
0.0833 (12)3298.411505
0.0917 (10.9091)65698.946544
0.1 (10)7635.662695
0.1083 (9.2308)32376.613079
0.1167 (8.5714)214348.824154
0.125 (8)305182.281592
0.1333 (7.5)134645.476069
0.1417 (7.0588)815.184575
0.15 (6.6667)3140.829377
0.1583 (6.3158)340.411298
0.1667 (6)4160.311881
0.175 (5.7143)36977.300742
0.1833 (5.4545)119638.500043
0.1917 (5.2174)275730.918992
0.2 (5)155616.384083
0.2083 (4.8)75238.396786
0.2167 (4.6154)97857.415697
0.225 (4.4444)55171.091452
0.2333 (4.2857)1563.122208
0.2417 (4.1379)12546.990004
0.25 (4)3846.614798
0.2583 (3.871)72.111559
0.2667 (3.75)21591.068234
0.275 (3.6364)51705.359302
0.2833 (3.5294)119880.145978
0.2917 (3.4286)6271.615736
0.3 (3.3333)52987.080806
0.3083 (3.2432)37331.841231
0.3167 (3.1579)7785.852188
0.325 (3.0769)4539.682528
0.3333 (3)23868.011242
0.3417 (2.9268)192703.84066
0.35 (2.8571)260724.469527
0.3583 (2.7907)74541.221211
0.3667 (2.7273)34338.887558
0.375 (2.6667)38858.971048
0.3833 (2.6087)2778.763637
0.3917 (2.5532)2258.119513
0.4 (2.5)36988.135076
0.4083 (2.449)38785.298159
0.4167 (2.4)7455.79768
0.425 (2.3529)33877.031392
0.4333 (2.3077)46125.439529
0.4417 (2.2642)89687.151417
0.45 (2.2222)64239.516938
0.4583 (2.1818)19551.377586
0.4667 (2.1429)60227.031445
0.475 (2.1053)44621.837465
0.4833 (2.069)4202.065495
0.4917 (2.0339)8559.419917
0.5 (2)2.50226



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ;
R code (references can be found in the software module):
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')