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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 computationMon, 05 Dec 2016 14:54:41 +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/05/t1480946097mc2fw8sjutuc22d.htm/, Retrieved Wed, 01 May 2024 18:07:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297737, Retrieved Wed, 01 May 2024 18:07:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [F1:N2774] [2016-12-03 13:43:19] [a4c5732063e280fade3b47e7f5057d96]
- RMP     [Spectral Analysis] [F1:N2774] [2016-12-05 13:54:41] [8d7b5e4c30a3b8052caee801f90adcea] [Current]
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Dataseries X:
5315.1
5327.75
5349.45
5346.8
5346.6
5325.25
5340.35
5354.75
5382.85
5392.35
5400.35
5410.8
5444.35
5424
5441.85
5447.6
5454.45
5478.8
5490.5
5500.75
5504.25
5513.65
5523.75
5536.4
5547.65
5562.85
5570.4
5589.7
5621.7
5612.3
5631.7
5652.85
5645.45
5664.1
5675.25
5689.65
5700.8
5711.35
5701.85
5732.5
5714.6
5746.35
5753
5764.1
5767.8
5781.9
5805
5805.2
5835.4
5838.8
5851.1
5854.85
5854.95
5870.9
5873.6
5882.75
5867.7
5879.05
5895.6
5891.5
5954.05
5952.95
5960.15
5942.6
5957.55
5949.15
5940.5
5940.1
5926.2
5926.8
5915.3
5912.05
5897
5887.75
5882.6
5905.45
5872
5881.95
5878.4
5874.2
5896.4
5890
5888.5
5873.3
5898.9
5887.65
5907.2
5921.3
5918.75
5920.95
5935.65
5941.3
5936
5931.4
5943.8
5949.85
5953.75
5963.75
5977.1
5973.7
6005.75
6014.5
6023.35
6042.8
6027.7
6041.15
6058.45
6073.2
6096.1
6103.3
6101.55
6115.15
6146.25
6134.3
6136.65
6168.05
6182.8
6204.3
6220.85
6229.75




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=297737&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=297737&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297737&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)1
Degree of seasonal differencing (D)0
Seasonal Period (s)1
Frequency (Period)Spectrum
0.0083 (120)777.691024
0.0167 (60)560.866909
0.025 (40)133.184567
0.0333 (30)92.866853
0.0417 (24)120.178205
0.05 (20)65.007243
0.0583 (17.1429)136.037647
0.0667 (15)67.270676
0.075 (13.3333)135.276374
0.0833 (12)58.844681
0.0917 (10.9091)3.050921
0.1 (10)196.839312
0.1083 (9.2308)43.65311
0.1167 (8.5714)93.665048
0.125 (8)46.424599
0.1333 (7.5)15.607384
0.1417 (7.0588)75.430547
0.15 (6.6667)182.133562
0.1583 (6.3158)87.071992
0.1667 (6)119.758781
0.175 (5.7143)0.780657
0.1833 (5.4545)55.428599
0.1917 (5.2174)461.636985
0.2 (5)55.229018
0.2083 (4.8)157.652633
0.2167 (4.6154)8.392282
0.225 (4.4444)4.639045
0.2333 (4.2857)26.900418
0.2417 (4.1379)77.583049
0.25 (4)76.599162
0.2583 (3.871)50.764821
0.2667 (3.75)223.314603
0.275 (3.6364)125.479788
0.2833 (3.5294)45.374264
0.2917 (3.4286)98.277871
0.3 (3.3333)347.045859
0.3083 (3.2432)267.480186
0.3167 (3.1579)282.937464
0.325 (3.0769)38.924728
0.3333 (3)448.226132
0.3417 (2.9268)160.913696
0.35 (2.8571)297.879099
0.3583 (2.7907)509.593787
0.3667 (2.7273)122.106256
0.375 (2.6667)347.676075
0.3833 (2.6087)164.099979
0.3917 (2.5532)55.115764
0.4 (2.5)157.865311
0.4083 (2.449)237.533026
0.4167 (2.4)717.721107
0.425 (2.3529)233.73174
0.4333 (2.3077)70.619148
0.4417 (2.2642)1512.315082
0.45 (2.2222)324.987449
0.4583 (2.1818)212.563739
0.4667 (2.1429)341.660408
0.475 (2.1053)605.498752
0.4833 (2.069)156.948687
0.4917 (2.0339)105.761528
0.5 (2)98.426111

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 1 \tabularnewline
Degree of seasonal differencing (D) & 0 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0083 (120) & 777.691024 \tabularnewline
0.0167 (60) & 560.866909 \tabularnewline
0.025 (40) & 133.184567 \tabularnewline
0.0333 (30) & 92.866853 \tabularnewline
0.0417 (24) & 120.178205 \tabularnewline
0.05 (20) & 65.007243 \tabularnewline
0.0583 (17.1429) & 136.037647 \tabularnewline
0.0667 (15) & 67.270676 \tabularnewline
0.075 (13.3333) & 135.276374 \tabularnewline
0.0833 (12) & 58.844681 \tabularnewline
0.0917 (10.9091) & 3.050921 \tabularnewline
0.1 (10) & 196.839312 \tabularnewline
0.1083 (9.2308) & 43.65311 \tabularnewline
0.1167 (8.5714) & 93.665048 \tabularnewline
0.125 (8) & 46.424599 \tabularnewline
0.1333 (7.5) & 15.607384 \tabularnewline
0.1417 (7.0588) & 75.430547 \tabularnewline
0.15 (6.6667) & 182.133562 \tabularnewline
0.1583 (6.3158) & 87.071992 \tabularnewline
0.1667 (6) & 119.758781 \tabularnewline
0.175 (5.7143) & 0.780657 \tabularnewline
0.1833 (5.4545) & 55.428599 \tabularnewline
0.1917 (5.2174) & 461.636985 \tabularnewline
0.2 (5) & 55.229018 \tabularnewline
0.2083 (4.8) & 157.652633 \tabularnewline
0.2167 (4.6154) & 8.392282 \tabularnewline
0.225 (4.4444) & 4.639045 \tabularnewline
0.2333 (4.2857) & 26.900418 \tabularnewline
0.2417 (4.1379) & 77.583049 \tabularnewline
0.25 (4) & 76.599162 \tabularnewline
0.2583 (3.871) & 50.764821 \tabularnewline
0.2667 (3.75) & 223.314603 \tabularnewline
0.275 (3.6364) & 125.479788 \tabularnewline
0.2833 (3.5294) & 45.374264 \tabularnewline
0.2917 (3.4286) & 98.277871 \tabularnewline
0.3 (3.3333) & 347.045859 \tabularnewline
0.3083 (3.2432) & 267.480186 \tabularnewline
0.3167 (3.1579) & 282.937464 \tabularnewline
0.325 (3.0769) & 38.924728 \tabularnewline
0.3333 (3) & 448.226132 \tabularnewline
0.3417 (2.9268) & 160.913696 \tabularnewline
0.35 (2.8571) & 297.879099 \tabularnewline
0.3583 (2.7907) & 509.593787 \tabularnewline
0.3667 (2.7273) & 122.106256 \tabularnewline
0.375 (2.6667) & 347.676075 \tabularnewline
0.3833 (2.6087) & 164.099979 \tabularnewline
0.3917 (2.5532) & 55.115764 \tabularnewline
0.4 (2.5) & 157.865311 \tabularnewline
0.4083 (2.449) & 237.533026 \tabularnewline
0.4167 (2.4) & 717.721107 \tabularnewline
0.425 (2.3529) & 233.73174 \tabularnewline
0.4333 (2.3077) & 70.619148 \tabularnewline
0.4417 (2.2642) & 1512.315082 \tabularnewline
0.45 (2.2222) & 324.987449 \tabularnewline
0.4583 (2.1818) & 212.563739 \tabularnewline
0.4667 (2.1429) & 341.660408 \tabularnewline
0.475 (2.1053) & 605.498752 \tabularnewline
0.4833 (2.069) & 156.948687 \tabularnewline
0.4917 (2.0339) & 105.761528 \tabularnewline
0.5 (2) & 98.426111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297737&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]1[/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]0.0083 (120)[/C][C]777.691024[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]560.866909[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]133.184567[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]92.866853[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]120.178205[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]65.007243[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]136.037647[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]67.270676[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]135.276374[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]58.844681[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]3.050921[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]196.839312[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]43.65311[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]93.665048[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]46.424599[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]15.607384[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]75.430547[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]182.133562[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]87.071992[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]119.758781[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]0.780657[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]55.428599[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]461.636985[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]55.229018[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]157.652633[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]8.392282[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]4.639045[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]26.900418[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]77.583049[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]76.599162[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]50.764821[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]223.314603[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]125.479788[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]45.374264[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]98.277871[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]347.045859[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]267.480186[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]282.937464[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]38.924728[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]448.226132[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]160.913696[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]297.879099[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]509.593787[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]122.106256[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]347.676075[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]164.099979[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]55.115764[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]157.865311[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]237.533026[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]717.721107[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]233.73174[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]70.619148[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]1512.315082[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]324.987449[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]212.563739[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]341.660408[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]605.498752[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]156.948687[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]105.761528[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]98.426111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297737&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297737&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)1
Degree of seasonal differencing (D)0
Seasonal Period (s)1
Frequency (Period)Spectrum
0.0083 (120)777.691024
0.0167 (60)560.866909
0.025 (40)133.184567
0.0333 (30)92.866853
0.0417 (24)120.178205
0.05 (20)65.007243
0.0583 (17.1429)136.037647
0.0667 (15)67.270676
0.075 (13.3333)135.276374
0.0833 (12)58.844681
0.0917 (10.9091)3.050921
0.1 (10)196.839312
0.1083 (9.2308)43.65311
0.1167 (8.5714)93.665048
0.125 (8)46.424599
0.1333 (7.5)15.607384
0.1417 (7.0588)75.430547
0.15 (6.6667)182.133562
0.1583 (6.3158)87.071992
0.1667 (6)119.758781
0.175 (5.7143)0.780657
0.1833 (5.4545)55.428599
0.1917 (5.2174)461.636985
0.2 (5)55.229018
0.2083 (4.8)157.652633
0.2167 (4.6154)8.392282
0.225 (4.4444)4.639045
0.2333 (4.2857)26.900418
0.2417 (4.1379)77.583049
0.25 (4)76.599162
0.2583 (3.871)50.764821
0.2667 (3.75)223.314603
0.275 (3.6364)125.479788
0.2833 (3.5294)45.374264
0.2917 (3.4286)98.277871
0.3 (3.3333)347.045859
0.3083 (3.2432)267.480186
0.3167 (3.1579)282.937464
0.325 (3.0769)38.924728
0.3333 (3)448.226132
0.3417 (2.9268)160.913696
0.35 (2.8571)297.879099
0.3583 (2.7907)509.593787
0.3667 (2.7273)122.106256
0.375 (2.6667)347.676075
0.3833 (2.6087)164.099979
0.3917 (2.5532)55.115764
0.4 (2.5)157.865311
0.4083 (2.449)237.533026
0.4167 (2.4)717.721107
0.425 (2.3529)233.73174
0.4333 (2.3077)70.619148
0.4417 (2.2642)1512.315082
0.45 (2.2222)324.987449
0.4583 (2.1818)212.563739
0.4667 (2.1429)341.660408
0.475 (2.1053)605.498752
0.4833 (2.069)156.948687
0.4917 (2.0339)105.761528
0.5 (2)98.426111



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ;
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')