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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 computationFri, 09 Dec 2011 05:52:19 -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/09/t132342795767liikdznc92f27.htm/, Retrieved Sun, 28 Apr 2024 10:41:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153250, Retrieved Sun, 28 Apr 2024 10:41:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact204
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2010-10-06 14:13:06] [3d53bd477a917086cfdff0f854c5e476]
-   PD  [Univariate Data Series] [rozen] [2010-12-07 20:04:29] [b98453cac15ba1066b407e146608df68]
- RMPD    [(Partial) Autocorrelation Function] [Times Series - Rozen] [2011-12-09 10:44:11] [586787d3e7267c593af3e1f6b16aa21a]
- RMP         [Spectral Analysis] [Times Series] [2011-12-09 10:52:19] [a0aae37dd27f4b65e222573f53b5a13b] [Current]
- R P           [Spectral Analysis] [Times Series] [2011-12-09 10:53:58] [586787d3e7267c593af3e1f6b16aa21a]
- R P           [Spectral Analysis] [Times Series] [2011-12-09 11:01:26] [586787d3e7267c593af3e1f6b16aa21a]
- RMP           [Standard Deviation-Mean Plot] [Times Series] [2011-12-09 11:06:30] [586787d3e7267c593af3e1f6b16aa21a]
- RMP           [ARIMA Backward Selection] [Times Series] [2011-12-09 11:19:36] [586787d3e7267c593af3e1f6b16aa21a]
-    D            [ARIMA Backward Selection] [Arima] [2011-12-17 16:17:50] [f033824ca1b38a5ddbb2c3414ea3bb75]
- RMPD            [Univariate Data Series] [Sterftegevallen p...] [2011-12-17 17:11:02] [f033824ca1b38a5ddbb2c3414ea3bb75]
- RMPD            [Univariate Data Series] [aantal sterftegev...] [2011-12-17 17:22:01] [f033824ca1b38a5ddbb2c3414ea3bb75]
- R  D              [Univariate Data Series] [Gemiddelde temp p...] [2011-12-17 17:23:28] [f033824ca1b38a5ddbb2c3414ea3bb75]
- RMPD          [Maximum-likelihood Fitting - Normal Distribution] [Histogram Connected] [2011-12-09 12:22:17] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Percentiles] [QQ Plot Connected] [2011-12-09 12:24:57] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Tukey lambda PPCC Plot] [Tukey Connected] [2011-12-09 12:27:19] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Skewness and Kurtosis Test] [Skewness-Kurtosis...] [2011-12-09 12:34:26] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Maximum-likelihood Fitting - Normal Distribution] [Histogram - Seperate] [2011-12-09 12:48:43] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Percentiles] [Q-Q Plot - Seperate] [2011-12-09 12:49:50] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Tukey lambda PPCC Plot] [Tukey - Seperate] [2011-12-09 12:52:02] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Skewness and Kurtosis Test] [Skewness/Kurtosis...] [2011-12-09 12:54:08] [586787d3e7267c593af3e1f6b16aa21a]
- RMPD          [Central Tendency] [Median and Mean -...] [2011-12-09 13:03:03] [586787d3e7267c593af3e1f6b16aa21a]
- R  D            [Central Tendency] [Mean and Median -...] [2011-12-09 13:12:15] [586787d3e7267c593af3e1f6b16aa21a]
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Dataseries X:
1.35
1.91
1.31
1.19
1.3
1.14
1.1
1.02
1.11
1.18
1.24
1.36
1.29
1.73
1.41
1.15
1.31
1.15
1.08
1.1
1.14
1.24
1.33
1.49
1.38
1.96
1.36
1.24
1.35
1.23
1.09
1.08
1.33
1.35
1.38
1.5
1.47
2.09
1.52
1.29
1.52
1.27
1.35
1.29
1.41
1.39
1.45
1.53
1.45
2.11
1.53
1.38
1.54
1.35
1.29
1.33
1.47
1.47
1.54
1.59
1.5
2
1.51
1.4
1.62
1.44
1.29
1.28
1.4
1.39
1.46
1.49




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153250&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153250&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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)12
Frequency (Period)Spectrum
0.0139 (72)0.06069
0.0278 (36)0.000771
0.0417 (24)0.004989
0.0556 (18)0.001801
0.0694 (14.4)0.015836
0.0833 (12)0.693324
0.0972 (10.2857)0.022039
0.1111 (9)0.009201
0.125 (8)0.001515
0.1389 (7.2)0.001955
0.1528 (6.5455)0.020195
0.1667 (6)0.032593
0.1806 (5.5385)0.006775
0.1944 (5.1429)0.003559
0.2083 (4.8)0.004074
0.2222 (4.5)0.00072
0.2361 (4.2353)0.004204
0.25 (4)0.172952
0.2639 (3.7895)0.012043
0.2778 (3.6)0.006716
0.2917 (3.4286)0.001257
0.3056 (3.2727)0.006429
0.3194 (3.1304)0.006293
0.3333 (3)0.19441
0.3472 (2.88)0.010463
0.3611 (2.7692)0.003835
0.375 (2.6667)0.005349
0.3889 (2.5714)7.5e-05
0.4028 (2.4828)0.009623
0.4167 (2.4)0.164117
0.4306 (2.3226)0.014434
0.4444 (2.25)0.003582
0.4583 (2.1818)0.000556
0.4722 (2.1176)0.007072
0.4861 (2.0571)0.003625
0.5 (2)0.033677

\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) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0139 (72) & 0.06069 \tabularnewline
0.0278 (36) & 0.000771 \tabularnewline
0.0417 (24) & 0.004989 \tabularnewline
0.0556 (18) & 0.001801 \tabularnewline
0.0694 (14.4) & 0.015836 \tabularnewline
0.0833 (12) & 0.693324 \tabularnewline
0.0972 (10.2857) & 0.022039 \tabularnewline
0.1111 (9) & 0.009201 \tabularnewline
0.125 (8) & 0.001515 \tabularnewline
0.1389 (7.2) & 0.001955 \tabularnewline
0.1528 (6.5455) & 0.020195 \tabularnewline
0.1667 (6) & 0.032593 \tabularnewline
0.1806 (5.5385) & 0.006775 \tabularnewline
0.1944 (5.1429) & 0.003559 \tabularnewline
0.2083 (4.8) & 0.004074 \tabularnewline
0.2222 (4.5) & 0.00072 \tabularnewline
0.2361 (4.2353) & 0.004204 \tabularnewline
0.25 (4) & 0.172952 \tabularnewline
0.2639 (3.7895) & 0.012043 \tabularnewline
0.2778 (3.6) & 0.006716 \tabularnewline
0.2917 (3.4286) & 0.001257 \tabularnewline
0.3056 (3.2727) & 0.006429 \tabularnewline
0.3194 (3.1304) & 0.006293 \tabularnewline
0.3333 (3) & 0.19441 \tabularnewline
0.3472 (2.88) & 0.010463 \tabularnewline
0.3611 (2.7692) & 0.003835 \tabularnewline
0.375 (2.6667) & 0.005349 \tabularnewline
0.3889 (2.5714) & 7.5e-05 \tabularnewline
0.4028 (2.4828) & 0.009623 \tabularnewline
0.4167 (2.4) & 0.164117 \tabularnewline
0.4306 (2.3226) & 0.014434 \tabularnewline
0.4444 (2.25) & 0.003582 \tabularnewline
0.4583 (2.1818) & 0.000556 \tabularnewline
0.4722 (2.1176) & 0.007072 \tabularnewline
0.4861 (2.0571) & 0.003625 \tabularnewline
0.5 (2) & 0.033677 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153250&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]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0139 (72)[/C][C]0.06069[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]0.000771[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]0.004989[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]0.001801[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]0.015836[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0.693324[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]0.022039[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.009201[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]0.001515[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]0.001955[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]0.020195[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.032593[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]0.006775[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]0.003559[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]0.004074[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.00072[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]0.004204[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.172952[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]0.012043[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]0.006716[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]0.001257[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]0.006429[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]0.006293[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.19441[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]0.010463[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]0.003835[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]0.005349[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]7.5e-05[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]0.009623[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0.164117[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]0.014434[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.003582[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]0.000556[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]0.007072[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]0.003625[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.033677[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153250&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)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0139 (72)0.06069
0.0278 (36)0.000771
0.0417 (24)0.004989
0.0556 (18)0.001801
0.0694 (14.4)0.015836
0.0833 (12)0.693324
0.0972 (10.2857)0.022039
0.1111 (9)0.009201
0.125 (8)0.001515
0.1389 (7.2)0.001955
0.1528 (6.5455)0.020195
0.1667 (6)0.032593
0.1806 (5.5385)0.006775
0.1944 (5.1429)0.003559
0.2083 (4.8)0.004074
0.2222 (4.5)0.00072
0.2361 (4.2353)0.004204
0.25 (4)0.172952
0.2639 (3.7895)0.012043
0.2778 (3.6)0.006716
0.2917 (3.4286)0.001257
0.3056 (3.2727)0.006429
0.3194 (3.1304)0.006293
0.3333 (3)0.19441
0.3472 (2.88)0.010463
0.3611 (2.7692)0.003835
0.375 (2.6667)0.005349
0.3889 (2.5714)7.5e-05
0.4028 (2.4828)0.009623
0.4167 (2.4)0.164117
0.4306 (2.3226)0.014434
0.4444 (2.25)0.003582
0.4583 (2.1818)0.000556
0.4722 (2.1176)0.007072
0.4861 (2.0571)0.003625
0.5 (2)0.033677



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; 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')