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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 computationThu, 17 Dec 2009 05:14:53 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/17/t1261052134b5eln0fk6adf7so.htm/, Retrieved Mon, 12 May 2025 09:34:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68783, Retrieved Mon, 12 May 2025 09:34:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact236

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [ws8] [2009-11-24 20:12:27] [8b1aef4e7013bd33fbc2a5833375c5f5]
-    D          [(Partial) Autocorrelation Function] [SHw WS8] [2009-11-25 18:52:43] [af2352cd9a951bedd08ebe247d0de1a2]
- RMPD            [Bivariate Granger Causality] [] [2009-12-11 18:26:06] [09f192433169b2c787c4a71fde86e883]
- RMPD                [Spectral Analysis] [] [2009-12-17 12:14:53] [71596e6a53ccce532e52aaf6113616ef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1322.4
1089.2
1147.3
1196.4
1190.2
1146
1139.8
1045.6
1050.9
1117.3
1120
1052.1
1065.8
1092.5
1422
1367.5
1136.3
1293.7
1154.8
1206.7
1199
1265
1247.1
1116.5
1153.9
1077.4
1132.5
1058.8
1195.1
1263.4
1023.1
1141
1116.3
1135.6
1210.5
1230
1136.5
1068.7
1372.5
1049.9
1302.2
1305.9
1173.5
1277.4
1238.6
1508.6
1423.4
1375.1
1344.1
1287.5
1446.9
1451
1604.4
1501.5
1522.8
1328
1420.5
1648
1631.1
1396.6
1663.4
1283
1582.4
1785.2
1853.6
1994.1
2042.8
1586.1
1942.4
1763.6
1819.9
1836
1449.9
1513.3
1677.7
1494.4
1375.3
1577.7
1537.7
1356.6
1469.6

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'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68783&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68783&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68783&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'Gwilym Jenkins' @ 72.249.127.135






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)12
Frequency (Period)Spectrum
0.0125 (80)3450.40218
0.025 (40)4124.310536
0.0375 (26.6667)5677.561319
0.05 (20)2121.337958
0.0625 (16)12006.510559
0.075 (13.3333)6802.431452
0.0875 (11.4286)1329.525019
0.1 (10)5026.553558
0.1125 (8.8889)1522.796507
0.125 (8)567.107674
0.1375 (7.2727)15199.000204
0.15 (6.6667)3390.083275
0.1625 (6.1538)84009.907087
0.175 (5.7143)16482.167744
0.1875 (5.3333)8916.75599
0.2 (5)20819.661857
0.2125 (4.7059)10389.287666
0.225 (4.4444)265.597
0.2375 (4.2105)10195.688725
0.25 (4)38411.315966
0.2625 (3.8095)7365.135499
0.275 (3.6364)4291.263673
0.2875 (3.4783)18429.710475
0.3 (3.3333)30288.460749
0.3125 (3.2)8713.866848
0.325 (3.0769)32643.429161
0.3375 (2.963)31825.514433
0.35 (2.8571)157772.053794
0.3625 (2.7586)76187.374085
0.375 (2.6667)49474.926207
0.3875 (2.5806)66978.299921
0.4 (2.5)22207.765739
0.4125 (2.4242)47305.707689
0.425 (2.3529)113602.979959
0.4375 (2.2857)31156.907389
0.45 (2.2222)2917.936716
0.4625 (2.1622)40084.658271
0.475 (2.1053)17307.534911
0.4875 (2.0513)50278.637639
0.5 (2)79582.534864

\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) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0125 (80) & 3450.40218 \tabularnewline
0.025 (40) & 4124.310536 \tabularnewline
0.0375 (26.6667) & 5677.561319 \tabularnewline
0.05 (20) & 2121.337958 \tabularnewline
0.0625 (16) & 12006.510559 \tabularnewline
0.075 (13.3333) & 6802.431452 \tabularnewline
0.0875 (11.4286) & 1329.525019 \tabularnewline
0.1 (10) & 5026.553558 \tabularnewline
0.1125 (8.8889) & 1522.796507 \tabularnewline
0.125 (8) & 567.107674 \tabularnewline
0.1375 (7.2727) & 15199.000204 \tabularnewline
0.15 (6.6667) & 3390.083275 \tabularnewline
0.1625 (6.1538) & 84009.907087 \tabularnewline
0.175 (5.7143) & 16482.167744 \tabularnewline
0.1875 (5.3333) & 8916.75599 \tabularnewline
0.2 (5) & 20819.661857 \tabularnewline
0.2125 (4.7059) & 10389.287666 \tabularnewline
0.225 (4.4444) & 265.597 \tabularnewline
0.2375 (4.2105) & 10195.688725 \tabularnewline
0.25 (4) & 38411.315966 \tabularnewline
0.2625 (3.8095) & 7365.135499 \tabularnewline
0.275 (3.6364) & 4291.263673 \tabularnewline
0.2875 (3.4783) & 18429.710475 \tabularnewline
0.3 (3.3333) & 30288.460749 \tabularnewline
0.3125 (3.2) & 8713.866848 \tabularnewline
0.325 (3.0769) & 32643.429161 \tabularnewline
0.3375 (2.963) & 31825.514433 \tabularnewline
0.35 (2.8571) & 157772.053794 \tabularnewline
0.3625 (2.7586) & 76187.374085 \tabularnewline
0.375 (2.6667) & 49474.926207 \tabularnewline
0.3875 (2.5806) & 66978.299921 \tabularnewline
0.4 (2.5) & 22207.765739 \tabularnewline
0.4125 (2.4242) & 47305.707689 \tabularnewline
0.425 (2.3529) & 113602.979959 \tabularnewline
0.4375 (2.2857) & 31156.907389 \tabularnewline
0.45 (2.2222) & 2917.936716 \tabularnewline
0.4625 (2.1622) & 40084.658271 \tabularnewline
0.475 (2.1053) & 17307.534911 \tabularnewline
0.4875 (2.0513) & 50278.637639 \tabularnewline
0.5 (2) & 79582.534864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68783&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]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0125 (80)[/C][C]3450.40218[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]4124.310536[/C][/ROW]
[ROW][C]0.0375 (26.6667)[/C][C]5677.561319[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]2121.337958[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]12006.510559[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]6802.431452[/C][/ROW]
[ROW][C]0.0875 (11.4286)[/C][C]1329.525019[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]5026.553558[/C][/ROW]
[ROW][C]0.1125 (8.8889)[/C][C]1522.796507[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]567.107674[/C][/ROW]
[ROW][C]0.1375 (7.2727)[/C][C]15199.000204[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]3390.083275[/C][/ROW]
[ROW][C]0.1625 (6.1538)[/C][C]84009.907087[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]16482.167744[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]8916.75599[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]20819.661857[/C][/ROW]
[ROW][C]0.2125 (4.7059)[/C][C]10389.287666[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]265.597[/C][/ROW]
[ROW][C]0.2375 (4.2105)[/C][C]10195.688725[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]38411.315966[/C][/ROW]
[ROW][C]0.2625 (3.8095)[/C][C]7365.135499[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]4291.263673[/C][/ROW]
[ROW][C]0.2875 (3.4783)[/C][C]18429.710475[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]30288.460749[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]8713.866848[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]32643.429161[/C][/ROW]
[ROW][C]0.3375 (2.963)[/C][C]31825.514433[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]157772.053794[/C][/ROW]
[ROW][C]0.3625 (2.7586)[/C][C]76187.374085[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]49474.926207[/C][/ROW]
[ROW][C]0.3875 (2.5806)[/C][C]66978.299921[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]22207.765739[/C][/ROW]
[ROW][C]0.4125 (2.4242)[/C][C]47305.707689[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]113602.979959[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]31156.907389[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]2917.936716[/C][/ROW]
[ROW][C]0.4625 (2.1622)[/C][C]40084.658271[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]17307.534911[/C][/ROW]
[ROW][C]0.4875 (2.0513)[/C][C]50278.637639[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]79582.534864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68783&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68783&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)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0125 (80)3450.40218
0.025 (40)4124.310536
0.0375 (26.6667)5677.561319
0.05 (20)2121.337958
0.0625 (16)12006.510559
0.075 (13.3333)6802.431452
0.0875 (11.4286)1329.525019
0.1 (10)5026.553558
0.1125 (8.8889)1522.796507
0.125 (8)567.107674
0.1375 (7.2727)15199.000204
0.15 (6.6667)3390.083275
0.1625 (6.1538)84009.907087
0.175 (5.7143)16482.167744
0.1875 (5.3333)8916.75599
0.2 (5)20819.661857
0.2125 (4.7059)10389.287666
0.225 (4.4444)265.597
0.2375 (4.2105)10195.688725
0.25 (4)38411.315966
0.2625 (3.8095)7365.135499
0.275 (3.6364)4291.263673
0.2875 (3.4783)18429.710475
0.3 (3.3333)30288.460749
0.3125 (3.2)8713.866848
0.325 (3.0769)32643.429161
0.3375 (2.963)31825.514433
0.35 (2.8571)157772.053794
0.3625 (2.7586)76187.374085
0.375 (2.6667)49474.926207
0.3875 (2.5806)66978.299921
0.4 (2.5)22207.765739
0.4125 (2.4242)47305.707689
0.425 (2.3529)113602.979959
0.4375 (2.2857)31156.907389
0.45 (2.2222)2917.936716
0.4625 (2.1622)40084.658271
0.475 (2.1053)17307.534911
0.4875 (2.0513)50278.637639
0.5 (2)79582.534864


Figures (Output of Computation)

Input Parameters & R Code

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