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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 computationMon, 15 Dec 2008 03:58:06 -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/2008/Dec/15/t12293387154xgljmn2soit3hl.htm/, Retrieved Wed, 15 May 2024 04:07:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33659, Retrieved Wed, 15 May 2024 04:07:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Spectral Analysis] [] [2008-12-15 10:58:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-19 12:12:10 [006ad2c49b6a7c2ad6ab685cfc1dae56] [reply] 
Fout, je moest een tabel verkrijgen. Tweede tabel in deze link: http://www.freestatistics.org/blog/index.php?v=date/2008/Dec/13/t1229200568x9fasiirnug8ibn.htm
Hierin moet je kijken naar 2 kolommen= de kolom met PE (percentage fouten, werkelijke standaardfout) en de kolom met SE (percentage standaardfouten, wordt berekend obv het model= theoretische schatting)




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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1961782
1787447
1953757
1828167
2078223
1777226
1538059
1678452
2262924
1616451
1829222
1763216
2138777
1565784
1781485
1962103
1775358
1837255
1917824
1878651
2124030
1948811
1947985
1719466
2139078
2086587
2020001
2405555
2152069
2791310
2397287
1885473
1978324
2165120
2052877
1726766
2267082
2501737
1916630
2177682
1859283
1718749
1819181
1463556
1979279
1723911
1528538
1635412
2255789
1698773
1635959
2054968
1794346
1938855
2112672
1446965
1610773
1576815
1509935
1769046

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33659&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33659&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33659&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)2
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0167 (60)554426988.992173
0.0333 (30)879546936.5355
0.05 (20)1582233768.84968
0.0667 (15)882000082.15568
0.0833 (12)7856457038.2885
0.1 (10)8042825636.03893
0.1167 (8.5714)44443265110.8928
0.1333 (7.5)8926210885.96788
0.15 (6.6667)6077818064.09912
0.1667 (6)1501028259.58312
0.1833 (5.4545)21459925709.3286
0.2 (5)136513971359.597
0.2167 (4.6154)82542650865.28
0.2333 (4.2857)176014777996.408
0.25 (4)488254311610.027
0.2667 (3.75)329899717117.281
0.2833 (3.5294)849483714903.463
0.3 (3.3333)354792543198.536
0.3167 (3.1579)286259373577.783
0.3333 (3)1391491371340.01
0.35 (2.8571)537769177536.613
0.3667 (2.7273)409222744018.196
0.3833 (2.6087)6952394769.32535
0.4 (2.5)685525333778.605
0.4167 (2.4)2274781604780.57
0.4333 (2.3077)27891672083.5373
0.45 (2.2222)96224115441.4614
0.4667 (2.1429)650901672647.809
0.4833 (2.069)578207359295.566
0.5 (2)1174035599800.69

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 2 \tabularnewline
Degree of seasonal differencing (D) & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0167 (60) & 554426988.992173 \tabularnewline
0.0333 (30) & 879546936.5355 \tabularnewline
0.05 (20) & 1582233768.84968 \tabularnewline
0.0667 (15) & 882000082.15568 \tabularnewline
0.0833 (12) & 7856457038.2885 \tabularnewline
0.1 (10) & 8042825636.03893 \tabularnewline
0.1167 (8.5714) & 44443265110.8928 \tabularnewline
0.1333 (7.5) & 8926210885.96788 \tabularnewline
0.15 (6.6667) & 6077818064.09912 \tabularnewline
0.1667 (6) & 1501028259.58312 \tabularnewline
0.1833 (5.4545) & 21459925709.3286 \tabularnewline
0.2 (5) & 136513971359.597 \tabularnewline
0.2167 (4.6154) & 82542650865.28 \tabularnewline
0.2333 (4.2857) & 176014777996.408 \tabularnewline
0.25 (4) & 488254311610.027 \tabularnewline
0.2667 (3.75) & 329899717117.281 \tabularnewline
0.2833 (3.5294) & 849483714903.463 \tabularnewline
0.3 (3.3333) & 354792543198.536 \tabularnewline
0.3167 (3.1579) & 286259373577.783 \tabularnewline
0.3333 (3) & 1391491371340.01 \tabularnewline
0.35 (2.8571) & 537769177536.613 \tabularnewline
0.3667 (2.7273) & 409222744018.196 \tabularnewline
0.3833 (2.6087) & 6952394769.32535 \tabularnewline
0.4 (2.5) & 685525333778.605 \tabularnewline
0.4167 (2.4) & 2274781604780.57 \tabularnewline
0.4333 (2.3077) & 27891672083.5373 \tabularnewline
0.45 (2.2222) & 96224115441.4614 \tabularnewline
0.4667 (2.1429) & 650901672647.809 \tabularnewline
0.4833 (2.069) & 578207359295.566 \tabularnewline
0.5 (2) & 1174035599800.69 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33659&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]2[/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]0.0167 (60)[/C][C]554426988.992173[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]879546936.5355[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]1582233768.84968[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]882000082.15568[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]7856457038.2885[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]8042825636.03893[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]44443265110.8928[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]8926210885.96788[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]6077818064.09912[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]1501028259.58312[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]21459925709.3286[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]136513971359.597[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]82542650865.28[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]176014777996.408[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]488254311610.027[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]329899717117.281[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]849483714903.463[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]354792543198.536[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]286259373577.783[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]1391491371340.01[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]537769177536.613[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]409222744018.196[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]6952394769.32535[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]685525333778.605[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]2274781604780.57[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]27891672083.5373[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]96224115441.4614[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]650901672647.809[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]578207359295.566[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]1174035599800.69[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33659&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33659&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)2
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0167 (60)554426988.992173
0.0333 (30)879546936.5355
0.05 (20)1582233768.84968
0.0667 (15)882000082.15568
0.0833 (12)7856457038.2885
0.1 (10)8042825636.03893
0.1167 (8.5714)44443265110.8928
0.1333 (7.5)8926210885.96788
0.15 (6.6667)6077818064.09912
0.1667 (6)1501028259.58312
0.1833 (5.4545)21459925709.3286
0.2 (5)136513971359.597
0.2167 (4.6154)82542650865.28
0.2333 (4.2857)176014777996.408
0.25 (4)488254311610.027
0.2667 (3.75)329899717117.281
0.2833 (3.5294)849483714903.463
0.3 (3.3333)354792543198.536
0.3167 (3.1579)286259373577.783
0.3333 (3)1391491371340.01
0.35 (2.8571)537769177536.613
0.3667 (2.7273)409222744018.196
0.3833 (2.6087)6952394769.32535
0.4 (2.5)685525333778.605
0.4167 (2.4)2274781604780.57
0.4333 (2.3077)27891672083.5373
0.45 (2.2222)96224115441.4614
0.4667 (2.1429)650901672647.809
0.4833 (2.069)578207359295.566
0.5 (2)1174035599800.69


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; 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')