Free Statistics

of Irreproducible Research!

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, 01 Dec 2008 12:05:35 -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/01/t1228158553grat88119yyig6w.htm/, Retrieved Sun, 05 May 2024 11:53:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27183, Retrieved Sun, 05 May 2024 11:53:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact258
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [NSTS_Q5] [2008-11-30 17:55:01] [9f5bfe3b95f9ec3d2ed4c0a560a9648a]
F RMPD      [Spectral Analysis] [NSTS_Q7 (woningen)] [2008-12-01 19:05:35] [a9e6d7cd6e144e8b311d9f96a24c5a25] [Current]
Feedback Forum
2008-12-08 17:06:25 [Sandra Hofmans] [reply
We gaan Lambda introduceren om zo de variantie gelijk te krijgen. Het Standard Deviation Plot gaat na of de spreiding afhankelijk is van het niveau van de tijdreeks. In de eerste tabel staat de vergelijking van de regressielijn die we door de punten van de grafiek kunnen tekenen geschreven. In de 2e tabel staat diezelfde regresievergelijking maar dan in de logaritmische vorm.

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Dataseries X:
2916
3180
4151
4023
3431
3874
2617
3580
5267
3832
3441
3228
3397
3971
4625
4486
4131
4686
3174
4282
4209
4159
3936
3153
3620
4227
4441
4808
4850
5040
3546
4669
5410
5134
4864
3999
4459
4622
5360
4658
5173
4845
3325
4720
4895
5071
4895
3805
4187
4435
4475
4774
5161
4529
3284
4303
4610
4691
4200
3471




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27183&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27183&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27183&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







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
0.0208 (48)618433.536215
0.0417 (24)1279174.432214
0.0625 (16)346637.639932
0.0833 (12)5953.797102
0.1042 (9.6)143289.271802
0.125 (8)6506.385137
0.1458 (6.8571)65319.079224
0.1667 (6)171295.051809
0.1875 (5.3333)110888.666835
0.2083 (4.8)279090.235928
0.2292 (4.3636)5764.69356
0.25 (4)5099.519495
0.2708 (3.6923)68318.794727
0.2917 (3.4286)165554.308117
0.3125 (3.2)105798.971617
0.3333 (3)250997.29363
0.3542 (2.8235)32544.856295
0.375 (2.6667)574638.23616
0.3958 (2.5263)15104.494688
0.4167 (2.4)47302.248683
0.4375 (2.2857)67734.10909
0.4583 (2.1818)237416.367915
0.4792 (2.087)144064.097201
0.5 (2)2847.350993

\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
0.0208 (48) & 618433.536215 \tabularnewline
0.0417 (24) & 1279174.432214 \tabularnewline
0.0625 (16) & 346637.639932 \tabularnewline
0.0833 (12) & 5953.797102 \tabularnewline
0.1042 (9.6) & 143289.271802 \tabularnewline
0.125 (8) & 6506.385137 \tabularnewline
0.1458 (6.8571) & 65319.079224 \tabularnewline
0.1667 (6) & 171295.051809 \tabularnewline
0.1875 (5.3333) & 110888.666835 \tabularnewline
0.2083 (4.8) & 279090.235928 \tabularnewline
0.2292 (4.3636) & 5764.69356 \tabularnewline
0.25 (4) & 5099.519495 \tabularnewline
0.2708 (3.6923) & 68318.794727 \tabularnewline
0.2917 (3.4286) & 165554.308117 \tabularnewline
0.3125 (3.2) & 105798.971617 \tabularnewline
0.3333 (3) & 250997.29363 \tabularnewline
0.3542 (2.8235) & 32544.856295 \tabularnewline
0.375 (2.6667) & 574638.23616 \tabularnewline
0.3958 (2.5263) & 15104.494688 \tabularnewline
0.4167 (2.4) & 47302.248683 \tabularnewline
0.4375 (2.2857) & 67734.10909 \tabularnewline
0.4583 (2.1818) & 237416.367915 \tabularnewline
0.4792 (2.087) & 144064.097201 \tabularnewline
0.5 (2) & 2847.350993 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27183&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]0.0208 (48)[/C][C]618433.536215[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]1279174.432214[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]346637.639932[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]5953.797102[/C][/ROW]
[ROW][C]0.1042 (9.6)[/C][C]143289.271802[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]6506.385137[/C][/ROW]
[ROW][C]0.1458 (6.8571)[/C][C]65319.079224[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]171295.051809[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]110888.666835[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]279090.235928[/C][/ROW]
[ROW][C]0.2292 (4.3636)[/C][C]5764.69356[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]5099.519495[/C][/ROW]
[ROW][C]0.2708 (3.6923)[/C][C]68318.794727[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]165554.308117[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]105798.971617[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]250997.29363[/C][/ROW]
[ROW][C]0.3542 (2.8235)[/C][C]32544.856295[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]574638.23616[/C][/ROW]
[ROW][C]0.3958 (2.5263)[/C][C]15104.494688[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]47302.248683[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]67734.10909[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]237416.367915[/C][/ROW]
[ROW][C]0.4792 (2.087)[/C][C]144064.097201[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]2847.350993[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27183&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27183&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
0.0208 (48)618433.536215
0.0417 (24)1279174.432214
0.0625 (16)346637.639932
0.0833 (12)5953.797102
0.1042 (9.6)143289.271802
0.125 (8)6506.385137
0.1458 (6.8571)65319.079224
0.1667 (6)171295.051809
0.1875 (5.3333)110888.666835
0.2083 (4.8)279090.235928
0.2292 (4.3636)5764.69356
0.25 (4)5099.519495
0.2708 (3.6923)68318.794727
0.2917 (3.4286)165554.308117
0.3125 (3.2)105798.971617
0.3333 (3)250997.29363
0.3542 (2.8235)32544.856295
0.375 (2.6667)574638.23616
0.3958 (2.5263)15104.494688
0.4167 (2.4)47302.248683
0.4375 (2.2857)67734.10909
0.4583 (2.1818)237416.367915
0.4792 (2.087)144064.097201
0.5 (2)2847.350993



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; par5 = 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')