Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationTue, 09 Dec 2008 08:06:02 -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/09/t1228835222adfg0cjk35zr0t9.htm/, Retrieved Sun, 19 May 2024 12:19:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31498, Retrieved Sun, 19 May 2024 12:19:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Spectral Analysis] [step3] [2008-12-09 15:06:02] [a413cf7744efd6bb212437a3916e2f23] [Current]
Feedback Forum
2008-12-14 13:29:52 [Gert-Jan Geudens] [reply
Foutieve berekening, je moet lambda hier gelijkstellen aan 1.
2008-12-14 13:30:42 [Gert-Jan Geudens] [reply
We willen nog even aan onze vorige feedback toevoegen dat we deze lambda is 1, kunnen afleiden uit de conclusies betreffende de eerste stap.
2008-12-15 14:29:10 [Jonas Scheltjens] [reply
De student heeft hier enkel de link en de grafiek gegeven zonder enige degelijke uitleg of verklaring (afgezien van “Seizoenaliteit is al wat afgenomen maar nog niet helemaal.”). Aangezien het niet de taak is van de persoon die de assessments doet om deze taak voor de student te maken, verwijs ik dan ook voor de algemene en volledige uitleg voor deze Step naar Step 3 voor de unemployment data, dewelke ik zeer uitgebreid heb besproken en waar alle informatie in staat om deze vraag correct op te lossen.

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Dataseries X:
1846.5
2796.3
2895.6
2472.2
2584.4
2630.4
2663.1
3176.2
2856.7
2551.4
3088.7
2628.3
2226.2
3023.6
3077.9
3084.1
2990.3
2949.6
3014.7
3517.7
3121.2
3067.4
3174.6
2676.3
2424
3195.1
3146.6
3506.7
3528.5
3365.1
3153
3843.3
3123.2
3361.1
3481.9
2970.5
2537
3257.6
3301.3
3391.6
2933.6
3283.2
3139.7
3486.4
3202.2
3294.4
3550.3
3279.3
2678.6
3451.4
3977.1
3814.8
3310.5
3971.8
4051.9
4057.6
4391.4
3628.9
4092.2
3822.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31498&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31498&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)0.1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0208 (48)0.324433
0.0417 (24)0.187686
0.0625 (16)0.072721
0.0833 (12)0.012337
0.1042 (9.6)0.062913
0.125 (8)0.007569
0.1458 (6.8571)0.042935
0.1667 (6)0.00159
0.1875 (5.3333)0.001875
0.2083 (4.8)0.000504
0.2292 (4.3636)0.03847
0.25 (4)0.000357
0.2708 (3.6923)0.013269
0.2917 (3.4286)0.013536
0.3125 (3.2)0.054317
0.3333 (3)0.031859
0.3542 (2.8235)0.033462
0.375 (2.6667)0.009077
0.3958 (2.5263)0.019477
0.4167 (2.4)0.00562
0.4375 (2.2857)0.012857
0.4583 (2.1818)0.00583
0.4792 (2.087)0.032622
0.5 (2)8.5e-05

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 0.1 \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) & 0.324433 \tabularnewline
0.0417 (24) & 0.187686 \tabularnewline
0.0625 (16) & 0.072721 \tabularnewline
0.0833 (12) & 0.012337 \tabularnewline
0.1042 (9.6) & 0.062913 \tabularnewline
0.125 (8) & 0.007569 \tabularnewline
0.1458 (6.8571) & 0.042935 \tabularnewline
0.1667 (6) & 0.00159 \tabularnewline
0.1875 (5.3333) & 0.001875 \tabularnewline
0.2083 (4.8) & 0.000504 \tabularnewline
0.2292 (4.3636) & 0.03847 \tabularnewline
0.25 (4) & 0.000357 \tabularnewline
0.2708 (3.6923) & 0.013269 \tabularnewline
0.2917 (3.4286) & 0.013536 \tabularnewline
0.3125 (3.2) & 0.054317 \tabularnewline
0.3333 (3) & 0.031859 \tabularnewline
0.3542 (2.8235) & 0.033462 \tabularnewline
0.375 (2.6667) & 0.009077 \tabularnewline
0.3958 (2.5263) & 0.019477 \tabularnewline
0.4167 (2.4) & 0.00562 \tabularnewline
0.4375 (2.2857) & 0.012857 \tabularnewline
0.4583 (2.1818) & 0.00583 \tabularnewline
0.4792 (2.087) & 0.032622 \tabularnewline
0.5 (2) & 8.5e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31498&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]0.1[/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]0.324433[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]0.187686[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]0.072721[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0.012337[/C][/ROW]
[ROW][C]0.1042 (9.6)[/C][C]0.062913[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]0.007569[/C][/ROW]
[ROW][C]0.1458 (6.8571)[/C][C]0.042935[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.00159[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]0.001875[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]0.000504[/C][/ROW]
[ROW][C]0.2292 (4.3636)[/C][C]0.03847[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.000357[/C][/ROW]
[ROW][C]0.2708 (3.6923)[/C][C]0.013269[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]0.013536[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]0.054317[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.031859[/C][/ROW]
[ROW][C]0.3542 (2.8235)[/C][C]0.033462[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]0.009077[/C][/ROW]
[ROW][C]0.3958 (2.5263)[/C][C]0.019477[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0.00562[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]0.012857[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]0.00583[/C][/ROW]
[ROW][C]0.4792 (2.087)[/C][C]0.032622[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]8.5e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31498&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)0.1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0208 (48)0.324433
0.0417 (24)0.187686
0.0625 (16)0.072721
0.0833 (12)0.012337
0.1042 (9.6)0.062913
0.125 (8)0.007569
0.1458 (6.8571)0.042935
0.1667 (6)0.00159
0.1875 (5.3333)0.001875
0.2083 (4.8)0.000504
0.2292 (4.3636)0.03847
0.25 (4)0.000357
0.2708 (3.6923)0.013269
0.2917 (3.4286)0.013536
0.3125 (3.2)0.054317
0.3333 (3)0.031859
0.3542 (2.8235)0.033462
0.375 (2.6667)0.009077
0.3958 (2.5263)0.019477
0.4167 (2.4)0.00562
0.4375 (2.2857)0.012857
0.4583 (2.1818)0.00583
0.4792 (2.087)0.032622
0.5 (2)8.5e-05



Parameters (Session):
par1 = 0.1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 0.1 ; 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')