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Author's title

Author

*Unverified author*

R Software Module

rwasp_spectrum.wasp

Title produced by software

Spectral Analysis

Date of computation

Tue, 09 Dec 2008 12:54:42 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228852527vygde2zrbmyfyn0.htm/, Retrieved Sun, 19 May 2024 10:10:33 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31754, Retrieved Sun, 19 May 2024 10:10:33 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

k_vanderheggen

Estimated Impact

180

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F       [Spectral Analysis] [eigen tijdreeks p...] [2008-12-09 19:54:42] [2731fa16c50d4727d0297daf34574cde] [Current]
-   P     [Spectral Analysis] [paper periodogram] [2008-12-14 16:25:55] [1640119c345fbfa2091dc1243f79f7a6] 
-   P     [Spectral Analysis] [] [2008-12-16 14:16:33] [74be16979710d4c4e7c6647856088456] 

Feedback Forum

2008-12-14 14:00:55 [Jasmine Hendrikx] [reply] 
Evaluatie stap 3 Spectral Analysis: 
De berekening is goed uitgevoerd met d=2 en D=0. Er is inderdaad een hele verbetering opgetreden, zoals de student correct vermeldt. De langetermijntrend is nu verdwenen (geen steile lijn meer aan de linkerkant). De lijn ligt nu inderdaad in het betrouwbaarheidsinterval, maar als men het beginpunt van de lijn op de diagonaal zou zetten, zou je zien dat er toch nog een deel buiten het betrouwbaarheidsinterval zou vallen, waardoor er dus nog wel een zekere verklaarbaarheid zou overblijven. Er zouden bijvoorbeeld ook nog conjunctuurbewegingen in kunnen zitten. Dit is ook vrij logisch, aangezien er hier gewerkt wordt met werkloosheidscijfers. Er lijkt precies toch nog seizoenaliteit aanwezig te zijn door de trappen, maar er treedt inderdaad geen verbetering op met D=1.  
2008-12-16 14:18:01 [Peter Van Doninck] [reply] 
http://www.freestatistics.org/blog/index.php?v=date/2008/Dec/16/t1229437024c00ueym25v1s3jb.htm 
 
dit is de correcte berekening! Hier valt het op dat de afwijking naar boven groter is dan bij de versie die de studente verbeterd heeft. Het valt hier op dat we te maken hebben met een AR-proces (afwijking naar boven toe)

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Dataseries X:

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Histogram

Boxplots

5.5
5.3
5.2
5.3
5.3
5
4.8
4.9
5.3
6
6.2
6.4
6.4
6.4
6.2
6.1
6
5.9
6.2
6.2
6.4
6.8
6.9
7
7
6.9
6.7
6.6
6.5
6.4
6.5
6.5
6.6
6.7
6.8
7.2
7.6
7.6
7.3
6.4
6.1
6.3
7.1
7.5
7.4
7.1
6.8
6.9
7.2
7.4
7.3
6.9
6.9
6.8
7.1
7.2
7.1
7
6.9
7
7.4
7.5
7.5
7.4
7.3
7
6.7
6.5
6.5
6.5
6.6
6.8
6.9
6.9
6.8
6.8
6.5
6.1
6
5.9
5.8
5.9
5.9
6.2
6.3
6.2
6
5.8
5.5
5.5
5.7
5.8

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=31754&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=31754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31754&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Raw Periodogram
Parameter	Value
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
0.0111 (90)	0.000282
0.0222 (45)	0.000633
0.0333 (30)	0.000158
0.0444 (22.5)	0.001322
0.0556 (18)	0.000744
0.0667 (15)	0.006079
0.0778 (12.8571)	0.12711
0.0889 (11.25)	0.010577
0.1 (10)	0.08693
0.1111 (9)	0.053983
0.1222 (8.1818)	0.069496
0.1333 (7.5)	0.014437
0.1444 (6.9231)	0.18808
0.1556 (6.4286)	0.330672
0.1667 (6)	0.244071
0.1778 (5.625)	0.284337
0.1889 (5.2941)	0.089366
0.2 (5)	0.029505
0.2111 (4.7368)	0.075021
0.2222 (4.5)	0.001595
0.2333 (4.2857)	0.0058
0.2444 (4.0909)	0.015779
0.2556 (3.913)	0.04884
0.2667 (3.75)	0.033989
0.2778 (3.6)	0.020917
0.2889 (3.4615)	0.000835
0.3 (3.3333)	0.029574
0.3111 (3.2143)	0.001831
0.3222 (3.1034)	0.014875
0.3333 (3)	0.131098
0.3444 (2.9032)	0.019225
0.3556 (2.8125)	0.056314
0.3667 (2.7273)	0.028275
0.3778 (2.6471)	0.034443
0.3889 (2.5714)	0.037817
0.4 (2.5)	0.04182
0.4111 (2.4324)	0.171217
0.4222 (2.3684)	0.124223
0.4333 (2.3077)	0.017208
0.4444 (2.25)	0.080965
0.4556 (2.1951)	0.01984
0.4667 (2.1429)	0.004898
0.4778 (2.093)	0.001774
0.4889 (2.0455)	0.151875
0.5 (2)	0.022386

\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
0.0111 (90) & 0.000282 \tabularnewline
0.0222 (45) & 0.000633 \tabularnewline
0.0333 (30) & 0.000158 \tabularnewline
0.0444 (22.5) & 0.001322 \tabularnewline
0.0556 (18) & 0.000744 \tabularnewline
0.0667 (15) & 0.006079 \tabularnewline
0.0778 (12.8571) & 0.12711 \tabularnewline
0.0889 (11.25) & 0.010577 \tabularnewline
0.1 (10) & 0.08693 \tabularnewline
0.1111 (9) & 0.053983 \tabularnewline
0.1222 (8.1818) & 0.069496 \tabularnewline
0.1333 (7.5) & 0.014437 \tabularnewline
0.1444 (6.9231) & 0.18808 \tabularnewline
0.1556 (6.4286) & 0.330672 \tabularnewline
0.1667 (6) & 0.244071 \tabularnewline
0.1778 (5.625) & 0.284337 \tabularnewline
0.1889 (5.2941) & 0.089366 \tabularnewline
0.2 (5) & 0.029505 \tabularnewline
0.2111 (4.7368) & 0.075021 \tabularnewline
0.2222 (4.5) & 0.001595 \tabularnewline
0.2333 (4.2857) & 0.0058 \tabularnewline
0.2444 (4.0909) & 0.015779 \tabularnewline
0.2556 (3.913) & 0.04884 \tabularnewline
0.2667 (3.75) & 0.033989 \tabularnewline
0.2778 (3.6) & 0.020917 \tabularnewline
0.2889 (3.4615) & 0.000835 \tabularnewline
0.3 (3.3333) & 0.029574 \tabularnewline
0.3111 (3.2143) & 0.001831 \tabularnewline
0.3222 (3.1034) & 0.014875 \tabularnewline
0.3333 (3) & 0.131098 \tabularnewline
0.3444 (2.9032) & 0.019225 \tabularnewline
0.3556 (2.8125) & 0.056314 \tabularnewline
0.3667 (2.7273) & 0.028275 \tabularnewline
0.3778 (2.6471) & 0.034443 \tabularnewline
0.3889 (2.5714) & 0.037817 \tabularnewline
0.4 (2.5) & 0.04182 \tabularnewline
0.4111 (2.4324) & 0.171217 \tabularnewline
0.4222 (2.3684) & 0.124223 \tabularnewline
0.4333 (2.3077) & 0.017208 \tabularnewline
0.4444 (2.25) & 0.080965 \tabularnewline
0.4556 (2.1951) & 0.01984 \tabularnewline
0.4667 (2.1429) & 0.004898 \tabularnewline
0.4778 (2.093) & 0.001774 \tabularnewline
0.4889 (2.0455) & 0.151875 \tabularnewline
0.5 (2) & 0.022386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31754&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]0.0111 (90)[/C][C]0.000282[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]0.000633[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]0.000158[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]0.001322[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]0.000744[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]0.006079[/C][/ROW]
[ROW][C]0.0778 (12.8571)[/C][C]0.12711[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]0.010577[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]0.08693[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.053983[/C][/ROW]
[ROW][C]0.1222 (8.1818)[/C][C]0.069496[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]0.014437[/C][/ROW]
[ROW][C]0.1444 (6.9231)[/C][C]0.18808[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]0.330672[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.244071[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]0.284337[/C][/ROW]
[ROW][C]0.1889 (5.2941)[/C][C]0.089366[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]0.029505[/C][/ROW]
[ROW][C]0.2111 (4.7368)[/C][C]0.075021[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.001595[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]0.0058[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]0.015779[/C][/ROW]
[ROW][C]0.2556 (3.913)[/C][C]0.04884[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]0.033989[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]0.020917[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]0.000835[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]0.029574[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]0.001831[/C][/ROW]
[ROW][C]0.3222 (3.1034)[/C][C]0.014875[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.131098[/C][/ROW]
[ROW][C]0.3444 (2.9032)[/C][C]0.019225[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]0.056314[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]0.028275[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]0.034443[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]0.037817[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]0.04182[/C][/ROW]
[ROW][C]0.4111 (2.4324)[/C][C]0.171217[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]0.124223[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]0.017208[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.080965[/C][/ROW]
[ROW][C]0.4556 (2.1951)[/C][C]0.01984[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]0.004898[/C][/ROW]
[ROW][C]0.4778 (2.093)[/C][C]0.001774[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]0.151875[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.022386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31754&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
Parameter	Value
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
0.0111 (90)	0.000282
0.0222 (45)	0.000633
0.0333 (30)	0.000158
0.0444 (22.5)	0.001322
0.0556 (18)	0.000744
0.0667 (15)	0.006079
0.0778 (12.8571)	0.12711
0.0889 (11.25)	0.010577
0.1 (10)	0.08693
0.1111 (9)	0.053983
0.1222 (8.1818)	0.069496
0.1333 (7.5)	0.014437
0.1444 (6.9231)	0.18808
0.1556 (6.4286)	0.330672
0.1667 (6)	0.244071
0.1778 (5.625)	0.284337
0.1889 (5.2941)	0.089366
0.2 (5)	0.029505
0.2111 (4.7368)	0.075021
0.2222 (4.5)	0.001595
0.2333 (4.2857)	0.0058
0.2444 (4.0909)	0.015779
0.2556 (3.913)	0.04884
0.2667 (3.75)	0.033989
0.2778 (3.6)	0.020917
0.2889 (3.4615)	0.000835
0.3 (3.3333)	0.029574
0.3111 (3.2143)	0.001831
0.3222 (3.1034)	0.014875
0.3333 (3)	0.131098
0.3444 (2.9032)	0.019225
0.3556 (2.8125)	0.056314
0.3667 (2.7273)	0.028275
0.3778 (2.6471)	0.034443
0.3889 (2.5714)	0.037817
0.4 (2.5)	0.04182
0.4111 (2.4324)	0.171217
0.4222 (2.3684)	0.124223
0.4333 (2.3077)	0.017208
0.4444 (2.25)	0.080965
0.4556 (2.1951)	0.01984
0.4667 (2.1429)	0.004898
0.4778 (2.093)	0.001774
0.4889 (2.0455)	0.151875
0.5 (2)	0.022386

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code