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Author's title

Paper: spectral analyis werkloosheid 31/01/2002 - 31/12/2007 met d = 1 en D...

Author*Unverified author*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationFri, 05 Dec 2008 04:46:39 -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/05/t12284777070gwssfb3ace2mbk.htm/, Retrieved Thu, 16 May 2024 07:04:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29196, Retrieved Thu, 16 May 2024 07:04:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 10:20:24] [27f46dbe13ae2811dfd3a6f3c54d4d50]
F   PD  [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 10:26:40] [27f46dbe13ae2811dfd3a6f3c54d4d50]
F   PD    [(Partial) Autocorrelation Function] [Paper: werklooshe...] [2008-12-05 10:43:32] [74be16979710d4c4e7c6647856088456]
F RMP       [Spectral Analysis] [paper: spectral a...] [2008-12-05 11:18:29] [74be16979710d4c4e7c6647856088456]
-   P         [Spectral Analysis] [Paper spectral an...] [2008-12-05 11:38:42] [74be16979710d4c4e7c6647856088456]
-               [Spectral Analysis] [Paper spectral an...] [2008-12-05 11:44:28] [74be16979710d4c4e7c6647856088456]
F                   [Spectral Analysis] [Paper: spectral a...] [2008-12-05 11:46:39] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F   P                 [Spectral Analysis] [Paper: spectral a...] [2008-12-05 11:50:13] [74be16979710d4c4e7c6647856088456]
F RMP                   [Standard Deviation-Mean Plot] [Paper: SD mean-pl...] [2008-12-05 13:05:29] [74be16979710d4c4e7c6647856088456]
-                         [Standard Deviation-Mean Plot] [paper stan dev me...] [2008-12-16 17:54:29] [5de5fb433ddcb9578e0fa830f795b7e9]
-    D                      [Standard Deviation-Mean Plot] [paper sdmp werk 20] [2008-12-18 13:23:55] [5de5fb433ddcb9578e0fa830f795b7e9]
-                       [Spectral Analysis] [paper spect D,d 1...] [2008-12-16 19:34:27] [cffae85c0a86f346d9df0bc892725b8f]
-    D                    [Spectral Analysis] [paper spec D,d 1,...] [2008-12-18 14:27:52] [5de5fb433ddcb9578e0fa830f795b7e9]
Feedback Forum
2008-12-15 18:05:43 [Kevin Truyts] [reply
De student heeft een juiste conclusie getrokken, maar volgens mij ligt de grafiek een stukje buiten het interval ten gevolge van seizonaliteit en niet ten gevolge van conjunctuur.
2008-12-16 06:48:48 [Nilay Erdogdu] [reply
in de raw periodogram zien we op een het einde een sprong, deze wijst op een sterke mate aan seizonaliteit. In de cumulatieve periodogram zien we dat de snel steigende curve weggewerkt is. De LTtrend is eruit gehaald. Er is echter nog wel een sterke golfbeweging aanwezig met een lange periode, deze wijst op conjunctuur.

Post a new message
Dataseries X:
95.20
95.00
94.00
92.20
91.00
91.20
103.40
105.00
104.60
103.80
101.80
102.40
103.80
103.40
102.00
101.80
100.20
101.40
113.80
116.00
115.60
113.00
109.40
111.00
112.40
112.20
111.00
108.80
107.40
108.60
118.80
122.20
122.60
122.20
118.80
119.00
118.20
117.80
116.80
114.60
113.40
113.80
124.20
125.80
125.60
122.40
119.00
119.40
118.60
118.00
116.00
114.80
114.60
114.60
124.00
125.20
124.00
117.60
113.20
111.40
112.20
109.80
106.40
105.20
102.20
99.80
111.00
113.00
108.40
105.40
102.00
102.80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29196&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]0 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=29196&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29196&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 time0 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)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0139 (72)0.529718
0.0278 (36)1.499673
0.0417 (24)1.963919
0.0556 (18)2.682549
0.0694 (14.4)0.083688
0.0833 (12)105.94798
0.0972 (10.2857)2.636439
0.1111 (9)1.339014
0.125 (8)0.000484
0.1389 (7.2)4.008439
0.1528 (6.5455)0.714812
0.1667 (6)201.038673
0.1806 (5.5385)0.38107
0.1944 (5.1429)1.295898
0.2083 (4.8)0.602836
0.2222 (4.5)1.47126
0.2361 (4.2353)0.013143
0.25 (4)43.821306
0.2639 (3.7895)2.325927
0.2778 (3.6)2.357261
0.2917 (3.4286)1.646192
0.3056 (3.2727)0.753529
0.3194 (3.1304)0.336701
0.3333 (3)54.93902
0.3472 (2.88)4.750441
0.3611 (2.7692)0.018518
0.375 (2.6667)0.992775
0.3889 (2.5714)0.099676
0.4028 (2.4828)0.291632
0.4167 (2.4)49.712083
0.4306 (2.3226)0.976112
0.4444 (2.25)2.163524
0.4583 (2.1818)0.04244
0.4722 (2.1176)0.298163
0.4861 (2.0571)1.010685
0.5 (2)25.281949

\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
0.0139 (72) & 0.529718 \tabularnewline
0.0278 (36) & 1.499673 \tabularnewline
0.0417 (24) & 1.963919 \tabularnewline
0.0556 (18) & 2.682549 \tabularnewline
0.0694 (14.4) & 0.083688 \tabularnewline
0.0833 (12) & 105.94798 \tabularnewline
0.0972 (10.2857) & 2.636439 \tabularnewline
0.1111 (9) & 1.339014 \tabularnewline
0.125 (8) & 0.000484 \tabularnewline
0.1389 (7.2) & 4.008439 \tabularnewline
0.1528 (6.5455) & 0.714812 \tabularnewline
0.1667 (6) & 201.038673 \tabularnewline
0.1806 (5.5385) & 0.38107 \tabularnewline
0.1944 (5.1429) & 1.295898 \tabularnewline
0.2083 (4.8) & 0.602836 \tabularnewline
0.2222 (4.5) & 1.47126 \tabularnewline
0.2361 (4.2353) & 0.013143 \tabularnewline
0.25 (4) & 43.821306 \tabularnewline
0.2639 (3.7895) & 2.325927 \tabularnewline
0.2778 (3.6) & 2.357261 \tabularnewline
0.2917 (3.4286) & 1.646192 \tabularnewline
0.3056 (3.2727) & 0.753529 \tabularnewline
0.3194 (3.1304) & 0.336701 \tabularnewline
0.3333 (3) & 54.93902 \tabularnewline
0.3472 (2.88) & 4.750441 \tabularnewline
0.3611 (2.7692) & 0.018518 \tabularnewline
0.375 (2.6667) & 0.992775 \tabularnewline
0.3889 (2.5714) & 0.099676 \tabularnewline
0.4028 (2.4828) & 0.291632 \tabularnewline
0.4167 (2.4) & 49.712083 \tabularnewline
0.4306 (2.3226) & 0.976112 \tabularnewline
0.4444 (2.25) & 2.163524 \tabularnewline
0.4583 (2.1818) & 0.04244 \tabularnewline
0.4722 (2.1176) & 0.298163 \tabularnewline
0.4861 (2.0571) & 1.010685 \tabularnewline
0.5 (2) & 25.281949 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29196&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]0.0139 (72)[/C][C]0.529718[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]1.499673[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]1.963919[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]2.682549[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]0.083688[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]105.94798[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]2.636439[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]1.339014[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]0.000484[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]4.008439[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]0.714812[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]201.038673[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]0.38107[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]1.295898[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]0.602836[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]1.47126[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]0.013143[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]43.821306[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]2.325927[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]2.357261[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]1.646192[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]0.753529[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]0.336701[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]54.93902[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]4.750441[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]0.018518[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]0.992775[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]0.099676[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]0.291632[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]49.712083[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]0.976112[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]2.163524[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]0.04244[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]0.298163[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]1.010685[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]25.281949[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29196&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29196&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)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0139 (72)0.529718
0.0278 (36)1.499673
0.0417 (24)1.963919
0.0556 (18)2.682549
0.0694 (14.4)0.083688
0.0833 (12)105.94798
0.0972 (10.2857)2.636439
0.1111 (9)1.339014
0.125 (8)0.000484
0.1389 (7.2)4.008439
0.1528 (6.5455)0.714812
0.1667 (6)201.038673
0.1806 (5.5385)0.38107
0.1944 (5.1429)1.295898
0.2083 (4.8)0.602836
0.2222 (4.5)1.47126
0.2361 (4.2353)0.013143
0.25 (4)43.821306
0.2639 (3.7895)2.325927
0.2778 (3.6)2.357261
0.2917 (3.4286)1.646192
0.3056 (3.2727)0.753529
0.3194 (3.1304)0.336701
0.3333 (3)54.93902
0.3472 (2.88)4.750441
0.3611 (2.7692)0.018518
0.375 (2.6667)0.992775
0.3889 (2.5714)0.099676
0.4028 (2.4828)0.291632
0.4167 (2.4)49.712083
0.4306 (2.3226)0.976112
0.4444 (2.25)2.163524
0.4583 (2.1818)0.04244
0.4722 (2.1176)0.298163
0.4861 (2.0571)1.010685
0.5 (2)25.281949



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')