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Author's title

Eigen tijdreeks Spectrum Analyse totaal werkzoekenden mannen zonder aanpass...

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationSat, 06 Dec 2008 08:03:16 -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/06/t1228575835wj5zba64bgs0a59.htm/, Retrieved Fri, 17 May 2024 02:00:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29688, Retrieved Fri, 17 May 2024 02:00:55 +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)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Spectral Analysis] [Identification an...] [2008-12-04 19:54:30] [063e4b67ad7d3a8a83eccec794cd5aa7]
F   PD      [Spectral Analysis] [Eigen tijdreeks S...] [2008-12-06 15:03:16] [6797a1f4a60918966297e9d9220cabc2] [Current]
Feedback Forum
2008-12-15 18:42:01 [Jeroen Michel] [reply
Ook hier zien we een goede en correcte conclusie van de student. De student stelt dat er tot 45% een langetermijn trend valt op te tekenen, vanaf dat punt zien we een wijziging binnen het patroon die eerder overgaat in een trapstructuur.

Post a new message
Dataseries X:
6,2
6,1
5,9
5,6
5,5
5,5
5,6
5,7
5,6
5,4
5,3
5,3
5,4
5,5
5,6
5,7
5,8
5,8
5,7
5,9
6,1
6,4
6,4
6,3
6,2
6,2
6,3
6,5
6,6
6,6
6,7
6,6
6,7
7
7,2
7,3
7,5
7,6
7,7
7,8
7,8
7,7
7,6
7,6
7,7
7,8
7,8
7,8
7,7
7,6
7,4
7,1
7,1
7,3
7,6
7,8
7,7
7,6
7,5
7,5
7,5
7,6
7,6
7,7
7,8
7,7
7,6
7,6
7,6
7,7
7,8
7,8
7,9
7,9
7,8
7,8
7,7
7,5
7,1
6,9
7,1
7,1
7,1
7
6,9
6,8
6,7
6,8
6,8
6,7
6,8
6,7
6,6
6,4
6,4
6,4
6,5
6,5
6,4
6,3
6,2
6,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=29688&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=29688&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29688&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0093 (108)15.671278
0.0185 (54)1.323979
0.0278 (36)4.090589
0.037 (27)0.566648
0.0463 (21.6)0.42272
0.0556 (18)0.207321
0.0648 (15.4286)0.06105
0.0741 (13.5)0.176047
0.0833 (12)0.043797
0.0926 (10.8)0.037322
0.1019 (9.8182)0.037247
0.1111 (9)0.194982
0.1204 (8.3077)0.182759
0.1296 (7.7143)0.024095
0.1389 (7.2)0.011387
0.1481 (6.75)0.176878
0.1574 (6.3529)0.008487
0.1667 (6)0.010116
0.1759 (5.6842)0.001585
0.1852 (5.4)0.03804
0.1944 (5.1429)0.015518
0.2037 (4.9091)0.005967
0.213 (4.6957)0.02677
0.2222 (4.5)0.000797
0.2315 (4.32)0.007081
0.2407 (4.1538)0.000721
0.25 (4)0.003711
0.2593 (3.8571)0.005135
0.2685 (3.7241)0.001761
0.2778 (3.6)0.003896
0.287 (3.4839)0.000519
0.2963 (3.375)0.00603
0.3056 (3.2727)0.000921
0.3148 (3.1765)0.002065
0.3241 (3.0857)0.000777
0.3333 (3)0.002058
0.3426 (2.9189)5.1e-05
0.3519 (2.8421)0.003538
0.3611 (2.7692)0.003436
0.3704 (2.7)0.000488
0.3796 (2.6341)0.00109
0.3889 (2.5714)0.001018
0.3981 (2.5116)0.00312
0.4074 (2.4545)0.00115
0.4167 (2.4)0.000137
0.4259 (2.3478)0.002992
0.4352 (2.2979)0.000329
0.4444 (2.25)0.000514
0.4537 (2.2041)0.00159
0.463 (2.16)0.000934
0.4722 (2.1176)0.000224
0.4815 (2.0769)0.001655
0.4907 (2.0377)0.000645
0.5 (2)4.9e-05

\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) & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0093 (108) & 15.671278 \tabularnewline
0.0185 (54) & 1.323979 \tabularnewline
0.0278 (36) & 4.090589 \tabularnewline
0.037 (27) & 0.566648 \tabularnewline
0.0463 (21.6) & 0.42272 \tabularnewline
0.0556 (18) & 0.207321 \tabularnewline
0.0648 (15.4286) & 0.06105 \tabularnewline
0.0741 (13.5) & 0.176047 \tabularnewline
0.0833 (12) & 0.043797 \tabularnewline
0.0926 (10.8) & 0.037322 \tabularnewline
0.1019 (9.8182) & 0.037247 \tabularnewline
0.1111 (9) & 0.194982 \tabularnewline
0.1204 (8.3077) & 0.182759 \tabularnewline
0.1296 (7.7143) & 0.024095 \tabularnewline
0.1389 (7.2) & 0.011387 \tabularnewline
0.1481 (6.75) & 0.176878 \tabularnewline
0.1574 (6.3529) & 0.008487 \tabularnewline
0.1667 (6) & 0.010116 \tabularnewline
0.1759 (5.6842) & 0.001585 \tabularnewline
0.1852 (5.4) & 0.03804 \tabularnewline
0.1944 (5.1429) & 0.015518 \tabularnewline
0.2037 (4.9091) & 0.005967 \tabularnewline
0.213 (4.6957) & 0.02677 \tabularnewline
0.2222 (4.5) & 0.000797 \tabularnewline
0.2315 (4.32) & 0.007081 \tabularnewline
0.2407 (4.1538) & 0.000721 \tabularnewline
0.25 (4) & 0.003711 \tabularnewline
0.2593 (3.8571) & 0.005135 \tabularnewline
0.2685 (3.7241) & 0.001761 \tabularnewline
0.2778 (3.6) & 0.003896 \tabularnewline
0.287 (3.4839) & 0.000519 \tabularnewline
0.2963 (3.375) & 0.00603 \tabularnewline
0.3056 (3.2727) & 0.000921 \tabularnewline
0.3148 (3.1765) & 0.002065 \tabularnewline
0.3241 (3.0857) & 0.000777 \tabularnewline
0.3333 (3) & 0.002058 \tabularnewline
0.3426 (2.9189) & 5.1e-05 \tabularnewline
0.3519 (2.8421) & 0.003538 \tabularnewline
0.3611 (2.7692) & 0.003436 \tabularnewline
0.3704 (2.7) & 0.000488 \tabularnewline
0.3796 (2.6341) & 0.00109 \tabularnewline
0.3889 (2.5714) & 0.001018 \tabularnewline
0.3981 (2.5116) & 0.00312 \tabularnewline
0.4074 (2.4545) & 0.00115 \tabularnewline
0.4167 (2.4) & 0.000137 \tabularnewline
0.4259 (2.3478) & 0.002992 \tabularnewline
0.4352 (2.2979) & 0.000329 \tabularnewline
0.4444 (2.25) & 0.000514 \tabularnewline
0.4537 (2.2041) & 0.00159 \tabularnewline
0.463 (2.16) & 0.000934 \tabularnewline
0.4722 (2.1176) & 0.000224 \tabularnewline
0.4815 (2.0769) & 0.001655 \tabularnewline
0.4907 (2.0377) & 0.000645 \tabularnewline
0.5 (2) & 4.9e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29688&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]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0093 (108)[/C][C]15.671278[/C][/ROW]
[ROW][C]0.0185 (54)[/C][C]1.323979[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]4.090589[/C][/ROW]
[ROW][C]0.037 (27)[/C][C]0.566648[/C][/ROW]
[ROW][C]0.0463 (21.6)[/C][C]0.42272[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]0.207321[/C][/ROW]
[ROW][C]0.0648 (15.4286)[/C][C]0.06105[/C][/ROW]
[ROW][C]0.0741 (13.5)[/C][C]0.176047[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0.043797[/C][/ROW]
[ROW][C]0.0926 (10.8)[/C][C]0.037322[/C][/ROW]
[ROW][C]0.1019 (9.8182)[/C][C]0.037247[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.194982[/C][/ROW]
[ROW][C]0.1204 (8.3077)[/C][C]0.182759[/C][/ROW]
[ROW][C]0.1296 (7.7143)[/C][C]0.024095[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]0.011387[/C][/ROW]
[ROW][C]0.1481 (6.75)[/C][C]0.176878[/C][/ROW]
[ROW][C]0.1574 (6.3529)[/C][C]0.008487[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.010116[/C][/ROW]
[ROW][C]0.1759 (5.6842)[/C][C]0.001585[/C][/ROW]
[ROW][C]0.1852 (5.4)[/C][C]0.03804[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]0.015518[/C][/ROW]
[ROW][C]0.2037 (4.9091)[/C][C]0.005967[/C][/ROW]
[ROW][C]0.213 (4.6957)[/C][C]0.02677[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.000797[/C][/ROW]
[ROW][C]0.2315 (4.32)[/C][C]0.007081[/C][/ROW]
[ROW][C]0.2407 (4.1538)[/C][C]0.000721[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.003711[/C][/ROW]
[ROW][C]0.2593 (3.8571)[/C][C]0.005135[/C][/ROW]
[ROW][C]0.2685 (3.7241)[/C][C]0.001761[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]0.003896[/C][/ROW]
[ROW][C]0.287 (3.4839)[/C][C]0.000519[/C][/ROW]
[ROW][C]0.2963 (3.375)[/C][C]0.00603[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]0.000921[/C][/ROW]
[ROW][C]0.3148 (3.1765)[/C][C]0.002065[/C][/ROW]
[ROW][C]0.3241 (3.0857)[/C][C]0.000777[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.002058[/C][/ROW]
[ROW][C]0.3426 (2.9189)[/C][C]5.1e-05[/C][/ROW]
[ROW][C]0.3519 (2.8421)[/C][C]0.003538[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]0.003436[/C][/ROW]
[ROW][C]0.3704 (2.7)[/C][C]0.000488[/C][/ROW]
[ROW][C]0.3796 (2.6341)[/C][C]0.00109[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]0.001018[/C][/ROW]
[ROW][C]0.3981 (2.5116)[/C][C]0.00312[/C][/ROW]
[ROW][C]0.4074 (2.4545)[/C][C]0.00115[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0.000137[/C][/ROW]
[ROW][C]0.4259 (2.3478)[/C][C]0.002992[/C][/ROW]
[ROW][C]0.4352 (2.2979)[/C][C]0.000329[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.000514[/C][/ROW]
[ROW][C]0.4537 (2.2041)[/C][C]0.00159[/C][/ROW]
[ROW][C]0.463 (2.16)[/C][C]0.000934[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]0.000224[/C][/ROW]
[ROW][C]0.4815 (2.0769)[/C][C]0.001655[/C][/ROW]
[ROW][C]0.4907 (2.0377)[/C][C]0.000645[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]4.9e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29688&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29688&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)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0093 (108)15.671278
0.0185 (54)1.323979
0.0278 (36)4.090589
0.037 (27)0.566648
0.0463 (21.6)0.42272
0.0556 (18)0.207321
0.0648 (15.4286)0.06105
0.0741 (13.5)0.176047
0.0833 (12)0.043797
0.0926 (10.8)0.037322
0.1019 (9.8182)0.037247
0.1111 (9)0.194982
0.1204 (8.3077)0.182759
0.1296 (7.7143)0.024095
0.1389 (7.2)0.011387
0.1481 (6.75)0.176878
0.1574 (6.3529)0.008487
0.1667 (6)0.010116
0.1759 (5.6842)0.001585
0.1852 (5.4)0.03804
0.1944 (5.1429)0.015518
0.2037 (4.9091)0.005967
0.213 (4.6957)0.02677
0.2222 (4.5)0.000797
0.2315 (4.32)0.007081
0.2407 (4.1538)0.000721
0.25 (4)0.003711
0.2593 (3.8571)0.005135
0.2685 (3.7241)0.001761
0.2778 (3.6)0.003896
0.287 (3.4839)0.000519
0.2963 (3.375)0.00603
0.3056 (3.2727)0.000921
0.3148 (3.1765)0.002065
0.3241 (3.0857)0.000777
0.3333 (3)0.002058
0.3426 (2.9189)5.1e-05
0.3519 (2.8421)0.003538
0.3611 (2.7692)0.003436
0.3704 (2.7)0.000488
0.3796 (2.6341)0.00109
0.3889 (2.5714)0.001018
0.3981 (2.5116)0.00312
0.4074 (2.4545)0.00115
0.4167 (2.4)0.000137
0.4259 (2.3478)0.002992
0.4352 (2.2979)0.000329
0.4444 (2.25)0.000514
0.4537 (2.2041)0.00159
0.463 (2.16)0.000934
0.4722 (2.1176)0.000224
0.4815 (2.0769)0.001655
0.4907 (2.0377)0.000645
0.5 (2)4.9e-05



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; 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')