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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationSun, 07 Dec 2008 08:02:51 -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/07/t1228662205tq951jdn7upixd9.htm/, Retrieved Sat, 18 May 2024 17:10:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30044, Retrieved Sat, 18 May 2024 17:10:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact242

Tree of Dependent Computations

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]
- RMPD  [Standard Deviation-Mean Plot] [Identification an...] [2008-12-07 14:45:52] [b943bd7078334192ff8343563ee31113]
- RM      [Variance Reduction Matrix] [Identification an...] [2008-12-07 14:47:22] [b943bd7078334192ff8343563ee31113]
- RMP       [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:51:36] [b943bd7078334192ff8343563ee31113]
F   P         [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:54:30] [b943bd7078334192ff8343563ee31113]
-   P           [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:58:01] [b943bd7078334192ff8343563ee31113]
F RMP               [Spectral Analysis] [Identification an...] [2008-12-07 15:02:51] [620b6ad5c4696049e39cb73ce029682c] [Current]
F RMP                 [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 15:05:29] [b943bd7078334192ff8343563ee31113]
F RMP                   [ARIMA Backward Selection] [Identification an...] [2008-12-07 15:45:38] [b943bd7078334192ff8343563ee31113]
-   P                     [ARIMA Backward Selection] [ARIMA Backward Mo...] [2008-12-12 14:40:13] [b943bd7078334192ff8343563ee31113]
- RMP                       [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-15 17:00:29] [b943bd7078334192ff8343563ee31113]
F   P                         [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-15 18:00:13] [b943bd7078334192ff8343563ee31113]
-   P                     [ARIMA Backward Selection] [ARIMA Backward Mo...] [2008-12-12 14:46:56] [b943bd7078334192ff8343563ee31113]
-   P                       [ARIMA Backward Selection] [ARIMA ciska] [2008-12-20 21:03:45] [ed2ba3b6182103c15c0ab511ae4e6284]
-   P                       [ARIMA Backward Selection] [] [2008-12-20 22:26:43] [b98453cac15ba1066b407e146608df68]
- RMP                       [ARIMA Forecasting] [] [2008-12-20 22:29:20] [b98453cac15ba1066b407e146608df68]
- R PD                    [ARIMA Backward Selection] [ARIMA olie] [2008-12-20 13:29:28] [7458e879e85b911182071700fff19fbd]
-    D                      [ARIMA Backward Selection] [Arima BEL20] [2008-12-22 11:36:19] [7458e879e85b911182071700fff19fbd]
- RMP                       [ARIMA Backward Selection] [] [2009-12-28 20:46:18] [a171cf7519360d15de770637ace99f7a]
- RMPD                      [ARIMA Backward Selection] [] [2009-12-28 20:54:47] [a171cf7519360d15de770637ace99f7a]
-   P                   [(Partial) Autocorrelation Function] [Identification an...] [2008-12-12 12:38:52] [b943bd7078334192ff8343563ee31113]
-   P                 [Spectral Analysis] [Identification an...] [2008-12-12 12:35:01] [b943bd7078334192ff8343563ee31113]
-   PD                [Spectral Analysis] [Cumulatief perdio...] [2008-12-20 12:12:22] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-12-12 12:37:13 [Ciska Tanghe] [reply] 
Aangezien we bij step 2 seizoenaliteit vastgesteld hebben (weliswaar tweejaarlijks) moet D gelijkgesteld worden aan 1 en niet aan 0.

Dit is een correcte berekening:

http://www.freestatistics.org/blog/date/2008/Dec/12/t12290853552smo7b119r403tw.htm


Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1593
1477.9
1733.7
1569.7
1843.7
1950.3
1657.5
1772.1
1568.3
1809.8
1646.7
1808.5
1763.9
1625.5
1538.8
1342.4
1645.1
1619.9
1338.1
1505.5
1529.1
1511.9
1656.7
1694.4
1662.3
1588.7
1483.3
1585.6
1658.9
1584.4
1470.6
1618.7
1407.6
1473.9
1515.3
1485.4
1496.1
1493.5
1298.4
1375.3
1507.9
1455.3
1363.3
1392.8
1348.8
1880.3
1669.2
1543.6
1701.2
1516.5
1466.8
1484.1
1577.2
1684.5
1414.7
1674.5
1598.7
1739.1
1674.6
1671.8
1802
1526.8
1580.9
1634.8
1610.3
1712
1678.8
1708.1
1680.6
2056
1624
2021.4
1861.1
1750.8
1767.5
1710.3
2151.5
2047.9
1915.4
1984.7
1896.5
2170.8
2139.9
2330.5
2121.8
2226.8
1857.9
2155.9
2341.7
2290.2
2006.5
2111.9
1731.3
1762.2
1863.2
1943.5
1975.2

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30044&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30044&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30044&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)-0.9
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0104 (96)0
0.0208 (48)0
0.0312 (32)0
0.0417 (24)0
0.0521 (19.2)0
0.0625 (16)0
0.0729 (13.7143)0
0.0833 (12)0
0.0938 (10.6667)0
0.1042 (9.6)0
0.1146 (8.7273)0
0.125 (8)0
0.1354 (7.3846)0
0.1458 (6.8571)0
0.1562 (6.4)0
0.1667 (6)0
0.1771 (5.6471)0
0.1875 (5.3333)0
0.1979 (5.0526)0
0.2083 (4.8)0
0.2187 (4.5714)0
0.2292 (4.3636)0
0.2396 (4.1739)0
0.25 (4)0
0.2604 (3.84)0
0.2708 (3.6923)0
0.2812 (3.5556)0
0.2917 (3.4286)0
0.3021 (3.3103)0
0.3125 (3.2)0
0.3229 (3.0968)0
0.3333 (3)0
0.3438 (2.9091)0
0.3542 (2.8235)0
0.3646 (2.7429)0
0.375 (2.6667)0
0.3854 (2.5946)0
0.3958 (2.5263)0
0.4062 (2.4615)0
0.4167 (2.4)0
0.4271 (2.3415)0
0.4375 (2.2857)0
0.4479 (2.2326)0
0.4583 (2.1818)0
0.4688 (2.1333)0
0.4792 (2.087)0
0.4896 (2.0426)0
0.5 (2)0

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & -0.9 \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
0.0104 (96) & 0 \tabularnewline
0.0208 (48) & 0 \tabularnewline
0.0312 (32) & 0 \tabularnewline
0.0417 (24) & 0 \tabularnewline
0.0521 (19.2) & 0 \tabularnewline
0.0625 (16) & 0 \tabularnewline
0.0729 (13.7143) & 0 \tabularnewline
0.0833 (12) & 0 \tabularnewline
0.0938 (10.6667) & 0 \tabularnewline
0.1042 (9.6) & 0 \tabularnewline
0.1146 (8.7273) & 0 \tabularnewline
0.125 (8) & 0 \tabularnewline
0.1354 (7.3846) & 0 \tabularnewline
0.1458 (6.8571) & 0 \tabularnewline
0.1562 (6.4) & 0 \tabularnewline
0.1667 (6) & 0 \tabularnewline
0.1771 (5.6471) & 0 \tabularnewline
0.1875 (5.3333) & 0 \tabularnewline
0.1979 (5.0526) & 0 \tabularnewline
0.2083 (4.8) & 0 \tabularnewline
0.2187 (4.5714) & 0 \tabularnewline
0.2292 (4.3636) & 0 \tabularnewline
0.2396 (4.1739) & 0 \tabularnewline
0.25 (4) & 0 \tabularnewline
0.2604 (3.84) & 0 \tabularnewline
0.2708 (3.6923) & 0 \tabularnewline
0.2812 (3.5556) & 0 \tabularnewline
0.2917 (3.4286) & 0 \tabularnewline
0.3021 (3.3103) & 0 \tabularnewline
0.3125 (3.2) & 0 \tabularnewline
0.3229 (3.0968) & 0 \tabularnewline
0.3333 (3) & 0 \tabularnewline
0.3438 (2.9091) & 0 \tabularnewline
0.3542 (2.8235) & 0 \tabularnewline
0.3646 (2.7429) & 0 \tabularnewline
0.375 (2.6667) & 0 \tabularnewline
0.3854 (2.5946) & 0 \tabularnewline
0.3958 (2.5263) & 0 \tabularnewline
0.4062 (2.4615) & 0 \tabularnewline
0.4167 (2.4) & 0 \tabularnewline
0.4271 (2.3415) & 0 \tabularnewline
0.4375 (2.2857) & 0 \tabularnewline
0.4479 (2.2326) & 0 \tabularnewline
0.4583 (2.1818) & 0 \tabularnewline
0.4688 (2.1333) & 0 \tabularnewline
0.4792 (2.087) & 0 \tabularnewline
0.4896 (2.0426) & 0 \tabularnewline
0.5 (2) & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30044&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]-0.9[/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]0.0104 (96)[/C][C]0[/C][/ROW]
[ROW][C]0.0208 (48)[/C][C]0[/C][/ROW]
[ROW][C]0.0312 (32)[/C][C]0[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]0[/C][/ROW]
[ROW][C]0.0521 (19.2)[/C][C]0[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]0[/C][/ROW]
[ROW][C]0.0729 (13.7143)[/C][C]0[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0[/C][/ROW]
[ROW][C]0.0938 (10.6667)[/C][C]0[/C][/ROW]
[ROW][C]0.1042 (9.6)[/C][C]0[/C][/ROW]
[ROW][C]0.1146 (8.7273)[/C][C]0[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]0[/C][/ROW]
[ROW][C]0.1354 (7.3846)[/C][C]0[/C][/ROW]
[ROW][C]0.1458 (6.8571)[/C][C]0[/C][/ROW]
[ROW][C]0.1562 (6.4)[/C][C]0[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0[/C][/ROW]
[ROW][C]0.1771 (5.6471)[/C][C]0[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]0[/C][/ROW]
[ROW][C]0.1979 (5.0526)[/C][C]0[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]0[/C][/ROW]
[ROW][C]0.2187 (4.5714)[/C][C]0[/C][/ROW]
[ROW][C]0.2292 (4.3636)[/C][C]0[/C][/ROW]
[ROW][C]0.2396 (4.1739)[/C][C]0[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0[/C][/ROW]
[ROW][C]0.2604 (3.84)[/C][C]0[/C][/ROW]
[ROW][C]0.2708 (3.6923)[/C][C]0[/C][/ROW]
[ROW][C]0.2812 (3.5556)[/C][C]0[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]0[/C][/ROW]
[ROW][C]0.3021 (3.3103)[/C][C]0[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]0[/C][/ROW]
[ROW][C]0.3229 (3.0968)[/C][C]0[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0[/C][/ROW]
[ROW][C]0.3438 (2.9091)[/C][C]0[/C][/ROW]
[ROW][C]0.3542 (2.8235)[/C][C]0[/C][/ROW]
[ROW][C]0.3646 (2.7429)[/C][C]0[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]0[/C][/ROW]
[ROW][C]0.3854 (2.5946)[/C][C]0[/C][/ROW]
[ROW][C]0.3958 (2.5263)[/C][C]0[/C][/ROW]
[ROW][C]0.4062 (2.4615)[/C][C]0[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0[/C][/ROW]
[ROW][C]0.4271 (2.3415)[/C][C]0[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]0[/C][/ROW]
[ROW][C]0.4479 (2.2326)[/C][C]0[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]0[/C][/ROW]
[ROW][C]0.4688 (2.1333)[/C][C]0[/C][/ROW]
[ROW][C]0.4792 (2.087)[/C][C]0[/C][/ROW]
[ROW][C]0.4896 (2.0426)[/C][C]0[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30044&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30044&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)-0.9
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0104 (96)0
0.0208 (48)0
0.0312 (32)0
0.0417 (24)0
0.0521 (19.2)0
0.0625 (16)0
0.0729 (13.7143)0
0.0833 (12)0
0.0938 (10.6667)0
0.1042 (9.6)0
0.1146 (8.7273)0
0.125 (8)0
0.1354 (7.3846)0
0.1458 (6.8571)0
0.1562 (6.4)0
0.1667 (6)0
0.1771 (5.6471)0
0.1875 (5.3333)0
0.1979 (5.0526)0
0.2083 (4.8)0
0.2187 (4.5714)0
0.2292 (4.3636)0
0.2396 (4.1739)0
0.25 (4)0
0.2604 (3.84)0
0.2708 (3.6923)0
0.2812 (3.5556)0
0.2917 (3.4286)0
0.3021 (3.3103)0
0.3125 (3.2)0
0.3229 (3.0968)0
0.3333 (3)0
0.3438 (2.9091)0
0.3542 (2.8235)0
0.3646 (2.7429)0
0.375 (2.6667)0
0.3854 (2.5946)0
0.3958 (2.5263)0
0.4062 (2.4615)0
0.4167 (2.4)0
0.4271 (2.3415)0
0.4375 (2.2857)0
0.4479 (2.2326)0
0.4583 (2.1818)0
0.4688 (2.1333)0
0.4792 (2.087)0
0.4896 (2.0426)0
0.5 (2)0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -0.9 ; par2 = 1 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = -0.9 ; par2 = 1 ; 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')