Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationMon, 08 Dec 2008 00:14:35 -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/08/t1228720518q8tl2cejfh5khg2.htm/, Retrieved Thu, 16 May 2024 12:24:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30354, Retrieved Thu, 16 May 2024 12:24:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Standard Deviation-Mean Plot] [step 1] [2008-12-06 12:33:55] [c45c87b96bbf32ffc2144fc37d767b2e]
- RMP   [Spectral Analysis] [cp] [2008-12-07 20:09:07] [c45c87b96bbf32ffc2144fc37d767b2e]
F   P       [Spectral Analysis] [cp] [2008-12-08 07:14:35] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
Feedback Forum
2008-12-15 20:13:30 [8e2cc0b2ef568da46d009b2f601285b2] [reply
Hier is een foutieve lambda gebruikt, een gevolg van vraag 1. Verder is de Cumulative periodogram correct berekend. Hoewel de bespreking van de grafiek zeer beknopt is.

Post a new message
Dataseries X:
3595
3914
4159
3676
3794
3446
3504
3958
3353
3480
3098
2944
3389
3497
4404
3849
3734
3060
3507
3287
3215
3764
2734
2837
2766
3851
3289
3848
3348
3682
4058
3655
3811
3341
3032
3475
3353
3186
3902
4164
3499
4145
3796
3711
3949
3740
3243
4407
4814
3908
5250
3937
4004
5560
3922
3759
4138
4634
3996
4308
4142
4429
5219
4929
5754
5592
4163
4962
5208
4755
4491
5732
5730
5024
6056
4901
5353
5578
4618
4724
5011
5298
4143
4617
4736
4214
5112
4197
4119
5104
4194
4583
3790
5557
4304
3838
4277
4951
4479
4677
4274
4782




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=30354&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=30354&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30354&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
0.0111 (90)0.050741
0.0222 (45)0.004253
0.0333 (30)0.019908
0.0444 (22.5)0.011769
0.0556 (18)0.006178
0.0667 (15)0.003045
0.0778 (12.8571)0.000139
0.0889 (11.25)0.000646
0.1 (10)0.001613
0.1111 (9)0.002615
0.1222 (8.1818)0.008797
0.1333 (7.5)0.001366
0.1444 (6.9231)0.001738
0.1556 (6.4286)0.000759
0.1667 (6)0.000479
0.1778 (5.625)0.001908
0.1889 (5.2941)0.003231
0.2 (5)0.000734
0.2111 (4.7368)0.010496
0.2222 (4.5)0.009019
0.2333 (4.2857)0.000482
0.2444 (4.0909)0.001562
0.2556 (3.913)0.000203
0.2667 (3.75)0.00138
0.2778 (3.6)0.010188
0.2889 (3.4615)0.001841
0.3 (3.3333)0.004986
0.3111 (3.2143)0.003793
0.3222 (3.1034)0.001088
0.3333 (3)7e-05
0.3444 (2.9032)0.006865
0.3556 (2.8125)0.003131
0.3667 (2.7273)0.001872
0.3778 (2.6471)0.000146
0.3889 (2.5714)0.002092
0.4 (2.5)0.000615
0.4111 (2.4324)0.000771
0.4222 (2.3684)0.001172
0.4333 (2.3077)0.005603
0.4444 (2.25)0.0073
0.4556 (2.1951)0.003434
0.4667 (2.1429)0.00473
0.4778 (2.093)0.000471
0.4889 (2.0455)0.001512
0.5 (2)0.000952

\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
0.0111 (90) & 0.050741 \tabularnewline
0.0222 (45) & 0.004253 \tabularnewline
0.0333 (30) & 0.019908 \tabularnewline
0.0444 (22.5) & 0.011769 \tabularnewline
0.0556 (18) & 0.006178 \tabularnewline
0.0667 (15) & 0.003045 \tabularnewline
0.0778 (12.8571) & 0.000139 \tabularnewline
0.0889 (11.25) & 0.000646 \tabularnewline
0.1 (10) & 0.001613 \tabularnewline
0.1111 (9) & 0.002615 \tabularnewline
0.1222 (8.1818) & 0.008797 \tabularnewline
0.1333 (7.5) & 0.001366 \tabularnewline
0.1444 (6.9231) & 0.001738 \tabularnewline
0.1556 (6.4286) & 0.000759 \tabularnewline
0.1667 (6) & 0.000479 \tabularnewline
0.1778 (5.625) & 0.001908 \tabularnewline
0.1889 (5.2941) & 0.003231 \tabularnewline
0.2 (5) & 0.000734 \tabularnewline
0.2111 (4.7368) & 0.010496 \tabularnewline
0.2222 (4.5) & 0.009019 \tabularnewline
0.2333 (4.2857) & 0.000482 \tabularnewline
0.2444 (4.0909) & 0.001562 \tabularnewline
0.2556 (3.913) & 0.000203 \tabularnewline
0.2667 (3.75) & 0.00138 \tabularnewline
0.2778 (3.6) & 0.010188 \tabularnewline
0.2889 (3.4615) & 0.001841 \tabularnewline
0.3 (3.3333) & 0.004986 \tabularnewline
0.3111 (3.2143) & 0.003793 \tabularnewline
0.3222 (3.1034) & 0.001088 \tabularnewline
0.3333 (3) & 7e-05 \tabularnewline
0.3444 (2.9032) & 0.006865 \tabularnewline
0.3556 (2.8125) & 0.003131 \tabularnewline
0.3667 (2.7273) & 0.001872 \tabularnewline
0.3778 (2.6471) & 0.000146 \tabularnewline
0.3889 (2.5714) & 0.002092 \tabularnewline
0.4 (2.5) & 0.000615 \tabularnewline
0.4111 (2.4324) & 0.000771 \tabularnewline
0.4222 (2.3684) & 0.001172 \tabularnewline
0.4333 (2.3077) & 0.005603 \tabularnewline
0.4444 (2.25) & 0.0073 \tabularnewline
0.4556 (2.1951) & 0.003434 \tabularnewline
0.4667 (2.1429) & 0.00473 \tabularnewline
0.4778 (2.093) & 0.000471 \tabularnewline
0.4889 (2.0455) & 0.001512 \tabularnewline
0.5 (2) & 0.000952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30354&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]0.0111 (90)[/C][C]0.050741[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]0.004253[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]0.019908[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]0.011769[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]0.006178[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]0.003045[/C][/ROW]
[ROW][C]0.0778 (12.8571)[/C][C]0.000139[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]0.000646[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]0.001613[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.002615[/C][/ROW]
[ROW][C]0.1222 (8.1818)[/C][C]0.008797[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]0.001366[/C][/ROW]
[ROW][C]0.1444 (6.9231)[/C][C]0.001738[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]0.000759[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.000479[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]0.001908[/C][/ROW]
[ROW][C]0.1889 (5.2941)[/C][C]0.003231[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]0.000734[/C][/ROW]
[ROW][C]0.2111 (4.7368)[/C][C]0.010496[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.009019[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]0.000482[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]0.001562[/C][/ROW]
[ROW][C]0.2556 (3.913)[/C][C]0.000203[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]0.00138[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]0.010188[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]0.001841[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]0.004986[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]0.003793[/C][/ROW]
[ROW][C]0.3222 (3.1034)[/C][C]0.001088[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]7e-05[/C][/ROW]
[ROW][C]0.3444 (2.9032)[/C][C]0.006865[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]0.003131[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]0.001872[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]0.000146[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]0.002092[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]0.000615[/C][/ROW]
[ROW][C]0.4111 (2.4324)[/C][C]0.000771[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]0.001172[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]0.005603[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.0073[/C][/ROW]
[ROW][C]0.4556 (2.1951)[/C][C]0.003434[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]0.00473[/C][/ROW]
[ROW][C]0.4778 (2.093)[/C][C]0.000471[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]0.001512[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.000952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30354&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30354&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
0.0111 (90)0.050741
0.0222 (45)0.004253
0.0333 (30)0.019908
0.0444 (22.5)0.011769
0.0556 (18)0.006178
0.0667 (15)0.003045
0.0778 (12.8571)0.000139
0.0889 (11.25)0.000646
0.1 (10)0.001613
0.1111 (9)0.002615
0.1222 (8.1818)0.008797
0.1333 (7.5)0.001366
0.1444 (6.9231)0.001738
0.1556 (6.4286)0.000759
0.1667 (6)0.000479
0.1778 (5.625)0.001908
0.1889 (5.2941)0.003231
0.2 (5)0.000734
0.2111 (4.7368)0.010496
0.2222 (4.5)0.009019
0.2333 (4.2857)0.000482
0.2444 (4.0909)0.001562
0.2556 (3.913)0.000203
0.2667 (3.75)0.00138
0.2778 (3.6)0.010188
0.2889 (3.4615)0.001841
0.3 (3.3333)0.004986
0.3111 (3.2143)0.003793
0.3222 (3.1034)0.001088
0.3333 (3)7e-05
0.3444 (2.9032)0.006865
0.3556 (2.8125)0.003131
0.3667 (2.7273)0.001872
0.3778 (2.6471)0.000146
0.3889 (2.5714)0.002092
0.4 (2.5)0.000615
0.4111 (2.4324)0.000771
0.4222 (2.3684)0.001172
0.4333 (2.3077)0.005603
0.4444 (2.25)0.0073
0.4556 (2.1951)0.003434
0.4667 (2.1429)0.00473
0.4778 (2.093)0.000471
0.4889 (2.0455)0.001512
0.5 (2)0.000952



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')