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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationTue, 09 Dec 2008 06:05:46 -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/09/t1228828025bi7vkv9nv6kvr70.htm/, Retrieved Fri, 17 May 2024 03:41:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31359, Retrieved Fri, 17 May 2024 03:41:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact206

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]
F RMPD  [Standard Deviation-Mean Plot] [Identification an...] [2008-12-09 12:57:00] [8ac58ef7b35dc5a117bc162cf16850e9]
F RM D    [Variance Reduction Matrix] [Identification an...] [2008-12-09 13:00:44] [8ac58ef7b35dc5a117bc162cf16850e9]
F RM        [(Partial) Autocorrelation Function] [Identification an...] [2008-12-09 13:03:20] [8ac58ef7b35dc5a117bc162cf16850e9]
F RM            [Spectral Analysis] [Identification an...] [2008-12-09 13:05:46] [acca1d0ee7cc95ffc080d0867a313954] [Current]
F RM              [(Partial) Autocorrelation Function] [Identification an...] [2008-12-09 13:10:48] [8ac58ef7b35dc5a117bc162cf16850e9]
- RMP               [ARIMA Backward Selection] [ARIMA workshop IP] [2008-12-09 16:55:50] [74be16979710d4c4e7c6647856088456]
F RMP               [ARIMA Backward Selection] [Identification an...] [2008-12-09 17:00:28] [74be16979710d4c4e7c6647856088456]
F                     [ARIMA Backward Selection] [step 5 ip] [2008-12-09 18:09:34] [74be16979710d4c4e7c6647856088456]
F   P               [(Partial) Autocorrelation Function] [step 4 ip] [2008-12-09 18:08:11] [74be16979710d4c4e7c6647856088456]
F   P             [Spectral Analysis] [step 2 cp ip] [2008-12-09 18:07:03] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-12-15 15:39:30 [Jessica Alves Pires] [reply] 
Ik vind enerzijds wel dat er enige seizoenaliteit aanwezig is, dit kan men zien aan de trapfunctie. Maar anderzijds valt de grafiek wel binnen het betrouwbaarheidsinterval dus is er geen sprake meer van voorspelbaarheid.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40
96.40
101.90
106.20
81.00
94.70
101.00
109.40
102.30
90.70
96.20
96.10
106.00
103.10
102.00
104.70
86.00
92.10
106.90
112.60
101.70
92.00
97.40
97.00
105.40
102.70
98.10
104.50
87.40
89.90
109.80
111.70
98.60
96.90
95.10
97.00
112.70
102.90
97.40
111.40
87.40
96.80
114.10
110.30
103.90
101.60
94.60
95.90
104.70
102.80
98.10
113.90
80.90
95.70
113.20
105.90
108.80
102.30
99.00
100.70
115.50

Tables (Output of Computation)





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=31359&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=31359&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31359&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.02 (50)3.875074
0.04 (25)59.711711
0.06 (16.6667)9.523267
0.08 (12.5)7.606068
0.1 (10)2.185706
0.12 (8.3333)3.137351
0.14 (7.1429)8.709469
0.16 (6.25)3.224594
0.18 (5.5556)18.278306
0.2 (5)4.005259
0.22 (4.5455)16.509143
0.24 (4.1667)4.630949
0.26 (3.8462)1.115416
0.28 (3.5714)1.60113
0.3 (3.3333)4.608198
0.32 (3.125)0.86306
0.34 (2.9412)59.632119
0.36 (2.7778)35.45788
0.38 (2.6316)3.708664
0.4 (2.5)24.7205
0.42 (2.381)24.720328
0.44 (2.2727)0.398693
0.46 (2.1739)3.91109
0.48 (2.0833)12.419976
0.5 (2)0.502252

\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) & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.02 (50) & 3.875074 \tabularnewline
0.04 (25) & 59.711711 \tabularnewline
0.06 (16.6667) & 9.523267 \tabularnewline
0.08 (12.5) & 7.606068 \tabularnewline
0.1 (10) & 2.185706 \tabularnewline
0.12 (8.3333) & 3.137351 \tabularnewline
0.14 (7.1429) & 8.709469 \tabularnewline
0.16 (6.25) & 3.224594 \tabularnewline
0.18 (5.5556) & 18.278306 \tabularnewline
0.2 (5) & 4.005259 \tabularnewline
0.22 (4.5455) & 16.509143 \tabularnewline
0.24 (4.1667) & 4.630949 \tabularnewline
0.26 (3.8462) & 1.115416 \tabularnewline
0.28 (3.5714) & 1.60113 \tabularnewline
0.3 (3.3333) & 4.608198 \tabularnewline
0.32 (3.125) & 0.86306 \tabularnewline
0.34 (2.9412) & 59.632119 \tabularnewline
0.36 (2.7778) & 35.45788 \tabularnewline
0.38 (2.6316) & 3.708664 \tabularnewline
0.4 (2.5) & 24.7205 \tabularnewline
0.42 (2.381) & 24.720328 \tabularnewline
0.44 (2.2727) & 0.398693 \tabularnewline
0.46 (2.1739) & 3.91109 \tabularnewline
0.48 (2.0833) & 12.419976 \tabularnewline
0.5 (2) & 0.502252 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31359&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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.02 (50)[/C][C]3.875074[/C][/ROW]
[ROW][C]0.04 (25)[/C][C]59.711711[/C][/ROW]
[ROW][C]0.06 (16.6667)[/C][C]9.523267[/C][/ROW]
[ROW][C]0.08 (12.5)[/C][C]7.606068[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]2.185706[/C][/ROW]
[ROW][C]0.12 (8.3333)[/C][C]3.137351[/C][/ROW]
[ROW][C]0.14 (7.1429)[/C][C]8.709469[/C][/ROW]
[ROW][C]0.16 (6.25)[/C][C]3.224594[/C][/ROW]
[ROW][C]0.18 (5.5556)[/C][C]18.278306[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]4.005259[/C][/ROW]
[ROW][C]0.22 (4.5455)[/C][C]16.509143[/C][/ROW]
[ROW][C]0.24 (4.1667)[/C][C]4.630949[/C][/ROW]
[ROW][C]0.26 (3.8462)[/C][C]1.115416[/C][/ROW]
[ROW][C]0.28 (3.5714)[/C][C]1.60113[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]4.608198[/C][/ROW]
[ROW][C]0.32 (3.125)[/C][C]0.86306[/C][/ROW]
[ROW][C]0.34 (2.9412)[/C][C]59.632119[/C][/ROW]
[ROW][C]0.36 (2.7778)[/C][C]35.45788[/C][/ROW]
[ROW][C]0.38 (2.6316)[/C][C]3.708664[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]24.7205[/C][/ROW]
[ROW][C]0.42 (2.381)[/C][C]24.720328[/C][/ROW]
[ROW][C]0.44 (2.2727)[/C][C]0.398693[/C][/ROW]
[ROW][C]0.46 (2.1739)[/C][C]3.91109[/C][/ROW]
[ROW][C]0.48 (2.0833)[/C][C]12.419976[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.502252[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31359&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31359&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)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.02 (50)3.875074
0.04 (25)59.711711
0.06 (16.6667)9.523267
0.08 (12.5)7.606068
0.1 (10)2.185706
0.12 (8.3333)3.137351
0.14 (7.1429)8.709469
0.16 (6.25)3.224594
0.18 (5.5556)18.278306
0.2 (5)4.005259
0.22 (4.5455)16.509143
0.24 (4.1667)4.630949
0.26 (3.8462)1.115416
0.28 (3.5714)1.60113
0.3 (3.3333)4.608198
0.32 (3.125)0.86306
0.34 (2.9412)59.632119
0.36 (2.7778)35.45788
0.38 (2.6316)3.708664
0.4 (2.5)24.7205
0.42 (2.381)24.720328
0.44 (2.2727)0.398693
0.46 (2.1739)3.91109
0.48 (2.0833)12.419976
0.5 (2)0.502252


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = 0 ; par7 = 0 ; par8 = 0 ; par9 = 0 ;
Parameters (R input):
par1 = 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')