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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 02 Dec 2008 17:15:01 -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/03/t1228263410zgebpij1iu2jyaa.htm/, Retrieved Fri, 17 May 2024 17:58:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28542, Retrieved Fri, 17 May 2024 17:58:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ8 non stationary time series
Estimated Impact228

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Standard Deviation-Mean Plot] [Q8 non stationary...] [2008-12-03 00:15:01] [9f72e095d5529918bf5b0810c01bf6ce] [Current]
Feedback Forum
2008-12-09 00:27:17 [Jessica Alves Pires] [reply] 
Ik heb de parameters gevonden, maar ik had deze best kunnen controleren adhv ACF en spectrale analyse.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10812
10738
10171
9721
9897
9828
9924
10371
10846
10413
10709
10662
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745

Tables (Output of Computation)





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=28542&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=28542&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28542&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110341418.4949223108931125
210584.4166666667202.975349301935576
311525.41666666671112.953683454603405
415460.9166666667695.1090768993592520
516322775.6835109056462166

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10341 & 418.494922310893 & 1125 \tabularnewline
2 & 10584.4166666667 & 202.975349301935 & 576 \tabularnewline
3 & 11525.4166666667 & 1112.95368345460 & 3405 \tabularnewline
4 & 15460.9166666667 & 695.109076899359 & 2520 \tabularnewline
5 & 16322 & 775.683510905646 & 2166 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28542&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]10341[/C][C]418.494922310893[/C][C]1125[/C][/ROW]
[ROW][C]2[/C][C]10584.4166666667[/C][C]202.975349301935[/C][C]576[/C][/ROW]
[ROW][C]3[/C][C]11525.4166666667[/C][C]1112.95368345460[/C][C]3405[/C][/ROW]
[ROW][C]4[/C][C]15460.9166666667[/C][C]695.109076899359[/C][C]2520[/C][/ROW]
[ROW][C]5[/C][C]16322[/C][C]775.683510905646[/C][C]2166[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28542&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28542&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:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110341418.4949223108931125
210584.4166666667202.975349301935576
311525.41666666671112.953683454603405
415460.9166666667695.1090768993592520
516322775.6835109056462166






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha26.0807641022395
beta0.0478691143263663
S.D.0.0654341804562054
T-STAT0.731561303169445
p-value0.517401136692253

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 26.0807641022395 \tabularnewline
beta & 0.0478691143263663 \tabularnewline
S.D. & 0.0654341804562054 \tabularnewline
T-STAT & 0.731561303169445 \tabularnewline
p-value & 0.517401136692253 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28542&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]26.0807641022395[/C][/ROW]
[ROW][C]beta[/C][C]0.0478691143263663[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0654341804562054[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.731561303169445[/C][/ROW]
[ROW][C]p-value[/C][C]0.517401136692253[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28542&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28542&T=2

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


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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha26.0807641022395
beta0.0478691143263663
S.D.0.0654341804562054
T-STAT0.731561303169445
p-value0.517401136692253






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.99009772383004
beta1.62070272176584
S.D.1.49522967815824
T-STAT1.08391556524089
p-value0.357737738073114
Lambda-0.620702721765837

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.99009772383004 \tabularnewline
beta & 1.62070272176584 \tabularnewline
S.D. & 1.49522967815824 \tabularnewline
T-STAT & 1.08391556524089 \tabularnewline
p-value & 0.357737738073114 \tabularnewline
Lambda & -0.620702721765837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28542&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.99009772383004[/C][/ROW]
[ROW][C]beta[/C][C]1.62070272176584[/C][/ROW]
[ROW][C]S.D.[/C][C]1.49522967815824[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.08391556524089[/C][/ROW]
[ROW][C]p-value[/C][C]0.357737738073114[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.620702721765837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28542&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28542&T=3

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


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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.99009772383004
beta1.62070272176584
S.D.1.49522967815824
T-STAT1.08391556524089
p-value0.357737738073114
Lambda-0.620702721765837


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')