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Author's title

Author*Unverified author*
R Software Modulerwasp_fitdistrbeta.wasp
Title produced by softwareMaximum-likelihood Fitting - Beta Distribution
Date of computationTue, 10 Mar 2009 10:03:54 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Mar/10/t12367011124b88zjearwhnrlu.htm/, Retrieved Thu, 28 Mar 2024 16:00:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38888, Retrieved Thu, 28 Mar 2024 16:00:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Maximum-likelihood Fitting - Beta Distribution] [jamestest1] [2009-03-10 16:03:54] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0.224565646
0.261571480
0.253029834
0.033938060
0.353208554
0.033295045
0.002171707
0.084136132
0.077468368
0.010160325
0.079746191
0.263485597
0.460389066
0.132348066
0.529154319
0.032287005
0.472190992
0.037985170
0.019795866
0.053763887
0.086771175
0.143764004
0.202780264
0.006932185
0.124637036
0.116166293
0.037363442
0.416532177
0.612491026
0.012781084
0.163992436
0.212717925
0.092409609
0.150134816
0.047430792
0.022017328
0.350262865
0.013821921
0.578796918
0.030264300
0.090627282
0.029354226
0.182663201
0.372085552
0.235142217
0.311617946
0.030548270
0.068424450
0.043757662
0.238109173
0.465951209
0.127494709
0.010810575
0.230141979
0.426687450
0.175605499
0.005595384
0.203565169
0.236888269
0.153586896
0.027445414
0.026240968
0.299075759
0.171469487
0.016355307
0.220064442
0.137054994
0.034683689
0.085767702
0.119746590
0.223347602
0.026601623
0.063485064
0.467803972
0.012650088
0.048496183
0.047170846
0.043196485
0.095073370
0.538513979
0.045034181
0.427235474
0.289835816
0.150884924
0.176887675
0.369202741
0.178461483
0.077501113
0.281105892
0.051375864
0.357311398
0.561861189
0.028342902
0.326209843
0.303994601
0.020530542
0.278139180
0.582716856
0.071720238
0.237546024




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38888&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38888&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







ParameterEstimated ValueStandard Deviation
shape10.8831688710459110.109123975144155
shape24.031503969887560.61174264711213

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
shape1 & 0.883168871045911 & 0.109123975144155 \tabularnewline
shape2 & 4.03150396988756 & 0.61174264711213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38888&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]shape1[/C][C]0.883168871045911[/C][C]0.109123975144155[/C][/ROW]
[ROW][C]shape2[/C][C]4.03150396988756[/C][C]0.61174264711213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38888&T=1

As an alternative you can also use a QR Code:  

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

ParameterEstimated ValueStandard Deviation
shape10.8831688710459110.109123975144155
shape24.031503969887560.61174264711213



Parameters (Session):
par1 = 0.1 ; par2 = 3 ; par3 = 2 ; par4 = 6 ;
Parameters (R input):
par1 = 0.1 ; par2 = 3 ; par3 = 2 ; par4 = 6 ;
R code (references can be found in the software module):
library(MASS)
PPCCBeta <- function(shape1, shape2, x)
{
x <- sort(x)
pp <- ppoints(x)
cor(qbeta(pp, shape1=shape1, shape2=shape2), x)
}
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if (par1 < 0.1) par1 <- 0.1
if (par1 > 10) par1 <- 10
if (par2 < 0.1) par2 <- 0.1
if (par2 > 10) par2 <- 10
if (par3 < 0.1) par3 <- 0.1
if (par3 > 10) par3 <- 10
if (par4 < 0.1) par4 <- 0.1
if (par4 > 10) par4 <- 10
par1h <- par1*10
par2h <- par2*10
par3h <- par3*10
par4h <- par4*10
sortx <- sort(x)
c <- array(NA,dim=c(par2h,par4h))
for (i in par1h:par2h)
{
for (j in par3h:par4h)
{
c[i,j] <- cor(qbeta(ppoints(x), shape1=i/10,shape2=j/10),sortx)
}
}
bitmap(file='test1.png')
filled.contour((par1h:par2h)/10,(par3h:par4h)/10,c[par1h:par2h,par3h:par4h],xlab='shape1',ylab='shape2',main='PPCC Contour Plot - Beta')
dev.off()
xbar <- mean(x)
xvar <- var(x)
(a <- (xbar*(1-xbar)/xvar - 1)*xbar)
(b <- (1-xbar)*a)
(f<-fitdistr(x, 'beta',list(shape1=a,shape2=b)))
xlab <- paste('Beta(shape1=',round(f$estimate[[1]],2))
xlab <- paste(xlab,', shape2=')
xlab <- paste(xlab,round(f$estimate[[2]],2))
xlab <- paste(xlab,')')
bitmap(file='test2.png')
myser <- qbeta(ppoints(x), shape1=f$estimate[[1]], shape2=f$estimate[[2]])
qqplot(myser, x, main='QQ plot (Beta)', xlab=xlab )
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'shape1',header=TRUE)
a<-table.element(a,f$estimate[1])
a<-table.element(a,f$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'shape2',header=TRUE)
a<-table.element(a,f$estimate[2])
a<-table.element(a,f$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')