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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_fitdistrgamma.wasp
Title produced by softwareMaximum-likelihood Fitting - Gamma Distribution
Date of computationSun, 15 Apr 2012 22:53:58 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/15/t1334544980sm32zmfaubmmlpd.htm/, Retrieved Wed, 24 Apr 2024 13:16:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164354, Retrieved Wed, 24 Apr 2024 13:16:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsf1, victories, GPs, distribution
Estimated Impact341

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Maximum-likelihood Fitting - Gamma Distribution] [Distribuição de v...] [2012-04-16 02:53:58] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91
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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' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164354&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164354&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164354&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' @ jenkins.wessa.net






ParameterEstimated ValueStandard Deviation
shape0.8053802016856170.0968809142350381
rate0.09601528832918830.0156352292026842

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
shape & 0.805380201685617 & 0.0968809142350381 \tabularnewline
rate & 0.0960152883291883 & 0.0156352292026842 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164354&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]shape[/C][C]0.805380201685617[/C][C]0.0968809142350381[/C][/ROW]
[ROW][C]rate[/C][C]0.0960152883291883[/C][C]0.0156352292026842[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164354&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164354&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:

ParameterEstimated ValueStandard Deviation
shape0.8053802016856170.0968809142350381
rate0.09601528832918830.0156352292026842


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 8 ;
Parameters (R input):
par1 = 1 ; par2 = 8 ;
R code (references can be found in the software module):
library(MASS)
PPCCGamma <- function(shape, rate, x)
{
x <- sort(x)
pp <- ppoints(x)
cor(qgamma(pp, shape=shape, rate=rate), x)
}
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 0.1) par1 <- 0.1
if (par1 > 50) par1 <- 50
if (par2 < 0.1) par2 <- 0.1
if (par2 > 50) par2 <- 50
par1h <- par1*10
par2h <- par2*10
sortx <- sort(x)
c <- array(NA,dim=c(par2h))
for (i in par1h:par2h)
{
c[i] <- cor(qgamma(ppoints(x), shape=i/10,rate=2),sortx)
}
bitmap(file='test1.png')
plot((par1h:par2h)/10,c[par1h:par2h],xlab='shape',ylab='correlation',main='PPCC Plot - Gamma')
dev.off()
f<-fitdistr(x, 'gamma')
f$estimate
f$sd
xlab <- paste('Gamma(shape=',round(f$estimate[[1]],2))
xlab <- paste(xlab,', rate=')
xlab <- paste(xlab,round(f$estimate[[2]],2))
xlab <- paste(xlab,')')
bitmap(file='test2.png')
qqplot(qgamma(ppoints(x), shape=f$estimate[[1]], rate=f$estimate[[2]]), x, main='QQ plot (Gamma)', 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,'shape',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,'rate',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')