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Author's title

Author

*Unverified author*

R Software Module

rwasp_fitdistrgamma.wasp

Title produced by software

Maximum-likelihood Fitting - Gamma Distribution

Date of computation

Sun, 14 May 2023 16:42:49 +0200

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2023/May/14/t168407544328xvn931wpvakik.htm/, Retrieved Thu, 10 Sep 2026 01:25:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319899, Retrieved Thu, 10 Sep 2026 01:25:25 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

371

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Maximum-likelihood Fitting - Gamma Distribution] [] [2023-05-14 14:42:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319899&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319899&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319899&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Parameter	Estimated Value	Standard Deviation
shape	0.355209604542507	0.0135730095669001
rate	0.00137734214276378	6.46989870814789e-05

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
shape & 0.355209604542507 & 0.0135730095669001 \tabularnewline
rate & 0.00137734214276378 & 6.46989870814789e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319899&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]shape[/C][C]0.355209604542507[/C][C]0.0135730095669001[/C][/ROW]
[ROW][C]rate[/C][C]0.00137734214276378[/C][C]6.46989870814789e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319899&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319899&T=1

As an alternative you can also use a QR Code:

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

Parameter	Estimated Value	Standard Deviation
shape	0.355209604542507	0.0135730095669001
rate	0.00137734214276378	6.46989870814789e-05

Figure 1

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Postscript link

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Figure 2

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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 &lt;- function(shape, rate, x)
{
x &lt;- sort(x)
pp &lt;- ppoints(x)
cor(qgamma(pp, shape=shape, rate=rate), x)
}
par1 &lt;- as.numeric(par1)
par2 &lt;- as.numeric(par2)
if (par1 &lt; 0.1) par1 &lt;- 0.1
if (par1 &gt; 50) par1 &lt;- 50
if (par2 &lt; 0.1) par2 &lt;- 0.1
if (par2 &gt; 50) par2 &lt;- 50
par1h &lt;- par1*10
par2h &lt;- par2*10
sortx &lt;- sort(x)
c &lt;- array(NA,dim=c(par2h))
for (i in par1h:par2h)
{
c[i] &lt;- 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&lt;-fitdistr(x, 'gamma')
f$estimate
f$sd
xlab &lt;- paste('Gamma(shape=',round(f$estimate[[1]],2))
xlab &lt;- paste(xlab,', rate=')
xlab &lt;- paste(xlab,round(f$estimate[[2]],2))
xlab &lt;- 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&lt;-table.start()
a&lt;-table.row.start(a)
a&lt;-table.element(a,'Parameter',1,TRUE)
a&lt;-table.element(a,'Estimated Value',1,TRUE)
a&lt;-table.element(a,'Standard Deviation',1,TRUE)
a&lt;-table.row.end(a)
a&lt;-table.row.start(a)
a&lt;-table.element(a,'shape',header=TRUE)
a&lt;-table.element(a,f$estimate[1])
a&lt;-table.element(a,f$sd[1])
a&lt;-table.row.end(a)
a&lt;-table.row.start(a)
a&lt;-table.element(a,'rate',header=TRUE)
a&lt;-table.element(a,f$estimate[2])
a&lt;-table.element(a,f$sd[2])
a&lt;-table.row.end(a)
a&lt;-table.end(a)
table.save(a,file='mytable.tab')

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Input Parameters & R Code