Thomas,
The Gamma distr. can be fitted via ML using:
Library("MASS")
GF <- fitdistr(given_data,"gamma")
sh <- GF$estimate[1]
ra <- GF$estimate[2]
Fitting via Moments, m:
var <- m[2] - m[1]*m[1]
sh <- m[1]*m[1]/var
sc <- m[1]/var
ra <- 1/sc
G_pdf <- dgamma(breaks,shape=sh,rate=ra,scale=1/ra)
Hope it helps,
Augusto
--------------------------------------------
Augusto Sanabria. MSc, PhD.
Mathematical Modeller
Risk Research Group
Geospatial & Earth Monitoring Division
Geoscience Australia (www.ga.gov.au)
Cnr. Jerrabomberra Av. & Hindmarsh Dr.
Symonston ACT 2601
Ph. (02) 6249-9155
-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Thomas Petzoldt
Sent: Tuesday, 28 November 2006 10:26
To: r-help@stat.math.ethz.ch
Subject: [R] ML fit of gamma distribution to grouped data
Hello,
we have a set of biological cell-size data, which are only available as
frequencies of discrete size classes, because of the high effort of
manual microscopic measurements.
The lengths are approximately gamma distributed, however the shape of
the distribution is relatively variable between different samples (maybe
it's a mixture in reality).
Is there any ML fitting (or moment-based) procedure for the gamma
distribution and grouped data already available in R?
Here is a small example:
breaks <- c(0, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150)
mids <- c(10, 25, 35, 45, 55, 65, 75, 85, 95, 125)
counts <- c(87, 5, 2, 2, 1, 1, 0, 0, 1, 1)
Any help is highly appreciated
Thomas P.
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