On 2011-08-06 15:14, Alexander Engelhardt wrote:
Hey,
I have a set of income data which I'd like to fit to a gamma
distribution. How can I estimate the two parameters of the gamma
distribution for a vector, e.g.
c(2039L, 2088L, 5966L, 2353L, 1966L, 2312L, 3305L, 2013L, 3376L,
3363L, 3567L, 4798L, 2032L, 1699L, 3001L, 2329L, 3944L, 2568L,
1699L, 4545L)
I sense this will be a very easy one-liner, but my searching didn't come
up with results yet.
Thanks in advance,
Alex
Straightforward, using the method of L-moments:
x <- c(2039L, 2088L, 5966L, 2353L, 1966L, 2312L, 3305L, 2013L, 3376L,
3363L, 3567L, 4798L, 2032L, 1699L, 3001L, 2329L, 3944L, 2568L,
1699L, 4545L)
library(lmom)
(pargam <- pelgam(samlmu(x))) # Parameter estimates
evplot(x, quagam, pargam) # check goodness of fit
Note that allowing the distribution to have a nonzero lower bound,
by fitting a 3-parameter gamma distribution ("Pearson type III" in
the terminology of package lmom), gives a visually much better fit:
evdistq(quape3, pelpe3(samlmu(x)), col='blue')
J. R. M. Hosking
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