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Last data update: 2014.03.03

R: wrapper for fitting the Poisson lognormal

texmex.fit

R Documentation

wrapper for fitting the Poisson lognormal

Description

A nice wrapper for the poilogMLE function.

Usage

  texmex.fit(n, start.mus=c(-2.0, -1.0, 0.0, 1.0, 2.0), start.sigs=rep(1.0, times=5), ...)

Arguments

`n`	vector of observed counts
`start.mus`	vector of starting `mu` values
`start.sigs`	vector of starting `sig` values
`...`	further parameters to go to `poilogMLE`

Details

It can be a little annoying to direclty use poilogMLE: the optimization can fail to converge if you choose a bad starting mu value. This function makes multiple attempts at fitting the poilog distribution, returning the first one that works.

For the first attempt, the first mu and sig are used as starting values. For the second attempt, the second elements of those vectors, etc.

Value

`par`	Maximum likelihood estimates of the parameters
`p`	Approximate fraction of OTUs revealed by the sample
`logLval`	Log likelihood of the data given the estimated parameters

Author(s)

Scott Olesen swo@mit.edu

Examples

# create some random data
x <- rpoilog(S=1000, mu=-2.0, sig=2.0, keep0=FALSE)

# fit that data
res <- texmex.fit(x)