initial estimate for the lognormal standard deviation
trunc
remove weight from zero counts?
method
optimization method for optim
control
list of parameters for optim
...
further parameters to go to optim
Details
The function estimates parameters mean mu and standard deviation sig.
The parameters must be given starting values for the optimization procedure.
The default values here worked well when fitting OTUs in the referenced paper.
The function uses the optimization procedures in optim to make the
maximum likelihood estimate. The method and control arguments are
passed to optim.
A zero-truncated distribution (see dpoilog) is assumed by default.
Truncation should only be turned off if all the known OTUs of the sequenced
community are known. In most cases, this is not applicable, since it is usually
not possible to know if an OTU had zero counts because it is not present in
the environment or if it is present but in low abundance.
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
# create some random data
x <- rpoilog(S=1000, mu=-2.0, sig=2.0, keep0=FALSE)
# fit that data
res <- poilogMLE(x, 2.0, -2.0)
# the results should be fairly robust to the starting parameters
res2 <- poilogMLE(x, 1.0, 0.5)