maxLikelihood.ESF: Maximization of the loglikelihood given the standard Neutral...

In GUILDS: Implementation of Sampling Formulas for the Unified Neutral Model of Biodiversity and Biogeography, with or without Guild Structure

Maximization of the loglikelihood given the standard Neutral Model, using the Etienne Sampling Formula

Description

This function computes the maximum likelihood estimates of the parameters of the Neutral model, using the Etienne Sampling Formula

Usage

maxLikelihood.ESF(init_vals, abund, verbose = FALSE)

Arguments

init_vals	A vector of initial starting values, of the format c(theta, m)
abund	Vector containing a record of the number of individuals per species
verbose	TRUE/FALSE flag, indicates whether intermediate output is shown on screen

Value

the output is a list containing the following:

par	a vector containing the parameter values at the maximum likelihood c(theta, m)
fvalues	the likelihood at the corresponding parameter values
conv	gives a message on convergence of optimization; conv = 0 means convergence

Author(s)

Thijs Janzen

References

Etienne, R.S. (2005). A new sampling formula for neutral biodiversity. Ecology Letters, 8(3), 253-260.

Examples

	A <- c(1, 1, 1, 3, 5, 8)
	maxLikelihood.ESF( c(7, 0.1), abund = A)

GUILDS documentation built on Aug. 21, 2023, 5:10 p.m.