maxLikelihood.ESF

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

A collection of sampling formulas for the unified neutral
model of biogeography and biodiversity. Alongside the sampling
formulas, it includes methods to perform maximum likelihood
optimization of the sampling formulas, methods to generate data given
the neutral model, and methods to estimate the expected species
abundance distribution. Sampling formulas included in the GUILDS
package are the Etienne Sampling Formula (Etienne 2005), the guild
sampling formula, where guilds are assumed to differ in dispersal
ability (Janzen et al. 2015), and the guilds sampling formula
conditioned on guild size (Janzen et al. 2015).

Thijs Janzen

GUILDS

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

Bart Haegeman

Franck Jabot

Jerome Chave

maxLikelihood.ESF function

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

Arguments

Author

Maximization of the loglikelihood given the standard Neutral Model, using the Etienne Sampling Formula — maxLikelihood.ESF

<dl>

 <dt>init_vals</dt>
<dd>A vector of initial starting values, of the format c(theta, m)</dd>


 <dt>abund</dt>
<dd>Vector containing a record of the number of individuals per species</dd>


 <dt>verbose</dt>
<dd>TRUE/FALSE flag, indicates whether intermediate output is shown on screen</dd>

</dl>

maxLikelihood.ESF: Maximization of the loglikelihood given the standard Neutral Model, using the Etienne Sampling Formula

Description

Usage

Value

Arguments

Author

References

Examples