priorpar: Defining the a priori parameters for the model.

In LauraJim/benmR: Implementation of a Bayesian Method for Estimating Niches from Presence Data

Description

priorpar uses the physiological tolerance limits of the species to determine the values of the parameters that define the a priori distribution.

Usage

priorpar(tolran, nsd, alpha = 2)

Arguments

tolran	numeric vector containing the tolerance limits of the species.
nsd	number of standard deviations covered by a tolerance range.
alpha	number of degrees of freedom in the a priori Wishart distribution.

Details

tolran must contain tolerance ranges of the species to every environmental variable that defines the environmental space. The lenght of this vector must be twice the number of environmental variables. The values contained in odd positions represent lower tolerance limits, and the values in even positions are the upper limits. The value of nsd is used to estimate the diagonal entries of the covariance matrix that defines the a priori (multivariate normal) distribution of the parameter A. It is set such that each range is approximately equals to nsd times the corresponding standard deviation. The value of alpha should be changed only when working with an environmental space of more than 2 dimensions.

Value

A list containing a vector of length equals to the number of dimensions in the environmental space, and two squared matrices with that same number of rows/columns. The first two elements represent the a priori parameters of mu and the third element is the scale matrix that defines the a priori distribution of A.

Examples

# 2-dimensional case with range covering 10 standard deviations
tolran1 <- c(1,2,-1,1)
priorpar(tolran1,10)

LauraJim/benmR documentation built on May 16, 2019, 11:11 p.m.