hzar.cov.rect: Generate a covariance matrix for the cline optimizer.
In hzar: Hybrid Zone Analysis using R

Description Usage Arguments Details Value Author(s) See Also

These methods are intended to generate covariance matrices suitable for use with MCMCmetrop1R.

hzar.cov.rect(clineLLfunc, param.lower, param.upper,
              pDiv = 11, random = 0, passCenter = FALSE)
hzar.cov.mcmc(clineLLfunc, mcmcRaw,
              pDiv = 15, random = 10000, passCenter = FALSE)

`clineLLfunc`	The log likelihood function of the parameters.
`param.lower`	The minimum boundary of the region of parameter space to consider.
`param.upper`	The maximum boundary of the region of parameter space to consider.
`pDiv`	If generating a covariance matrix using a lattice, the lattice should have this many points on an edge.
`random`	Use `random` number of points drawn from a uniform likelihood space to generate the covariance matrix. If 0, use a lattice to generate the covariance matrix.
`passCenter`	Should weighted mean of the parameter space be returned.
`mcmcRaw`	A mcmc object used to refine the covariance matrix.

This method is adaptive, refining the pDiv and random parameters until either it can generate a useable matrix without too high of a memory cost, or random > 1e9 (use a 1 billion or more samples).

A square matrix with a width equal to the number of free parameters.

Graham Derryberry asterion@alum.mit.edu

MCMCmetrop1R

hzar documentation built on May 2, 2019, 7 a.m.