profile.cauphyfit: Method for Profiling `cauphyfit` Objects

Description

Investigates the profile log-likelihood function for a fitted model of class cauphyfit.

Usage

# S3 method for cauphyfit
profile(fitted, which = 1:npar, level = 0.8, npoints = 100, ...)

Value

An object of class profile.cauphyfit, which is a list with an element for each parameter being profiled. The elements are data-frames with two variables:

par.vals:: a matrix of parameter values for each fitted model.
profLogLik:: the profile log likelihood.

Arguments

fitted: the cauphyfit fitted model object.
which: the original model parameters which should be profiled. This can be a numeric or character vector. By default, all parameters are profiled.
level: highest confidence level for parameters intervals, computed using the approximated Hessian (see compute_vcov).
npoints: number of points to profile the likelihood for each parameter.
...: further arguments passed to or from other methods.

Details

This function computes a confidence interval for the parameters using confint.cauphyfit, and then computes the likelihood function on a grid with npoints values evenly spaced between the bounds of the interval, for each parameter one by one, all other parameters being fixed.

Examples

Run this code

phy <- ape::rphylo(5, 0.1, 0)
dat <- rTraitCauchy(n = 1, phy = phy, model = "cauchy", parameters = list(root.value = 0, disp = 1))
fit <- fitCauchy(phy, dat, model = "cauchy", method = "reml")
pr <- profile(fit)
plot(pr)