dentist: Computing uncertainty by sampling points around maximum likelihood estimates

Abstract

AbstractIt is standard statistical practice to provide measures of uncertainty around parameter estimates. Unfortunately, this very basic and necessary enterprise is often absent in macroevolutionary studies.dentist is an R package allows an estimate of confidence intervals around parameter estimates without an analytic solution to likelihood equations or an approximation based on local curvature at a peak. This package works by “denting” the likelihood surface by sampling points a specified distance around the maximum likelihood estimate following what is essentially a Metropolis-Hastings walk.We describe the importance of estimating uncertainty around parameter estimates as well as demonstrate the ability of dentist to accurately estimate confidence intervals.We introduce several plotting tools to visualize the results of a dentist analysis. dentist is freely available fromhttps://github.com/bomeara/dentist, written in the R language, and can be used for any given likelihood function.