has_tipvals

has_tipvals.glinv_gauss

has_tipvals.glinv

Returns true if and only if the <code>glinv_gauss</code> model were initialised with <code>X=NULL</code>
and the user had never called <code>set_tips</code> on it.

A framework for analytically computing the asymptotic confidence intervals and maximum-likelihood estimates of a class of continuous-time Gaussian branching processes defined by Mitov V, Bartoszek K, Asimomitis G, Stadler T (2019) <doi:10.1016/j.tpb.2019.11.005>. The class of model includes the widely used Ornstein-Uhlenbeck and Brownian motion branching processes. The framework is designed to be flexible enough so that the users can easily specify their own sub-models, or re-parameterizations, and obtain the maximum-likelihood estimates and confidence intervals of their own custom models.

Hao Chi Kiang

glinvci

Phylogenetic Comparative Methods with Uncertainty Estimates

Woodrow Kiang

has_tipvals function

<dl><dt>mod</dt>
<dd>A <code>glinv_gauss</code> object.</dd></dl>

Arguments

Check if a glinv_gauss model contains trait values at their tips. — has_tipvals

<dl>

<dt>mod</dt>
<dd>A <code>glinv_gauss</code> object.</dd>

</dl>

has_tipvals: Check if a `glinv_gauss` model contains trait values at their tips.

Description

Usage

Value

Arguments