marginal_ci

<code>marginal_ci</code> computes the marginal confidence interval for each parameters
using the variance-covariance matrix output by `varest.glinv`.

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

marginal_ci function

<dl><dt>varest_result</dt>
<dd>The output from `varest.glinv`.</dd>
<dt>lvl</dt>
<dd>Confidence level. Default to 95 percent.</dd></dl>

Arguments

Getting marginal confidence interval for GLInv model — marginal_ci

<dl>

<dt>varest_result</dt>
<dd>The output from `varest.glinv`.</dd>


<dt>lvl</dt>
<dd>Confidence level. Default to 95 percent.</dd>

</dl>

marginal_ci: Getting marginal confidence interval for GLInv model

Description

Usage

Value

Arguments