dlmtree.control.mix

Control settings for dlmtree model fitting, when used for mixture models

Estimation of distributed lag models (DLMs) based on a Bayesian additive regression trees framework. Includes several extensions of DLMs: treed DLMs and distributed lag mixture models (Mork and Wilson, 2023) <doi:10.1111/biom.13568>; treed distributed lag nonlinear models (Mork and Wilson, 2022) <doi:10.1093/biostatistics/kxaa051>; heterogeneous DLMs (Mork, et. al., 2024) <doi:10.1080/01621459.2023.2258595>; monotone DLMs (Mork and Wilson, 2024) <doi:10.1214/23-BA1412>. The package also includes visualization tools and a 'shiny' interface to check model convergence and to help interpret results.

Daniel Mork

dlmtree

Bayesian Treed Distributed Lag Models

Seongwon Im

Ander Wilson

dlmtree.control.mix function

<dl><dt>interactions</dt>
<dd>'noself' (default) which estimates interactions only between two 
different exposures, 'all' which also allows interactions within the same exposure, or 'none' 
which eliminates all interactions and estimates only main effects of each exposure.</dd>
<dt>sparsity.prior</dt>
<dd>positive scalar hyperparameter for sparsity of exposures. (default: 1)</dd></dl>

Arguments

Control settings for dlmtree model fitting, when used for mixture models — dlmtree.control.mix

<dl>

<dt>interactions</dt>
<dd>'noself' (default) which estimates interactions only between two 
different exposures, 'all' which also allows interactions within the same exposure, or 'none' 
which eliminates all interactions and estimates only main effects of each exposure.</dd>


<dt>sparsity.prior</dt>
<dd>positive scalar hyperparameter for sparsity of exposures. (default: 1)</dd>

</dl>

dlmtree.control.mix: Control settings for dlmtree model fitting, when used for mixture models

Description

Usage

Value

Arguments