sim.tdlnm

Method for creating simulated data for TDLNM

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

sim.tdlnm function

<dl><dt>sim</dt>
<dd>character (A - D) specifying simulation scenario</dd>
<dt>error.to.signal</dt>
<dd>scalar value setting error: sigma^2/var(f)</dd></dl>

Arguments

Creates simulated data for TDLNM — sim.tdlnm

<dl>

<dt>sim</dt>
<dd>character (A - D) specifying simulation scenario</dd>


<dt>error.to.signal</dt>
<dd>scalar value setting error: sigma^2/var(f)</dd>

</dl>

sim.tdlnm: Creates simulated data for TDLNM

Description

Usage

Value

Arguments

Details

Examples