splitPIP

Calculates the posterior inclusion probability (PIP).

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

splitPIP function

<dl><dt>dlnm</dt>
<dd>A numeric matrix containing the model fit information</dd>
<dt>nlags</dt>
<dd>total number of lags</dd>
<dt>niter</dt>
<dd>number of mcmc iterations</dd></dl>

Arguments

Calculates the posterior inclusion probability (PIP). — splitPIP

<dl>

<dt>dlnm</dt>
<dd>A numeric matrix containing the model fit information</dd>


<dt>nlags</dt>
<dd>total number of lags</dd>


<dt>niter</dt>
<dd>number of mcmc iterations</dd>

</dl>

splitPIP: Calculates the posterior inclusion probability (PIP).

Description

Usage

Value

Arguments