pm25Exposures

<p>Data.frame containing a sample of weekly average PM2.5 exposures
across a range of states/counties. The PM2.5 data was downloaded from US EPA
(https://aqs.epa.gov/aqsweb/airdata/download_files.html) daily data summaries
and averaged by week. Forty-week ranges were assess for non-missingness
and grouped for this dataset.</p>

datasets

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

pm25Exposures function

<p>data.frame; columns: S = state, C = city, 1-40 = weekly exposure data</p>

pm25Exposures: PM2.5 Exposure data

Description

Usage

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References