zinbCo

<p>Data.frame containing a sample of weekly average wildfire PM, PM2.5, O3
across a range of counties of Colorado. The exposure data was downloaded from US EPA
(https://aqs.epa.gov/aqsweb/airdata/download_files.html) daily data summaries
and averaged by week.</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

zinbCo function

Format

Time-series exposure data for ZINB simulated data — zinbCo

Time-series exposure data for ZINB simulated data

zinbCo: Time-series exposure data for ZINB simulated data

Description

Usage

Arguments

Format

References