dlmtree1.0.0 package

Bayesian Treed Distributed Lag Models

predict.hdlmm

Calculates predicted response for HDLMM

print.hdlm

Print a hdlm Object

print.hdlmm

Print a hdlmm Object

print.monotone

Print a monotone Object

print.summary.hdlm

Prints an overview with summary of model class 'hdlm'

print.summary.hdlmm

Prints an overview with summary of model class 'hdlmm'

print.summary.monotone

Prints an overview with summary of model class 'monotone'

print.summary.tdlm

Prints an overview with summary of model class 'tdlm'

print.summary.tdlmm

Prints an overview with summary of model class 'tdlmm'

print.summary.tdlnm

Prints an overview with summary of model class 'tdlnm'

print.tdlm

Print a tdlm Object

print.tdlmm

Print a tdlmm Object

print.tdlnm

Print a tdlnm Object

rcpp_pgdraw

Multiple draw polya gamma latent variable for var c[i] with size b[i]

rtmvnorm

Truncated multivariate normal sampler, mean mu, cov sigma, truncated (...

ruleIdx

Calculates the weights for each modifier rule

scaleModelMatrix

Centers and scales a matrix

shiny.hdlm

Executes a 'shiny' app for HDLM.

shiny.hdlmm

Executes a 'shiny' app for HDLMM.

shiny

shiny

summary.tdlmm

Creates a summary object of class 'tdlmm'

summary.tdlnm

Creates a summary object of class 'tdlnm'

tdlmm

Treed Distributed Lag Mixture Models (Deprecated)

tdlmm_Cpp

dlmtree model with tdlmm approach

tdlnm

Treed Distributed Lag Non-Linear Models (Deprecated)

tdlnm_Cpp

dlmtree model with tdlnm approach

zeroToInfNormCDF

Integrates (0,inf) over multivariate normal

dlnmPLEst

Calculates the distributed lag effect with DLM matrix for non-linear m...

drawTree

Draws a new tree structure

estDLM

Calculates subgroup-specific lag effects for heterogeneous models

plot.summary.tdlnm

Returns variety of plots for model summary of class 'tdlnm'

ppRange

Makes a 'pretty' output of a group of numbers

predict.hdlm

Calculates predicted response for HDLM

dlnmEst

Calculates the distributed lag effect with DLM matrix for non-linear m...

summary.tdlm

Creates a summary object of class 'tdlm'

dlmtreeTDLM_cpp

dlmtree model with nested HDLM approach

dlmtreeTDLMFixedGaussian

dlmtree model with fixed Gaussian approach

dlmtreeTDLMNestedGaussian

dlmtree model with nested Gaussian approach

adj_coexposure

Adjusting for expected changes in co-exposure (TDLMM)

combine.models

Combines information from DLMs of single exposure

combine.models.tdlmm

Combines information from DLMs of mixture exposures.

cppIntersection

fast set intersection tool assumes sorted vectors A and B

dlmEst

Calculates the distributed lag effect with DLM matrix for linear model...

dlmtree-package

dlmtree: Bayesian Treed Distributed Lag Models

dlmtree

Fit tree structured distributed lag models

dlmtreeGPFixedGaussian

dlmtree model with fixed Gaussian process approach

dlmtreeGPGaussian

dlmtree model with Gaussian process approach

dlmtreeHDLMGaussian

dlmtree model with shared HDLM approach

dlmtreeHDLMMGaussian

dlmtree model with HDLMM approach

get_sbd_dlmtree

Download simulated data for dlmtree articles

mixEst

Calculates the lagged interaction effects with MIX matrix for linear m...

monotdlnm_Cpp

dlmtree model with monotone tdlnm approach

pip

Calculates posterior inclusion probabilities (PIPs) for modifiers in H...

plot.summary.monotone

Returns variety of plots for model summary of class 'monotone'

plot.summary.tdlm

Plots a distributed lag function for model summary of 'tdlm'

plot.summary.tdlmm

Plots DLMMs for model summary of class 'tdlmm'

sim.hdlmm

Creates simulated data for HDLM & HDLMM

sim.tdlmm

Creates simulated data for TDLM & TDLMM

sim.tdlnm

Creates simulated data for TDLNM

splitPIP

Calculates the posterior inclusion probability (PIP).

splitpoints

Determines split points for continuous modifiers

summary.hdlm

Creates a summary object of class 'hdlm'

summary.hdlmm

Creates a summary object of class 'hdlmm'

summary.monotone

Creates a summary object of class 'monotone'

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 help interpret results.

  • Maintainer: Daniel Mork
  • License: GPL (>= 3)
  • Last published: 2024-05-31