sim.tdlmm: Creates simulated data for TDLM & TDLMM

In dlmtree: Bayesian Treed Distributed Lag Models

Creates simulated data for TDLM & TDLMM

Description

Method for creating simulated data for TDLM & TDLMM

Usage

sim.tdlmm(
  sim = "A",
  n = 5000,
  error = 10,
  mean.p = 0.5,
  prop.active = 0.05,
  expList = NULL,
  r = 1
)

Arguments

sim	character (A - F) specifying simulation scenario
n	sample size for simulation
error	positive scalar specifying error variance for Gaussian response
mean.p	scalar between zero and one specifying mean probability for simulation scenario A
prop.active	proportion of active exposures for simulation scenario C
expList	named list of exposure data
r	dispersion parameter of negative binomial distribution

Details

sim.tdlmm

Simulation scenarios:

• Scenario A: Binary response with single exposure effect

• Scenario B: Continuous response with main effect of PM2.5 and interaction

• Scenario C: Continuous response to test exposure selection using exposure

• Scenario D: Continuous response to test exposure selection using one exposure of main effect and two interaction effects among four exposures

• Scenario E: Zero-inflated count response with single exposure effect

• Scenario F: Zero-inflated count response with single exposure effect with main effect of PM2.5 and interaction

Value

Simulated data and true parameters

Examples

sim.tdlmm(sim = "A", mean.p = 0.5, n = 1000)

dlmtree documentation built on June 22, 2024, 10:05 a.m.