WGBP: GBP Approximation (Logistic)

In eyanchenko/r2d2glmm: Implements Methods from Yanchenko and Reich (2021+)

GBP Approximation (Logistic)

Description

This function finds the closest generalized beta prime (GBP) distribution to the true pdf of W as measured by the Pearson chi-squared divergence

Usage

WGBP(
  a = 1,
  b = 1,
  lambda = 0.25,
  b0 = 0,
  link = c("Logistic", "Poisson", "Poisson_offsets", "ZIP", "NegBinom", "Arbitrary"),
  theta = 1,
  mu,
  sigma2,
  disp = FALSE
)

Arguments

a	value of a for prior R2~Beta(a,b)
b	value of b for prior R2~Beta(a,b)
lambda	tuning parameter
b0	value of beta0
link	link function used to compute R2. Default options are "Logistic", "Poisson", "Poisson_offsets", "ZIP" and "NegBinom". Also can have user-inputted link function using "Arbitrary".
theta	dispersion parameter (if necessary)
mu	if link="Arbitrary", then this is the mean function of the linear predictor. May depend on theta
sigma2	if link="Arbitrary", then this is the variance function of the linear predictor. May depend on theta
disp	logical. TRUE if arbitrary link function depends on a dispersion parameter

Value

parameters (alpha,beta,c,d) for GBP

eyanchenko/r2d2glmm documentation built on July 1, 2023, 12:37 p.m.