bvar: Gibbs sampler to implement a first order bvar model

In nickseedorff/bmrarm: Bayesian Mixed Response Autoregressive Models

Gibbs sampler to implement a first order bvar model

Description

Gibbs sampler to implement a first order bvar model

Usage

bvar(
  formula,
  data,
  sig_prior = 1e+06,
  nsim = 1000,
  burn_in = 100,
  thin = 10,
  seed = 14
)

Arguments

formula	an object of class "formula"; a symbolic description of the model to be fitted
data	a dataframe containing outcome variables, covariates, and a patient or subject identifier
sig_prior	scalar, prior variance on the regression coefficients
nsim	positive integer, number of iterations with default of 1000
burn_in	positive integer, number of iterations to remove with default of 100
thin	positive integer, specifiers the period of saving samples. Default of 10
seed	positive integer, seed for random number generation

Value

bmrvarx

nickseedorff/bmrarm documentation built on April 17, 2025, 9:43 p.m.