vm_reg: Bayesian inference for von Mises regression.

In keesmulder/circbayes: Bayesian Analysis of Circular Data

Description

Bayesian inference for von Mises regression.

Usage

vm_reg(formula, data, prior_b0kp = c(0, 0, 0), prior_btdt = c(0, 1),
  niter = 1000, r = 2, ...)

Arguments

formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
data	A data frame or matrix containing the circular observations and predictors.
prior_b0kp	Numeric vector of length 3. The prior parameters of the von Mises conjugate prior for the intercept and concentration parameter.
prior_btdt	Numeric vector of length 2. The prior parameters for the normal prior on the regression coefficients.
niter	Number of iterations to perform MCMC for.
r	Parameter of the link function, g(x) = r * arctan(x).
...	Further arguments passed to circglmbayes::circGLM.

Value

Object of type vm_reg_mod.

Examples

dat <- rvm_reg(30)
vm_reg(th ~ ., data = dat)

keesmulder/circbayes documentation built on May 30, 2019, 2:04 p.m.