beta_priors: Set prior specifications for the slope parameters

In estimateW: Estimation of Spatial Weight Matrices

Set prior specifications for the slope parameters

Description

This function allows the user to specify custom values for Gaussian priors on the slope parameters.

Usage

beta_priors(
  k,
  beta_mean_prior = matrix(0, k, 1),
  beta_var_prior = diag(k) * 100
)

Arguments

k	The total number of slope parameters in the model.
beta_mean_prior	numeric k by 1 matrix of prior means \underline{\mu}_\beta.
beta_var_prior	A k by k matrix of prior variances \underline{V}_\beta. Defaults to a diagonal matrix with 100 on the main diagonal.

Details

For the slope parameters \beta the package uses common Normal prior specifications. Specifically, p(\beta)\sim\mathcal{N}(\underline{\mu}_\beta,\underline{V}_\beta).

This function allows the user to specify custom values for the prior hyperparameters \underline{\mu}_\beta and \underline{V}_\beta. The default values correspond to weakly informative Gaussian priors with mean zero and a diagonal prior variance-covariance matrix with 100 on the main diagonal.

Value

A list with the prior mean vector (beta_mean_prior), the prior variance matrix (beta_var_prior) and the inverse of the prior variance matrix (beta_var_prior_inv).

estimateW documentation built on June 8, 2025, 10:07 a.m.