sigma_priors

Set prior specification for the error variance using an inverse Gamma distribution

Bayesian estimation of spatial weight matrices in spatial
econometric panel models. Allows for estimation of spatial
autoregressive (SAR), spatial error (SEM), spatial Durbin (SDM),
spatial error Durbin (SDEM) and spatially lagged explanatory variable
(SLX) type specifications featuring an unknown spatial weight matrix.
Methodological details are given in Krisztin and Piribauer (2022)
<doi:10.1080/17421772.2022.2095426>.

Tamas Krisztin

estimateW

Estimation of Spatial Weight Matrices

Philipp Piribauer

sigma_priors function

<dl><dt>sigma_rate_prior</dt>
<dd>Sigma rate prior parameter (scalar), default: \(0.001\).</dd>
<dt>sigma_shape_prior</dt>
<dd>Sigma shape prior parameter (scalar), default: \(0.001\).
This function allows the user to specify priors for the error variance \(\sigma^2\).</dd></dl>

Arguments

Set prior specification for the error variance using an inverse Gamma distribution — sigma_priors

<dl>

<dt>sigma_rate_prior</dt>
<dd>Sigma rate prior parameter (scalar), default: \(0.001\).</dd>


<dt>sigma_shape_prior</dt>
<dd>Sigma shape prior parameter (scalar), default: \(0.001\).
This function allows the user to specify priors for the error variance \(\sigma^2\).</dd>

</dl>

sigma_priors: Set prior specification for the error variance using an inverse Gamma distribution

Description

Usage

Arguments