R: Estimation of Spatial Weight Matrices

# Estimation of Spatial Weight Matrices

## Documentation for package ‘estimateW’ version 0.2.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

bbinompdf | Probability density for a hierarchical prior setup for the elements of the adjacency matrix based on the beta binomial distribution
betapdf | The four-parameter Beta probability density function
beta_priors | Set prior specifications for the slope parameters
beta_sampler | An R6 class for sampling slope parameters
covid | Covid incidences data
logdetAinvUpdate | Efficient update of the log-determinant and the matrix inverse
logdetPaceBarry | Pace and Barry's log determinant approximation
logdetSpline | Spline-based log determinant approximation
normalgamma | A Markov Chain Monte Carlo (MCMC) sampler for a linear panel model
nuts1growth | Regional growth data for European NUTS-1 regions
plot.estimateW | Graphical summary of the estimated adjacency matrix Omega
plot.sim_dgp | Graphical summary of a generated spatial weight matrix
rho_priors | Specify prior for the spatial autoregressive parameter and sampling settings
rho_sampler | An R6 class for sampling the spatial autoregressive parameter rho
sar | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial autoregressive model (SAR) with exogenous spatial weight matrix.
sarw | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial autoregressive model (SAR) with unknown spatial weight matrix
sdem | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin error model (SDEM) with exogenous spatial weight matrix.
sdemw | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin error model (SDEM) with unknown spatial weight matrix
sdm | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin model (SDM) with exogenous spatial weight matrix.
sdmw | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin model (SDM) with unknown spatial weight matrix
sem | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial error model (SEM) with exogenous spatial weight matrix.
semw | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial error model (SEM) with unknown spatial weight matrix
sigma_priors | Set prior specification for the error variance using an inverse Gamma distribution
sigma_sampler | An R6 class for sampling for sampling sigma^2
sim_dgp | Simulating from a data generating process
slx | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial SLX model with exogenous spatial weight matrix
slxw | A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial SLX model with unknown spatial weight matrix
W_priors | Set prior specifications for the spatial weight matrix
W_sampler | An R6 class for sampling the elements of W