Package: estimateW 0.0.1

estimateW: Estimation of Spatial Weight Matrices

Bayesian estimation of spatial weight matrices in spatial econometric panel models. Allows for estimation of spatial autoregressive (SAR), spatial Durbin (SDM), 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>.

Authors:Tamas Krisztin [aut, cre], Philipp Piribauer [aut]

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estimateW.pdf |estimateW.html✨
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NEWS

# Install 'estimateW' in R:
install.packages('estimateW', repos = c('https://tkrisztin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tkrisztin/estimatew/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • covid - Covid incidences data

On CRAN:

2.70 score 2 scripts 203 downloads 24 exports 7 dependencies

Last updated 1 years agofrom:ecc0f625ae. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64NOTENov 21 2024
R-4.5-linux-x86_64NOTENov 21 2024
R-4.4-win-x86_64NOTENov 21 2024
R-4.4-mac-x86_64NOTENov 21 2024
R-4.4-mac-aarch64NOTENov 21 2024
R-4.3-win-x86_64NOTENov 21 2024
R-4.3-mac-x86_64NOTENov 21 2024
R-4.3-mac-aarch64NOTENov 21 2024

Exports:bbinompdfbeta_priorsbeta_samplerbetapdflogdetAinvUpdatelogdetPaceBarrynormalgammarho_priorsrho_samplersampleW_fastsarsarwsdemsdemwsdmsdmwsemsemwsigma_priorssigma_samplersim_dgpslxwW_priorsW_sampler

Dependencies:latticeMatrixmatrixcalcplot.matrixR6RcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Probability density for a hierarchical prior setup for the elements of the adjacency matrix based on the beta binomial distributionbbinompdf
Set prior specifications for the slope parametersbeta_priors
An R6 class for sampling slope parametersbeta_sampler
The four-parameter Beta probability density functionbetapdf
Covid incidences datacovid
Efficient update of the log-determinant and the matrix inverselogdetAinvUpdate
Pace and Barry's log determinant approximationlogdetPaceBarry
A Markov Chain Monte Carlo (MCMC) sampler for a linear panel modelnormalgamma
Graphical summary of the estimated adjacency matrix Omegaplot.estimateW
Graphical summary of a generated spatial weight matrixplot.sim_dgp
Specify prior for the spatial autoregressive parameter and sampling settingsrho_priors
An R6 class for sampling the spatial autoregressive parameter rhorho_sampler
A fast sampling step implemented in C++ for updating the spatial weight matrix.sampleW_fast
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial autoregressive model (SAR) with exogenous spatial weight matrix.sar
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial autoregressive model (SAR) with unknown spatial weight matrixsarw
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin error model (SDEM) with exogenous spatial weight matrix.sdem
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin error model (SDEM) with unknown spatial weight matrixsdemw
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin model (SDM) with exogenous spatial weight matrix.sdm
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial Durbin model (SDM) with unknown spatial weight matrixsdmw
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial error model (SEM) with exogenous spatial weight matrix.sem
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial error model (SEM) with unknown spatial weight matrixsemw
Set prior specification for the error variance using an inverse Gamma distributionsigma_priors
An R6 class for sampling for sampling sigma^2sigma_sampler
Simulating from a data generating processsim_dgp
A Markov Chain Monte Carlo (MCMC) sampler for the panel spatial SLX model with unknown spatial weight matrixslxw
Set prior specifications for the spatial weight matrixW_priors
An R6 class for sampling the elements of WW_sampler