BVAR - Hierarchical Bayesian Vector Autoregression

Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.

Last updated 3 months ago

bayesianbvarforecastsimpulse-responsesvector-autoregressions

7.49 score 51 stars 1 dependents 68 scripts 951 downloads

sanic - Solving Ax = b Nimbly in C++

Routines for solving large systems of linear equations and eigenproblems in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Dense and sparse problems are supported.

Last updated 2 years ago

bicgstabcholeskyconjugate-gradienteigenlinear-equationssolverscpp

4.13 score 9 stars 1 dependents 1 scripts 136 downloads

bsreg - Bayesian Spatial Regression Models

Fit Bayesian models with a focus on the spatial econometric models.

Last updated 3 years ago

3.74 score 11 stars 1 scripts 259 downloads

BVARverse - Tidy Bayesian Vector Autoregression

Functions to prepare tidy objects from estimated models via 'BVAR' (see Kuschnig & Vashold, 2019 <doi:10.13140/RG.2.2.25541.60643>) and visualisation thereof. Bridges the gap between estimating models with 'BVAR' and plotting the results in a more sophisticated way with 'ggplot2' as well as passing them on in a tidy format.

Last updated 4 years ago

bayesiandata-sciencevector-autoregressions

3.00 score 2 stars 7 scripts 266 downloads