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 10 days ago

bayesianbvarforecastsimpulse-responsesvector-autoregressions

7.48 score 50 stars 1 packages 65 scripts 1.0k 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 1 years ago

bicgstabcholeskyconjugate-gradienteigenlinear-equationssolvers

4.13 score 9 stars 1 packages 1 scripts 190 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 218 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 143 downloads