README.md

In kvasilopoulos/abvar: Vector Autoregression Models

varm

Introduction

The goal of {varm} is the estimation and identification of Vector Autoregressive (VAR) models. Still is a work in progess, any suggestion for what might be of interest is much appreciated.

irf -> array[impulse, response, horizon, n]

Ideas on subroutines

Defers the computation until specific point

Naming: - gen - _ - impl

Status

• [ ] VAR
  • [x] VAR impulse response function (IRFs)
    • [ ] Identification
      • [ ] Reduce form
      • [x] Cholesky
      • [ ] Long-run restrictions
      • [ ] Sign restrictions
        • [ ] Uhlig
        • [ ] Rubio Ramirez
        • [ ] Fry Pagan
      • [ ] Proxy
        • [ ] Mertens and Ravn/Stock and Watson
    • [ ] Confidence bands
      • [ ] Asymptotic
      • [ ] Monte Carlo
      • [x] Bootstrap
      • [ ] Wild bootstrap
      • [ ] Block bootstrap
• [ ] BVAR

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("kvasilopoulos/varm")

Please note that the ‘varm’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

kvasilopoulos/abvar documentation built on April 27, 2021, 6:38 a.m.