README.md

In jetroant/rbsvarbm: Bayesian estimation of statistically identified robust structural vectorautoregressive models

rbsvarbm

This is a less stable version of rbsvar (see https://github.com/jetroant/rbsvar), an R-package for Bayesian estimation of statistically identified robust structural vectorautoregressive models. rbsvarbm includes new features not yet implemented in rbsvar Most notably, bm stands for bigmemory (R-package), which allows for file backed memory structures, whenever memory becomes a limiting factor when estimating big models.

Getting Started

Prerequisites

Make sure you have the latest version of R installed on your computer. On top of that, see the operating system specific further prerequisities below for the development version of the package to work on your computer.

Windows:

Rtools must be installed on your computer. See: https://cran.r-project.org/bin/windows/Rtools/

Mac:

Make sure you have Xcode installed. If not, it can be found from the App Store OR it can be installed in the shell by:

xcode-select --install

After installing Xcode, a few more steps might still be necessary. For comprehensive instructions, see: https://thecoatlessprofessor.com/programming/cpp/openmp-in-r-on-os-x/#after-3-4-0

In short, (i) the official gfortran 6.1 build (see: https://gcc.gnu.org/wiki/GFortranBinaries#MacOS-11) and (ii) clang (compiler, see: https://uofi.box.com/v/r-macos-clang-pkg) may need to be downloaded and installed.

Linux:

Everything should be just fine. Just make sure you have everything Rcpp needs.

Installing the package

If you do not have devtools installed, install it in R by:

install.packages("devtools")

After devtools is installed, install and load the package by:

devtools::install_github("jetroant/rbsvarbm")
library(rbsvarbm)

jetroant/rbsvarbm documentation built on Dec. 20, 2021, 11:06 p.m.