bvhar 2.4.1

• Fixed Average LPL computation process in pseudo out-of-sample forecasting.

• Added IRF classes in C++.

R

• Fixed wrong post-processing of MCMC posterior draws. This can change the results of post-analysis of the old code.

Python

• -DBVHAR_USE_PYBIND11 macro is required to use the header with Pybind11.

C++

• Added boost.Random-based constructor for each MCMC initial values struct.

• Now header-only C++ library is available.

• Use Catch2 for C++ unit tests.