MCMCprecision 0.3.6
===========

* Fixed WARNING: Found ‘__assert_fail’, possibly from ‘assert’ (C)


MCMCprecision 0.3.5
===========

* Registered C++ routines
* Improved Description file


MCMCprecision 0.3.3
===========

* Alternative method to compute eigenvectors: RcppEigen package
* Improved starting values for Dirichlet estimation algorithm
* Maximum likelihood estimation of stationary distribution: stationary.mle()
* Changed default prior to epsilon=1/M (M= number of sampled models)
* Changed default method to compute eigenvalue decomposition to RcppArmadillo (method="arma")


MCMCprecision 0.3.0
===========

* Improved estimation of Dirichlet parameters to get effective sample size (C++ version of fixed-point algorithm by Mink, 2000)
* New function best.k() to get summary for the k models with highest posterior model probability
* Exports function rdirichlet()
* Updated licence: GPL-3 (instead of GPL-2)


MCMCprecision 0.2.1
===========

* New function best.k() to assess estimation uncertainty for the k models with the highest posterior model probabilities


MCMCprecision 0.2.0
===========

* Implementations with RcppArmadillo::eig_gen and base::eigen
