This is the first released version of revamped HTLR.

The Gibbs sampling routine is completely refactored using RcppArmadillo, which leads to a significant performance gain on multi-core/distributed machines.

The fitted model object is registered to S3 class htlrfit, coming with a set of useful S3 methods print(), summary(), predict(), as.matrix(), and nobs().

New model fitting function htlr() has a more accessible interface, while htlr_fit() and htlr_predict() are still keeped for the best possible backward compatibility.

Better cohesion with bayesplot and other packages of RStan toolchain.

Added new dataset colon.