NEWS.md

In longhaiSK/HTLR: Bayesian Logistic Regression with Heavy-Tailed Priors

HTLR 0.4-3

New Features

• Added option for users to keep samples of warmup iterations.

Improvements

• Bug fix [#7].

HTLR 0.4-2

New Features

• Added new function std() for feature standardization.

• Added new dataset diabetes392.

Improvements

• htlr() and predict.htlr.fit() now handles non-matrix input, i.e. data.frame.

• Minor speed improvement on htlr() and gendata_FAM().

• Updated documentation of htlr().

Note

• Changed package license from GPLv2 to GPLv3.

HTLR 0.4-1

Bug Fixes

• Fixed potential memory leak issue in ARS module.

HTLR 0.4

New Features

• 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.

HTLR 0.3

Note

• This is HTLR originally created by Longhai Li with legacy version number 3.1-1.

• Not compatible with macOS.

longhaiSK/HTLR documentation built on Oct. 24, 2022, 5:33 p.m.