Add-on packages for R:
- Inverse Regression for Analysis of Sentiment in Text
Inference for text documents and the associated sentiment
characteristics. Includes fast sparse multinomial inverse regression for phrase counts, as well as partial least squares and related tools.
- Dynamic Regression Trees (with R.B. Gramacy).
Sequential inference for dynamic treed regression and
classification; constant, linear, and multinomial leaf models are
implemented with demos including
optimization, active learning, and classification.
Bmix - Sampling for (dynamic) stick-breaking mixtures.
Basic implementation for almost anything I've done with npBayes,
including particle learning and Gibbs sampling for static DP mixtures,
particle learning for dynamic BAR stick-breaking, and DP regression.
tgp - Treed Gaussian processes (with R.B. Gramacy).
Bayesian partition tree regression for constant, linear, or GP leaves;
with sensitivity analysis, sequential design, optimization, and more.