Changes in version 1.0                         

PTT 1.0 is the first official release of the package.

Models

  - Provides adaptive Pólya tree (APT), Markov APT, and optional Pólya
    tree (OPT) models for Bayesian nonparametric density estimation.
  - Provides conditional APT and conditional OPT models for
    conditional-density estimation through recursive partitioning of the
    predictor space.
  - Supports univariate and multivariate observations on the unit
    hypercube or a data-adaptive standardized hyperrectangle.

Inference and results

  - Uses exact forward-backward inference on finite recursive partition
    trees.
  - Computes log marginal likelihoods, posterior root shrinkage
    probabilities, posterior predictive densities, and hierarchical MAP
    partitions.
  - Generates posterior partition samples using R's random-number
    generator for reproducible simulation.
  - Reports predictive densities in the physical coordinates of the
    selected sample space.

Package interface

  - Supplies documented R interfaces backed by registered C++ routines
    using Rcpp and RcppArmadillo.
  - Validates observations, prediction matrices, sample spaces, and
    model parameters before native computation.
  - Includes plotting utilities for two-dimensional partitions and ROC
    curves.
  - Includes package-level documentation, method references, citation
    metadata, API and numerical regression tests, and seven reproducible
    visual demos for marginal and conditional models in one and two
    dimensions.