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PTT 1.0.1
Correctness
- Fixes undefined behavior in conditional hierarchical MAP partition
output caused by using an unsigned counter with
-1 as its
initial sentinel.
- Uses 64-bit node offsets to avoid truncation when indexing larger
trees.
- Rejects predictor/response dimension and shrinkage-state
configurations that exceed the capacity of the internal partition
representation.
Validation
- Adds regression checks for conditional partition boundaries and
supported input capacities.
- Audits the remaining bit shifts and verifies the package examples,
tests, and demos with undefined-behavior and address sanitizers.
PTT 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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