My GitHub: teazrq

Reinforcement Learning Trees (RLT)

Orthogonality Constrained Optimization and Dimension Reduction (orthoDr)

  • CRAN: link
  • GitHub: link
  • Examples: link
  • This package offers an optimization solver for orthogonality constrained problems: \(\min f(X)\) s.t. \(X^T X = I\) by utilizing the algorithm developed by Wen and Yin (2013). We utilize this to solve a variety of semiparametric dimension reduction and personalized medicine problems.

Dimension Reduction Forests (drforest)

  • GitHub: link
  • This package provides the statistical estimation methods for dimension reduction forests and local subspace variable importance.
  • Local subspace variable importance can be used for detecting influential variables in a personalized prediction/recommendation.

Random Forests for Heterogeneous Treatment Effect Estimation with Multiple Responses (MOTE.RF)

  • GitHub: link
  • Designed for a setting in which the covariates \(X\) and multivariate response \(Y\) are both measured before and after the intervention.
  • Applied to a microbiome study to estimate the dietary effect on multiple health outcomes.

A Nonnegative Matrix Factorization Tool Box (MatrixFact)

  • GitHub: link
  • This package implements a variety of matrix factorization tools, such as NMF, ONMF, semi-NMF, semi-orthogonal NMF, and some of their extensions to binary data.
  • Our method semi-orthogonal NMF can be applied to a document-word matrix to extract meaningful information for analyzing text data.

Recursively Imputed Survival Trees (RIST)

© Ruoqing Zhu, 2025. All rights reserved.