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Department of Statistics
Matthew Heiner

Software

GitHub page: https://github.com/mheiner/

Slice Sampling

  • R package on CRAN

    • qslice implements various general-purpose slice samplers for use in MCMC, including the quantile slice sampler.

  • Reference

    • Quantile Slice Sampling
      Heiner, M., Johnson, S., Christensen, J., and Dahl, D. (2024+), arXiv preprint

Covariate-Dependent Product Partition Models

  • Julia
    • ProductPartitionModels.jl implements Gaussian PPMx models (for continuous response and covariates) including imputation-free local regression on partially observed covariates. See the article for details. Code for fitting and assessing the models in R is found in VDLocalReg_examples.
  • Reference
    • A Projection Approach to Local Regression with Variable-Dimension Covariates
      Heiner, M., Page, G. and Quintana, F. (2024+), Journal of Computational and Graphical Statistics. (link to paper)

Bayesian Nonparametric Density Autoregression

  • Julia
    • BNP_WMReg_Joint.jl provides implementation of a nonparametric mixture of autoregressive models with lag selection. See the article for details. Code for fitting and assessing the models is found in BNP_WMAR_examples.
  • Reference
    • Bayesian Nonparametric Density Autoregression with Lag Selection Heiner, M. and Kottas, A. (2022), Bayesian Analysis. (link to paper)

Mixture Transition Distribution (MTD)

  • Julia
    • MTD.jl provides a Bayesian implementation of the MTD model, along with our extension for model selection. See the article for details. Code for fitting and assessing the models is found in MTD_examples.
  • Reference
    • Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models
      Heiner, M. and Kottas, A. (2022), Journal of Computational and Graphical Statistics. (link to paper)

Sparse Probability Vectors

  • Julia
    • SparseProbVec provides functions to sample the sparse Dirichlet mixture and stick-breaking mixture distributions for probability vectors. See the article for details.
  • R
    • SparseProbVec is an R package. See the test script and function documentation for usage examples.
  • Reference
    • Structured priors for sparse probability vectors with application to model selection in Markov chains
      Heiner, M., Kottas, A., and Munch, S. (2019), Statistics and Computing. (link to paper)