3 citations · 7 across the 5 of their papers we have counts for
6 papers
Hierarchical Absorbing Markov Chain Models for Pooling Sparse Combat Sequence Data
Brigham Halverson, Matthew Heiner, Leonardo Lamas +1
By viewing tactics in no-gi Brazilian jiu-jitsu (NGJJ) as discrete states, we estimate the transition probabilities of tactical progression, while simultaneously exploring the effe…
Quantile Slice Sampling
Matthew J. Heiner, Samuel B. Johnson, Joshua R. Christensen +1
We propose and demonstrate a novel, effective approach to slice sampling. Using the probability integral transform, we first generalize Neal's shrinkage algorithm, standardizing th…
A Projection Approach to Local Regression with Variable-Dimension Covariates
Matthew J. Heiner, Garritt L. Page, Fernando Andrés Quintana
Incomplete covariate vectors are known to be problematic for estimation and inferences on model parameters, but their impact on prediction performance is less understood. We develo…
Autoregressive Density Modeling with the Gaussian Process Mixture Transition Distribution
Matthew Heiner, Athanasios Kottas
We develop a mixture model for transition density approximation, together with soft model selection, in the presence of noisy and heterogeneous nonlinear dynamics. Our model builds…
Bayesian Nonparametric Density Autoregression with Lag Selection
Matthew Heiner, Athanasios Kottas
We develop a Bayesian nonparametric autoregressive model applied to flexibly estimate general transition densities exhibiting nonlinear lag dependence. Our approach is related to B…
Estimation and selection for high-order Markov chains with Bayesian mixture transition distribution models
Matthew Heiner, Athanasios Kottas
We develop two models for Bayesian estimation and selection in high-order, discrete-state Markov chains. Both are based on the mixture transition distribution, which constructs a t…