Research

Dynamic and mixture modeling of complex, dependent data with Markov chain Monte Carlo.

Interests:

• Bayesian Nonparametrics
• Time Series and Dynamic Models
• Mixture Modeling
• Sparse Signal Recovery
• Markov chain Monte Carlo

With Applications In:

• Ecology
• Hydrology
• Atmospheric Biomonitoring
• Sports

Peer-Reviewed Articles

• A Projection Approach to Local Regression with Variable-Dimension Covariates
  Heiner, M., Page, G., and Quintana, F. (2024+), Journal of Computational and Graphical Statistics.
• Trace element chemistry and strontium isotope ratios of atmospheric particulate matter reveal air quality impacts from mineral dust, urban pollution, and fireworks in the Wasatch Front, Utah, USA.
  Marcy, M. J., Carling, G. T., Thompson, A. N., Bickmore, B. R., Nelson, S. T., Rey, K. A., Fernandez, D. P., Heiner, M., and Adams, B. (2024), Applied Geochemistry
• No-gi Brazilian jiu-jitsu: A Markovian analysis of elite-level combat dynamics
  Lamas, L., Heiner, M., Ferreira, M., Moura, A., Rangel, W., Fellingham, G., and Lage, V. (2023+), International Journal of Sports Science & Coaching
• Multivariate Receptor Modeling with Widely Dispersed Lichens as Bioindicators of Air Quality
  Heiner, M., Grimm, T., Smith, H., Leavitt, S. D., Christensen, W. F., Carling, G. T., St. Clair, L. L. (2023), Environmetrics, 24(3), e2785.
• Model-based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France
  Heiner, M., Heaton, M., Abbott, B., White, P., Minaudo, C., Dupas, R. (2023), Journal of Agricultural, Biological, and Environmental Statistics, 28, 74—98.
• Bayesian Nonparametric Density Autoregression with Lag Selection
  Heiner, M. and Kottas, A. (2022), Bayesian Analysis, 17(4), 1245—1273.
• 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, 31(1), 100—112.
• Autoregressive Density Modeling with the Gaussian Process Mixture Transition Distribution
  Heiner, M. and Kottas, A. (2021), Journal of Time Series Analysis, 43, 157—177.
• 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, 29, 1077—1093.
• Modeling the offensive-defensive interaction and resulting outcomes in basketball
  Lamas, L., Santana, F., Heiner, M., Ugrinowitsch, C., and Fellingham, G. (2015), PloS one, 10, e0144435.
• Skill importance in women’s soccer
  Heiner, M., Fellingham, G., and Thomas, C. (2014), Journal of Quantitative Analysis in Sports, 10, 287—302.
  

Talks & Posters

• Quantile Slice Sampling with Transformations to Approximate Targets
  
  • Poster at ISBA World Meeting, Venice, Italy, July 2024.
  • Poster at Bayesian Nonparametrics Networking Workshop, Melbourne, Australia, December 2023.
  • Poster at Bayes Comp, Levi, Finland, March 2023.
• A Projection Approach to Local Regression with Variable-Dimension Covariates"
  
  • BNP-ISBA Webinar, jointly presented with Fernando Quintana and Garritt Page, February 2023.
• Shrinkage on the Simplex: Bayesian Inference with Sparse and Structured Compositional Data
  
  • 36th New England Statistics Symposium, virtual, June 2023
  • ISBA World Meeting, Montreal, QC, June 2022.
  • Seminar of LIFEPLAN Working Group at University of Helsinki, virtual, January 2022.
• Multivariate Receptor Modeling with Widely Dispersed Lichens as Bioindicators of Air Quality
  
  • Joint Statistical Meetings, Toronto, Ontario, August 2023
• Model-based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France
  
  • Classification Society Annual Meeting, Kelowna, BC, June 2024
  • 16th International Conference of the ERCIM WG on Computational and Methodological Statistics, virtual, December 2023.
  • Joint Statistical Meetings (JSM), virtual, August 2021.
• Estimation and Selection for High-order Markov chains with Mixture Transition Distribution Models
  
  • ISBA World Meeting, virtual, June 2021.
  • BYU/USU Applied Math Seminar, virtual, November 2020.
  • NBER-NSF SBIES Conference, virtual, August 2020.
• Bayesian Nonparametric Density Autoregression with Lag Selection
  
  • 13th International Conference of the ERCIM WG on Computational and Methodological Statistics, virtual, December 2020.
  • Joint Statistical Meetings (JSM), virtual, August 2020.
• Bayesian model selection for Markov chains using sparse probability vectors
  
  • Joint Statistical Meetings (JSM), Vancouver, BC, July 2018. (slides, poster)
  • Chapter Meeting, San Francisco Chapter of the American Statistical Association, San Francisco, CA, June 2018. (slides) (travel award recipient for JSM 2018)
  • Graduate Research Symposium, University of California, Santa Cruz, Santa Cruz, CA, April 2018.
• The Interaction of Arctic sea ice and global temperature, and their bias in climate simulation experiments
  
  • Engineering Summer Intern Seminar, Lawerence Livermore National Laboratory, Livermore, CA, August 2016.
• Characterizing natural climate variability of mean global temperature in CMIP-5 models
  
  • Applied Statistics Group Seminar, Lawerence Livermore National Laboratory, Livermore, CA, September 2015.
• Skill importance in women’s soccer
  
  • Student Research Conference, Brigham Young University, Provo, UT, March 2013. (slides) (best in section award)
• Bayesian analysis of diet intervention in young adults
  
  • Student Research Conference, Brigham Young University, Provo, UT, March 2012.