Michael David Escobar is an American biostatistician who is known for Bayesian nonparametrics, mixture models.
Education and career
Escobar earned a degree in mathematics at Tufts University in 1981 followed by a doctorate in statistics at Yale University in 1988 under the supervision of John Hartigan. Between 1990 and 1994, he was an assistant professor at Carnegie Mellon University. Escobar subsequently joined the University of Toronto faculty. In 2015, he was elected a fellow of the American Statistical Association.
Bibliography
- Escobar, Michael D. (1994). "Estimating Normal Means with a Dirichlet Process Prior". Journal of the American Statistical Association. 89 (425): 268–277. doi:10.1080/01621459.1994.10476468. ISSN 0162-1459.
- Escobar, Michael D.; West, Mike (1995). "Bayesian Density Estimation and Inference Using Mixtures". Journal of the American Statistical Association. 90 (430): 577–588. doi:10.1080/01621459.1995.10476550. ISSN 0162-1459.
- Escobar, Michael D.; West, Mike (1998), Dey, Dipak; Müller, Peter; Sinha, Debajyoti (eds.), "Computing Nonparametric Hierarchical Models", Practical Nonparametric and Semiparametric Bayesian Statistics, vol. 133, New York, NY: Springer New York, pp. 1–22, doi:10.1007/978-1-4612-1732-9_1, ISBN 978-0-387-98517-6, retrieved 2023-04-11
- Austin, Peter C; Escobar, Michael; Kopec, Jacek A (2000). "The use of the Tobit model for analyzing measures of health status". Quality of Life Research. 9 (8): 901–910. doi:10.1023/A:1008938326604. PMID 11284209.
References
- ^ "Curriculum Vitae Michael D. Escobar" (PDF). University of Toronto. Retrieved 16 October 2022.
- "Faculty Member Michael Escobar Ph.D." University of Toronto. Retrieved 16 October 2022.
- "ASA Fellows". American Statistical Association. Retrieved 16 October 2022.