John Hughes is an Associate Research Professor of Statistics at Penn State.
Hughes received his Ph.D. in statistics from Penn State in 2011. He received his M.S. in computer science from Frostburg State University in 2002, and his B.S. in mathematics and computer science from the same in 1995.
Hughes' methodological research focuses on models for dependent data (especially high-dimensional data such as spatial and spatiotemporal data), statistical computing, and Bayesian methods. His interdisciplinary collaborations have spanned a number of fields, including environmental and occupational health, bioimaging, and the spatial epidemiology of HPV-related cancers.
(Please visit Dr. Hughes' website at www.johnhughes.org for a full list of publications.)
- M. Bezener, J. Hughes, and G. Jones. Bayesian spatiotemporal modeling using hierarchical spatial priors, with applications to functional magnetic resonance imaging (with discussion). Bayesian Analysis, 13(4):1261–1313, 2018.
- E. Kurum, J. Hughes, R. Li, and S. Shiffman. Time-varying copula models for longitudinal data. Statistics and Its Interface, 11(2):203–221, 2018.
- D. Musgrove, J. Hughes, and L. E. Eberly. Fast, fully Bayesian spatiotemporal inference for fMRI data. Biostatistics, 17(2):291–303, 2016.
- J. Hughes. copCAR: A flexible regression model for areal data. Journal of Computational and Graphical Statistics, 24(3):733–755, 2015.
- J. Hughes. ngspatial: An R package for fitting the centered autologistic and sparse spatial generalized linear mixed models for areal data. The R Journal, 6(2):81–95, 2014.
- J. Hughes, S. Shastry, W. O. Hancock, and J. Fricks. Estimating velocity for processive motor proteins with random detachment. Journal of Agricultural, Biological, and Environmental Statistics, 18(2):204–217, 2013.
- J. Hughes and M. Haran. Dimension reduction and alleviation of confounding for spatial generalized linear mixed models. Journal of the Royal Statistical Society, Series B, 75(1):139–159, 2013.
- J. Hughes, M. Haran, and P. C. Caragea. Autologistic models for binary data on a lattice. Environmetrics, 22(7):857–871, 2011.
- J. Hughes and J. Fricks. A mixture model for quantum dot images of kinesin motor assays. Biometrics, 67(2):588–595, 2011.
- J. Hughes, J. Fricks, and W. Hancock. Likelihood inference for particle location in fluorescence microscopy. The Annals of Applied Statistics, 4(2):830–848, 2010.
STAT 544 - Categorical Data Analysis I (Spring, 2021)