Murali Haran
Associate Professor of Statistics
Research Summary
Statistical computing (Markov chain Monte Carlo algorithms); spatial models (Gaussian random field models); methods for complex computer models; interdisciplinary collaborations in environmental sciences, climate science, disease modeling, ecology
Huck Affiliations
Links
Publication Tags
Climate Calibration Model Uncertainty Climate Models Model Calibration Ice Modeling Emulation Projection Statistics Bayesian Inference Computer Model Sea Ice Time Series Output Spatial Data Method Infectious Diseases Dimension Reduction Methodology Gaussian Process Climate Modeling Earth (Planet) Random GraphsMost Recent Publications
A two-stage Cox process model with spatial and nonspatial covariates
Claire Kelling, Murali Haran, 2022, Spatial Statistics
ICE MODEL CALIBRATION USING SEMICONTINUOUS SPATIAL DATA
Won Chang, Bledar A. Konomi, Georgios Karagiannis, Yawen Guan, Murali Haran, 2022, Annals of Applied Statistics on p. 1937-1961
PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models
Ben Seiyon Lee, Murali Haran, 2022, Technometrics on p. 187-198
Modeling the Social and Spatial Proximity of Crime: Domestic and Sexual Violence Across Neighborhoods
Claire Kelling, Corina Graif, Gizem Korkmaz, Murali Haran, 2021, Journal of Quantitative Criminology on p. 481-516
A Function Emulation Approach for Doubly Intractable Distributions
Jaewoo Park, Murali Haran, 2020, Journal of Computational and Graphical Statistics on p. 66-77
A fast particle-based approach for calibrating a 3-d model of the antarctic ice sheet
Ben Seiyon Lee, Murali Haran, Robert W. Fuller, David Pollard, Klaus Keller, 2020, Annals of Applied Statistics on p. 605-634
Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models
Jaewoo Park, Murali Haran, 2020, Journal of Computational and Graphical Statistics on p. 269-283
Computer Model Calibration Based on Image Warping Metrics: An Application for Sea Ice Deformation
Yawen Guan, Christian Sampson, J. Derek Tucker, Won Chang, Anirban Mondal, Murali Haran, Deborah Sulsky, 2019, Journal of Agricultural, Biological, and Environmental Statistics on p. 444-463
Quantifying spatio-temporal variation of invasion spread
Joshua Goldstein, Jaewoo Park, Murali Haran, Andrew Liebhold, Ottar N. Bjørnstad, 2019, Proceedings of the Royal Society B: Biological Sciences
Stilt: Easy emulation of time series AR(1) computer model output in multidimensional parameter space
Roman Olson, Kelsey L. Ruckert, Won Chang, Klaus Keller, Murali Haran, Soon Il An, 2019, R Journal on p. 209-225
Most-Cited Papers
Dimension reduction and alleviation of confounding for spatial generalized linear mixed models
John Hughes, Murali Haran, 2013, Journal of the Royal Statistical Society. Series B: Statistical Methodology on p. 139-159
Piecing together the past: Statistical insights into paleoclimatic reconstructions
Martin P. Tingley, Peter F. Craigmile, Murali Haran, Bo Li, Elizabeth Mannshardt, Bala Rajaratnam, 2012, Quaternary Science Reviews on p. 1-22
Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: Comparison of simple and advanced statistical techniques
David Pollard, Won Chang, Murali Haran, Patrick Applegate, Robert DeConto, 2016, Geoscientific Model Development on p. 1697-1723
A climate sensitivity estimate using Bayesian fusion of instrumental observations and an Earth System model
Roman Olson, Ryan Sriver, Marlos Goes, Nathan M. Urban, H. Damon Matthews, Murali Haran, Klaus Keller, 2012, Journal of Geophysical Research: Atmospheres
Uncertainty analysis in climate change assessments
Richard W. Katz, Peter F. Craigmile, Peter Guttorp, Murali Haran, Bruno Sansó, Michael L. Stein, 2013, Nature Climate Change on p. 769-771
Emulating a gravity model to infer the spatiotemporal dynamics of an infectious disease
Roman Jandarov, Murali Haran, Ottar Bjørnstad, Bryan Grenfell, 2014, Journal of the Royal Statistical Society. Series C: Applied Statistics on p. 423-444
Fast dimension-reduced climate model calibration and the effect of data aggregation
Won Chang, Murali Haran, Roman Olson, Klaus Keller, 2014, Annals of Applied Statistics on p. 649-673
Bayesian Inference in the Presence of Intractable Normalizing Functions
Jaewoo Park, Murali Haran, 2018, Journal of the American Statistical Association on p. 1372-1390
Inferring likelihoods and climate system characteristics from climate models and multiple tracers
K. Sham Bhat, Murali Haran, Roman Olson, Klaus Keller, 2012, Environmetrics on p. 345-362
Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
Won Chang, Murali Haran, Patrick Applegate, David Pollard, 2016, Journal of the American Statistical Association on p. 57-72