Previous Projects

National Institute of Statistical Science

Continental Limnology - Developing joint distribution models for studying the spatial patterns of continental-scale pools of lake nutrients, their environmental drivers, and identifying the role that ecological novelty affects continental-scale prediction.

Select Publications

Williams, B., E.M. Schliep, B.K. Fosdick. R. Elmore (2025). Expected Points Above Average: A Novel Player Metric Based on Bayesian Hierarchical Modeling using NBA Data. Annals of Applied Statistics, 19(4), 3492-3507.

Gelfand, A.E. and E.M. Schliep (2025). Model-based spatial data fusion. Annual Review of Statistics and Its Application, 13.

Collins, K.M.∗, E.M. Schliep, C.K. Wikle, T. Wagner (2025). Model-based decomposition of spatially varying temporal shifts in seasonal streamflow across north temperate US Rivers. Water Resources Research, 61(9).

Kang, B.∗, E.M. Schliep, A.E. Gelfand, C.W. Clark, C.A. Hudak, C.A. Mayo, R. Schosberg, T.M. Yack, R.S. Schick. (2025). Joint Spatiotemporal Modeling of Zooplankton and Whale Abundance in a Dynamic Marine Environment. Journal of the Royal Statistical Society, Series C (Applied Statistics), 75(1), 120-138.

Kang, B.∗, E.M. Schliep, A.E. Gelfand, T.M. Yack, C.W. Clark, R.S. Schick. (2025). Analyzing whale calling through Hawkes process modeling. Journal of the American Statistical Association, 120(552), 2040-2052.

Soranno, P.A., P.J. Hanly, K.E. Webster, T. Wagner, A. McDonald, A. Shuvo, E.M. Schliep, K.L. Reinl, I.M. McCullough, P.N. Tan, N.R. Lottig, K.S. Cheruvelil. (2025) Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low disturbance watersheds. Proceedings of the National Academy of Sciences of the United States of America, 122(9), e2416172122..

Schliep, E.M., A.E. Gelfand, C.W. Clark, C.M. Mayo, B. McKenna, S.E. Parks, T.M. Yack, R.S. Schick. (2024) Assessing marine mammal abundance: a novel data fusion. Annals of Applied Statistics.

Custer, C.A., J.S. North, E.M. Schliep, H.K. Masui, M.R. Verhoeven, G.J.A. Hansen, T. Wagner. (2024) Predicting fish responses to climate change using a joint species, spatially dependent physiologically guided abundance model. Ecology.

North, J.S., E.M. Schliep, G.J.A. Hansen, H. Kundel, C.A. Custer, P. McLaughlin, T. Wagner (2023). Accounting for spatio-temporal sampling variation in joint species distribution models. Journal of Applied Ecology.

North, J.S., C.K. Wikle, E.M. Schliep (2023). A Bayesian Approach for Spatio-Temporal Data-Driven Dynamic Equation Discovery. Bayesian Analysis.

North, J. S., C.K Wikle, & E. M. Schliep (2023). A Review of Data‐Driven Discovery for Dynamic Systems. International Statistical Review.

Schliep, E. M., C.K. Wikle, & R. Daw (2023). Correcting for informative sampling in spatial covariance estimation and kriging predictions. Journal of Geographical Systems, 1-27.

North, J.S., C.K. Wikle, E.M. Schliep (2022). A Bayesian Approach for Data-Driven Dynamic Equation Discovery. Journal of Agricultural, Biological, and Environmental Statistics. doi:10.1007/s13253-022-00514-1

Schliep, E.M., A.E. Gelfand, J. Abaurrea, J. As ́ın, M. A. Beamonte, A.C. Cebri ́an. (2021) Long-term spatial modeling for characteristics of extreme heat events. Journal of the Royal Statistical Society, Series A (Statistics in Society), 184(3), 1070-1092.

Schliep, E.M., T.L.J. Schafer, M. Hawkey. (2021) Distributed lag models to identify the cumulative effects of training and recovery in athletes using multivariate ordinal wellness data. Journal of Quantitative Analysis of Sports, 17(3), 241-254.

North, J.S., E.M. Schliep, C.K. Wikle. (2021) On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi-annual harmonics. Environmetrics, 32(6), e2665.

Schliep, E.M., S.M. Collins, S. Rojas Salazar∗, N.R. Lottig, E.M. Stanley (2020). Data fusion model to identify environmental drivers and improve estimation of total nitrogen in lakes. The Annals of Applied Statistics, 14(4), 1651-1675.

Gelfand, A.E., E.M. Schliep (2018). Bayesian Inference and Computing for Spatial Point Patterns. NSF-CBMS Regional Conference Series in Probability and Statistics, 10, i-125. Institute of Mathematical Statistics and the American Statistical Association.