Editors
Richard A. Davis is chair and Howard Levene Professor of Statistics at Columbia Uni-
versity, New York. He is currently president (2015–16) of the Institute of Mathematical
Statistics. He received his PhD in mathematics from the University of California at San
Diego in 1979 and has held academic positions at MIT, Colorado State University, and vis-
iting appointments at numerous other universities. He is coauthor (with Peter Brockwell)
of the bestselling books, Time Series: Theory and Methods and Introduction to Time Series and
Forecasting. Together with Torben Andersen, Jens-Peter Kreiss, and Thomas Mikosch, he
coedited the Handbook in Financial Time Series. In 1998, he won (with collaborator W.T.M.
Dunsmuir) the Koopmans Prize for Econometric Theory. He has served on the editorial
boards of major journals in probability and statistics and most recently was editor in chief
of the Bernoulli Journal (2010–2012). His research interests include time series, applied
probability, extreme value theory, and spatial-temporal modeling.
Scott H. Holan is a professor in the Department of Statistics at the University
of Missouri, Columbia, Missouri. He received his PhD in statistics from Texas A&M Uni-
versity in 2004. His research is primarily focused on time-series analysis, spatio-temporal
methodology, Bayesian methods, and hierarchical models and is largely motivated by
problems in federal statistics, econometrics, ecology, and environmental science. He is a
fellow of the American Statistical Association and an elected member of the International
Statistics Institute.
Robert Lund received his PhD in statistics from the University of North Carolina
in 1993. He is currently professor in the Department of Mathematical Sciences at Clemson
University, after an 11-year stint in the Statistics Department at the University of Georgia.
He is a 2007 Fellow of the American Statistical Association and was the 2005–2007 chief edi-
tor of the Journal of the American Statistical Association, Reviews section. He has published
over 80 refereed papers and has graduated 17 doctoral students. His interests are in time
series, applied probability, and statistical climatology.
Nalini Ravishanker is a professor in the Department of Statistics at the University of
Connecticut, Storrs. Her primary research interests include time series and times-to-events
analysis, Bayesian dynamic modeling, and signal processing. Her primary interdisci-
plinary research areas are ecology, nance, marketing, and transportation engineering. She
has an undergraduate degree in statistics from Presidency College, Chennai, India, and
a PhD in statistics and operations research from the Stern School of Business, New York
University. She is coauthor of the textbook A First Course in Linear Model Theory.She is
a fellow of the American Statistical Association and elected member of the International
Statistical Institute, the theory and methods editor of Applied Stochastic Models in Business
and Industry, and an associate editor for the Journal of Forecasting.
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