Springer Contemporary Developments in Statistical Theory: A Festschrift for Hira Lal Koul: 68 (Springer Proceedings in Mathematics & Statistics, 68)

Product Description This volume highlights Prof. Hira Koul’s achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others. Chapters are all original papers that explore the frontiers of these areas and will assist researchers and graduate students working in Statistics, Econometrics and related areas. Prof. Hira Koul was the first Ph.D. student of Prof. Peter Bickel. His distinguished career in Statistics includes the receipt of many prestigious awards, including the Senior Humbolt award (1995), and dedicated service to the profession through editorial work for journals and through leadership roles in professional societies, notably as the past president of the International Indian Statistical Association. Prof. Hira Koul has graduated close to 30 Ph.D. students, and made several seminal contributions in about 125 innovative research papers. The long list of his distinguished collaborators is represented by the contributors to this volume. From the Back Cover This volume highlights Prof. Hira Koul’s achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others. Chapters are all original papers that explore the frontiers of these areas and will assist researchers and graduate students working in Statistics, Econometrics and related areas. Prof. Hira Koul was the first Ph.D. student of Prof. Peter Bickel. His distinguished career in Statistics includes the receipt of many prestigious awards, including the Senior Humbolt award (1995), and dedicated service to the profession through editorial work for journals and through leadership roles in professional societies, notably as the past president of the International Indian Statistical Association. Prof. Hira Koul has graduated close to 30 Ph.D. students, and made several seminal contributions in about 125 innovative research papers. The long list of his distinguished collaborators is represented by the contributors to this volume. About the Author Soumendra Lahiri is a Professor of Statistics at the North Carolina State University. His research interests include Nonparametric Statistics, Time Series, Spatial Statistics, and Statistical inference for high dimensional data. He served as an Editor of Sankhya, Series A (2007-2009) and currently, he is on the editorial boards of the Annals of Statistics and the Journal of Statistical Planning and Inference. He is a fellow of the ASA and the IMS, and an elected member of the International Statistical Institute. Anton Schick is Professor and Chair of the Department of Mathematical Sciences at Binghamton University. His research interests include semiparametric efficiency, U-statistics, empirical likelihood, residual-based inference, incomplete data, curve estimation, and inference for stochastic processes. He currently serves on the editorial boards of Statistics and Probability Letters, Statistical Inference for Stochastic Processes, and the Journal of the Indian Statistical Association. Ashis SenGupta is Professor (HAG), at Indian Statistical Institute, Kolkata. His research interests are in Multivariate Analysis and Inference, Probability distributions on manifolds, Directional Statistics, Reliability and Environmental Statistics. He has been a frequent vistor to several universities in USA as a visiting faculty including Stanford University; University of Wisconsin - Madison; University of California - Santa Barabara and Riverside; and Michigan State University-East Lansing. He is an Editor-in-Chief of Environmental & Ecological Statistics, Springer, USA, and an Editor of Scientiae Mathematicae Japonicae, Japan. He has been President of International Indian Statistical