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Exploring Research Frontiers in Contemporary Statistics and Econometrics

by Van Keilegom, Ingrid.
Authors: Wilson, Paul W.%editor. | SpringerLink (Online service) Physical details: XV, 265p. 41 illus. online resource. ISBN: 379082349X Subject(s): Statistics. | Mathematical statistics. | Economics %Statistics. | Statistics. | Statistical Theory and Methods. | Statistics for Business/Economics/Mathematical Finance/Insurance. | Statistics and Computing/Statistics Programs.
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Léopold Simar became Professor of Statistics at the Université catholique de Louvain (UCL) in 1992, after moving from the Faculté des Sciences Economiques Sociales et Politiques (FSESP) at Facultés Universitaires Saint-Louis in Brussels, where he had served as Professor of Statistics since 1974 and as Dean of the FSESP from 1978 to 1990. He founded the Institute of Statistics at the UCL in 1992, and chaired the Institute from its creation until 2004. During this period, the Institute became recognized as a leading center for research in mathematical statistics. Over his long and successful career, Léopold Simar has worked on a variety of topics in statistics, including count-data models, Bayesian estimation and inference, and frontier estimation. He is regarded as one of the world's leading experts on frontier estimation; his work in this area has found application in a broad variety of fields, including efficiency studies in industry, air traffic control, the research output of universities, insurance companies, etc. This book collects contributions written by well-known statisticians and econometricians to acknowledge Léopold Simar’s far-reaching scientific impact on Statistics and Econometrics throughout his career. The papers contained herein were presented at a conference in Louvain-la-Neuve in May 2009 in honor of his retirement.  The contributions cover a broad variety of issues surrounding frontier estimation, which Léopold Simar has contributed much to over the past two decades, as well as related issues such as semiparametric regression and models for censored data.

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