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Magda Peligrad
Charles Phelps Taft Professor
811D Old Chemistry Building
513-556-4066
magda.peligrad@uc.edu
Professional Summary
Magda Peligrad is a professor in the Department of Mathematical Sciences whose area of expertise is Probability Theory and Stochastic Processes. Her research deals with dependent structures and covers various aspects of modeling the dependence, maximal inequalities, and limit theorems. Most of the stochastic processes studied are weakly dependent, i.e. processes for which the dependence is diminishing with time. Example of these processes are: classes of Markov processes, Mixing Processes, Martingale like –sequences, time series, shift processes, associate processes and many others. Some of the limit theorems she discovered have immediate applicability to Statistics of dependent data, Nonparametric statistics and to Ergodic theory, making her field of research multidisciplinary. The results of her research is the subject of over 50 papers and chapters in various books, and a very large number of lectures in United States and abroad. Her research was rewarded by several National Science Foundation and National Security Agency grants. In 2003 she received the title of Taft Professor at the University of Cincinnati.
Education
Ph D., Center of Statistics of the Roumanian Academy of Science., 1981.
Research Interests
Probability Theory and Stochastic Processes, with a stress on dependent structures and their limit theorems that can be an immediately implemented in Statistics.
Research Support
Taft research support , Funded 2007
National Security Agency , Funded 2007 to 2009.
Taft research support , Funded 2005
Taft cost share grant , Funded 2005
National Security Agency , Funded 2004 to 2006.
Taft research support , Funded 2004
Taft Competitive Fellowship , Funded 2003
Taft Travel Grant, Funded 09-2002
Professional Development Grant, OBR. Funded 2002
NSF Travel Grant , Funded 05-2000
Taft Travel Grant, Funded 05-2000
Professional Development Grant, OBR. Funded 05-2000 to 05-2001.
Professional Development Grant, OBR. Funded 2000
Taft research Grant, Funded 07-1999 to 08-1999.
Professional Development Grant, OBR. Funded 1999
Taft travel Grant, Funded 08-1998 to 09-1998.
Taft Research Grant, Funded 07-1997 to 08-1997.
Professional Development Grant, OBR. Funded 05-1997 to 05-1998.
Taft Travel Grant for Sabbatical, Funded 01-1995 to 06-1995.
Taft Grants for Travel, Funded 06-1993
NSF Research Grant, (DMS-9304010); Funded 07-1992 to 01-1996.
Taft Grants for Travel, Funded 06-1991
NSF Research Grant, (DMS-9007986); Funded 11-1990 to 12-1992.
NSF/AWM Travel Grant, (DMS-8914344); Funded 08-1990
Taft Grant for Research, Funded 07-1990 to 08-1990.
NSF Research Grant, (DMS-8702759); Funded 06-1989
NSF Research Grant, (DMS-8905615); Funded 06-1989 to 06-1990.
Taft Grants for Travel, Funded 08-1986
NSF Research Grant, (DMS-8503016); Funded 06-1985 to 06-1987.
Peer Reviewed Publications
Utev, Sergey, & Biao, Wei (2007). A maximal L(p)- Inequality for stationary sequences and application. Proc. AMS, 135(2), 541-550.
Utev, Sergey (2006). Invariance principle for stochastic processes with short memory. IMS Lectures Notes and Monograph Series, 51, 18-32.
Merlevede, Florence (2006). On the weak invariance principle for stationary sequences under projective criteria. Journal of Theoretical Probabilities, 19(3), 647-689.
Merlevede, Florence, & Utev, Sergey (2006). Recent advances in invariance principles for stationary sequences. Probability Surveys, 3, 1-36.
Utev, Sergey (2006). Another approach to Brownian motion. Stochastic Processes and their Applications, 116, 279-292.
Utev, Sergey (2006). Central limit theorem for stationary linear processes. The Annals of Probability, 34(4).
Utev, Sergey (2005). A new maximal inequality and invariance principle for stationary sequences. Annals of Probability, 33(2), 798-815.
Utev, Sergey (2003). Maximal inequalities and an invariance principle for a class of weakly dependent random variables. Journal of Theoretical Probabilities, 16(1), 101-115.
(2002). Some remarks on Coupling of dependent random variables. Statist.Probab.Letters, 60(2), 201-209.
Dembo, A. (2001). Moderate deviations for the blockwise bootstrap.
(2001). A note on the Uniform laws for dependent processes via coupling. Journal of Theoretical Probabilities, 14(4), 979-988.
Merlevede, Florence (2000). The functional Central limit theorem for strong mixing sequences of random variables. Annals of Probability, 28(3), 1336-1352.
Book Chapters
Merlevede, Florence (2002). Empirical ProcessTechniques for Dependent Data. On the coupling of dependent random variables and applications (pp. 171-193). Birkhaeuser.
Invited Presentations
(11-2005). Maximal inequalities and invariance principle for martingale-like sequences. Georgia Tech
(05-2005). Some sharp inequalities and asymptotic results under martingale-like conditions. University of Michigan
(03-2005). New advances on maximal inequalities for stationary processes and invariance principles. University of Rome
(10-2004). Invariance Principles and Maximal Inequalities for Dependent Structures. University of Delaware
(05-2003). A new class of dependent random variables. University of Paris , Paris, France.
(10-2002). Inequalities for dependent random variables. University of Paris , Paris, France.
(12-2001). Limit theorems for weakly dependent random variables. University of Paris, Paris, France.
(12-2001). Maximal inequalities for a class of weakly dependent random variables. University of Paris, Nanterre, France.
(11-2001). Basic techniques for weakly dependent sequences. University of Paris , Nanterre, France.
(11-2001). Rosenthal Inequalities for interlaced mixing sequences. Institute Henry Poincare
(05-2001). Coupling methods for Dependent data. Laboratoire de Statistique, Universite de Paris, Paris, France.
(05-2001). Uniform strong laws for nonergodic sequences based on coupling methods. University of Delft, Holland .
(05-2001). Limit theorems for dependent data via coupling methods. Center Borel, Institute Henry Poincare, Paris, France.
(10-2000). Basic tools for weak-dependent sequences and their application to limit theorems. 22nd Midwest probability Colloquium, Northwestern University, Evanston, IL.
(05-2000). Almost sure results for dependent data via coupling. Indiana University , Bloomington, IN.
