|Date:||10:00 29 October 2015 - 17:00 30 October 2015|
|Tutor:||Jon Wellner University of Washington|
|Venue:||Institute for Fiscal Studies|
|Prices:||HE delegates: £75; Charity/Government: £200; other delegates: £450; All prices are exclusive of VAT|
This course will cover some of the basics of empirical process theory and the application of the theory to problems in statistics. The focus will be on some of the basic convergence theory and methods together with inequalities for dealing with minimum contrast and maximum likelihood estimators in nonparametric and semiparametric models.
1. Van der Vaart, A. W. and Wellner, J. A. (1996). Weak Convergence and Empirical Processes. Springer, New York.
2. Dudley, R. M. (1999). Uniform Central Limit Theorems. Cambridge University Press, Cambridge.
3. Van de Geer, S. (2000). Applications of Empirical Process Theory. Cambridge University Press, Cambridge.
4. de la Pena, V. H., and Gin e, E. (1999). Decoupling: From Dependence to Independence. Springer, New York.
5. Wellner, J. A. (2003 - 2005). Empirical Processes: Theory and Applications.
Notes available on-line at: http://www.stat.washington.edu/jaw/RESEARCH/TALKS/talks.html
This is event is jointly organised by the Cambridge-INET Institute.