Iain Johnstone is a Professor of Statistics and Health Research and Policy at Stanford University. A 2013 recipient of Cornell's Distinguished Alumni award, he is a statistician with research interests in statistical decision theory and wavelet-like methods (and their uses) in estimation theory, asymptotics and application areas such as statistical inverse problems and statistical signal processing. Other interests include simulation methodology, volume tests of significance, hazard rate estimation and maximum entropy methods. For more information and a publications list, visit his personal webpage.
Title: Eigenvalues and Variance Components
Abstract: Motivated by questions in quantitative genetics, we consider high dimensional versions of some common variance component models. We focus on quadratic estimators of 'genetic covariance' and study the behavior of both the bulk of the estimated eigenvaluesand the largest estimated eigenvalue in some plausible asymptotic models. This is joint work with Mark Blows and Zhou Fan.