Linear regression using Hilbert-space valued covariates with unknown reproducing kernel

Music City Center 

In this talk we present a new method of linear regression using Hilbert-space valued covariates with unknown reproducing kernels. We develop a computationally efficient approach to estimation and derive asymptotic theory for the regression parameter estimates under mild assumptions. We demonstrate the approach in simulation studies as well as in a data analyses using two- and three-dimensional brain images as predictors.