High-Dimensional Inference

Converting High-Dimensional Regression to High-Dimensional Conditional Density Estimation

There is a growing demand for nonparametric conditional density estimators (CDEs) in fields such as astronomy and economics. In astronomy, for example, one can dramatically improve estimates of the parameters that dictate the evolution of the …

Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting.

In some applications (e.g., in cosmology and economics), the regression E[Z|x] is not adequate to represent the association between a predictor x and a response Z because of multi-modality and asymmetry of f(z|x); using the full density instead of a …

A Spectral Series Approach to High-Dimensional Nonparametric Regression.

A key question in modern statistics is how to make fast and reliable inferences for complex, high-dimensional data. While there has been much interest in sparse techniques, current methods do not generalize well to data with nonlinear structure. In …