We focus on the problem of simultaneous variable selection and estimation for nonlinear models based on modal regression (MR), when the number of coefficients diverges with sample size. With appropriate selection of the tuning parameters, the resulting estimator is shown to be consistent and to...

Single index models are natural extensions of linear models and overcome the so-called curse of dimensionality. They have applications to many fields, such as medicine, economics and finance. However, most existing methods based on least squares or likelihood are sensitive when there are...

The aim of this paper is to study the distribution of portfolio returns across portfolios and for given asset returns. We focus on the most common type of investment considering portfolios whose weights are non-negative and sum up to 1. We provide algorithms and formulas from computational...

The semiparametric linear model is an important alternative to the Cox proportional hazards model for censored survival outcomes. In this dissertation, we provide some new insights for the parameter estimators and their asymptotic properties in the semiparametric linear model with censored...

This paper explores the stochastic collocation technique, applied on a monotonic spline, as an arbitrage-free and model-free interpolation of implied volatilities. We explore various spline formulations, including B-spline representations. We explain how to calibrate the different...