Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...

Two forms of CoVaR have recently been introduced in the literature for measuring systemic risk, differing on whether or not the conditioning is on a set of measure zero. We focus on the former, and ...

We study a nonparametric deconvolution density estimation problem. The estimator is obtained by an EM algorithm for a smoothed maximum likelihood estimation problem, which has a unique continuous ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 34, No. 4 (Dec., 2006), pp. 535-561 (27 pages) The authors propose a new monotone nonparametric estimate for a regression ...