A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the...

This thesis consists of two parts. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis consists of two chapters. One chapter is concerned with the development of efficient estimators of the marginal distribution functions...

We re-examine the methods used in estimating comovements among U.S. regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi-maximum likelihood estimator. Hence, we propose applying the self- weighted quasi-maximum exponential...

In this research, we employ a full-range tail dependence copula to capture the intraday dynamic tail dependence patterns of 30 s log returns among stocks in the US market in the year of 2020, when the market experienced a significant sell-off and a rally thereafter. We also introduce a...

An elliptical copula model is a distribution function whose copula is that of an elliptical distribution. The tail dependence function in such a bivariate model has a parametric representation with two parameters: a tail parameter and a correlation parameter. The correlation parameter can be...