In this paper, the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables are investigated. Some sufficient conditions for the convergence are provided. In addition, the Marcinkiewicz-Zygmund type strong law of large...

We consider a generalization of Baum-Katz theorem for random variables satisfying some cover conditions. Consequently, we get the result for many dependent structure, such as END, -mixing, -mixing and -mixing, etc.

In this paper, the complete convergence for maximal weighted sums of extended negatively dependent (END, for short) random variables is investigated. Some sucient conditions for the complete convergence and some applications to a nonparametric model are provided. The results obtained in the...

In this article, we propose a new class of semiparametric instrumental variable models with partially varying coefficients, in which the structural function has a partially linear form and the impact of endogenous structural variables can vary over different levels of some exogenous variables....

In this paper, we propose a new class of regime shift models with flexible switching mechanism that relies on a nonparametric probability function of the observed threshold variables. The proposed models generally embrace traditional threshold models with contaminated threshold variables or...

This paper is concerned with selecting important covariates and estimating the index direction simultaneously for high dimensional single-index models. We develop an efficient Threshold Gradient Directed Regularization method via maximizing Distance Covariance (DC-TGDR) between the single index...

In this article, we study a nonparametric approach regarding a general nonlinear reduced form equation to achieve a better approximation of the optimal instrument. Accordingly, we propose the nonparametric additive instrumental variable estimator (NAIVE) with the adaptive group Lasso.We...

Open-ended responses are widely used in market research studies. Processing of such responses requires labor-intensive human coding. This paper focuses on unsupervised topic models and tests their ability to automate the analysis of open-ended responses. Since state-of-the-art topic models...

Modeling the joint tails of multiple nancial time series has important implications for risk management. Classical models for dependence often encounter a lack of t in the joint tails, calling for additional exibility. In this paper we introduce a new nonparametric time-varying mixture copula...