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This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi and Rivest (1995). Although interval esti...
For copulas whose partial derivatives are not continuous everywhere on the interior of the unit cube, the empirical copula process does not converge weakly with respect to the supremum distance. This ...
The paper is devoted to statistical analysis of zero intelligence models of continuous double auction, in particular to an estimation of parameters of limit order books. We review "classical" zero int...
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities, and size of international wars, are believed to follow power-law distributions. The accurate identifi...
We present some new density estimation algorithms obtainedby bootstrap ag-gregation like Bagging. Our algorithms are analyzed and empirically compared to other methods found in the statistical literat...
In many applications that require matrix solutions of minimal rank, the underlying cost function is non-convex leading to an intractable, NP-hard optimization problem.Consequently, the convex nuclear ...
We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-n...
We establish the validity of the empirical Edgeworth expansion (EE) for a studentized trimmed mean, under the sole condition that the underlying distribution function of the observations satisfies a l...
Considerable literature has been devoted to developing statistical inferential results for risk measures, especially for those that are of the form of L-functionals. However, practical and theoretic...

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