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High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood Variable selec- tion
2016/1/26
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...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood
2016/1/20
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...
Power of Change-Point Tests for Long-Range Dependent Data
Change-point problems nonparametric change-point tests Wilcoxon two-sample rank test power of test local alternatives asymptotic relativeefficiency of tests long-range dependent data,long memory functional limit theorem
2013/4/28
We investigate the power of the CUSUM test and the Wilcoxon change-point test for a shift in the mean of a process with long-range dependent noise. We derive analytiv formulas for the power of these t...
Rate of convergence of predictive distributions for dependent data
Bayesian predictive inference central limit theorem conditional identity indistribution empirical distribution exchangeability
2010/3/9
This paper deals with empirical processes of the type
Cn(B) =pn{μn(B)− P(Xn+1 2 B |X1, . . . ,Xn)},
where (Xn) is a sequence of random variables and μn = (1/n)Pn
i=1 Xi the empirical measure...
Dynamics of Bayesian Updating with Dependent Data and Misspecified Models
Dynamics Bayesian Updating Dependent Data Misspecified Models
2010/3/17
Much is now known about the consistency of Bayesian updat-
ing on infinite-dimensional parameter spaces with independent or Marko-
vian data. Necessary conditions for consistency include the prior p...
A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data
Kernel estimator quantile function rate of convergence strong mixing strong uniform consistency truncated data
2009/9/16
In this paper we study some asymptotic properties of the kernel conditional quantile estimator with randomly left-truncated data which exhibit some kind of dependence. We extend the result obtained by...
Nonparametric estimation for dependent data with an application to panel time series
Density estimation nonparametric regression 2-mixing,nonlinear processes panel time series
2010/4/29
In this paper we consider nonparametric estimation for dependent data, where the
observations do not necessarily come from a linear process. We study density estimation
and also discuss associated p...