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Copula function’s concentration set and its concentrated partition
Copula function local correlation structure concentration set concentration measure
2016/1/25
The research on the local correlation structure of copula function is an attractive topic.This paper investigates bivariate copula function’s local correlation structure by defining its concentration ...
We consider an optimizing process (or parametric optimization problem), i.e., an optimization problem that depends on some parameters. We present a method for imputing or estimating the objective func...
On a notion of maps between orbifolds I. Function spaces
Mapping spatial topology maps banach
2014/12/25
This is the first of a series of papers which is devoted to a comprehensive theory of maps between orbifolds. In this paper, we define the maps in the more general context of orbispaces, and establish...
Fourier methods for smooth distribution function estimation
Fourier analysis kernel distribution estimation mean integrated squared error optimal bandwidth sinc kernel
2013/6/14
In this paper we show how to use Fourier transform methods to analyze the asymptotic behavior of kernel distribution function estimators. Exact expressions for the mean integrated squared error in ter...
Fourier analysis of stationary time series in function space
Cumulants discrete Fourier transform functional data analy-sis functional time series periodogram operator spectral density operator weak depen-dence
2013/6/14
We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in su...
Weighted estimation of the dependence function for an extreme-value distribution
bivariate extreme dependence function jackknife empirical likelihood method
2013/4/28
Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands ...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data
Bivariate current status data constrained maximum likelihood estimation empirical process sieve maximum likelihood estimation tensor spline basis functions
2012/11/23
The analysis of the joint cumulative distribution function (CDF) with bivariate event time data is a challenging problem both theoretically and numerically. This paper develops a tensor spline-based s...
Competing Process Hazard Function Models for Player Ratings in Ice Hockey
Process Hazard Function Models Player Ratings Ice Hockey
2012/9/17
Evaluating the overall ability of players in the National Hockey League (NHL) is a dicult task. Existing methods such as the famous \plus/minus" statistic have many shortcomings. Standard linear regr...
Clustering function: a measure of social influence
clustering coecient power law social network intersection graph
2012/9/19
A commonly used characteristic of statistical dependence of adjacency relations in real networks, the clustering coecient, evaluates chances that two neighbours of a given vertex are adjacent. Anothe...
Asymptotic Efficiency of Goodness-of-fit Tests for the Power Function Distribution Based on Puri--Rubin Characterization
Power function distribution,U-statistics characterizations Bahadur efficiency
2012/9/18
We construct integral and supremum type goodness-of-fit tests for the family of power distribution functions. Test statistics are functionals of U−empirical processes and are based on the classi...
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function
Block coordinate descent iteration complexity composite minimization
2011/7/19
In this paper we develop a randomized block-coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth block-separable convex function and prove that it obtains an $\epsilon$-...
Test function: A new approach for covering the central subspace
Sufficient dimension reduction Central subspace Inverse regression
2011/7/5
In this paper we offer a complete methodology for sufficient dimension reduction called the test function (TF). TF provides a new family of methods for the estimation of the central subspace (CS) base...
Classification Loss Function for Parameter Ensembles in Bayesian Hierarchical Models
Classification Loss Function Parameter Ensembles Bayesian Hierarchical Models
2011/6/20
Our perspective in this paper follows the framework adopted by Lin et al. (2006), who intro-
duced several loss functions for the identi cation of the elements of a parameter ensemble that
represent...