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On the eigenfunctions of the complex Ornstein-Uhlenbeck operators
eigenfunctions complex Ornstein-Uhlenbeck operators
2016/1/25
Starting from the 1-dimensional complex-valued Ornstein-Uhlenbeck process, we present two natural ways to imply the associated eigenfunctions of the 2-dimensional normal Ornstein-Uhlenbeck operators i...
Complementary Design Theory for Uniform Designs
Complementary design discrepancy uniformity
2016/1/25
Uniform design is to seek its design points to be uniformly scattered on the experimental domain under some discrepancy measure. In this paper all the design points of a full factorial design can be s...
A Strong Law of Large Numbers for Super-stable Processes
Super-stable process Super-Brownian motion Strong law of large Preprint submitted to Annals of Probability
2016/1/25
A Strong Law of Large Numbers for Super-stable Processes.
Integrative approaches for microRNA target prediction: combining sequence information and the paired mRNA and miRNA expression profiles
miRNA target prediction expression profile integrative analysis
2016/1/25
Gene regulation is a key factor in gaining a full understanding of molecular biology. microRNA (miRNA), a novel class of non-coding RNA, has recently been found to be one crucial class of post-transac...
Optimal designs for multiple treatments with unequal variances
Optimal treatment allocation D-optimality D A -optimality
2016/1/20
The response of a patient in a clinical trial usually depends on both the se-lected treatment and some latent covariates, while its variance varies across the treatment groups. A general heteroscedast...
Construction of uniform U designs
discrepancy generalized wordtype pattern U design stochastic algorithm
2016/1/20
Orthogonal array based-Latin hypercubes, also called U designs, have popularly been adopted for designing a computer experiment. The relationship between the averaged squared discrepancy of all U desi...
Direct Regression Modelling of High-order Moments in Big Data
Big data Higher-order moment U-statistics Estimating equation Divide-and-conquer
2016/1/20
Big data problems present great challenges to statisti-cal analyses, especially from the computational side. In this paper, we consider regression estimation of high-order mo-ments in big data problem...
Law of large numbers for branching symmetric Hunt processes with measure-valued branching rates
Law of large numbers branching Hunt processes spine approach h-transform spectral gap
2016/1/20
We establish weak and strong law of large numbers for a class of branching symmetric Hunt processes with the branching rate being a smooth measure with respect to the underlying Hunt process, and the ...
Strong law of large numbers for supercritical superprocesses under second moment condition
superprocess scaling limit theorem Hunt process spec- tral gap h-transform martingale measure
2016/1/20
Strong law of large numbers for supercritical superprocesses under second moment condition.
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators
Harmonic function boundary Harnack principle gradient estimate
2016/1/20
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators.
Overshoot in biological systems modeled by Markov chains:a nonequilibrium dynamic phenomenon
Overshoot adaptation Markov chains net flux oscillation nonequilibrium
2016/1/20
A number of biological systems can be modeled by Markov chains. Recently, there has been an increasing concern about when biological systems modeled by Markov chains will perform a dynamic phenomenon ...
Regularization methods for high-dimensional instrumental variables regression with an application to genetical genomics
Causal inference Confounding Endogeneity Sparse regression
2016/1/20
In genetical genomics studies, it is important to jointly analyze gene expression data and genetic variants in exploring their associations with complex traits, where the dimensionality of gene expres...
Discovering and Orienting the Edges Connected to a Target Variable in a DAG via a Sequential Local Learning Approach
Causal network Directed acyclic graph Discover causes and effects
2016/1/20
Given a target variable and observational data, we propose a sequential learning approach for discovering direct cause and effect variables of the target under the causal network frame-work. In the ap...
Copula function’s concentration set and its concentrated partition
Copula function local correlation structure concentration set concentration measure
2016/1/20
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 ...
Closed-form expansions of discretely monitored asian options in diffusion models
discretely monitored Asian options the CEV model the CIR process the Black-Scholes model the Brennan and Schwartz process small-time expansion
2016/1/20
In this paper we propose a closed-form asymptotic expansion approach to pricing discretely monitored Asian options in general one-dimensional diffusion models. Our expansion is a small-time expansion ...