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Direct Regression Modelling of High-order Moments in Big Data
Big data Higher-order moment U-statistics Estimating equation Divide-and-conquer
2016/1/26
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...
High-order-mode soliton structures in two-dimensional lattices with defocusing nonlinearity
Discrete soliton self-focusing defocusing nonlinear dipole the structure of vortex solitons
2014/12/25
While fundamental-mode discrete solitons have been demonstrated with both self-focusing and defocusing nonlinearity, high-order-mode localized states in waveguide lattices have been studied thus far o...
Adjusted empirical likelihood with high-order precision
Bartlett correction confidence region Edgeworth expansion
2010/10/14
Empirical likelihood is a popular nonparametric or semi-parametric statistical method with many nice statistical properties. Yet when the sample size is small, or the dimension of the accompanying est...
Compressing Parameters in Bayesian High-order Models with Application to Logistic Sequence Models
compressing parameters high-ordermodels Markov chain Monte Carlo logistic models interaction
2009/9/22
Bayesian classication and regression with high-order interactions is
largely infeasible because Markov chain Monte Carlo (MCMC) would need to be
applied with a great many parameters, whose number in...