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Penalized M-estimators are used in many areas of science and engineering to fit models with some low-dimensional structure in high-dimensional settings. In many problems arising in bioinformatics, sig...
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shi...
The Lasso is a popular statistical tool invented by Robert Tibshirani for linear regression when the number of covariates is greater than or comparable to the number of observations. The validity of t...
We give answer to an open problem regarding consistency of the maximum likelihood estimators (MLEs) in generalized linear mixed models (GLMMs) involving crossed random effects. The solution to the ope...
This paper addresses the estimation of the nonparametric conditional moment restricted model that involves an infinite dimensional parameter g0. We estimate it in a quasi-Bayesian way based on the l...
The stochastic block model (SBM) is a probabilistic model de- signed to describe heterogeneous directed and undirected graphs. In this paper, we address the asymptotic inference on SBM by use of max...
The random numbers drivingMarkov chainMonte Carlo (MCMC) simulation are usually modeled as independent U(0, 1) random variables. Tribble [Markov chain Monte Carlo algorithms using completely unifor...
A new class of statistical deformable models is introduced to study high-dimensional curves or images. These models are useful to analyze the geometric modes of variation of a data set around a commo...
The paper investigates noncommutative sequential tests. There are defined consistency and uniform consistency of such. tests, and then sufficient and necessary conditions-for the test to be consist...
Consistency of M-estimators in a linear model, generated by nonmonotone and discontinuous psi-functions
We study the nonparametric spline density estimators of probability density. The equivalence of weak convergence for L,-consistency of one density and completely for L,-consistency of all densities...
In the paper, a sequential confidence set based on an estimation process of a multivariate parameter is constructed. Under the assumption that the estimation process scaled by an increasing positiv...
A large number of statistical models is described by a family of reversed submartingales converging to degenerated limits. The problem under consideration is to estimate the maximum points of the l...
Consistency and Identifiability Revisited。
We consider the problem of forecasting the next (observable) state of an unknown ergodic dynamical system from a noisy observation of the present state. Our main result shows, for example, that sup...

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