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Non-asymptotic analysis and inference for an outlyingness induced winsorized mean
Robust estimation of a mean vector, a topic regarded as obsolete in the traditional robust statistics community, has recently surged in machine...
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Explicit Non-Asymptotic Bounds for the Distance to the First-Order Edgeworth Expansion
In this article, we obtain explicit bounds on the uniform distance between the cumulative distribution function of a standardized sum
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Matrix-variate generalized linear model with measurement error
Matrix-variate generalized linear model (mvGLM) has been investigated successfully under the framework of tensor generalized linear model, because...
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Faster Asymptotic Solutions for N-Mixtures on Large Populations
We derive an asymptotic likelihood function for open-population N -mixture models and show that it has favorable computational complexity and accuracy...
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Global-Local Shrinkage Priors for Asymptotic Point and Interval Estimation of Normal Means under Sparsity
The paper addresses asymptotic estimation of normal means under sparsity. The primary focus is estimation of multivariate normal means where we...
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Variable selection for nonparametric quantile regression via measurement error model
This paper proposes a variable selection procedure for the nonparametric quantile regression based on the measurement error model (MEM). The “false”...
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An Analog of the Bickel–Rosenblatt Test for Error Density in the Linear Regression Model
This paper addresses the problem of testing the goodness-of-fit hypothesis pertaining to error density in multiple linear regression models with...
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A non-classical parameterization for density estimation using sample moments
Probability density estimation is a core problem in statistics and data science. Moment methods are an important means of density estimation, but...
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Right-censored nonparametric regression with measurement error
This study focuses on estimating a nonparametric regression model with right-censored data when the covariate is subject to measurement error. To...
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Efficiency Bound Under Identifiability Constraints in Semiparametric Models
The purpose of this work is to define an adequate efficiency bound in some models presenting some identification problems. We show how it is possible...
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Non-Asymptotic Bounds
Most asymptotic errors in statistical inference are based on error estimates when the sample size n and the dimension p of observations are large....
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Bounds on generalized family-wise error rates for normal distributions
The Bonferroni procedure has been one of the foremost frequentist approaches for controlling the family-wise error rate (FWER) in simultaneous...
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Asymptotic theory in network models with covariates and a growing number of node parameters
We propose a general model that jointly characterizes degree heterogeneity and homophily in weighted, undirected networks. We present a moment...
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Investigating non-inferiority or equivalence in time-to-event data under non-proportional hazards
The classical approach to analyze time-to-event data, e.g. in clinical trials, is to fit Kaplan–Meier curves yielding the treatment effect as the...
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An analog of Bickel–Rosenblatt test for fitting an error density in the two phase linear regression model
This paper discusses a test of goodness-of-fit of a known error density in a two phase linear regression model in the case jump size at the phase...
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Asymptotic justification of maximum likelihood estimation for the proportional excess hazard model in analysis of cancer registry data
Population-based cancer registry studies are conducted to investigate the various cancer question and have important impacts on cancer control. In...
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Sparse Constrained Projection Approximation Subspace Tracking
In this paper we revisit the well-known constrained (orthogonal) projection approximation subspace tracking algorithm and derive, for the first time,...
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Kernel density estimation by stagewise algorithm with a simple dictionary
This study proposes multivariate kernel density estimation by stagewise minimization algorithm based on U -divergence and a simple dictionary. The...
