Results 1 to 10 of about 259 (37)
Open Mathematics, 2022 One of the most common challenges in multivariate statistical analysis is estimating the mean parameters. A well-known approach of estimating the mean parameters is the maximum likelihood estimator (MLE).
Benkhaled Abdelkader +4 more
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On shrinkage estimators improving the positive part of James-Stein estimator
Demonstratio Mathematica, 2021 In this work, we study the estimation of the multivariate normal mean by different classes of shrinkage estimators. The risk associated with the quadratic loss function is used to compare two estimators. We start by considering a class of estimators that
Hamdaoui Abdenour
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A unifying causal framework for analyzing dataset shift-stable learning algorithms
Journal of Causal Inference, 2022 Recent interest in the external validity of prediction models (i.e., the problem of different train and test distributions, known as dataset shift) has produced many methods for finding predictive distributions that are invariant to dataset shifts and ...
Subbaswamy Adarsh +2 more
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Properties of restricted randomization with implications for experimental design
Journal of Causal Inference, 2022 Recently, there has been increasing interest in the use of heavily restricted randomization designs which enforce balance on observed covariates in randomized controlled trials.
Nordin Mattias, Schultzberg Mårten
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Admissible predictive density estimation [PDF]
, 2008 Let $X|\mu\sim N_p(\mu,v_xI)$ and $Y|\mu\sim N_p(\mu,v_yI)$ be independent $p$-dimensional multivariate normal vectors with common unknown mean $\mu$. Based on observing $X=x$, we consider the problem of estimating the true predictive density $p(y|\mu ...
Brown, Lawrence D. +2 more
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Minimax estimation of the Wigner function in quantum homodyne tomography with ideal detectors [PDF]
, 2006 We estimate the quantum state of a light beam from results of quantum homodyne measurements performed on identically prepared pulses. The state is represented through the Wigner function, a ``quasi-probability density'' on $\mathbb{R}^{2}$ which may take
A. Ourjoumtsev +24 more
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Improved minimax predictive densities under Kullback--Leibler loss [PDF]
, 2006 Let $X| \mu \sim N_p(\mu,v_xI)$ and $Y| \mu \sim N_p(\mu,v_yI)$ be independent p-dimensional multivariate normal vectors with common unknown mean $\mu$.
George, Edward I. +2 more
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Optimal Testing for Planted Satisfiability Problems [PDF]
, 2015 We study the problem of detecting planted solutions in a random satisfiability formula. Adopting the formalism of hypothesis testing in statistical analysis, we describe the minimax optimal rates of detection.
Berthet, Quentin
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On the concentration of measure phenomenon for stable and related random vectors
, 2004 Concentration of measure is studied, and obtained, for stable and related random vectors.Comment: Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.
Houdre, Christian, Marchal, Philippe
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, 2010 This paper considers estimation of the predictive density for a normal linear model with unknown variance under alpha-divergence loss for -1
Maruyama, Yuzo, Strawderman, William E.
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