Results 31 to 40 of about 1,669,248 (311)
Finite-Sample Bounds on the Accuracy of Plug-In Estimators of Fisher Information
Entropy, 2021 Finite-sample bounds on the accuracy of Bhattacharya’s plug-in estimator for Fisher information are derived. These bounds are further improved by introducing a clipping step that allows for better control over the score function.
Wei Cao +3 more
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Adaptive Estimation of Nonparametric Functionals
J. Mach. Learn. Res., 2016 We provide general adaptive upper bounds for estimating nonparametric functionals based on second order U-statistics arising from finite dimensional approximation of the infinite dimensional models. We then provide examples of functionals for which the theory produces rate optimally matching adaptive upper and lower bounds.
Lin Liu +3 more
openaire +4 more sources
Adaptive Reduction of Curse of Dimensionality in Nonparametric Instrumental Variable Estimation
MathematicsNonparametric estimation of instrumental variable treatment effects typically builds on various nonparametric identification results. However, these estimators often face challenges from the curse of dimensionality in practice, as multi-dimensional ...
Ming-Yueh Huang, Kwun Chuen Gary Chan
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Entropy, 2008 At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation.
Julian Sorensen
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Optimal designs for testing the functional form of a regression via nonparametric estimation techniques [PDF]
, 2000 For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the ...
Stefanie Biedermann +3 more
core +1 more source
Bias Adjustment for a Nonparametric Entropy Estimator
Entropy, 2013 Zhang in 2012 introduced a nonparametric estimator of Shannon’s entropy, whose bias decays exponentially fast when the alphabet is finite. We propose a methodology to estimate the bias of this estimator.
Zhiyi Zhang, Michael Grabchak
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Nonparametric Estimation of Range Value at Risk
Computation, 2023 Range value at risk (RVaR) is a quantile-based risk measure with two parameters. As special examples, the value at risk (VaR) and the expected shortfall (ES), two well-known but competing regulatory risk measures, are both members of the RVaR family. The
Suparna Biswas, Rituparna Sen
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Nonparametric Regression Estimation for Circular Data
Proceedings, 2019 Non-parametric regression with a circular response variable and a unidimensional linear regressor is a topic which was discussed in the literature.
Andrea Meilán-Vila +3 more
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Energy Reports, 2022 In today’s increasingly serious world energy crisis, Renewable energy such as wind energy has gradually penetrated into life. Aiming at the uncertainty of wind power and the need of a mass of sample data in nonparametric kernel density estimation, a wind
Kai Zhang +6 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the association and discriminative performance of serum biomarkers with clinical disease progression and survival in patients with amyotrophic lateral sclerosis (ALS). Methods This retrospective study, conducted at Houston Methodist Hospital, Houston, TX, used longitudinal serum samples collected between January 2018 and ...
David R. Beers +7 more
wiley +1 more source