Results 271 to 280 of about 607,794 (304)

Bayesian nonparametric set construction for robust optimization

2015 American Control Conference (ACC), 2015
This paper presents a Bayesian nonparametric, data-driven, nonconvex uncertainty set construction for robust optimization. First, a basic uncertainty set is constructed from a union of posterior predictive ellipsoids for the Dirichlet process Gaussian mixture.
Trevor Campbell, Jonathan P. How
openaire   +2 more sources

A robust nonparametric method for quantifying undetected extinctions

Conservation Biology, 2016
Abstract How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required.
Chisholm, R., Giam, X., Sadanandan, K., Fung, T., Rheindt, F.   +4 more
openaire   +3 more sources

Robust Statistics for Nonparametric Group Analysis in fMRI

3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006., 2006
In order to deal with inhomogeneous groups of subjects in fMRI studies, we investigate several robust statistics to perform random-effect analysis on the mean population effect (sign statistic, Wilcoxon's signed rank statistic and empirical t statistic).
Sébastien Mériaux, Alexis Roche, Bertrand Thirion, Ghislaine Dehaene-Lambertz   +3 more
openaire   +1 more source

Robust Nonparametric Regression for Heavy-Tailed Data

Journal of Agricultural, Biological and Environmental Statistics, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ferdos Gorji, Mina Aminghafari
openaire   +2 more sources

Robust Nonparametric Statistical Methods

Technometrics, 1999
Jie Mi, T. P. Hettmansperger, J. W. McKean   +2 more
openaire   +2 more sources

Essays in Econometrics: Nonparametrics and Robustness

2021
This thesis consists of three chapters. In each chapter I consider a particular problem in econometrics with implications for applied research, and in each case I attempt to solve that problem. In Chapter 1 I consider the task of inferring causal effects when only `proxy controls' are available.
openaire   +1 more source

Robust Nonparametric Regression and Modality

2003
The paper considers the problem of nonparametric regression with emphasis on controlling the number of local extremes and on resistance against patches of outliers. The robust taut string method is introduced and robustness properties are discussed. An automatic procedure is described.
openaire   +1 more source

Bayesian Robustness and Bayesian Nonparametrics

2000
Bayesian robustness studies the sensitivity of Bayesian answers to user inputs, especially to the specification of the prior. Nonparametric Bayesian models, on the other hand, refrain from specifying a specific prior functional form P, but instead assume a second-level hyperprior on P with support on a suitable space of probability measures ...
openaire   +1 more source

Rule selection invariance as a robustness check in collective choice and nonparametric statistical settings

Public Choice, 2022
Shane Sanders
exaly  

Robustness of Statistical Methods and Nonparametric Statistics.

Journal of the Royal Statistical Society. Series A (General), 1987
Eric Ziegel, D. Rasch, M. Tiku
openaire   +1 more source