A new proof for the peakedness of linear combinations of random variables

DOI10.1016/j.spl.2016.03.012zbMath1338.60054OpenAlexW2329065058MaRDI QIDQ277283

Shan Ju, Xiaoqing Pan

Publication date: 4 May 2016

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.03.012

zbMATH Keywords

majorizationlog-concavitypeakednessSchur-concaveSchur-convexstochastically arrangement increasing

Mathematics Subject Classification ID

Inequalities; stochastic orderings (60E15) Order statistics; empirical distribution functions (62G30) Reliability and life testing (62N05)

Cites Work

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• Peakedness for weighted sums of symmetric random variables
• Some new notions of dependence with applications in optimal allocation problems
• Stochastic orders
• Stochastic comparisons of weighted sums of arrangement increasing random variables
• Multivariate arrangement increasing functions with applications in probability and statistics
• Functions decreasing in transposition and their applications in ranking problems
• On peakedness of distributions of convex combinations.
• Some recent developments on majorization inequalities in probability and statistics
• Notions of multivariate dependence and their applications in optimal portfolio selections with dependent risks
• Some inequalities of linear combinations of independent random variables. II
• EFFICIENCY OF LINEAR ESTIMATORS UNDER HEAVY-TAILEDNESS: CONVOLUTIONS OF [alpha-SYMMETRIC DISTRIBUTIONS]
• Some Inequalities of Linear Combinations of Independent Random Variables. I.
• Bivariate characterization of some stochastic order relations
• Peakedness of Distributions of Convex Combinations
• On Random Variables with Comparable Peakedness
• Inequalities: theory of majorization and its applications

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