The Bruss-Robertson Inequality:Elaborations, Extensions, and Applications

J. Michael Steele

Mathematica Applicanda (2016)

  • Volume: 44, Issue: 1
  • ISSN: 1730-2668

Abstract

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The Bruss-Robertson inequality gives a bound on themaximal number of elements of a random sample whose sum is less than a specifiedvalue, and the extension of that inequality which is given hereneither requires the independence of the summands nor requires the equality of their marginal distributions. A review is also given of the applications of the Bruss-Robertson inequality,especially the applications to problems of combinatorial optimization such as the sequential knapsack problem and the sequential monotone subsequence selection problem.

How to cite

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J. Michael Steele. "The Bruss-Robertson Inequality:Elaborations, Extensions, and Applications." Mathematica Applicanda 44.1 (2016): null. <http://eudml.org/doc/292892>.

@article{J2016,
abstract = {The Bruss-Robertson inequality gives a bound on themaximal number of elements of a random sample whose sum is less than a specifiedvalue, and the extension of that inequality which is given hereneither requires the independence of the summands nor requires the equality of their marginal distributions. A review is also given of the applications of the Bruss-Robertson inequality,especially the applications to problems of combinatorial optimization such as the sequential knapsack problem and the sequential monotone subsequence selection problem.},
author = {J. Michael Steele},
journal = {Mathematica Applicanda},
keywords = {order statistic inequalities, knapsack problem, monotone subsequence problem},
language = {eng},
number = {1},
pages = {null},
title = {The Bruss-Robertson Inequality:Elaborations, Extensions, and Applications},
url = {http://eudml.org/doc/292892},
volume = {44},
year = {2016},
}

TY - JOUR
AU - J. Michael Steele
TI - The Bruss-Robertson Inequality:Elaborations, Extensions, and Applications
JO - Mathematica Applicanda
PY - 2016
VL - 44
IS - 1
SP - null
AB - The Bruss-Robertson inequality gives a bound on themaximal number of elements of a random sample whose sum is less than a specifiedvalue, and the extension of that inequality which is given hereneither requires the independence of the summands nor requires the equality of their marginal distributions. A review is also given of the applications of the Bruss-Robertson inequality,especially the applications to problems of combinatorial optimization such as the sequential knapsack problem and the sequential monotone subsequence selection problem.
LA - eng
KW - order statistic inequalities, knapsack problem, monotone subsequence problem
UR - http://eudml.org/doc/292892
ER -

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