Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Maximizing the expected range from dependent observations under
  mean-variance information   In this article we derive the best possible upper bound for
$E[\max{X_i}-\min_i{X_i}]$ under given means and variances on $n$ random
variables $X_i$. The random vector $(X_1,...,X_n)$ is allowed to have any
dependence structure, provided $E X_i=\mu_i$ and $Var X_i=\sigma_i^2$,
$0<\sigma_i<\infty$. We provide an explicit characterization of the $n$-variate
distributions that attain the equality (extremal random vectors), and the tight
bound is compared to other existing results.
  Key words and phrases: Range; Dependent Observations; Tight Expectation
Bounds; Extremal Random Vectors; Probability Matrices; Characterizations.

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The categories of this paper are: cmp-lg
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The categories of this paper are: chem-ph
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The categories of this paper are: nlin
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The categories of this paper are: solv-int
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The categories of this paper are: gr-qc
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The categories of this paper are: atom-ph
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The categories of this paper are: q-bio
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: cond-mat
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The categories of this paper are: cs
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The categories of this paper are: funct-an
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The categories of this paper are: patt-sol
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The categories of this paper are: astro-ph