Generalizations of some concentration inequalities

M. Ashraf Bhat and G. Sankara Raju Kosuru

Statistics & Probability Letters, 2022, vol. 182, issue C

Abstract: For a real-valued measurable function f and a nonnegative, nondecreasing function ϕ, we first obtain a Chebyshev type inequality which provides an upper bound for ϕ(λ1)μ({x∈Ω:f(x)≥λ1})+∑k=2nϕ(λk)−ϕ(λk−1)μ({x∈Ω:f(x)≥λk}), where 0<λ1<λ2<⋯<λn<∞. Using this, generalizations of a few concentration inequalities such as Markov, reverse Markov, Bienaymé–Chebyshev, Cantelli and Hoeffding inequalities are obtained.

Keywords: Markov’s inequality; Chebyshev’s inequality; Cantelli’s inequality; Hoeffding’s inequality (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2021.109298

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