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Exact inequalities for sums of asymmetric random variables, with applications. (English) Zbl 1122.60021

Summary: Let \({\text{BS}}_{1},\dots,{\text{BS}}_{n}\) be independent identically distributed random variables each having the standardized Bernoulli distribution with parameter \({p \in (0, 1)}\). Set
\[ m_*(p):=\begin{cases} (1 + p + 2 p^{2})/(2\sqrt{p - p^{2}} + 4 p^{2}) &\text{if }0 < p \leq \frac 12,\\ 1 &\text{if }\frac 12 \leq p < 1.\end{cases} \]
Let \({m \geq m_{*}(p)}\). Let \(f\) be such a function that \(f\) and \(f''\) are nondecreasing and convex. Then it is proved that for all nonnegative numbers \({c_{1},\dots,c_{n}}\) one has the inequality
\[ {{\mathsf{E}} f(c_1{\text{B\!S}}_1+\dots+c_n{\text{B\!S}}_n)\leq{\mathsf{E}} f\big(s^{(m)}({\text{B\!S}}_1+\dots+{\text{BS}}_{n})\big),} \]
where \(s^{(m)}:= (\frac 1n \sum_{i=1}^n c_i^{2m})^{1/2m}\). The lower bound \({m_{*}(p)}\) on \(m\) is exact for each \({p\in (0,1)}\). Moreover, \({\mathsf{E}} f(c_1{\text{B\!S}}_1+\dots+c_n{\text{B\!S}}_n)\) is Schur-concave in \({(c_{1}^{2m},\dots,c_{n}^{2m})}\).
A number of corollaries are obtained, including upper bounds on generalized moments and tail probabilities of (super)martingales with differences of bounded asymmetry, and also upper bounds on the maximal function of such (super)martingales. Applications to generalized self-normalized sums and \(t\)-statistics are given.

MSC:

60E15 Inequalities; stochastic orderings
60G50 Sums of independent random variables; random walks
60G42 Martingales with discrete parameter
60G48 Generalizations of martingales
62F03 Parametric hypothesis testing
62F25 Parametric tolerance and confidence regions
62G10 Nonparametric hypothesis testing
60G15 Gaussian processes
60E05 Probability distributions: general theory
62E10 Characterization and structure theory of statistical distributions

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