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Moment inequality of the minimum for nonnegative negatively orthant dependent random variables
Author(s) -
Xuejun Wang,
Shijie Wang,
Shuhe Hu
Publication year - 2014
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1407475w
Subject(s) - orthant , mathematics , random variable , combinatorics , sequence (biology) , moment (physics) , statistics , physics , classical mechanics , genetics , biology
Let $\{x_n,n\geq1\}$ be a sequence of positive numbers and $\{\xi_n,n\geq1\}$ be a sequence of nonnegative negatively orthant dependent random variables satisfying certain distribution conditions. An exponential inequality for the minimum $\min_{1\leq i\leq n} x_i\xi_i$ is given. In addition, the moment inequality of the minimum for nonnegative negatively orthant dependent random variables is established as follows: $$ \left(\mathbb{E} ~k-\min_{1\leq i\leq n}|x_i\xi_i|^p\right)^{1/p}\leq \beta^{-1} C(p,k) \max_{1\leq j\leq k}\frac{k+1-j}{\sum_{i=j}^n1/x_i},~2\leq k\leq n,$$ where $C(p,k)=4\sqrt{2}\max\{p, \ln (1+k)\}$. If $k=1$, the following inequality is presented: $$\mathbb{E}\left(\min_{1\leq i\leq n}|x_i\xi_i|^p\right)\leq \beta^{-p} \Gamma (1+p)\left(\sum_{i=1}^n\frac{1}{|x_i|}\right)^{-p}.$$ Our results generalize the corresponding ones for independent random variables to the case of negatively orthant dependent random variables.

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