Let x 1,x 2,… be independent identically distributed (i.i.d.) random variables, in which x n=0 or 1 and the probability of ｛x n=1｝ is p. Here p is unknown. Let τ be any finite stopping ...Let x 1,x 2,… be independent identically distributed (i.i.d.) random variables, in which x n=0 or 1 and the probability of ｛x n=1｝ is p. Here p is unknown. Let τ be any finite stopping time for (x n,n1). For any sequential sample (x 1,x 2,…,x τ ) and γ∈(0,1), we have given an optimal confidence limit of p with confidence level γ . Some related problems are also discussed.展开更多
Classical Kolmogorov's and Rosenthal's inequalities for the maximum partial sums of random variables are basic tools for studying the strong laws of large numbers.In this paper,motived by the notion of indepen...Classical Kolmogorov's and Rosenthal's inequalities for the maximum partial sums of random variables are basic tools for studying the strong laws of large numbers.In this paper,motived by the notion of independent and identically distributed random variables under the sub-linear expectation initiated by Peng(2008),we introduce the concept of negative dependence of random variables and establish Kolmogorov's and Rosenthal's inequalities for the maximum partial sums of negatively dependent random variables under the sub-linear expectations.As an application,we show that Kolmogorov's strong law of larger numbers holds for independent and identically distributed random variables under a continuous sub-linear expectation if and only if the corresponding Choquet integral is finite.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.2019CDXYST00162018CDXYST0024)+2 种基金the China Scholarship Council(Grant No.201606055028)the National Natural Science Foundation of China(Grant No.11671060)the MOE Project of Humanities and Social Sciences on the West and the Border Area(Grant No.14XJC910001)
基金the Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)the Scientific Program of Department of Education of Jiangxi Province of China(Grant No.GJJ190732)。
文摘Let x 1,x 2,… be independent identically distributed (i.i.d.) random variables, in which x n=0 or 1 and the probability of ｛x n=1｝ is p. Here p is unknown. Let τ be any finite stopping time for (x n,n1). For any sequential sample (x 1,x 2,…,x τ ) and γ∈(0,1), we have given an optimal confidence limit of p with confidence level γ . Some related problems are also discussed.
基金supported by National Natural Science Foundation of China(Grant No.11225104)the Fundamental Research Funds for the Central Universities
文摘Classical Kolmogorov's and Rosenthal's inequalities for the maximum partial sums of random variables are basic tools for studying the strong laws of large numbers.In this paper,motived by the notion of independent and identically distributed random variables under the sub-linear expectation initiated by Peng(2008),we introduce the concept of negative dependence of random variables and establish Kolmogorov's and Rosenthal's inequalities for the maximum partial sums of negatively dependent random variables under the sub-linear expectations.As an application,we show that Kolmogorov's strong law of larger numbers holds for independent and identically distributed random variables under a continuous sub-linear expectation if and only if the corresponding Choquet integral is finite.
