令{ Yn,n≥0 }表示独立同分布随机环境ξ=(ξn)n≥0中的加权分枝过程,本文针对统计量log(Yn0+nYn0),借助Markov不等式建立了一个相关概率不等式,这一结果可以用于探索种群动态和概率特性,有助于深入理解随机环境中加权分枝模型的本质。L...令{ Yn,n≥0 }表示独立同分布随机环境ξ=(ξn)n≥0中的加权分枝过程,本文针对统计量log(Yn0+nYn0),借助Markov不等式建立了一个相关概率不等式,这一结果可以用于探索种群动态和概率特性,有助于深入理解随机环境中加权分枝模型的本质。Let { Yn,n≥0 }denote the weighted branching process in independently and identically distributed random environments ξ=(ξn)n≥0. In this paper, focusing on a statistic log(Yn0+nYn0), we establish a related probability inequality using Markov’s inequality. This result can be used to investigate population dynamics and probabilistic characteristics, contributing to a deeper understanding of the essence of weighted branching models in random environments.展开更多
文[1]给出了如下的Can-Hang不等式:已知a,b,c>0,abc=1,求证:1 a 2+a+1+1 b 2+b+1+1 c 2+c+1≥1.(1)本文给出不等式(1)的三种加权推广及引申.命题1设a,b,c>0,abc=1,1≤λ≤4,则∑1λa 2+a+1≥3λ+2(2)(其中“∑”表示轮换对称和,...文[1]给出了如下的Can-Hang不等式:已知a,b,c>0,abc=1,求证:1 a 2+a+1+1 b 2+b+1+1 c 2+c+1≥1.(1)本文给出不等式(1)的三种加权推广及引申.命题1设a,b,c>0,abc=1,1≤λ≤4,则∑1λa 2+a+1≥3λ+2(2)(其中“∑”表示轮换对称和,以下同).展开更多
文摘令{ Yn,n≥0 }表示独立同分布随机环境ξ=(ξn)n≥0中的加权分枝过程,本文针对统计量log(Yn0+nYn0),借助Markov不等式建立了一个相关概率不等式,这一结果可以用于探索种群动态和概率特性,有助于深入理解随机环境中加权分枝模型的本质。Let { Yn,n≥0 }denote the weighted branching process in independently and identically distributed random environments ξ=(ξn)n≥0. In this paper, focusing on a statistic log(Yn0+nYn0), we establish a related probability inequality using Markov’s inequality. This result can be used to investigate population dynamics and probabilistic characteristics, contributing to a deeper understanding of the essence of weighted branching models in random environments.
文摘文[1]给出了如下的Can-Hang不等式:已知a,b,c>0,abc=1,求证:1 a 2+a+1+1 b 2+b+1+1 c 2+c+1≥1.(1)本文给出不等式(1)的三种加权推广及引申.命题1设a,b,c>0,abc=1,1≤λ≤4,则∑1λa 2+a+1≥3λ+2(2)(其中“∑”表示轮换对称和,以下同).
