近似截尾正态分布的均值
Approximating the mean of a truncated normal distribution
摘要：
在一些应用中出现的一个重要问题是截断正态分布的均值估计。在本文中，提出了一个迭代确定性计划近似这个平均值。它的灵感来自于一个迭代的马尔可夫链蒙特卡罗（MCMC）方案，解决了这个问题，它可以被看作是一个泛化最近提出的相关模型。给出了该格式收敛于唯一不动点的条件。最后，理论结果也支持计算机模拟，这也表明该方法的快速收敛的解向量是非常接近的截断正态分布的平均值的研究。
英文摘要：
A non trivial problem that arises in several applications is the estimation of the mean of a truncated normal distribution. In this paper, an iterative deterministic scheme for approximating this mean is proposed. It has been inspired from an iterative Markov chain Monte Carlo (MCMC) scheme that addresses this problem and it can be viewed as a generalization of a recently proposed relevant model. Conditions are provided under which it is proved that the scheme converges to a unique fixed point. Finally, the theoretical results are also supported by computer simulations, which also show the rapid convergence of the method to a solution vector that is very close to the mean of the truncated normal distribution under study.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
