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基于随机加权先验的P-Ⅲ分布参数贝叶斯估计
引用本文:殷建,宋松柏. 基于随机加权先验的P-Ⅲ分布参数贝叶斯估计[J]. 水文, 2015, 35(3): 1-7
作者姓名:殷建  宋松柏
作者单位:西北农林科技大学水利与建筑工程学院
基金项目:国家自然科学基金项目(51179160,50879070,51079037);高等学校博士学科点专项科研基金(20110204110017);
摘    要:研究随机加权先验法进行P-Ⅲ分布参数贝叶斯估计。应用随机加权法确定分布参数的先验分布,MCMC自适应采样算法(AM)进行参数的后验分布采样,并与矩法、极大似然法和概率权重矩法等传统水文频率分析方法进行比较。实例表明,AM方法估算参数下,实测样本与对应频率设计值离差平方和最小,是一种可行的水文频率分析途径。

关 键 词:贝叶斯方法;随机加权先验;AM算法;参数估计
收稿时间:2014-06-09

A Bayesian Method for Estimation Parameters of P-III Distribution Based on Randomly Weighted Prior
YIN Jian,SONG Songbai. A Bayesian Method for Estimation Parameters of P-III Distribution Based on Randomly Weighted Prior[J]. Hydrology, 2015, 35(3): 1-7
Authors:YIN Jian  SONG Songbai
Affiliation:College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, 712100, China
Abstract:The randomly weighted prior bayesian method was investigated to estimate the parameters of P-III distribution. The parameters prior distribution is determined by randomly weighted method, employing the AM algorithm to sampling analysis for the poste riori distribution of parameters, and compared with the traditional hydrological frequency analysis methods, such as Moments method, Maximum Likelihood method and Probability Weighted Moment method. The examples show that the parameters obtained by the Bayesian AM algorithm has the minimum sum of squares of deviations between the measured samples and design values under their frequencies. The AM algorithm is a feasible hydrological frequency analysis approach.
Keywords:Bayesian method   randomly weighted prior   AM algorithm   parameter estimation
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