摘要翻译:
在一般Besov空间中,利用贝叶斯方法研究了小波收缩的后验收敛速度。本文从非参数贝叶斯渐近的角度出发,研究后验分布本身的收敛速度,而不是研究与特定损失函数相关的贝叶斯估计量。我们得到了与在\Citet{abramovich04}中相同的速率,其中作者研究了几个贝叶斯估计的收敛性。
---
英文标题:
《On posterior distribution of Bayesian wavelet thresholding》
---
作者:
Heng Lian
---
最新提交年份:
2007
---
分类信息:
一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
--
一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
--
---
英文摘要:
We investigate the posterior rate of convergence for wavelet shrinkage using a Bayesian approach in general Besov spaces. Instead of studying the Bayesian estimator related to a particular loss function, we focus on the posterior distribution itself from a nonparametric Bayesian asymptotics point of view and study its rate of convergence. We obtain the same rate as in \citet{abramovich04} where the authors studied the convergence of several Bayesian estimators.
---
PDF链接:
https://arxiv.org/pdf/709.3339