摘要
极值分布在地震、洪灾和其它自然灾害的预测中是非常有用的.在许多应用方面,很有必要对散度建模.本文推广经典极值回归模型,研究了联合位置与散度模型,并提出了一种同时对位置模型和散度模型的变量选择方法.同时证明了惩罚极大似然估计具有相合性和oracle性质,通过随机模拟研究了所提出方法的有限样本性质.
The extreme-value distribution is very useful in predicting the probability that an extreme earthquake, flood or other natural disaster will occur. In many applications, there is a great need to model the dispersion. In this paper, a unified procedure is proposed to simultaneously select signifi- cant variables in joint location and dispersion models which provide a useful extension of the general extreme-value regression model. It is further shown that the presented penalized maximum likelihood estimator enjoys the consistency and the oracle property. Numerical simulation is conducted to exam- ine the finite sample properties of the proposed method.
出处
《工程数学学报》
CSCD
北大核心
2012年第5期670-680,共11页
Chinese Journal of Engineering Mathematics
基金
国家自然科学基金(11126309
11026209)
云南省自然科学基金(2009ZC039M
2011FB016
2011FZ044)
昆明理工大学博士科研启动基金(2009-024)~~
关键词
异方差模型
联合位置与散度模型
惩罚极大似然估计
变量选择
估计理论
heteroscedastic regression models
joint location and dispersion models
penalized maxi-mum likelihood estimator
variable selection
estimation theory
