【摘 要】
：
Growing-dimensional data with likelihood unavailable are often encoun-tered in various fields.This paper presents a penalized exponentially tilted likelihoo
【机 构】
：
YunnanUniversity,China
【出 处】
：
数学统计在医学成像及大数据应用的集成方法研讨会(MSMIA2016)
论文部分内容阅读
Growing-dimensional data with likelihood unavailable are often encoun-tered in various fields.This paper presents a penalized exponentially tilted likelihood(PETL)for variable selection and parameter estimation for growing dimensional un-conditional moment models in the presence of correlation among variables and model misspecification.
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