作者：Ma, Yanyuan; Hart, Jeffrey D.
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：A local likelihood estimator for a nonparametric nuisance function is proposed in the context of semiparametric skew-normal distributions. Constraints imposed on such functions result in a nonparametric estimator with a different target function for maximization from classical local likelihood estimators. The optimal asymptotic semiparametric efficiency bound on parameters of interest is achieved by using this estimator in conjunction with an estimating equation formed by summing efficient sco...
作者：Chaudhuri, Sanjay; Drton, Mathias; Richardson, Thomas S.
作者单位：National University of Singapore; University of Chicago; University of Washington; University of Washington Seattle
摘要：We consider estimation of the covariance matrix of a multivariate random vector under the constraint that certain covariances are zero. We first present an algorithm, which we call iterative conditional fitting, for computing the maximum likelihood estimate of the constrained covariance matrix, under the assumption of multivariate normality. In contrast to previous approaches, this algorithm has guaranteed convergence properties. Dropping the assumption of multivariate normality, we show how t...
