Model selection via testing: an alternative to (penalized) maximum likelihood estimators

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Model selection via testing: an alternative to (penalized) maximum likelihood estimators

This paper is devoted to the definition and study of a family of model selection oriented estimators that we shall call T-estimators (“T” for tests). Their construction is based on former ideas about deriving estimators from some families of tests due to Le Cam [L.M. Le Cam, Convergence of estimates under dimensionality restrictions, Ann. Statist. 1 (1973) 38–53 and L.M. Le Cam, On local and gl...

متن کامل

Variable Selection via Penalized Likelihood

Variable selection is vital to statistical data analyses. Many of procedures in use are ad hoc stepwise selection procedures, which are computationally expensive and ignore stochastic errors in the variable selection process of previous steps. An automatic and simultaneous variable selection procedure can be obtained by using a penalized likelihood method. In traditional linear models, the best...

متن کامل

Confidence Sets Based on Penalized Maximum Likelihood Estimators

Confidence intervals based on penalized maximum likelihood estimators such as the LASSO, adaptive LASSO, and hard-thresholding are analyzed. In the known-variance case, the finite-sample coverage properties of such intervals are determined and it is shown that symmetric intervals are the shortest. The length of the shortest intervals based on the hard-thresholding estimator is larger than the l...

متن کامل

Regularization parameter selection for penalized-maximum likelihood methods in PET

Penalized maximum likelihood methods are commonly used in positron emission tomography (PET). Due to the fact that a Poisson data-noise model is typically assumed, standard regularization parameter choice methods, such as the discrepancy principle or generalized cross validation, can not be directly applied. In recent work of the authors, regularization parameter choice methods for penalized ne...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Annales de l'Institut Henri Poincare (B) Probability and Statistics

سال: 2006

ISSN: 0246-0203

DOI: 10.1016/j.anihpb.2005.04.004