High dimensional nuisance parameters: an example from parametric survival analysis
نویسندگان
چکیده
منابع مشابه
Regularized Parametric Regression for High-dimensional Survival Analysis
Survival analysis aims to predict the occurrence of specific events of interest at future time points. The presence of incomplete observations due to censoring brings unique challenges in this domain and differentiates survival analysis techniques from other standard regression methods. In many applications where the distribution of the survival times can be explicitly modeled, parametric survi...
متن کاملA Paradox of Semiparametric Estimators with Infinite Dimensional Nuisance Parameters
Pierce (1982) found a paradoxical phenomenon. Let θ = (β, γ) be parameters which we would like to estimate. In many cases, we are only interested in some parameters and the rest is nuisance parameters. Let β be parameters we were interested in and γ be nuisance parameters. Usually, an estimator of β has smaller variance when the nuisance parameter γ is known. Pierce (1982) found that under some...
متن کاملNeighborhoods as Nuisance Parameters
Deviations from the center within a robust neighborhood may naturally be considered an innnite dimensional nuisance parameter. Thus, in principle, the semiparametric method may be tried, which is to compute the scores function for the main parameter minus its orthogonal projection on the closed linear tangent space for the nuisance parameter, and then rescale for Fisher consistency. We derive s...
متن کاملThe elimination of nuisance parameters
We review the Bayesian approach to the problem of the elimination of nuisance parameters from a statistical model. Many Bayesian statisticians feel that the framework of Bayesian statistics is so clear and simple that the elimination of nuisance parameters should not be considered a problem: one has simply to compute the marginal posterior distribution of the parameter of interest. However we w...
متن کاملNoninformative Priors and Nuisance Parameters
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].. Taylor & Francis, Ltd. and American Statistical Associati...
متن کاملذخیره 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: Information Geometry
سال: 2020
ISSN: 2511-2481,2511-249X
DOI: 10.1007/s41884-020-00030-6