The semiparametric Bernstein–von Mises theorem
نویسندگان
چکیده
منابع مشابه
A semiparametric Bernstein - von Mises theorem for Gaussian process priors
This paper is a contribution to the Bayesian theory of semiparametric estimation. We are interested in the so-called Bernstein-von Mises theorem, in a semiparametric framework where the unknown quantity is (θ , f ), with θ the parameter of interest and f an infinite-dimensional nuisance parameter. Two theorems are established, one in the case with no loss of information and one in the informati...
متن کاملQuadratic semiparametric Von Mises calculus.
We discuss a new method of estimation of parameters in semiparametric and nonparametric models. The method is based on U-statistics constructed from quadratic influence functions. The latter extend ordinary linear influence functions of the parameter of interest as defined in semiparametric theory, and represent second order derivatives of this parameter. For parameters for which the matching c...
متن کاملSemiparametric Bernstein–von Mises for the error standard deviation
Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of ...
متن کاملMises’ democracy–dictatorship equivalence theorem: A critique
Ludwig von Mises argues that public opinion, not the form of government, is the ultimate determinant of policy. The implication is that, holding public opinion constant, democracies and dictatorships will have the same policies—a result I call Mises’ Democracy–Dictatorship Equivalence Theorem. According to Mises, dictators have to comply with public opinion or else they will be overthrown. I ar...
متن کاملOn the Bernstein - von Mises Theorem with Infinite Dimensional Parameters
If there are many independent, identically distributed observations governed by a smooth, finite-dimensional statistical model, the Bayes estimate and the maximum likelihood estimate will be close. Furthermore, the posterior distribution of the parameter vector around the posterior mean will be close to the distribution of the maximum likelihood estimate around truth. Thus, Bayesian confidence ...
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: The Annals of Statistics
سال: 2012
ISSN: 0090-5364
DOI: 10.1214/11-aos921