MCMC Confidence Sets for Identified Sets

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Confidence Sets for Network Structure

Latent variable models are frequently used to identify structure in dichotomous network data, in part because they give rise to a Bernoulli product likelihood that is both well understood and consistent with the notion of exchangeable random graphs. In this article we propose conservative confidence sets that hold with respect to these underlying Bernoulli parameters as a function of any given ...

متن کامل

Confidence regions for level sets

This paper discusses a universal approach to the construction of confidence regions for level sets {h(x) ≥ 0} ⊂ Rd of a function h of interest. The proposed construction is based on a plug-in estimate of the level sets using an appropriate estimate �hn of h. The approach provides finite sample upper and lower confidence limits. This leads to generic conditions under which the constructed confid...

متن کامل

Confidence sets for phylogenetic trees

Inferring evolutionary histories (phylogenetic trees) has important applications in biology, criminology and public health. However, phylogenetic trees are complex mathematical objects that reside in a non-Euclidean space, which complicates their analysis. While our mathematical, algorithmic, and probabilistic understanding of the behavior of phylogenies in their metric space is relatively matu...

متن کامل

Confidence Sets for Persistence Diagrams

Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features as one varies a tuning parameter. Features with short lifetimes are informally considered to be “topological noise,” and those with a long lifetime are considered to be “topological signal.” In this paper, we bring some statis...

متن کامل

Nonparametric Confidence Sets for Density

We present a method for constructing nonparametric confidence sets for density functions based on an approach due to Beran and Dümbgen (1998). We expand the density in an appropriate basis and we estimate the basis coefficients by using linear shrinkage methods. We then find the limiting distribution of an asymptotic pivot based on the quadratic loss function. Inverting this pivot yields a conf...

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: SSRN Electronic Journal

سال: 2016

ISSN: 1556-5068

DOI: 10.2139/ssrn.2775253