English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A Geometric Approach to Confidence Sets for Ratios: Fieller‘s Theorem, Generalizations, and Bootstrap

von Luxburg, U., & Franz, V. (2009). A Geometric Approach to Confidence Sets for Ratios: Fieller‘s Theorem, Generalizations, and Bootstrap. Statistica Sinica, 19(3), 1095-1117.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:

Creators

show
hide
 Creators:
von Luxburg, U1, 2, Author           
Franz, VH1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: We present a geometric method to determine confidence sets for the
ratio E(Y)/E(X) of the means of random variables X and Y. This
method reduces the problem of constructing confidence sets for the
ratio of two random variables to the problem of constructing
confidence sets for the means of one-dimensional random variables. It
is valid in a large variety of circumstances. In the case of normally
distributed random variables, the so constructed confidence sets
coincide with the standard Fieller confidence sets. Generalizations of
our construction lead to definitions of exact and conservative
confidence sets for very general classes of distributions, provided
the joint expectation of (X,Y) exists and the linear combinations of
the form aX + bY are well-behaved. Finally, our geometric method
allows to derive a very simple bootstrap approach for constructing
conservative confidence sets for ratios which perform favorably in
certain situations, in particular in the asymmetric heavy-tailed
regime.

Details

show
hide
Language(s):
 Dates: 2009-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 5080
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Statistica Sinica
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Taipei : Institute of Statistical Science, Academia Sinica; International Chinese Statistical Association
Pages: - Volume / Issue: 19 (3) Sequence Number: - Start / End Page: 1095 - 1117 Identifier: ISSN: 1996-8507
CoNE: https://pure.mpg.de/cone/journals/resource/19968507