Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/2594
|
Title: | Asymptotic linearity and limit distributions, approximations. |
Authors: | Mexia, J.T., Oliveira, M.M., |
Keywords: | Asymptotic linearity |
Issue Date: | 2010 |
Abstract: | Linear and quadratic forms as well as other low degree polynomials play an important
role in statistical inference. Asymptotic results and limit distributions are obtained for a
class of statistics depending on m þ X, with X any random vector and m non-random
vector with JmJ-þ1. This class contain the polynomials in m þ X. An application to
the case of normal X is presented. This application includes a new central limit theorem
which is connected with the increase of non-centrality for samples of fixed size.
Moreover upper bounds for the suprema of the differences between exact and
approximate distributions and their quantiles are obtained. |
URI: | http://hdl.handle.net/10174/2594 |
Type: | article |
Appears in Collections: | CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
|