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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.
Type: article
Appears in Collections:CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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