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Title: Multivariate Application Domains for the Delta Method
Authors: Mexia, João
Nunes, Célia
Oliveira, Manuela
Editors: Austin, Robert H.
Crespi, Vincent H.
Johnson Jr, A.T. Charlie
Tanaka, Masaaki
Wang, Enge G.
Alavi, Saman
Arenholz, Elke
Biercuk, Michael J.
Carter, Troy A.
Detavernier, Detavernier
Endo, Yasuki
Gadre, Shridhar R.
Gao, Fei
Gerstman, Bernard S.
Hone, James C.
Huang, Liang
Li, Jingjing
Michaelides, Angelos
Mockensturm, Eric M.
Mondal, Partha P.
Paluch, Marian
Prellier, Wilfrid
Xie, Xin-Cheng
Xue, Qi-Kun
Theodore, E. Simos
Psihoyios, George
Tsitouras, Ch.
Zacharias, Anastassi
Keywords: Delta method
asymptotic linearity
normal case.
Issue Date: 2011
Publisher: American Institute of Physics.
Abstract: Given statistics with components Yi = gi(μ +X), i = 1, ...,m, and domains D such that, when μ ∈ D, distributions derived applying to Delta method may be used. The case in which X is normal is singled out. Then the approximate distributions are normal and may be applied in situations with high non-centrality parameter Δ = μtΣ−1μ where Σ is the variance-covariance matrix of X.
ISBN: 978-0-7354-0956-9
Type: article
Appears in Collections:CIMA - Artigos em Livros de Actas/Proceedings

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