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Asymptotic Normality of Sums of Dependent
Inference for the Multivariate
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applications approach approximation assume assumption asymptotic Banach space called characteristic function coefficients complex components computed consider continuous correct correlation corresponding decision defined denote depends derived determine discussed distribution elements equality equation error estimate example exists expectations expression fact factorization Fisher function Gaussian give given Hence hypothesis implies independent integral Introduction joint known Lemma likelihood limit linear Math mean measure methods multiple multivariate analysis normal Note observed obtained operator parameter population positive possible prediction present probability problem procedure proof properties random variables ratio References regression Research respect rule sample satisfies scattering shows space square statistics stochastic suppose Table Theorem theory tion transformation University values variance variates vector Wishart write