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Titlebook: Asymptotics in Statistics; Some Basic Concepts Lucien Cam,Grace Yang Book 19901st edition Springer-Verlag New York Inc. 1990 DEX.LAN.Statis

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https://doi.org/10.1007/978-1-4419-8963-5 distribution of likelihood ratios. Here we shall describe some consequences of a condition, called ., that simplifies many arguments in passages to the limit. We also introduce a technical tool, the Hellinger transform, that is often convenient in studies involving independent observations.
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,The Compressible Navier–Stokes System, probability measures . on some space .. Then one considers experiments . where . is the joint distribution of . observations ., .,..., . all independent with individual distribution .. One studies the asymptotic behavior of the system as . tends to infinity. We shall refer to this as the “standard i.i.d. case”.
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A. Koldobsky,D. Ryabogin,Artem ZvavitchIn the present volume we describe a few concepts and tools that we have found useful in thinking about asymptotic problems in Statistics. They revolve largely around the idea of approximating a family of measures say ℇ = {..;θ Є Θ} by other families, say . that may be better known or more tractable.
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Fourier Analysis and Its ApplicationsThe classical theory of asymptotics in Statistics relies heavily on certain local quadratic approximations to the logarithms of likelihood ratios. Such approximations will be studied here but in a restricted framework.
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Locally Asymptotically Normal Families,The classical theory of asymptotics in Statistics relies heavily on certain local quadratic approximations to the logarithms of likelihood ratios. Such approximations will be studied here but in a restricted framework.
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https://doi.org/10.1007/978-1-4684-0377-0DEX; LAN; Statistica; Variance; boundary element method; construction; field; form; functions; likelihood; max
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Springer Series in Statisticshttp://image.papertrans.cn/b/image/163855.jpg
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https://doi.org/10.1007/978-1-4419-8963-5indices Θ is called the parameter space. To obtain a statistical decision problem in the sense of Wald we also need a set . of possible decisions and a loss function . defined on Θ × . and taking values in (− ∞, +∞].
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