Gatha Cognition®
Perception, Learning and Reasoning

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Bivariate Extremes: Models and Statistical Decision

Statistical Theory of Extremes


Statistical decision , Asymptotic approximation , Samples , Differentiable models , Logistic modes

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Large samples, \(\mathrm{ F^{n}( x,y ) }\)  is replaced by an asymptotic approximation for statistical decision of extremes. The discussions decide the fitness and accuracy of those approximations. The differentiable models, non-differentiable models of statistical decision, intrinsic estimation of the dependence functions, ready-to-wear model and estimations of the association between the margins with some examples are discussed in this chapter. Differentiable models, the logistic one gives a good fit but shows the logistic and the natural models can be very close and difficult to separate for moderate samples.

Bivariate Extremes: Models and Statistical Decision

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