Slide 6_2_distribution 最近の更新履歴 Keisuke Kawata's HP
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The results presented in this section illustrate the behaviour of the proposed estimators in finite samples, when the original estimator is the Hill estimator, b γ n (k) ≡ γ b n H
The maximum likelihood estimates are much better than the moment estimates in terms of the bias when the relative difference between the two parameters is large and the sample size
We derive rigorously a homogenized model for the displacement of one compressible miscible fluid by another in a partially fractured porous reservoir.. We denote by the
In the previous section we have established a sample-path large deviation principle on a finite time grid; this LDP provides us with logarithmic asymptotics of the probability that
The class of estimators introduced is dependent on some control or tuning parameters and has the advantage of providing estimators with stable sample paths, as functions of the number
The maximum likelihood estimates are much better than the moment estimates in terms of the bias when the relative difference between the two parameters is large and the sample size
Instead an elementary random occurrence will be denoted by the variable (though unpredictable) element x of the (now Cartesian) sample space, and a general random variable will
Using the semigroup approach for stochastic evolution equations in Banach spaces we obtain existence and uniqueness of solutions with sample paths in the space of continuous