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Start Over Subject admissibility

1. A direct approach to the Weiss conjecture for bounded analytic semigroups

Creator:
Hamid, Bounit, Abderrahim, Driouich, and Omar, El-Mennaoui
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
infinite dimensional systems, analytic semigroups, unbounded observation operator, admissibility, and fractional power
Language:
English
Description:
We give a new proof of the Weiss conjecture for analytic semigroups. Our approach does not make any recourse to the bounded $H^{\infty }$-calculus and is based on elementary analysis.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

2. Admissible invariant estimators in a linear model

Creator:
Stępniak, Czesław
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
linear estimator, invariant estimator, admissibility, and one-way / two-way ANOVA
Language:
English
Description:
Let y be observation vector in the usual linear model with expectation Aβ and covariance matrix known up to a multiplicative scalar, possibly singular. A linear statistic aTy is called invariant estimator for a parametric function ϕ=cTβ if its MSE depends on β only through ϕ. It is shown that aTy is admissible invariant for ϕ, if and only if, it is a BLUE of ϕ, in the case when ϕ is estimable with zero variance, and it is of the form kϕˆ, where k∈⟨0,1⟩ and ϕˆ is an arbitrary BLUE, otherwise. This result is used in the one- and two-way ANOVA models. Our paper is self-contained and accessible, also for non-specialists.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

3. An admissible estimator of a lower-bounded scale parameter under squared-log error loss function

Creator:
Mahmoudi, Eisa and Zakerzadeh, Hojatollah
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
admissibility, Bayes estimator, truncated parameter spaces, and squared-log error los
Language:
English
Description:
Estimation in truncated parameter space is one of the most important features in statistical inference, because the frequently used criterion of unbiasedness is useless, since no unbiased estimator exists in general. So, other optimally criteria such as admissibility and minimaxity have to be looked for among others. In this paper we consider a subclass of the exponential families of distributions. Bayes estimator of a lower-bounded scale parameter, under the squared-log error loss function with a sequence of boundary supported priors is obtained. An admissible estimator of a lower-bounded scale parameter, which is the limiting Bayes estimator, is given. Also another class of estimators of a lower-bounded scale parameter, which is called the truncated linear estimators, is considered and several interesting properties of the estimators in this class are studied. Some comparisons of the estimators in this class with an admissible estimator of a lower-bounded scale parameter are presented.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

4. Characterization of admissible linear estimators under extended balanced loss function

Creator:
Mirezi, Buatikan and Kaçıranlar, Selahattin
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
admissibility, extended balanced loss function, and linear admissible estimator
Language:
English
Description:
In this paper, we study the admissibility of linear estimator of regression coefficient in linear model under the extended balanced loss function (EBLF). The sufficient and necessary condition for linear estimators to be admissible are obtained respectively in homogeneous and non-homogeneous classes. Furthermore, we show that admissible linear estimator under the EBLF is a convex combination of the admissible linear estimator under the sum of square residuals and quadratic loss function.
Rights:
http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public