M. Naser Esfahani

Iranshahr University

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Hamed Ahmadzade

University of Sistan and Baluchestan

Rong Gao

Northwest A&F University

Nader Nematollahi

Allameh Tabataba'i University

Cooperative Institutions

University of Sistan and Baluchestan

Chongqing University

Ferdowsi University of Mashhad

Northwest A&F University

Hebei University of Technology

Yunnan Water Conservancy and Hydropower Survey and Design Institute

Allameh Tabataba'i University

University of Manitoba

Shiraz University

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Estimation of Lower Bounded Scale Parameter of Rescaled F-distribution under Entropy Loss Function

Journal of Statistical Research of Iran (2010)

Nader Nematollahi M. Naser Esfahani

We consider the problem of estimating the scale parameter &beta of a rescaled F-distribution when &beta has a lower bounded constraint of the form &beta&gea, under the entropy loss function. An admissible minimax estimator of the scale parameter &beta, which is the pointwise limit of a sequence of Bayes estimators, is given. Also in the class of truncated linear estimators, the admissible estimators and the only minimax estimator of &beta are obtained.

Scale parameter

Pointwise

Invariant estimator

Beta distribution

10.18869/acadpub.jsri.7.1.73

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Covariance and Pseudo-Covariance of Complex Uncertain Variables

Journal of Intelligent & Fuzzy Systems (2019)

Rong Gao Hamed Ahmadzade M. Naser Esfahani

Covariance is a measure to characterize the joint variability of two complex uncertain variables. Since, calculating covariance is not easy based on uncertain measure, we present two formulas for covariance and pseudo covariance of complex uncertain variables. For calculating the covariance of comp lex uncertain variables, some theorems are proved and several formulas are provided by using the inverse uncertainty distribution. The main results are explained by using several examples.

Matérn covariance function

Covariance mapping

Covariance and correlation

10.3233/jifs-181233

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Citations (6)