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Proposed Entropy Loss function and application to find Bayesian estimator for Exponential distribution parameter
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The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (Mbias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial values for the parameters  and initial value b, to get to estimator balanced add between two loss function ,moreover, the optimal sample size determination under proposed entropy loss function.

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of the parameter of the Pareto distribution manual Using the general mediator estimator
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Estimation of the tail index parameter of a one - parameter Pareto model has wide important by the researchers because it has awide application in the econometrics science and reliability theorem.

Here we introduce anew estimator of "generalized median" type and compare it with the methods of Moments and Maximum likelihood by using the criteria, mean square error.

 The estimator of generalized median type performing best over all.

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
Bayesian Estimation for the Parameters and Reliability Function of Basic Gompertz Distribution under Squared Log Error Loss Function
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In this paper, some estimators for the unknown shape parameters and reliability function of Basic Gompertz distribution were obtained, such as Maximum likelihood estimator and some Bayesian estimators under Squared log error loss function by using Gamma and Jefferys priors. Monte-Carlo simulation was conducted to compare the performance of all estimates of the shape parameter and Reliability function, based on mean squared errors (MSE) and integrated mean squared errors (IMSE's), respectively. Finally, the discussion is provided to illustrate the results that are summarized in tables.

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Publication Date
Sun Jun 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Notes on Exponential Distribution
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المتغير العشوائي X  له توزيع أسي اذا كان له دالة احتمالية الكثافة بالشكل:

عندما  ، هذه هي الحالة الخاصة لتوزيع كاما.

غالباً جداً ولسبب معقول تأخذ . الحالة الخاصة لـ (1) التي نحصل عليها تسمى بالتوزيع الاسي لمعلمة واحدة.

اذا كانت  ، ، التوزيع في هذه الحالة يسمى التوزيع الاسي القياسي

اما بالنسب

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Publication Date
Thu Aug 25 2016
Journal Name
International Journal Of Mathematics Trends And Technology
Pretest Single Stage Shrinkage Estimator for the Shape Parameter of the Power Function Distribution
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
new Estimator of the parameter of negative exponential
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the main of this paper is to give a comprehensive presentation of estimating methods namely maximum likelihood bayes and proposed methods for the parameter

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between Bayesian Method and Full Maximum Likelihood to estimate Poisson regression model hierarchy and its application to the maternal deaths in Baghdad
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Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The use of the genetic algorithm to estimate the parameters function of the hypoexponential distribution by simulation
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In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimators of the parameter and Reliability Function of Inverse Rayleigh Distribution" A comparison study "
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     In this paper, Bayesian estimator for the parameter and reliability function of inverse Rayleigh distribution (IRD) were obtained Under three types of loss function, namely, square error loss function (SELF), Modified Square error loss function (MSELF) and Precautionary loss function (PLF),taking into consideration the  informative and non- informative  prior. The performance of such estimators was assessed on the basis of mean square error (MSE) criterion by performing a Monte Carlo simulation technique.

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between some well- Known methods to estimate the parameter of the proposed method of measurement and the reliability of the distribution function with two parameters Rally by simulation
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Abstract

            Rayleigh distribution is one of the important distributions used for analysis life time data, and has applications in reliability study and physical interpretations. This paper introduces four different methods to estimate the scale parameter, and also estimate reliability function; these methods are Maximum Likelihood, and Bayes and Modified Bayes, and Minimax estimator under squared error loss function, for the scale and reliability function of the generalized Rayleigh distribution are obtained. The comparison is done through simulation procedure, t

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Bayesian Inference for Reliability Function of Gompertz Distribution
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Abstract<p>In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based o</p> ... Show More
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