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Under Different Priors &Two Loss Functions To Compare Bayes Estimators With Some of Classical Estimators For the Parameter of Exponential Distribution
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المستخلص:

          في هذا البحث , استعملنا طرائق مختلفة لتقدير معلمة القياس للتوزيع الاسي كمقدر الإمكان الأعظم ومقدر العزوم ومقدر بيز في ستة أنواع مختلفة عندما يكون التوزيع الأولي لمعلمة القياس : توزيع لافي  (Levy) وتوزيع كامبل من النوع الثاني وتوزيع معكوس مربع كاي وتوزيع معكوس كاما وتوزيع غير الملائم (Improper) وتوزيع Non-informative. وفقا لدالتي الخسارة هي : دالة الخسارة التربيعية و دالة الخسارة التربيعية الموزونة. استعمل أسلوب المحاكاة في مقارنة اداء كل مقدر, بافتراض عدة حالات لمعلمة التوزيع الاسي استعملت لتوليد البيانات ولأحجام مختلفة من العينات ( صغيرة , متوسطة , كبيرة). وقد أظهرت نتائج المحاكاة بان طريقة بيز الأفضل وفقا لمقياس اقل قيمة متوسط مربع الأخطاء (MSE) , متوسط مربع الأخطاء الموزونة (MWSE) مقارنة بطريقتي الإمكان الأعظم (MLE)  وطريقة العزوم (ME) . وفقا للنتائج المستحصلة , نرى بانه عندما يكون التوزيع الاولي لـ توزيع معكوس كاما عند قيم معينة لمعلمتي التوزيع الاولي , أعطى نتائج أفضل وفقا لاقل قيمة لـ MSE ولـ MWSE مقارنة بنفس القيم المستحصلة بطريقتي MLE و ME,عندما تكون القيمة الحقيقة المفترضة لـ ولكل حجوم العينات (n). وعندما يكون التوزيع الاولي لـ هو غير الملائم  (Improper) عند قيم معينة لمعلمتي التوزيع الاولي, اعطى نتائج أفضل وفقا لاقل قيمة لـ MSE  ولـ MWSE مقارنة بنفس القيم المستحصلة بطريقتي MLE و ME, للقيم الحقيقة المفترضة لـ ولكل حجوم العينات (n) .

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimators for the Parameter of the Inverted Exponential Distribution Under different Double informative priors
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In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Bayes Estimators of Reliability in the Exponential Distribution
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Abstract

           We produced a study in Estimation for Reliability of the Exponential distribution based on the Bayesian approach. These estimates are derived using Bayesian approaches. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .we derived bayes estimators of reliability under four types when the prior distribution for the scale parameter of the Exponential distribution is: Inverse Chi-squar

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayes Estimators With others , for scale parameter and Reliability function of two parameters Frechet distribution
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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
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

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Bayes Estimators for the parameter of Rayleigh Distribution with Simulation
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   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Comparing Weibull Stress – Strength Reliability Bayesian Estimators for Singly Type II Censored Data under Different loss Functions
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     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Estimator for the Scale Parameter of the Normal Distribution Under Different Prior Distributions
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In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Analysis for the Scale Parameter of Gompertz Distribution
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In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Different Estimators for the shape Parameter and the Reliability function of Kumaraswamy Distribution
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In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Bayesian Estimation for The Shape Parameter of The Power Function Distribution (PFD-I) to Use Hyper Prior Functions
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The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

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