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Article
A Comparison Between the Bayesian and the Classical Estimators of Weibull Distribution

Authors: Fadhil abdulabaas --- Yahya Mahdi Al – Mayali --- Irtifaa AbulKadhum Neama
Journal: Journal of Kufa for Mathematics and Computer مجلة الكوفة للرياضيات والحاسوب ISSN: 11712076 Year: 2013 Volume: 1 Issue: 8 Pages: 21-28
Publisher: University of Kufa جامعة الكوفة

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Abstract

In this paper ,we study estimation of two parameters of Weibull distribution .Methods of estimation used are maximum likelihood estimator (MLE) and Bayes. We compared the numerical results by simulation in MATLAB program. The comparison show that the Bayes estimator gives the best results ( less error) .


Article
Parameter Estimation of Binomial distribution using T.O.M with Exponential Family

Author: Jubran Abdulameer K
Journal: Journal of Kufa for Mathematics and Computer مجلة الكوفة للرياضيات والحاسوب ISSN: 11712076 Year: 2014 Volume: 2 Issue: 1 Pages: 48-51
Publisher: University of Kufa جامعة الكوفة

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Abstract

In this research we will estimate the parameter of binomial distribution that has exponential family using T.O.M (Term Omission Method) and compare it with (MLE) method using MSE (Mean Square Error) with simulation.


Article
Estimate survival function for censored sample type two Bladder cancer
تقدير دالة البقاء لعينة مراقبة من النوع الثاني لمرضى سرطان المثانة

Author: Hind Jawad Kadhum Al-Bderi هند جواد كاظم
Journal: Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات ISSN: 20740204 / 25213504 Year: 2016 Volume: 8 Issue: 2 Pages: 62-70
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

This research cares to estimate the unlabeled parameters for generalized Rayleigh distribution model depend on censored samples type two ; Utilizing the maximum likelihood estimator method to get the derivation of the point estimation for all unlabeled parameters depend on iterative technique , as Newton – Raphson method , then to derive Lindley approximation estimator method . At last , checking whether this model ( GRD ) suits to a set of real data .

هذا البحث يهتم بتقدير المعلمات غير المعلومة لنموذج توزيع رالي المعمم لعينات منفردة تحت المراقبة من النوع الثاني . استخدمت طريقة تقدير الإمكان الأعظم لاشتقاق التقدير النقطي لجميع المعلمات غير المعلومة بالاعتماد على طرائق التكرار ومنها طريقة نيوتن – رافسون, ثم اشتقاق طريقة بيز المعتمدة على تقريب Lindely . وأخيراً تم اختبار مدى ملائمة النموذج الحالي (نموذج توزيع رالي المعمم ) لمجموعة بيانات حقيقية.


Article
Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function

Journal: Ibn Al-Haitham Journal For Pure And Applied Science مجلة ابن الهيثم للعلوم الصرفة والتطبيقية ISSN: 16094042/25213407 Year: 2019 Volume: 32 Issue: 1 Pages: 187-196
Publisher: Baghdad University جامعة بغداد

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Abstract

In the current study, the researchers have been obtained Bayes estimators for the shape andscale parameters of Gamma distribution under the precautionary loss function, assuming thepriors, represented by Gamma and Exponential priors for the shape and scale parametersrespectively. Moment, Maximum likelihood estimators and Lindley’s approximation have beenused effectively in Bayesian estimation.Based on Monte Carlo simulation method, those estimators are compared depending on themean squared errors (MSE’s). The results show that, the performance of Bayes estimator underprecautionary loss function with Gamma and Exponential priors is better than other estimates inall cases.


Article
Estimate the Two Parameters of Gamma Distribution Under Entropy Loss Function

Authors: Loaiy F. Naji --- Huda A. Rasheed
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2019 Volume: 60 Issue: 1 Pages: 127-134
Publisher: Baghdad University جامعة بغداد

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Abstract

AbstractIn this paper, Bayes estimators for the shape and scale parameters of Gammadistribution under the Entropy loss function have been obtained, assuming Gammaand Exponential priors for the shape and scale parameters respectively. Moment,Maximum likelihood estimators and Lindley’s approximation have been usedeffectively in Bayesian estimation. Based on Monte Carlo simulation method, thoseestimators are compared depending on the mean squared errors (MSE’s). The resultsshow that, the performance of the Bayes estimator under Entropy loss function isbetter than other estimates in all cases.


Article
Comparing Different Fuzzy Reliability Function of Exponential Maxwell

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Abstract

This paper deals with comparing different estimators of fuzzy Reliability function for new probability distribution called expontiated Maxwell the methods of estimations are maximum likelihood and L- Moments and proposed method One (probability weighted moments), The comparison is done by simulation as well as application on time to failure of machines , at Dura refinery Baghdad All results of comparison are explained in tables , and compared by statistical Measures Mean square error(MSE). The comparison is done using simulation procedure , and all the results are explained in tables.


Article
A comparison among methods for estimation of the parameter of the Maxwell- Boltzmann distribution using simulation

Author: Layla Matter Nassir ليلى مطر ناصر
Journal: Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات ISSN: 20740204 / 25213504 Year: 2014 Volume: 6 Issue: 2 Pages: 186-200
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

The Maxwell or Maxwell- Boltzmann distribution was invented to solve problems related to physics, chemistry and plays an important role in and other allied sciences. So in this paper Bayesian using special priorinformation for estimating the scale parameter of Maxwell distribution, the maximum likelihood estimation andthree different types of moments are presented for this. The simulation by matlab program is used to compare these estimators with respect to the Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE), the results of comparison showed that for all the varying sample size, the estimators of Bayes method with special prior distribution is followed by the Maximum likelihood estimatorhas smaller MSE and MAPE compared to others, and in all cases the statistical hypotheses had been satisfied for both methods the MSEand MAPE decrease as sample size increases.

يعتبر توزيع Maxwell or Maxwell- Boltzmann من التوزيعات المهمة التي وضعت لحل المشاكل العلمية ضمن علوم الفيزياء والكيمياء وكذلك يلعب دورا مهما ضمن علوم تطبيقية اخرى لذلك فقد تم في هذا البحث استخدام طريقة بيز اعتمادا على معلومات سابقة خاصة و طريقة الامكان الاعظم وكذلك طريقة العزوم بثلاث حالات وباستخدام المحاكاة اعتمادا على برنامج ماتلاب تم تقدير المعلمةله ضمن كل طريقة وتمت المقارنة بين النتائج اعتمادا علىMean Square Error (MSE) و Mean Absolute Percentage Error (MAPE)اظهرت النتائج ان افضل تقدير هو بيز وياتي بعده الامكان الاعظم ثم طريقة العزوم ولجميع حجوم العينة حيث حصلنا على اقل قيم للخطأ وتم استيفاء النظرية الاحصائية في هذه التقديرات حيث كان الخطأ يقل كلما ازداد حجم العينة


Article
Bayers estimator of reliability function and the maximum likelihood estimator for this function.
مقدر بيز لدالة المعولية لأنموذج باريتو للفشل من النوع الأول

Authors: ستار محمد صالح --- صباح هادي
Journal: journal of Economics And Administrative Sciences مجلة العلوم الاقتصادية والإدارية ISSN: 2227 703X / 2518 5764 Year: 2010 Volume: 16 Issue: 57 Pages: 145-150
Publisher: Baghdad University جامعة بغداد

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Abstract

In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).

يرجع توزيع باريتو الى عالم الاقتصاد (Vilfredo Pareto) حيث وضع اساس هذا التوزيع في علم الاقتصاد من خلال دراسة توزيع الدخول (Incomes). عندما تكون الدخول متجاوزة لحد معلوم موجب مثل K.ان معولية أنموذج باريتو للفشل تنشا كخليط من التوزيعات الاسية، وان هذا الخليط يمتلك دالة مخاطرة (Hazard Function) متناقصة مع الزمن وعلى هذا الاساس فان معولية أنموذج باريتو للفشل لها تطبيقات متنوعة عند دراسة معولية الانظمة المختلفة [3].


Article
On Shrinkage Estimation for R (s, k) in Case of Exponentiated Pareto Distribution

Journal: Ibn Al-Haitham Journal For Pure And Applied Science مجلة ابن الهيثم للعلوم الصرفة والتطبيقية ISSN: 16094042/25213407 Year: 2019 Volume: 32 Issue: 1 Pages: 147-156
Publisher: Baghdad University جامعة بغداد

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Abstract

This paper concerns with deriving and estimating the reliability of the multicomponentsystem in stress-strength model R(s,k), when the stress and strength are identicalindependent distribution (iid), follows two parameters Exponentiated Pareto Distribution(EPD) with the unknown shape and known scale parameters. Shrinkage estimationmethod including Maximum likelihood estimator (MLE), has been considered.Comparisons among the proposed estimators were made depending on simulation basedon mean squared error (MSE) criteria.


Article
مقارنة مقدرات بيز مع اخرين، لمعلمة القياس ودالة المعولية لتوزيع Frechet ذي المعلمتين
Comparing Bayes Estimators With others , for scale parameter and Reliability function of two parameters Frechet distribution

Author: ميسون حميد فرج
Journal: journal of Economics And Administrative Sciences مجلة العلوم الاقتصادية والإدارية ISSN: 2227 703X / 2518 5764 Year: 2016 Volume: 22 Issue: 88 Pages: 1-15
Publisher: Baghdad University جامعة بغداد

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Abstract

يهتم هذا البحث بمقارنة مقدر الإمكان الأعظم ومقدر Bayes مقترح بإفتراض دالة خسارة Entropy وكذلك مقدر Bayes مقترح آخر، لتقدير معلمة القياس، ومن ثم دالة المعولية. و بواسطة المحاكاة باعتبار

This Paper deals with comparing maximum likelihood estimator , and the second one is proposed Bayes estimator under General Entropy loss Function using Prior ,while the third estimator is also Bayes under quadratic loss Function and using proposed prior , After estimator ,we also estimate Reliability Function R and considering the shape parameter

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