برآورد پارامتری بیز تجربی شدت ترافیک در سیستم صف m∕m∕1

در این مقاله، برآورد بیزی و بیز تجربی پارامتر شدت ترافیک در مدل صف  تحت توابع زیان متقارن و نامتقارن و بر اساس دو پیشین مختلف ناآگاهی بخش و بتا موردبررسی قرار می‌گیرد. برآورد پارامترهای این مدل بهروش‌های بیزی، درستنمایی ماکسیمم، گشتاوری ارائه می‌شود. خواص و کاربردهای این دو برآوردگر در نتایج عددی موردبحث قرارگرفته است.

Parametric Estimation of Empirical Bayes of Traffic Intensity in M/M/1 Queue System

Armero and Bayarri get Bayesian estimation from traffic intensity in M/M/1 model in 1994. Sharma and Kumar get Bayesian and classical estimations of different parameters of M/M/1 model under loss function in 1999. Furthermore, use of classical methods to estimate unknown parameters of previous distribution is suggested by Mises for the first time in 1943. In this paper, Bayesian estimation and empirical Bayes of traffic intensity parameter are assessed in the M/M/1 queuing model. Estimation of the parameters of this model is presented by methods of Bayes, likelihood, and moment. The characteristics and applications of both estimators are discussed in numerical results. The quadratic theory has many uses in communication theory, computer design, etc. The statistical deduction in quadratic process and quadrant process estimation, such as rate of entry, service rates and traffic jams, has attracted researchers in the past few years. Suppose that the M / M / 1 queue system with an average log rate λ, as well as an average service rate of 1 / μ