Hyperbolic Cosine Log-Logistic Distribution and Estimation of Its Parameters by Using Maximum Likelihood Bayesian and Bootstrap Methods

Bayesian and Iterative Maximum Likelihood Estimation of the Coefficients in Logistic Regression Analysis with Linked Data

This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...

Markov Logarithmic Series Distribution and Estimation of its Parameters by Method of E-Bayesian

In the analysis of Bernoulli's variables, an investigation of the their dependence is of the prime importance. In this paper, the distribution of the Markov logarithmic series is introduced by the execution of the first-order dependence among Bernoulli variables. In order to estimate the parameters of this distribution, maximum likelihood, moment, Bayesian and also a new method which called the...

comparative dna interaction studies of antiviral drug, zidovudine and its complex using different instrumental methods

هدف از این مطالعه بررسی امکان استفاده از داروهای شناخته شده در درمان سایر بیماریها به عنوان داروهای ضد سرطان است. همچنین با استفاده از این داروها در ساختمان کمپلکس فلز می توان شاخص های دارویی بدست آمده را بررسی نمود. داروی ضد ویروس ایدز(hiv)به نام زیدوودین(azt)انتخاب و.کمپلکس.محلول.در.آب[pt(azt)2]cl2سنتزو به روشهای مختلف فیزیکی و شیمیایی شناسایی گردید. بر هم کنش مقایسه ای این دارو و کمپلکس پلا...

Maximum Likelihood Estimation of Dirichlet Distribution Parameters

The Dirichlet distribution is one that has often been turned to in Bayesian statistical inference as a convenient prior distribution to place over proportional data. To properly motivate its study, we will begin with a simple coin toss example, where the task will be to find a suitable distribution P which summarizes our beliefs about the probability that the toss will result in heads, based on...

LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters

UNLABELLED We present a Markov chain Monte Carlo coalescent genealogy sampler, LAMARC 2.0, which estimates population genetic parameters from genetic data. LAMARC can co-estimate subpopulation Theta = 4N(e)mu, immigration rates, subpopulation exponential growth rates and overall recombination rate, or a user-specified subset of these parameters. It can perform either maximum-likelihood or Bayes...

Maximum Log Likelihood Estimation using EM Algorithm and Partition Maximum Log Likelihood Estimation for Mixtures of Generalized Lambda Distributions