Likelihood Approach for Bayesian Logistic Weighted Model

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Efficient Bayesian Optimal Design for Logistic Model

Consider a Bayesian optimal design with many support points which poses the problem of collecting data with a few number of observations at each design point. Under such a scenario the asymptotic property of using Fisher information matrix for approximating the covariance matrix of posterior ML estimators might be doubtful. We suggest to use Bhattcharyya matrix in deriving the information matri...

متن کامل

Maximum Weighted Likelihood Estimator in Logistic Regression

The least weighted squares estimator is a well known technique in robust regression. Its likelihood analogy in logistic regression is the maximum weighted likelihood estimator, proposed in Vandev and Neykov (1998) and Mueller and Neykov (2003). This article mentions already proved properties, shows its inconsistency and compare it to the other estimators by an extensive simulation. Introduction...

متن کامل

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...

متن کامل

Approximating Bayesian inference by weighted likelihood

The author proposes to use weighted likelihood to approximate Bayesian inference when no external or prior information is available. He proposes a weighted likelihood estimator that minimizes the empirical Bayes risk under relative entropy loss. He discusses connections among the weighted likelihood, empirical Bayes and James–Stein estimators. Both simulated and real data sets are used for illu...

متن کامل

Bayesian Logistic Regression Model Choice via Laplace-Metropolis Algorithm

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Cihan University-Erbil Scientific Journal

سال: 2020

ISSN: 2707-6377,2519-6979

DOI: 10.24086/cuesj.v4n2y2020.pp9-12