Estimation of Dirichlet distribution parameters with bias-reducing adjusted score functions

03/03/2021
by   Vincenzo Gioia, et al.
0

The Dirichlet distribution, also known as multivariate beta, is the most used to analyse frequencies or proportions data. Maximum likelihood is widespread for estimation of Dirichlet's parameters. However, for small sample sizes, the maximum likelihood estimator may shows a significant bias. In this paper, Dirchlet's parameters estimation is obtained through modified score functions aiming at mean and median bias reduction of the maximum likelihood estimator, respectively. A simulation study and an application compare the adjusted score approaches with maximum likelihood.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/29/2022

Maximum likelihood estimation of the Weibull distribution with reduced bias

In this short note we derive a new bias-adjusted maximum likelihood esti...
research
06/12/2020

Fast Maximum Likelihood Estimation and Supervised Classification for the Beta-Liouville Multinomial

The multinomial and related distributions have long been used to model c...
research
05/06/2019

Maximum likelihood (ML) estimators for scaled mutation parameters with a strand symmetric mutation model in equilibrium

With the multiallelic parent-independent mutation-drift model, the equil...
research
04/18/2020

Efficient implementation of median bias reduction

In numerous regular statistical models, median bias reduction (Kenne Pag...
research
11/05/2020

Accurate inference in negative binomial regression

Negative binomial regression is commonly employed to analyze overdispers...
research
02/14/2020

Upper and Lower Class Functions for Maximum Likelihood Estimator for Single server Queues

Upper and lower class functions for the maximum likelihood estimator of ...
research
05/15/2018

On the Estimation of Parameters from Time Traces originating from an Ornstein-Uhlenbeck Process

In this article, we develop a Bayesian approach to estimate parameters f...

Please sign up or login with your details

Forgot password? Click here to reset