collaborators

5 papers

stat.ML2024

Statistical tuning of artificial neural network

Mohamad Yamen AL Mohamad, Hossein Bevrani, Ali Akbar Haydari

Neural networks are often regarded as "black boxes" due to their complex functions and numerous parameters, which poses significant challenges for interpretability. This study addr…

stat.CO2024

Bayesian Bell regression model for fitting of overdispersed count data with application

Ameer Musa Imran Alhseeni, Hossein Bevrani

The Bell regression model (BRM) is a statistical model that is often used in the analysis of count data that exhibits overdispersion. In this study, we propose a Bayesian analysis…

stat.CO2024

Shrinkage estimators in zero-inflated Bell regression model with application

Solmaz Seifollahi, Hossein Bevrani, Zakariya Yahya Algamal

We propose Stein-type estimators for zero-inflated Bell regression models by incorporating information on model parameters. These estimators combine the advantages of unrestricted…

stat.AP2024

Comparative analysis of two new wind speed T-X models using Weibull and log-logistic distributions for wind energy potential estimation in Tabriz, Iran

Meysam Mohammadpour, Hossein Bevrani

To assess the potential of wind energy in a specific area, statistical distribution functions are commonly used to characterize wind speed distributions. The selection of an approp…

stat.ME2024

Bayesian Analysis of the Beta Regression Model Subject to Linear Inequality Restrictions with Application

Solmaz Seifollahi, Hossein Bevrani, Kristofer Mansson

ReRecent studies in machine learning are based on models in which parameters or state variables are bounded restricted. These restrictions are from prior information to ensure the…