Work

A weighted error-minimizer parameter estimation technique for one-inflated positive Poisson distribution

Year: 2025

Type: article

Abstract: An error-minimizing estimator is always preferred in model fittings. However, each error-minimizing estimator minimizes error differently. This paper combines four error-minimizing estimators, which are root mean-squared error, mean absolute error, root mean-squared log error and mean absolute percentage error via a weighted approach. The estimation involves two levels. In the first-level estimation, the estimated parameters are obtained by minimizing error values differently and separately. In the second-level estimation, the resulting estimates from the first-level estimation are combined by either fixed and controlled weights or free and uncontrolled weights. A real crime dataset on the frequency of drunk drivers was considered for demonstration of the technique.

Source: Results in Control and Optimization

DOI: 10.1016/j.rico.2025.100569

Author: Razik Ridzuan Mohd Tajuddin

Institution: National University of Malaysia

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,470

Funder: Universiti Kebangsaan Malaysia