The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), ...

Although the Poisson-exponential regression model under the last activation scheme was firstly suggested by the TTT plot graphical procedure presented above, for sake of comparison we fitted the ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease (COPD). However, patients would benefit from better identification of ...

Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of ...

This study unraveled attack and defense patterns that may help predict match results for the 2022 Brazilian Championship Series A, using data-driven models considering 10 variations of the Poisson ...

Training a Poisson regression model is the process of finding the values of the intercept/constant and the coefficients so that predicted y count values (before rounding) closely match the known, ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Tzougas, G. and di Cerchiara, A.P. (2021) Bivariate Mixed Poisson Regression Models with Varying Dispersion. North American Actuarial Journal, 27, 211-241.

This project aims to develop a Poisson regression model to predict the number of rings in a dataset. Poisson regression is a type of generalized linear model used for modeling count data, where the ...