96 citations · 374 across the 25 of their papers we have counts for
5 papers · 1 filter
nn2poly: An R Package for Converting Neural Networks into Interpretable Polynomials
Pablo Morala, Jenny Alexandra Cifuentes, Rosa E. Lillo +1
The nn2poly package provides the implementation in R of the NN2Poly method to explain and interpret feed-forward neural networks by means of polynomial representations that predict…
Comparing Lasso and Adaptive Lasso in High-Dimensional Data: A Genetic Survival Analysis in Triple-Negative Breast Cancer
Pilar González-Barquero, Rosa E. Lillo, Álvaro Méndez-Civieta
In high-dimensional survival analysis, effective variable selection is crucial for both model interpretation and predictive performance. This paper investigates Cox regression with…
Analysis of an aggregate loss model in a Markov renewal regime
Pepa Ramírez-Cobo, Emilio Carrizosa, Rosa Elvira Lillo
In this article we consider an aggregate loss model with dependent losses. The losses occurrence process is governed by a two-state Markovian arrival process (MAP2), a Markov renew…
A bivariate two-state Markov modulated Poisson process for failure modelling
Yoel G. Yera, Rosa E. Lillo, Bo F. Nielsen +2
Motivated by a real failure dataset in a two-dimensional context, this paper presents an extension of the Markov modulated Poisson process (MMPP) to two dimensions. The one-dimensi…
Fitting procedure for the two-state Batch Markov modulated Poisson process
Yoel G. Yera, Rosa E. Lillo, Pepa Ramírez-Cobo
The Batch Markov Modulated Poisson Process (BMMPP) is a subclass of the versatile Batch Markovian Arrival process (BMAP) which has been proposed for the modeling of dependent event…