6 citations · 11 across the 7 of their papers we have counts for
7 papers
Prior Smoothing for Multivariate Disease Mapping Models
Garazi Retegui, María Dolores Ugarte, Jaione Etxeberria +1
To date, we have seen the emergence of a large literature on multivariate disease mapping. That is, incidence of (or mortality from) multiple diseases is recorded at the scale of a…
Improving Disease Risk Estimation in Small Areas by Accounting for Spatiotemporal Local Discontinuities
G. Santafé, A. Adin, M. D. Ugarte
This work proposes a two-step method to enhance disease risk estimation in small areas by integrating spatiotemporal cluster detection within a Bayesian hierarchical spatiotemporal…
Suicide Mortality in Spain (2010-2022): Temporal Trends, Spatial Patterns, and Risk Factors
A. Adin, G. Retegui, A. Sánchez Villegas +1
Background: Suicide remains a major public health concern worldwide, responsible for more than 700,000 deaths in 2021, accounting for approximately 1.1\% of all global deaths. Whil…
Multivariate Spatio-temporal Modelling for Completing Cancer Registries and Forecasting Incidence
Garazi Retegui, Jaione Etxeberria, María Dolores Ugarte
Cancer data, particularly cancer incidence and mortality, are fundamental to understand the cancer burden, to set targets for cancer control and to evaluate the evolution of the im…
On the Age of Information in Single-Server Queues with Aged Updates
Fernando Miguelez, Urtzi Ayesta, Josu Doncel +1
The Age of Information (AoI) is a performance metric that quantifies the freshness of data in systems where timely updates are critical. Most state-of-the-art methods typically ass…
Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers
Garazi Retegui, Jaione Etxeberria, María Dolores Ugarte
Rare cancers affect millions of people worldwide each year. However, estimating incidence or mortality rates associated with rare cancers presents important difficulties and poses…
An Adaptive Learning Approach to Multivariate Time Forecasting in Industrial Processes
Fernando Miguelez, Josu Doncel, Maria Dolores Ugarte
Industrial processes generate a massive amount of monitoring data that can be exploited to uncover hidden time losses in the system. This can be used to enhance the accuracy of mai…