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Multivariate Bayesian spatio-temporal P-spline models to analyze crimes against women
(Oxford University Press, 2021)
Artículo / Artikulua,
Univariate spatio-temporal models for areal count data have received great attention in recent years for estimating risks. However, models for studying multivariate responses are less commonly used mainly due to the ...
Flexible Bayesian P-splines for smoothing age-specific spatio-temporal mortality patterns
(SAGE, 2019)
Artículo / Artikulua,
In this paper age-space-time models based on one and two-dimensional P-splines with
B-spline bases are proposed for smoothing mortality rates, where both xed relative scale
and scale invariant two-dimensional penalties ...
Detecting change-points in the time series of surfaces occupied by pre-defined NDVI categories in continental Spain from 1981 to 2015
(Springer, 2018)
Capítulo de libro / Liburuen kapitulua,
The free access to satellite images since more than 40 years ago
has provoked a rapid increase of multitemporal derived information of remote
sensing data that should be summarized and analyzed for future inferences. ...
A unique cardiac electrocardiographic 3D model. Toward interpretable AI diagnosis
(Elsevier, 2022)
Artículo / Artikulua,
Mathematical models of cardiac electrical activity are one of the most important tools for elucidating information about heart diagnostics. In this paper, we present an efficient mathematical formulation for this modeling ...
Steering the synthesis of Fe3O4 nanoparticles under sonication by using a fractional factorial design
(Elsevier, 2021)
info:eu-repo/semantics/article,
Superparamagnetic iron oxide nanoparticles (MNPs) have the potential to act as heat sources in magnetic hyperthermia. The key parameter for this application is the specific absorption rate (SAR), which must be as large as ...
High-dimensional order-free multivariate spatial disease mapping
(Springer, 2023)
Artículo / Artikulua,
Despite the amount of research on disease mapping in recent years, the use of multivariate models for areal spatial data remains
limited due to difficulties in implementation and computational burden. These problems are ...
Scalable Bayesian modeling for smoothing disease mapping risks in large spatial data sets using INLA
(Elsevier, 2021)
Artículo / Artikulua,
Several methods have been proposed in the spatial statistics literature to analyse big data sets in continuous domains. However, new methods for analysing high-dimensional areal data are still scarce. Here, we propose a ...
Machine learning procedures for daily interpolation of rainfall in Navarre (Spain)
(Springer, 2023)
Capítulo de libro / Liburuen kapitulua,
Kriging is by far the most well known and widely used statistical method
for interpolating data in spatial random fields. The main reason is that it provides
the best linear unbiased predictor and it is an exact interpolator ...
Cytokinins are involved in drought tolerance of Pinus radiata plants originating from embryonal masses induced at high temperatures
(Oxford University Press, 2021)
info:eu-repo/semantics/article,
Vegetative propagation through somatic embryogenesis is an effective method to produce elite varieties and can be applied as a tool to study the response of plants to different stresses. Several studies show that environmental ...
Body composition and resting energy expenditure in a group of children with achondroplasia
(Elsevier, 2024)
Artículo / Artikulua,
Background: Persons with achondroplasia develop early obesity, which is a comorbidity associated with other complications. Currently, there are no validated specific predictive equations to estimate resting energy expenditure ...