Jorge Mateu
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View article: A self-exciting spatio-temporal model with a smooth space-time-varying productivity parameter
A self-exciting spatio-temporal model with a smooth space-time-varying productivity parameter Open
The self-exciting spatio-temporal point process model is a fundamental tool for studying recurrent events in fields such as economics, criminology, and seismology. Existing models often assume that the productivity parameter, which measure…
View article: Spatial Downscaling of Multivariate Disease Risk
Spatial Downscaling of Multivariate Disease Risk Open
Downscaling areal health data to a finer resolution is important for understanding the intricate spatial patterns of disease. It helps to identify shared risk factors and to develop targeted public health interventions. This paper introduc…
View article: Spatio-temporal intensity estimation for inhomogeneous Poisson point processes on linear networks: A roughness penalty method
Spatio-temporal intensity estimation for inhomogeneous Poisson point processes on linear networks: A roughness penalty method Open
View article: A nonparametric test of independence between the second-order structure of point patterns and covariates
A nonparametric test of independence between the second-order structure of point patterns and covariates Open
We introduce a novel nonparametric method for testing the hypothesis of independence between a marked point process with functional marks and a covariate. In a special case, when the functional marks are constructed using the local indicat…
View article: A concordance coefficient for lattice data: An application to poverty indices in Chile
A concordance coefficient for lattice data: An application to poverty indices in Chile Open
This paper introduces a novel coefficient for measuring agreement between two lattice sequences observed in the same areal units, motivated by the analysis of different methodologies for measuring poverty rates in Chile. Building on the mu…
View article: A poisson cokriging modeling of mosquito-borne diseases in Colombia
A poisson cokriging modeling of mosquito-borne diseases in Colombia Open
Mosquito-borne diseases pose a significant public health concern in Colombia, necessitating robust quantification of their geographic patterns to guide and optimize interventions. This study explores the spatial dynamics and interactions a…
View article: A Spatio-Temporal Dirichlet Process Mixture Model on Linear Networks for Crime Data
A Spatio-Temporal Dirichlet Process Mixture Model on Linear Networks for Crime Data Open
Analyzing crime events is crucial to understand crime dynamics and it is largely helpful for constructing prevention policies. Point processes specified on linear networks can provide a more accurate description of crime incidents by consi…
View article: Probabilistic Deep Learning for Highly Multivariate Spatio-Temporal Log-Gaussian Cox Processes
Probabilistic Deep Learning for Highly Multivariate Spatio-Temporal Log-Gaussian Cox Processes Open
Multivariate spatio-temporal point patterns have become increasingly common due to the advancement of technology for massive data collection. Parameter estimation is vital for understanding the distributional patterns within such data. How…
View article: Function‐Valued Marked Spatial Point Processes on Linear Networks: Application to Urban Cycling Profiles
Function‐Valued Marked Spatial Point Processes on Linear Networks: Application to Urban Cycling Profiles Open
In the literature on spatial point processes, there is an emerging challenge in studying marked point processes with points being labelled by functions. In this paper, we focus on point processes living on linear networks and, from distinc…
View article: Spatio-Temporal Hawkes Point Processes: A Review
Spatio-Temporal Hawkes Point Processes: A Review Open
Hawkes processes are a particularly interesting class of stochastic point processes that were introduced in the early seventies by Alan Hawkes, notably to model the occurrence of seismic events. They are also called self-exciting point pro…
View article: Spatio-Temporal-Network Point Processes for Modeling Crime Events with Landmarks
Spatio-Temporal-Network Point Processes for Modeling Crime Events with Landmarks Open
Self-exciting point processes are widely used to model the contagious effects of crime events living within continuous geographic space, using their occurrence time and locations. However, in urban environments, most events are naturally c…
View article: A point process approach for the classification of noisy calcium imaging data
A point process approach for the classification of noisy calcium imaging data Open
We study noisy calcium imaging data, with a focus on the classification of spike traces. As raw traces obscure the true temporal structure of neuron's activity, we performed a tuned filtering of the calcium concentration using two methods:…
View article: Estimating velocities of infectious disease spread through spatio-temporal log-Gaussian Cox point processes
Estimating velocities of infectious disease spread through spatio-temporal log-Gaussian Cox point processes Open
Understanding the spread of infectious diseases such as COVID-19 is crucial for informed decision-making and resource allocation. A critical component of disease behavior is the velocity with which disease spreads, defined as the rate of c…
View article: Multivariate Poisson cokriging: A geostatistical model for health count data
Multivariate Poisson cokriging: A geostatistical model for health count data Open
Multivariate disease mapping is important for public health research, as it provides insights into spatial patterns of health outcomes. Geostatistical methods that are widely used for mapping spatially correlated health data encounter chal…
View article: Summary characteristics for multivariate function‐valued spatial point process attributes
Summary characteristics for multivariate function‐valued spatial point process attributes Open
Summary Prompted by modern technologies in data acquisition, the statistical analysis of spatially distributed function‐valued quantities has attracted a lot of attention in recent years. In particular, combinations of functional variables…
View article: Function-valued marked spatial point processes on linear networks: application to urban cycling profiles
Function-valued marked spatial point processes on linear networks: application to urban cycling profiles Open
In the literature on spatial point processes, there is an emerging challenge in studying marked point processes with points being labelled by functions. In this paper, we focus on point processes living on linear networks and, from distinc…
View article: SpatFD: Functional Geostatistics: Univariate and Multivariate Functional Spatial Prediction
SpatFD: Functional Geostatistics: Univariate and Multivariate Functional Spatial Prediction Open
Depends R (>= 3.6.0)Description Performance of functional kriging, cokriging, optimal sampling and simulation for spatial prediction of functional data.The framework of spatial prediction, optimal sampling and simulation are extended from …
View article: Climate model selection via conformal clustering of spatial functional data
Climate model selection via conformal clustering of spatial functional data Open
Climate model selection stands as a critical process in climate science and research. It involves choosing the most appropriate climate models to address specific research questions, simulating climate behaviour, or making projections abou…
View article: ANOVA for Metric Spaces, with Applications to Spatial Data
ANOVA for Metric Spaces, with Applications to Spatial Data Open
We give a review of some recent ANOVA-like procedures for testing group differences based on data in a metric space and present a new such
\nprocedure. Our statistic is derived from the classic Levene’s test for detecting differences in di…
View article: Semi-parametric profile pseudolikelihood via local summary statistics for spatial point pattern intensity estimation
Semi-parametric profile pseudolikelihood via local summary statistics for spatial point pattern intensity estimation Open
Second-order statistics play a crucial role in analysing point processes. Previous research has specifically explored locally weighted second-order statistics for point processes, offering diagnostic tests in various spatial domains. Howev…
View article: Generalized functional additive mixed models with (functional) compositional covariates for areal Covid-19 incidence curves
Generalized functional additive mixed models with (functional) compositional covariates for areal Covid-19 incidence curves Open
We extend the generalized functional additive mixed model to include compositional and functional compositional (density) covariates carrying relative information of a whole. Relying on the isometric isomorphism of the Bayes Hilbert space …
View article: PENDAMPINGAN DAN PENINGKATAN KUALITAS ANALISIS DATA DALAM PUBLIKASI ILMIAH BAGI CIVITAS AKADEMIK STIKES MAJAPAHIT MOJOKERTO
PENDAMPINGAN DAN PENINGKATAN KUALITAS ANALISIS DATA DALAM PUBLIKASI ILMIAH BAGI CIVITAS AKADEMIK STIKES MAJAPAHIT MOJOKERTO Open
Efforts to assist and improve the quality of data analysis in scientific publications for the academic community of Stikes Majapahit Mojokerto are held as an effort to increase the achievement of scientific publications in reputable public…
View article: A nonseparable first-order spatiotemporal intensity for events on linear networks: An application to ambulance interventions
A nonseparable first-order spatiotemporal intensity for events on linear networks: An application to ambulance interventions Open
The algorithms used for the optimal management of an ambulance fleet require an accurate description of the spatiotemporal evolution of the emergency events. In the last years, several authors have proposed sophisticated statistical approa…
View article: A dynamical mathematical model for crime evolution based on a compartmental system with interactions
A dynamical mathematical model for crime evolution based on a compartmental system with interactions Open
We use data on imprisonment in Spain to fit a system of three ordinary differential equations that describes the temporal evolution of three different groups in the country: offenders that are not in prison, offenders that are in prison, a…
View article: A brief review and guidance on the spatiotemporal sampling designs for disease vector surveillance
A brief review and guidance on the spatiotemporal sampling designs for disease vector surveillance Open
Obtaining a representative sample of disease vectors (mosquitoes, flies, ticks, etc.) is essential for researchers to draw meaningful conclusions about the entire vector population in a target study area and during a specific study period.…
View article: Jorge Mateu's contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’
Jorge Mateu's contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’ Open
View article: A Poisson Cokriging Modeling of Co-circulation of Mosquito-borne Diseases in Colombia
A Poisson Cokriging Modeling of Co-circulation of Mosquito-borne Diseases in Colombia Open
Co-circulation of diseases is a public health concern phenomenon as it often informs of population cross-exposure, susceptibility, and cross-protection dynamics. While it commonly occurs, spatial analysis predominately focuses on understan…
View article: Variable selection for inhomogeneous spatio-temporal Poisson point processes
Variable selection for inhomogeneous spatio-temporal Poisson point processes Open
Spatio-temporal point pattern data are becoming prevalent in many scientific disciplines. We model the first-order intensity of spatio-temporal point pattern data, considering the intensity as a parametric log-linear function of spatial, t…
View article: A Poisson cokriging method for bivariate count data
A Poisson cokriging method for bivariate count data Open
View article: Jorge Mateu’s contribution to the Discussion of ‘Flexible marked spatio-temporal point processes with applications to event sequences from association football’ by Narayanan, Kosmidis, and Dellaportas
Jorge Mateu’s contribution to the Discussion of ‘Flexible marked spatio-temporal point processes with applications to event sequences from association football’ by Narayanan, Kosmidis, and Dellaportas Open