ADBD - Anàlisi de Dades Complexes per a les Decisions Empresarials
El grup fa recerca i transferència de coneixement en tres àmbits:
a) Estadística industrial, amb aplicacions per millorar la qualitat i la productivitat dels processos industrials, la logística industrial, la predicció, la gestió i millora de la qualitat (Six Sigma) i el disseny emocional dels productes (Kansei Engineering).
b) L'ús de l'anàlisi en entorns empresarials i industrials. Estem treballant en la caracterització dels clients i el “churn” (detecció precoç de l'abandonament) i la fiabilitat i el manteniment preventiu de màquines remotes.
c) L'anàlisi de dades complexes, d'aplicacions espacials i / o temporals discretes i sovint dependents dels mètodes no paramètrics bayesians i d'enginyeria i anàlisi de resultats electorals, demografia, ecologia i anàlisi estadística del estil literari.
d) Millors formes d'ensenyar estadística als estudiants universitaris i també als professionals de l'empresa i la indústria.
El grupo realiza investigación y transferencia de conocimiento en tres ámbitos:
a) Estadística industrial, con aplicaciones para mejorar la calidad y la productividad de los procesos industriales, la logística industrial, la predicción, la gestión y mejora de la calidad (Six Sigma) y el diseño emocional de los productos (Kansei Engineering).
b) El uso del análisis en entornos empresariales e industriales. Estamos trabajando en la caracterización de los clientes y Churn (detección precoz del abandono) y la fiabilidad y el mantenimiento preventivo de máquinas remotas.
c) El análisis de datos complejos, de aplicaciones espaciales y / o temporales discretas ya menudo dependientes de los métodos no paramétricos bayesianos y de ingeniería y análisis de resultados electorales, demografía, ecología y análisis estadístico del estilo literario.
d) Mejores formas de enseñar estadística a los estudiantes universitarios y también a los profesionales de la empresa y la industria.
The group does research and knowledge transfer in three areas:
a) Industrial Statistics, with applications to improve the quality and productivity of industrial processes, industrial logistics, forecasting, quality management and improvement (Six Sigma) and the emotional design of products (Kansei Engineering).
b) The use of analytics in business and industrial environments. We are working on customer characterization and Churn (early detection of abandonment) and reliability and preventive maintenance of remote machines.
c) The analysis of complex data, discrete and often dependent spatial and / or temporal applications of Bayesian nonparametric methods and engineering and analysis of election results, demographics, ecology, and the statistical analysis of literary style.
d) Better ways to teach statistics to university students and also to business and industry professionals.
The group does research and knowledge transfer in three areas:
a) Industrial Statistics, with applications to improve the quality and productivity of industrial processes, industrial logistics, forecasting, quality management and improvement (Six Sigma) and the emotional design of products (Kansei Engineering).
b) The use of analytics in business and industrial environments. We are working on customer characterization and Churn (early detection of abandonment) and reliability and preventive maintenance of remote machines.
c) The analysis of complex data, discrete and often dependent spatial and / or temporal applications of Bayesian nonparametric methods and engineering and analysis of election results, demographics, ecology, and the statistical analysis of literary style.
d) Better ways to teach statistics to university students and also to business and industry professionals.
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Articles de revista [139]
Recent Submissions
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Disease mapping with individual level information; a case study of acute myocardial infarction mortality
(Elsevier, 2025-04-28)
Article
Open AccessWhen mapping relative mortality risk under specific causes of death in time, one can use small areas and single year mortality data to explore the space time variation in detail. To reduce the variability of the initial ... -
On the relationship between Uhlig extended and beta-Bartlett processes
(2022-01)
Article
Open AccessStochastic volatility processes are used in multivariate time-series analysis to track time-varying patterns in covariance matrices. Uhlig extended and beta-Bartlett processes are especially convenient for analyzing ... -
Differentially private methods for compositional data
(2024-11-25)
Article
Restricted access - publisher's policyConfidential data, such as electronic health records, activity data from wearable devices, and geolocation data, are becoming increasingly prevalent. Differential privacy provides a framework to conduct statistical analyses ... -
Remembering George EP box in quality quandaries: great ideas, practical advice, clearly presented
(2023-07-03)
Article
Open Access -
Exploring the relationship between gaze patterns and image preference using eye-tracking technology
(College of Design, National Taichung University of Science and Technology, 2024)
Conference report
Open AccessThe idea of using physiological measurements for Kansei Engineering is attractive as it offers a non-subjective way to capture the perceptions of users, in contrast with the more common self-reporting tools. Eye-tracking ... -
Differentially private methods for managing model uncertainty in linear regression models
(2025-03-01)
Article
Open AccessIn this article, we propose differentially private methods for hypothesis testing, model averaging, and model selection for normal linear models. We propose Bayesian methods based on mixtures of g-priors and non-Bayesian ... -
Differentially private hypothesis testing with the subsampled and aggregated randomized response mechanism
(2025)
Article
Open AccessRandomized response is one of the oldest and most well-known methods used to analyze confidential data. However, its utility for differentially private hypothesis testing is limited because it cannot simulaneously achieve ... -
Bayesian bootstraps for massive data
(2020-06-01)
Article
Open AccessIn this article, we present data-subsetting algorithms that allow for the approximate and scalable implementation of the Bayesian bootstrap. They are analogous to two existing algorithms in the frequentist literature: the ... -
Properties of the generalized inverse Gaussian with applications to Monte Carlo simulation and distribution function evaluation
(2025-05)
Article
Restricted access - publisher's policyWe introduce two mixture representations for the generalized inverse Gaussian (GIG) distribution. One mixture representation expresses the GIG as a continuous mixture of inverse Gaussians. The other reveals a relationship ... -
Learning undergraduate Engineering Fluid Mechanics course assisted by journal articles and research argumentation
(Tempus Publications, 2025-02-01)
Article
Restricted access - publisher's policyA new approach in engineering education encourages students to engage with scientific discovery by reading research articles rather than relying solely on textbooks. Although frequently overlooked in undergraduate programs, ... -
Selection of network parameters in direct ANN modeling of roughness obtained in FFF processes
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-01-06)
Article
Open AccessArtificial neural network (ANN) models have been used in the past to model surface roughness in manufacturing processes. Specifically, different parameters influence surface roughness in fused filament fabrication (FFF) ... -
Baleen stable isotopes reveal climate-driven behavioural shifts in North Atlantic fin whales
(Elsevier, 2024-12-10)
Article
Open AccessClimate variability impacts the structure and functioning of marine ecosystems and can trigger behavioural responses in organisms. We investigated whether such variability modulates diet and migration in the North Atlantic ...