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Mostrando ítems 11-17 de 17
A Bi-Objective Scheduling Problem in a Home Care Business
(MDPI, 2021)
[Abstract] In this work we study a routing and scheduling problem for a home care business. The problem is composed of two conflicting objectives, therefore we study it as a bi-objective one. We obtain the Pareto frontier ...
Robust Methods for Soft Clustering of Multidimensional Time Series
(MDPI, 2021)
[Abstract] Three robust algorithms for clustering multidimensional time series from the perspective of underlying processes are proposed. The methods are robust extensions of a fuzzy C-means model based on estimates of the ...
Nonparametric Inference for Mixture Cure Model When Cure Information Is Partially Available
(MDPI, 2021)
[Abstract] We introduce nonparametric estimators to estimate the conditional survival function, cure probability and latency function in the setting of a mixture cure model when the cure status is partially known. For the ...
The Bootstrap for Testing the Equality of Two Multivariate Stochastic Processes with an Application to Financial Markets
(MDPI, 2022)
[Abstract] The problem of testing the equality of generating processes of two multivariate time series is addressed in this work. To this end, we construct two tests based on a distance measure between stochastic processes. ...
Nonparametric Inference in Mixture Cure Models
(MDPI, 2018-09)
[Abstract]: A completely nonparametric method for the estimation of mixture cure models is proposed. Nonparametric estimators for the cure probability (incidence) and for the survival function of the uncured population ...
Unsupervised classification of categorical time series through innovative distances
(Avestia Publishing, 2022)
[Abstract]: In this paper, two novel distances for nominal time series are introduced. Both of them are based on features describing the serial dependence patterns between each pair of categories. The first dissimilarity ...
Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings
(2019)
[Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying
anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. ...