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Mostrando ítems 1-9 de 9
Artículo
Analysis of an aggregate loss model in a Markov renewal regime
(ELSEVIER SCIENCE INC, 2020-12-22)
In this article we consider an aggregate loss model with dependent losses. The loss oc- currence process is governed by a two-state Markovian arrival process ( MAP 2 ), a Markov renewal process that allows for (1) correlated ...
Tesis Doctoral
Enhancing robustness and sparsity via mathematical optimization
(2016-09-22)
Esta tesis se centra en derivar métodos robustos o dispersos bajo la perspectiva de la optimización para problemas que tradicionalmente se engloban en los campos de la Estadística o de la Investigación Operativa. Concretamente, ...
Artículo
A global optimisation approach for parameter estimation of a mixture of double Pareto lognormal and lognormal distributions
(PERGAMON-ELSEVIER SCIENCE LTD, 2013-10-30)
The double Pareto Lognormal(dPlN) statistical distribution, defined interms of both an exponentiated skewed Laplace distribution and alog normal distribution, has proven suitable for fitting heavy tailed data. In this ...
Artículo
Cost-sensitive feature selection for support vector machines
(Elsevier, 2018-03)
Feature Selection (FS) is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more interpretable and more effective by ...
Artículo
Robust newsvendor problem with autoregressive demand
(Elsevier, 2016-04)
This paper explores the classic single-item newsvendor problem under a novel setting which combines temporal dependence and tractable robust optimization. First, the demand is modeled as a time series which follows an ...
Artículo
The Markovian arrival process: A statistical model for daily precipitation amounts
(ELSEVIER SCIENCE BV, 2013-12-21)
The Markovian arrival process (MAP) is a stochastic process that allows for modeling dependent and non-exponentially distributed observations. Due to its versatility, it has been widely applied in different contexts, from ...
Artículo
A cost-sensitive constrained Lasso
(Springer, 2020-03-02)
The Lasso has become a benchmark data analysis procedure, and numerous variants have been proposed in the literature. Although the Lasso formulations are stated so that overall prediction error is optimized, no full ...
Artículo
Embedding the production policy in location-allocation decisions
(Springer, 2019-11-21)
This paper investigates how the production policy, as well as other factors, affect the facility location-allocation decisions. We focus on a p-median location problem in which one single perishable product is to be ...
Artículo
On support vector machines under a multiple-cost scenario
(Springer, 2018-07-31)
Support vector machine (SVM) is a powerful tool in binary classification, known to attain excellent misclassification rates. On the other hand, many realworld classification problems, such as those found in medical ...