Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Galeano, Pedro"'
In this paper, we employ Credit Default Swaps (CDS) to model the joint and conditional distress probabilities of banks in Europe and the U.S. using factor copulas. We propose multi-factor, structured factor, and factor-vine models where the banks in
Externí odkaz:
http://arxiv.org/abs/2401.03443
Autor:
Febrero-Bande, Manuel, Galeano, Pedro, García-Portugués, Eduardo, González-Manteiga, Wenceslao
Publikováno v:
Computational Statistics, 2024
A goodness-of-fit test for the Functional Linear Model with Scalar Response (FLMSR) with responses Missing at Random (MAR) is proposed in this paper. The test statistic relies on a marked empirical process indexed by the projected functional covariat
Externí odkaz:
http://arxiv.org/abs/2304.04712
This paper proposes methods to detect outliers in functional data sets and the task of identifying atypical curves is carried out using the recently proposed kernelized functional spatial depth (KFSD). KFSD is a local depth that can be used to order
Externí odkaz:
http://arxiv.org/abs/1501.01859
Autor:
Febrero-Bande, Manuel, Galeano, Pedro, García-Portugués, Eduardo, González-Manteiga, Wenceslao
Publikováno v:
Computational Statistics; Sep2024, Vol. 39 Issue 6, p3405-3429, 25p
Publikováno v:
In Computational Statistics and Data Analysis November 2020 151
Publikováno v:
In Energy Economics October 2020 92
Publikováno v:
In Journal of Econometrics May 2020 216(1):35-52
This survey reviews the existing literature on the most relevant Bayesian inference methods for univariate and multivariate GARCH models. The advantages and drawbacks of each procedure are outlined as well as the advantages of the Bayesian approach v
Externí odkaz:
http://arxiv.org/abs/1402.0346
Publikováno v:
TEST, December 2014, Volume 23, Issue 4, pp 725-750
We enlarge the number of available functional depths by introducing the kernelized functional spatial depth (KFSD). KFSD is a local-oriented and kernel-based version of the recently proposed functional spatial depth (FSD) that may be useful for study
Externí odkaz:
http://arxiv.org/abs/1305.2957
This paper presents a general notion of Mahalanobis distance for functional data that extends the classical multivariate concept to situations where the observed data are points belonging to curves generated by a stochastic process. More precisely, a
Externí odkaz:
http://arxiv.org/abs/1304.4786