Zobrazeno 1 - 10
of 1 009
pro vyhledávání: '"Portugués, A."'
A kernel density estimator for data on the polysphere $\mathbb{S}^{d_1}\times\cdots\times\mathbb{S}^{d_r}$, with $r,d_1,\ldots,d_r\geq 1$, is presented in this paper. We derive the main asymptotic properties of the estimator, including mean square er
Externí odkaz:
http://arxiv.org/abs/2411.04166
We provide a class of diffusion processes for continuous time-varying multivariate angular data with explicit transition probability densities, enabling exact likelihood inference. The presented diffusions are time-reversible and can be constructed f
Externí odkaz:
http://arxiv.org/abs/2409.02705
Publikováno v:
Statistics & Probability Letters, 215:110218, 2024
We introduce a test of uniformity for (hyper)spherical data motivated by the stereographic projection. The closed-form expression of the test statistic and its null asymptotic distribution are derived using Gegenbauer polynomials. The power against r
Externí odkaz:
http://arxiv.org/abs/2405.13531
Autor:
Simonetta, Federico, Llorens, Ana, Serrano, Martín, García-Portugués, Eduardo, Torrente, Álvaro
This paper presents a comprehensive investigation of existing feature extraction tools for symbolic music and contrasts their performance to determine the set of features that best characterizes the musical style of a given music score. In this regar
Externí odkaz:
http://arxiv.org/abs/2307.05107
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
Publikováno v:
Test, 32(4):1508-1529, 2023
Two new omnibus tests of uniformity for data on the hypersphere are proposed. The new test statistics exploit closed-form expressions for orthogonal polynomials, feature tuning parameters, and are related to a "smooth maximum" function and the Poisso
Externí odkaz:
http://arxiv.org/abs/2304.04519
Publikováno v:
Statistics and Computing, 33(5):107, 2023
Principal Component Analysis (PCA) is a well-known linear dimension-reduction technique designed for Euclidean data. In a wide spectrum of applied fields, however, it is common to observe multivariate circular data (also known as toroidal data), rend
Externí odkaz:
http://arxiv.org/abs/2212.10856
We solve the non-discounted, finite-horizon optimal stopping problem of a Gauss-Markov bridge by using a time-space transformation approach. The associated optimal stopping boundary is proved to be Lipschitz continuous on any closed interval that exc
Externí odkaz:
http://arxiv.org/abs/2211.05835
Publikováno v:
Stochastics, 96(1):921-946, 2024
We study the barrier that gives the optimal time to exercise an American option written on a time-dependent Ornstein--Uhlenbeck process, a diffusion often adopted by practitioners to model commodity prices and interest rates. By framing the optimal e
Externí odkaz:
http://arxiv.org/abs/2211.04095
Autor:
Manuel Rodríguez Portugués
Publikováno v:
Revista de Estudios de la Administración Local y Autonómica, Iss 22 (2024)
Recensión del libro de Luis Medina Alcoz: Historia del derecho administrativo español, con prólogo de Manuel Rebollo Puig, Marcial Pons, 2022, 535 pp.
Externí odkaz:
https://doaj.org/article/4f8ff091f3914860b2c8aeaa31112e87
