Zobrazeno 1 - 10
of 31
pro vyhledávání: '"A. Ausín Olivera"'
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
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Factor copula models have been recently proposed for describing the joint distribution of a large number of variables in terms of a few common latent factors. In this paper, we employ a Bayesian procedure to make fast inferences for multi-factor and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::19c55de2eeba77ba0208f56fe054526e
http://hdl.handle.net/10016/27652
http://hdl.handle.net/10016/27652
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
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Copula densities are widely used to model the dependence structure of financial time series. However, the number of parameters involved becomes explosive in high dimensions which results in most of the models in the literature being static. Factor co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::fc0cb7ba868e80bbb9fae23474cedfc9
http://hdl.handle.net/10016/24552
http://hdl.handle.net/10016/24552
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
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In order to understand the future behavior of the glaciers, their mass balance should be studied. The loss of water produced by melting, known as glacier discharge, is one of the components of this mass balance. In this paper, a vine copula structure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::92a54de32b554fefab5d1bd140044ba5
http://hdl.handle.net/10016/23812
http://hdl.handle.net/10016/23812
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
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Modelling glacier discharge is an important issue in hydrology and climate research. Glaciers represent a fundamental water resource when melting of snow contributes to runoff. Glaciers are also studied as natural global warming sensors. GLACKMA asso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d0ff47ddade36c834747a074b514b185
http://hdl.handle.net/10016/21089
http://hdl.handle.net/10016/21089
Publikováno v:
SEMERGEN - Medicina de Familia. 31:21-30
El asma bronquial aunque es una enfermedad que afecta a dos millones de personas en nuestro pais, alrededor del 13%-15% de los ninos y el 4%-8% de los adultos, sigue siendo una enfermedad infradiagnosticada poco tratada. Tal vez el hecho que se trate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9c19aa932baa75593ad5deb107528db
https://doi.org/10.1016/s1138-3593(05)72877-x
https://doi.org/10.1016/s1138-3593(05)72877-x
Publikováno v:
SEMERGEN - Medicina de Familia. 30:514-523
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9427aae9aecdeaebf641f885a5d5004f
https://doi.org/10.1016/s1138-3593(04)74361-0
https://doi.org/10.1016/s1138-3593(04)74361-0
Autor:
Virbickaite, Audrone, Lopes, Hedibert F., Ausín Olivera, María Concepción, Galeano San Miguel, Pedro
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
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This paper designs a Particle Learning (PL) algorithm for estimation of Bayesian nonparametric Stochastic Volatility (SV) models for financial data. The performance of this particle method is then compared with the standard Markov Chain Monte Carlo (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ef13282dc7b85aae7189f89c5ce1d950
https://hdl.handle.net/10016/19576
https://hdl.handle.net/10016/19576
Autor:
Galeano San Miguel, Pedro, Ausín Olivera, María Concepción, Virbickaite, Audrone, Lopes, Hedibert F.
This paper designs a Particle Learning (PL) algorithm for estimation of Bayesian nonparametric Stochastic Volatility (SV) models for financial data. The performance of this particle method is then compared with the standard Markov Chain Monte Carlo (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::1a7e0dfd27351e3fdb18792fdd4572da
https://e-archivo.uc3m.es/bitstream/handle/10016/19576/ws142819.pdf?sequence=1
https://e-archivo.uc3m.es/bitstream/handle/10016/19576/ws142819.pdf?sequence=1
This paper introduces a new approach to Bayesian nonparametric inference for densities on the hypercube, based on the use of a multivariate Bernstein polynomial prior. Posterior convergence rates under the proposed prior are obtained. Furthermore, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::88a52e64b2c1e458b77303908a1da085
https://e-archivo.uc3m.es/bitstream/handle/10016/16965/WS131211.pdf?sequence=1
https://e-archivo.uc3m.es/bitstream/handle/10016/16965/WS131211.pdf?sequence=1
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
instname
We use an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model to estimate the time-varying volatilities of financial returns. The ADCC-GJR-GARCH model takes into consideration the asymmetries in individual assets volatilities, as well a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ea995274d23583c221634a0d9c40e802
https://hdl.handle.net/10016/16967
https://hdl.handle.net/10016/16967