Zobrazeno 1 - 10
of 35
pro vyhledávání: '"María Dolores Martínez-Miranda"'
Publikováno v:
Financial Innovation, Vol 10, Iss 1, Pp 1-16 (2024)
Abstract The availability of many variables with predictive power makes their selection in a regression context difficult. This study considers robust and understandable low-dimensional estimators as building blocks to improve overall predictive powe
Externí odkaz:
https://doaj.org/article/958b8a3121934d70b61f5a0fc09e07dc
Publikováno v:
Mathematics, Vol 9, Iss 18, p 2260 (2021)
In this paper, we apply and further illustrate a recently developed extended continuous chain ladder model to forecast mesothelioma deaths. Making such a forecast has always been a challenge for insurance companies as exposure is difficult or impossi
Externí odkaz:
https://doaj.org/article/6fa3e26c593c4a28ad1e807df7920461
Autor:
MUNIR HIABU, MARÍA DOLORES MARTÍNEZ-MIRANDA, JENS PERCH NIELSEN, JAAP SPREEUW, CARSTEN TANGGAARD, ANDRÉS M. VILLEGAS
Publikováno v:
Revista Colombiana de Estadística, Vol 38, Iss 2, Pp 399-411
This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theo
Externí odkaz:
https://doaj.org/article/ddb400a6673f41669d3c00a281418630
Publikováno v:
Insurance: Mathematics and Economics. 96:31-52
A very popular forecasting tool in the actuarial sciences is the so-called chain ladder. Mammen et al. (2015) recently introduced in-sample forecasting, a general forecasting technique applicable in many fields which builds on the continuous chain la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e817c71b1280b8fde76462a11edfbcec
https://doi.org/10.1016/j.insmatheco.2020.10.003
https://doi.org/10.1016/j.insmatheco.2020.10.003
Autor:
Rocío Raya-Miranda, Antonio J. López-Montoya, Maria Luz Gamiz, María Dolores Martínez-Miranda
Publikováno v:
Wiley StatsRef: Statistics Reference
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::538df771a46181cacee8d40ef81a9f4b
https://doi.org/10.1002/9781118445112.stat08264
https://doi.org/10.1002/9781118445112.stat08264
Autor:
Rocío Raya-Miranda, María Dolores Martínez-Miranda, Antonio Jesús López-Montoya, Maria Luz Gamiz
Publikováno v:
Quality and Reliability Engineering International. 35:99-115
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd68751d460bdfc6aca4ac268914baad
https://doi.org/10.1002/qre.2383
https://doi.org/10.1002/qre.2383
Publikováno v:
Computational Statistics & Data Analysis
It is shown how to overcome a new missing data problem in survival analysis. Iterative nonparametric techniques are utilized and the missing data information is both estimated and used for further estimation in each iterative step. Theory is develope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8f738749d3deeb84deb167e4c1c2227
http://europepmc.org/articles/PMC8666881
http://europepmc.org/articles/PMC8666881
Publikováno v:
Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname
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This is the accepted manuscript of the following article: Borrajo, M., González-Manteiga, W., & Martínez-Miranda, M. (2019). Testing for significant differences between two spatial patterns using covariates. Spatial Statistics, 100379. doi: 10.1016
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d73e2ecef29bc8122f4a0264861a8139
http://hdl.handle.net/10347/20315
http://hdl.handle.net/10347/20315
Publikováno v:
Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname
instname
This is the accepted manuscript of the following article: Borrajo, M., González-Manteiga, W., & Martínez-Miranda, M. (2020). Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates. Computational Statisti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42506d353407d7daecb95067fe29e264
https://doi.org/10.1016/j.csda.2019.106875
https://doi.org/10.1016/j.csda.2019.106875
Publikováno v:
Risks
Volume 7
Issue 4
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Volume 7
Issue 4
Digibug. Repositorio Institucional de la Universidad de Granada
instname
A new Bornhuetter–Ferguson method is suggested herein. This is a variant of the traditional chain ladder method. The actuary can adjust the relative ultimates using externally estimated relative ultimates. These correspond to linear constraints on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8c7de81d47b7246c005fa0114e671e1
https://doi.org/10.3390/risks7040119
https://doi.org/10.3390/risks7040119