PELAEZ SUAREZ, REBECA

category: Visiting Professor

https://orcid.org/0000-0002-3386-5751

Positions

Academic Department : Statistics
Research Group : Nonparametric Inference for Complex Data and its Applications (NICDA)

Subjects

Mathematics
Statistics

Contact Info

repelaez@est-econ.uc3m.es >> Other Contact Information

Co-author Network

Co-researcher Network

sample of publications

articles
- Length-of-stay times in hospital for COVID-19 patients using the smoothed Beran"s estimator with bootstrap bandwidth selection. REVSTAT-Statistical Journal. 2024
- Probability of default estimation in credit risk using mixture cure models. COMPUTATIONAL STATISTICS & DATA ANALYSIS. 189:107853-1-107853-23. 2024
- Nonparametric estimation of the conditional survival function with double smoothing. JOURNAL OF NONPARAMETRIC STATISTICS. 31:1063-1090. 2022
- Bootstrap bandwidth selection and confidence regions for double smoothed default probability estimation. Mathematics. 10:1-25. 2022
- Nonparametric estimation of the probability of default with double smoothing. SORT-Statistics and Operations Research Transactions. 45:93-120. 2021
- Probability of default estimation in credit risk using a nonparametric approach. TEST. 30:383-405. 2021

researcher on

Gymkana La Ciencia de los Datos awarded by FUNDACION ESPAÑOLA DE CIENCIA Y TECNOLOGIA F.S.P. 2024 - 2025

other activities

mobility
- The purpose of the stay was to deepen in some of the topics of the thesis, whose framework is nonparametric estimation of the probability of default in credit risk. The stay took place at the Katholieke Universiteit Leuven (KU Leuven) under the supervision of Professor Ingrid Van Keilegom.The research carried out during the stay was based on the use of cure models to estimate the probability of default. Cure models have been used in different contexts, but mainly medical. More recently, cure models have been introduced to model problems in credit risk, given that a large proportion of the population may never experience the event of interest, the default, in the duration of their credits. Several researchers, including Professor Ingrid Van Keilegom, have proposed conditional survival function estimators based on mixed cure models. During this stay, such estimators were used to estimate the probability of default. It is important to take into account that the default probability function can be written as a transformation of the survival function. Desirable asymptotic properties of the resulting probability of default estimators were proved and their behaviour was analysed by simulation. In addition, the simulations carried out allowed us to compare the behaviour of the probability of default estimators obtained by means of cure models with the nonparametric estimators considered up to that moment in the thesis. This study concludes with a brief analysis of credit data illustrating the use of these estimators. The probability of default is estimated for a set of credits granted by a German financial institution. (2021)

category

Visiting Professor

ORCID iD

https://orcid.org/0000-0002-3386-5751