Browsing by Acedemic Degree "Programa Oficial de Doutoramento en Estatística e Investigación Operativa"
Now showing items 1-18 of 18
-
Cost-sensitive learning for credit risk
(2024)[Abstract]: This thesis addresses the problem of fraud detection and credit risk from a cost sensitive perspective, exploring techniques that maximize the benefits to a financial institution while minimizing the probability ... -
Decision Support Systems for Scheduling and Routing Problems in a Home Care Business
(2023)[Abstract] Home care services aim to help elderly, sick or dependent people in maintain their quality of life without having to leave their homes. This type of problem is denoted as Home Care Scheduling Problem (HCSP) and ... -
Exact bootstrap methods for non parametric curve estimation: reducing the complexity of machine learning methods
(2020)[Abstract] This thesis deals with bandwidth selection for nonparametric curve estimation. In particular, closed expressions for some error criteria of kernel estimators have been proposed. Additionally, bootstrap ... -
High dimensional single-index mixture cure models
(2024)[Abstract] In survival analysis, there are situations in which not all subjects are susceptible to the final event. For example, if the event is a cancer therapy-related adverse effect, there will be a fraction of patients ... -
Methodological Contributions in Semiparametric Regression Models for Functional Data
(2021)[Abstract] This doctoral thesis is dedicated to functional regression for scalar response. In particular, we focus on functional semiparametric models, which combine the practical advantages of parametric and nonparametric ... -
New methodological contributions in statistical learning for time series
(2023)[Abstract] Time series databases are becoming omnipresent in several fields (e.g., computer sciences, finance, biology...), which makes the development of data mining algorithms for these objects a top priority among machine ... -
New methodological contributions in time series clustering
(2017)[Abstract] This thesis presents new procedures to address the analysis cluster of time series. First of all a two-stage procedure based on comparing frequencies and magnitudes of the absolute maxima of the spectral ... -
Nonparametric Density and Regression Estimation for Samples of Very Large Size
(2021)[Abstract] This dissertation mainly deals with the problem of bandwidth selection in the context of nonparametric density and regression estimation for samples of very large size. Some bandwidth selection methods have ... -
Nonparametric estimation of the probability of default in credit risk.
(2022)[Abstract] Financial institutions are interested in knowing the probability that their clients declare themselves unable to pay the debts incurred by granting a credit. The aim of this work is to propose models to estimate ... -
Nonparametric Inference for Big-But-Biased Data
(2021)[Abstract] It is often believed that in a Big Data context, given the large amount of data available, the data re ect precisely the underlying population. However, the data are often strongly biased due to the procedure ... -
Nonparametric Inference for Regression Models with Spatially Correlated Errors
(2020)[Abstract] Regression estimation can be approached using nonparametric procedures, producing exible estimators and avoiding misspeci cation problems. Alternatively, parametric methods may be preferable to nonparametric ... -
Nonparametric Inference for the Mixture Cure Model When the Cure Status is Partially Known
(2022)[Abstract] Classical analysis of time-to-event data assumes that all individuals will eventually experience the event of interest. However, when there is evidence of long-term survivors, cure models should be used ... -
Nonparametric Inference in Mixture Cure Models
(2018)[Abstract] A completely nonparametric method for the estimation of mixture cure models is proposed. An incidence estimator is extensively studied and a latency estimator is presented. These estimators, which are based ... -
Nuevas aportaciones del análisis de datos funcionales en el control estadístico de procesos
(2018)[Abstract] This thesis report proposes new methodologies in the field of statistical quality control (SQC), specifical!y those techniques adapted to data obtained by sensors, continuously monitored with respect to time, ... -
Optimization and Allocation in Some Decision Problems with Several Agents or with Stochastic Elements
(2021)[Abstract] This dissertation addresses sorne decision problems that arise in project management, cooperative game theory and vehicle route optimization. We start with the problem of allocating the delay costs of a ... -
Pointwise forecast, confidence and prediction intervals in electricity demand and price
(2016)[Abstract] Analysis of the electricity demand and price is presented, within the Spanish Electricity Market, applying statistical tools from the field of functional data. It begins with a descriptive analysis of the ... -
Poisson mixed models: applications to small area data
(2017)[Abstract] Small area estimation deals with the estimation of parameters in small subsets (small areas) of a global population. In the small arcas, sample sizes are UBUallY too small since designa are developed for the ... -
Statistical learning in complex and temporal data: distances, two-sample testing, clustering, classification and Big Data
(2019)[Resumo] Esta tesis trata sobre aprendizaxe estatístico en obxetos complexos, con énfase en series temporais. O problema abórdase introducindo coñecemento sobre o dominio do fenómeno subxacente, mediante distancias e ...