Graphic summary
  • Show / hide key
  • Information


Scientific and technological production
  •  

1 to 50 of 93 results
  • Muestras de muestras: Aplicaciones relevantes de la estadística en la economía y la sociedad digital

     Valero Baya, Jordi; Perez Casany, Marta; Ginebra Molins, Josep; Mercader Prats, Magdalena; Müller, Hans-Georg; Puig Oriol, Xavier; Delicado Useros, Pedro Francisco
    Competitive project

     Share

  • A dynamic model of the proteins that form the initial iron-sulfur cluster biogenesis machinery in yeast mitochondria

     Amela Abellán, Isaac; Delicado Useros, Pedro Francisco; Gomez, Antonio; Querol Murillo, Enrique; Cedano, J
    Protein journal
    Vol. 32, num. 3, p. 183-196
    DOI: 10.1007/s10930-013-9475-4
    Date of publication: 2013-03
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    The assembly of iron-sulfur clusters (ISCs) in eukaryotes involves the protein Frataxin. Deficits in this protein have been associated with iron inside the mitochondria and impair ISC biogenesis as it is postulated to act as the iron donor for ISCs assembly in this organelle. A pronounced lack of Frataxin causes Friedreich¿s Ataxia, which is a human neurodegenerative and hereditary disease mainly affecting the equilibrium, coordination, muscles and heart. Moreover, it is the most common autosomal recessive ataxia. High similarities between the human and yeast molecular mechanisms that involve Frataxin have been suggested making yeast a good model to study that process. In yeast, the protein complex that forms the central assembly platform for the initial step of ISC biogenesis is composed by yeast frataxin homolog, Nfs1¿Isd11 and Isu. In general, it is commonly accepted that protein function involves interaction with other protein partners, but in this case not enough is known about the structure of the protein complex and, therefore, how it exactly functions. The objective of this work is to model the protein complex in order to gain insight into structural details that end up with its biological function. To achieve this goal several bioinformatics tools, modeling techniques and protein docking programs have been used. As a result, the structure of the protein complex and the dynamic behavior of its components, along with that of the iron and sulfur atoms required for the ISC assembly, have been modeled. This hypothesis will help to better understand the function and molecular properties of Frataxin as well as those of its ISC assembly protein partners.

  • Geofd: an R package for function-valued geostatistical prediction

     Giraldo, Ramon; Mateu Mahiques, Jorge; Delicado Useros, Pedro Francisco
    Revista colombiana de estadística
    Vol. 35, num. 3, p. 385-407
    Date of publication: 2012-12
    Journal article

    Read the abstract Read the abstract  Share Reference managers Reference managers Open in new window

    Spatially correlated curves are present in a wide range of applied disciplines. In this paper we describe the R package geofd which implements ordinary kriging prediction for this type of data. Initially the curves are pre-processed by tting a Fourier or B-splines basis functions. After that the spatial dependence among curves is estimated by means of the tracevariogram function. Finally the parameters for performing prediction by ordinary kriging at unsampled locations are by estimated solving a linear system based estimated trace-variogram. We illustrate the software analyzing real and simulated data.

  • Hierarchical clustering of spatially correlated functional data

     Giraldo, Ramon; Delicado Useros, Pedro Francisco; Mateu Mahiques, Jorge
    Statistica neerlandica
    Vol. 66, num. 4, p. 403-421
    DOI: 10.1111/j.1467-9574.2012.00522.x
    Date of publication: 2012-11
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    Classification problems of functional data arise naturally in many applications. Several approaches have been considered for solving the problem of finding groups based on functional data. In this paper, we are interested in detecting groups when the functional data are spatially correlated. Our methodology allows to find spatially homogeneous groups of sites when the observations at each sampling location consist of samples of random functions. In univariable and multivariable geostatistics, various methods of incorporating spatial information into the clustering analysis have been considered. Here, we extend these methods to the functional context to fulfil the task of clustering spatially correlated curves. In our approach, we initially use basis functions to smooth the observed data, and then, we weight the dissimilarity matrix among curves by either the trace-variogram or the multivariable variogram calculated with the coefficients of the basis functions. This paper contains a simulation study as well as the analysis of a real data set corresponding to average daily temperatures measured at 35 Canadian weather stations.

  • Estadística y probabilidad orientada al análisis de datos discreto

     Perez Casany, Marta; Ginebra Molins, Josep; Valero Baya, Jordi; Fontdecaba Rigat, Sara; Puig Oriol, Xavier; Delicado Useros, Pedro Francisco
    Competitive project

     Share

  • Dependencia no lineal variables aleatorias evaluación y aplicaciones

     Smrekar, Marcelo R.
    Department of Statistics and Operations Research, Universitat Politècnica de Catalunya
    Theses

     Share Reference managers Reference managers Open in new window

  • Ordinary kriging for function-valued spatial data

     Giraldo, Ramon; Delicado Useros, Pedro Francisco; Mateu Mahiques, Jorge
    Environmental and ecological statistics
    Vol. 18, num. 3, p. 411-426
    DOI: 10.1007/s10651-010-0143-y
    Date of publication: 2011
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    In various scientific fields properties are represented by functions varying over space. In this paper, we present a methodology to make spatial predictions at non-data locations when the data values are functions. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterion used in multivariable spatial prediction in order to estimate the kriging parameters. The curves are pre-processed by a non-parametric fitting, where the smoothing parameters are chosen by cross-validation. The approach is illustrated by analyzing real data based on soil penetration resistances.

  • On tree intensity estimation for forest inventories: some statistical issues

     Comas Rodriguez, Carlos; Mateu Mahiques, Jorge; Delicado Useros, Pedro Francisco
    Biometrical journal
    Vol. 53, num. 6, p. 994-1010
    DOI: 10.1002/bimj.201000193
    Date of publication: 2011-11
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Dimensionality reduction when data are density functions

     Delicado Useros, Pedro Francisco
    Computational statistics and data analysis
    Vol. 55, num. 1, p. 401-420
    DOI: 10.1016/j.csda.2010.05.008
    Date of publication: 2011-01-01
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    Functional Data Analysis deals with samples where a whole function is observed for each individual. A relevant case of FDA is when the observed functions are density functions. Among the particular characteristics of density functions, the most of the fact that they are an example of infinite dimensional compositional data (parts of some whole which only carry relative information) is made. Several dimensionality reduction methods for this particular type of data are compared: functional principal components analysis with or without a previous data transformation, and multidimensional scaling for different interdensity distances, one of them taking into account the compositional nature of density functions. The emphasis is on the steps previous and posterior to the application of a particular dimensionality reduction method: care must be taken in choosing the right density function transformation and/or the appropriate distance between densities before performing dimensionality reduction; subsequently the graphical representation of dimensionality reduction results must take into account that the observed objects are density functions. The different methods are applied1 to artificial and real data (population pyramids for 223 countries in year 2000). As a global conclusion, the use of multidimensional scaling based on compositional distance is recommended.

  • A second order approach to analyse spatial point patterns with functional marks

     Comas Rodriguez, Carlos; Delicado Useros, Pedro Francisco; Mateu Mahiques, Jorge
    Test
    Vol. 20, num. 3, p. 503-523
    DOI: 10.1007/s11749-010-0215-1
    Date of publication: 2011-10
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Análisis espacial de datos electorales. Aplicación al municipio de Barcelona

     Broner, Sonia Judith
    Department of Statistics and Operations Research, Universitat Politècnica de Catalunya
    Theses

     Share Reference managers Reference managers Open in new window

  • ANALISIS DE DATOS COMPLEJOS

     Puig Oriol, Xavier; Fontdecaba Rigat, Sara; Valero Baya, Jordi; Ginebra Molins, Josep; Riba Civil, Alexandre; Font Valverde, Marti; Rodero De Lamo, Lourdes; Delicado Useros, Pedro Francisco
    Competitive project

     Share

  • Statistics for spatial functional data: some recent contributions

     Delicado Useros, Pedro Francisco; Giraldo, Ramon; Comas, C.; Mateu Mahiques, Jorge
    Environmetrics
    Vol. 21, num. 3-4, p. 224-239
    DOI: 10.1002/env.1003
    Date of publication: 2010-06
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional data presenting spatial dependence. The three classic types of spatial data structures (geostatistical data, point patterns, and areal data) can be combined with functional data as it is shown in the examples of each situation provided here. We also review some contributions in the literature on spatial functional data.

  • Confidence intervals for median survival time with recurrent event data

     Gonzalez Ruiz, Juan Ramon; Peña, Edesl A.; Delicado Useros, Pedro Francisco
    Computational statistics and data analysis
    Vol. 54, num. 1, p. 78-89
    DOI: 10.1016/j.csda.2009.07.012
    Date of publication: 2010-01
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    Several methods of constructing confidence intervals for the median survival time of a recurrent event data are developed. One of them is based on asymptotic variances estimated using some transformations. Others are based on bootstrap techniques. Two types of recurrent event models are considered: the first one is a model where the inter-event times are independent and identically distributed, and the second one is a model where the inter-event times are associated, with the association arising from a gamma frailty model. Bootstrap and asymptotic confidence intervals are studied through simulation. These methods are applied and compared using two real data sets arising in the biomedical and public health settings, using an available R package. The first example belongs to data from a study concerning small bowel motility where an independent model may be assumed. The second example involves hospital readmissions in patients diagnosed with colorectal cancer. In this example the interoccurrence times are correlated.

  • Distance-based local linear regression for functional predictors

     Boj, E; Delicado Useros, Pedro Francisco; Fortiana, J
    Computational statistics and data analysis
    Vol. 54, num. 2, p. 429-437
    DOI: 10.1016/j.csda.2009.09.010
    Date of publication: 2010-02
    Journal article

    Read the abstract Read the abstract View View Open in new window  Share Reference managers Reference managers Open in new window

    The problem of nonparametrically predicting a scalar response variable from a functional predictor is considered. A sample of pairs (functional predictor and response) is observed. When predicting the response for a new functional predictor value, a semi-metric is used to compute the distances between the new and the previously observed functional predictors. Then each pair in the original sample is weighted according to a decreasing function of these distances. A Weighted (Linear) Distance-Based Regression is fitted, where the weights are as above and the distances are given by a possibly different semi-metric. This approach can be extended to nonparametric predictions from other kinds of explanatory variables (e.g., data of mixed type) in a natural way.

  • Continuous Time-Varying Kriging for Spatial Prediction of Functional Data: An Environmental Application

     Giraldo, Ramon; Delicado Useros, Pedro Francisco; Mateu Mahiques, Jorge
    Journal of agricultural biological and environmental statistics
    Vol. 15, num. 1, p. 66-82
    DOI: 10.1007/s13253-009-0012-z
    Date of publication: 2010-03
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • DockAnalyse: an application for the analysis of protein-protein interactions

     Amela Abellán, Isaac; Delicado Useros, Pedro Francisco; Gomez, Antonio; Bonas, Silvia; Querol, Enric; Cedano, J
    BMC structural biology
    Vol. 10, num. 37, p. 1-11
    DOI: 10.1186/1472-6807-10-37
    Date of publication: 2010-10-22
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Computational statistics and data analysis

     Delicado Useros, Pedro Francisco
    Collaboration in journals

     Share

  • GEOSTATISTICAL ANALYSIS OF FUNCTIONAL DATA

     Giraldo, Ramon
    Department of Statistics and Operations Research, Universitat Politècnica de Catalunya
    Theses

     Share Reference managers Reference managers Open in new window

  • Friedreich ataxia: a computational dynamic model of the key proteins involved in the yeast Fe-S cluster biogenesis

     Amela, I.; Cedano, J; Delicado Useros, Pedro Francisco; Querol, Enric
    New biotechnology
    Vol. 25, num. supplement 1, p. S342-S343
    DOI: 10.1016/j.nbt.2009.06.1001
    Date of publication: 2009-09
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Analysing musical performance through functional data analysis: rhythmic structure in Schumann's Traumerei

     Almansa, J; Delicado Useros, Pedro Francisco
    Connection science
    Vol. 21, num. 2-3, p. 207-225
    Date of publication: 2009-01
    Journal article

     Share Reference managers Reference managers Open in new window

  • Measuring non-linear dependence for two random variables distributed along a curve

     Delicado Useros, Pedro Francisco; Marcelo, Smrekar
    Statistics and computing
    Vol. 19, num. 3, p. 225-269
    Date of publication: 2009-09
    Journal article

     Share Reference managers Reference managers Open in new window

  • Spatial statistics for functional data

     Delicado Useros, Pedro Francisco; Giraldo, Ramon; Comas Rodriguez, Carlos; Mateu Mahiques, Jorge
    International Workshop on Spatio-Temporal Modelling (METMA4)
    p. 1
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • From multivariable to functional cokriging: an alternative for space-time prediction

     Sanchez Giraldo, Raquel; Delicado Useros, Pedro Francisco; Mateu Mahiques, Jorge
    International Workshop on Spatio-Temporal Modelling (METMA4)
    p. 4
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Comparing methods for dimensionality reduction when data are density functions.

     Delicado Useros, Pedro Francisco
    Compositional Data Analysis Workshop (CodaWork '08)
    Presentation's date: 2008-05-27
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Local Linear Functional Regression Based on Weighted Distance-based Regression

     Boj, E; Delicado Useros, Pedro Francisco; Fortiana, J
    First International Workshop on Functional and Operatorial Statistics
    p. 57-63
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Shape of sample plots for homogeneous spatial point processes

     Comas Rodriguez, Carlos; Mateu Mahiques, Jorge; Delicado Useros, Pedro Francisco
    International Workshop on Spatio-Temporal Modelling (METMA4)
    p. 2
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Analysing spatial point patterns with associated functional data

     Delicado Useros, Pedro Francisco; Comas Rodriguez, Carlos; Mateu Mahiques, Jorge
    International Workshop on Spatio-Temporal Modelling (METMA4)
    p. 3
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Point-Wise Kriging for Spatial Prediction of Functional Data

     Delicado Useros, Pedro Francisco; Giraldo, Ramon; Mateu Mahiques, Jorge
    First International Workshop on Functional and Operatorial Statistics
    p. 135-141
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Point-wise Kriging for spatial prediction of functional data

     Delicado Useros, Pedro Francisco; Giraldo, Ramon; Mateu Mahiques, Jorge
    Date of publication: 2008-09
    Book chapter

     Share Reference managers Reference managers Open in new window

  • Local Linear Functional Regression based on Weighted Distance-Based Regression

     Delicado Useros, Pedro Francisco
    Date of publication: 2008-09
    Book chapter

     Share Reference managers Reference managers Open in new window

  • A small sample comparison of maximum likelihood, moments and L-moments methods for the asymmetric exponential power distribution

     Delicado Useros, Pedro Francisco; Goria, M N
    Computational statistics and data analysis
    Vol. 52, num. 3, p. 1661-1673
    DOI: 10.1016/j.csda.2007.05.021
    Date of publication: 2008-01
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Explaining electoral participation by an economic capacity index in Barcelona

     Broner, Sonia Judith; Delicado Useros, Pedro Francisco
    22 International Workshop on Statistical Modelling (IWSM'2007)
    p. 126-129
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Diseños Alternativos de Sondeos Electorales

     Delicado Useros, Pedro Francisco
    Congreso Nacional de Estadística e Investigación Operativa
    Presentation's date: 2007-09-25
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Regresión lineal local funcional basada en distancias

     Delicado Useros, Pedro Francisco
    Congreso Nacional de Estadística e Investigación Operativa
    Presentation's date: 2007-09-25
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Geostatistics for functional data: An ordinary kriging approach

     Delicado Useros, Pedro Francisco
    22 International Workshop on Statistical Modelling (IWSM'2007)
    Presentation's date: 2007-07-02
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Functional k-sample problem when data are density functions

     Delicado Useros, Pedro Francisco
    Computational statistics
    Vol. 22, num. 3, p. 391-410
    Date of publication: 2007-09
    Journal article

     Share Reference managers Reference managers Open in new window

  • A web server for automatic analysis and extraction of relevant biological knowledge

     Cedano, J; Huerta, Mario; Estrada Palacios, Immaculada; Delicado Useros, Pedro Francisco
    Computer in medicine
    Vol. 37, num. 11, p. 1672-1675
    Date of publication: 2007-11
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Análisis de datos complejos: métodos paramétricos, no paramétricos y basados en distancias

     Puig Oriol, Xavier; Delicado Useros, Pedro Francisco; Riba Civil, Alexandre; Perez Casany, Marta
    Competitive project

     Share

  • Functional ANOVA when data are a weighted sample of density functions

     Delicado Useros, Pedro Francisco
    Quatrièmes Journées de Statistique Fonctionelle et Operationell
    Presentation's date: 2006-06-01
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Spatial data analysis for 2004 electoral data in Barcelona

     Broner, Sonia Judith; Delicado Useros, Pedro Francisco
    International Workshop on Spatio-Temporal Modelling
    p. 93-94
    Presentation of work at congresses

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Inference for a general class of models for recurrent events with application to cancer data  Open access

     Gonzalez Ruiz, Juan Ramon
    Department of Statistics and Operations Research, Universitat Politècnica de Catalunya
    Theses

    Read the abstract Read the abstract Access to the full text Access to the full text Open in new window  Share Reference managers Reference managers Open in new window

    La necesidad del análisis de supervivencia aparece cuando necesitamos estudiar las propiedades estadísticas de una variable que describe el tiempo hasta que ocurre un evento único. En algunas ocasiones, podemos observar que el evento de interés ocurre repetidamente en un mismo individuo, como puede ser el caso de un paciente diagnosticado de cáncer que recae a lo largo del tiempo o cuando una persona es reingresada repetidas veces en un hospital. En este caso hablamos de análisis de supervivencia con eventos recurrentes. La naturaleza recurrente de los eventos hace necesario el uso de otras técnicas distintas a aquellas que utilizamos cuando analizamos tiempos de supervivencia para un evento único. En esta tesis, tratamos este tipo de análisis principalmente motivados por dos estudios en investigación en cáncer que fueron creados especialmente para este trabajo. Uno de ellos hace referencia a un estudio sobre readmisiones hospitalarias en pacientes diagnosticados con cáncer colorectal, mientras que el otro hace referencia a pacientes diagnosticados con linfomas no Hodgkinianos. Este último estudio es especialmente relevante ya que incluimos información sobre el efecto del tratamiento después de las recaídas y algunos autores han mostrado la necesidad de desarrollar un modelo específico para pacientes que presentan este tipo de enfermedades. Nuestra contribución al análisis univariante es proponer un método para construir intervalos de confianza para la mediana de supervivencia en el caso de eventos recurrentes. Para ello, hemos utilizado dos aproximaciones. Una de ellas se basa en las varianzas asintóticas derivadas de dos estimadores existentes de la función de supervivencia, mientras que el otro utiliza técnicas de remuestreo. Esta última aproximación es útil ya que uno de los estimadores utilizados todavía no tiene una forma cerrada para su varianza. La nueva contribución de este trabajo es el estudio de cómo hacer remuestreo en la presencia de datos con eventos recurrentes que aparecen de un esquema conocido como --sum-quota accrual" y la informatividad del mecanismo de censura por la derecha que presentan este tipo de datos. Demostramos la convergencia d bil y los intervalos de confianza asintóticos se construyen utilizando dicho resultado. Por otro lado, el análisis multivariante trata el problema de cómo incorporar más de una covariable en el análisis. En problemas con eventos recurrentes, también necesitamos tener en cuenta que además de las covariables, la hetereogeneidad, el número de ocurrencias, o especialmente, el efecto de las intervenciones después de las reocurrencias puede modificar la probabilidad de observar un nuevo evento en un paciente. Este último punto es muy importante ya que todavía no se ha tenido en cuenta en estudios biomédicos. Para tratar este problema, hemos basado nuestro trabajo en un nuevo modelo para eventos recurrentes propuesto por Peña y Hollander, 2004. Nuestra contribución a este punto es la adaptación de las recaídas en cáncer utilizando este modelo en el que el efecto de las intervenciones se representa mediante un proceso llamado --edad efectiva' que actúa sobre la función de riesgo basal. Hemos llamado a este modelo modelo dinámico de cáncer (--dynamic cancer model'). También tratamos el problema de la estimación de parámetros de la clase general de modelos para eventos recurrentes propuesta por Peña y Hollander donde el modelo dinámico de cáncer se puede ver como un caso especial de este modelo general. Hemos desarrollado dos aproximaciones. La primera se basa en inferencia semiparamétrica, donde la función de riesgo basal se especifica de forma no paramétrica y usamos el algoritmo EM. La segunda es una aproximación basada en verosimilitud penalizada donde adoptamos dos estrategias diferentes. Una de ellas se basa en penalizar la verosimilitud parcial donde la penalización recae en los coeficientes de regresión. La segunda penaliza la verosimilitud completa y da una estimación no paramétrica de la función de riesgo basal utilizando un estimador continuo. La solución se aproxima utilizando splines. La principal ventaja de este método es que podemos obtener fácilmente una estimación suave de la función de riesgo así como una estimación de la varianza de la varianza de la fragilidad, mientras que con las otras aproximaciones esto no es posible. Además este último método presenta un coste computacional bastante más bajo que los otros. Los resultados obtenidos con datos reales, indican que la flexibilidad de este modelo es una garantía para analizar datos de pacientes que recaen a lo largo del tiempo y que son intervenidos después de las recaídas tumorales.El aspecto computacional es otra de las contribuciones importantes de esta tesis al campo de los eventos recurrentes. Hemos desarrollado tres paquete de R llamados survrec, gcmrec y frailtypack que están accesibles en CRAN, http://www.r-project.org/. Estos paquetes permiten al usuario calcular la mediana de supervivencia y sus intervalos de confianza, estimar los par metros del modelo de Peña y Hollander (en particular el modelo dinámico de cáncer) utilizando el algoritmo EM y la verosimilitud penalizada, respectivamente.

    Survival analysis arises when we are interested in studying statistical properties of a variable which describes the time to a single event. In some situations, we may observe that the event of interest occurs repeatedly in the same individual, such as when a patient diagnosed with cancer tends to relapse over time or when a person is repeatedly readmitted in a hospital. In this case we speak about survival analysis with recurrent events. Recurrent nature of events makes necessary to use other techniques from those used when we analyze survival times from one single event. In this dissertation we deal with this type of analysis mainly motivatedby two studies on cancer research that were created specially for this research. One of them belongs to a study on hospital readmissions in patients diagnosed with colorectal cancer, while the other one deals with patients diagnosed with non-Hodgkin's lymphoma. This last study is mainly relevant since we include information about the effect of treatment after relapses and some authors have stated the needed of developing a specific model for relapsing patients in cancer settings.Our first contribution to univariate analysis is to propose a method to construct confidence intervals for the median survival time in the case of recurrent event settings. Two different approaches are developed. One of them is based on asymptotic variances derived from two existing estimators of survival function, while the other one uses bootstrap techniques. This last approach is useful since one of the estimators used, does not have any closed form for its variance yet. The new contribution to this work is the examination of the question of how to do bootstrapping in the presence of recurrent event data arising from a sum-quota accrual scheme and informativeness of right censoring mechanism. Weak convergence is proved and asymptotic confidence intervals are built to according this result. On the other hand, multivariate analysis addresses the problem of how incorporate more than one covariate in the analysis. In recurrent event settings, we also need to take into account that apart from covariates, the heterogeneity, the number of occurrences or specially, the effect of interventions after re occurrences may modify the probability of observing a new event in a patient. This last point is a very important one since it has not been taken into consideration in biomedical studies yet. To address this problem, we base our work on a new model for recurrent events proposed by Peña and Hollander. Our contribution to this topic is to accommodate the situation of cancer relapses to this model model in which the effect of interventions is represented by an effective age process acting on the baseline hazard function. We call this model dynamic cancer model.We also address the problem of estimating parameters of the general class of models for recurrent events proposed by Peña and Hollander, 2004, where the dynamic cancer model may be seen as a special case of this general model. Two general approaches are developed. First approach is based on semiparametric inference, where a baseline hazard function is nonparametrically specified and uses the EM algorithm. The second one is a penalized likelihood approach where two different strategies are adopted. One of them is based on penalizing the partial likelihood where the penalization bears on a regression coefficient. The second penalized approach penalized full likelihood, and it gives a non parametric estimation of the baseline hazard function using a continuous estimator. The solution is then approximated using splines. The main advantage of this method is that we caneasily obtain smooth estimates of the hazard function and an estimation of the variance of frailty variance, while in the other approaches this is not possible. In addition, this last approach has a quite less computational cost than the other ones. The results obtained using dynamic cancer model in real data sets, indicate that the flexibility of this method provides a safeguard for analyzing data where patients relapse over time and interventions are performed after tumoral reoccurrences.Computational issue is another important contribution of this work to recurrent event settings. We have developed three R packages called survrec, gcmrec, and frailtypack that are available at CRAN, http://www.r-project.org/. These packages allow users to compute median survival time and their confidence intervals, to estimate the parameters involved in the Peña and Hollander's model (in particular in the dynamic cancer model) using EM algorithm, and to estimate this parameters using penalized approach, respectively.

  • Local likelihood density estimation based on smooth truncation

     Delicado Useros, Pedro Francisco
    Biometrika
    Vol. 93, num. 2, p. 472-480
    DOI: 10.1093/biomet/93.2.472
    Date of publication: 2006-06
    Journal article

    View View Open in new window  Share Reference managers Reference managers Open in new window

  • Análisis Multivariante No Lineal: técnicas no paramétricas y basadas en distancias

     Delicado Useros, Pedro Francisco; Perez Casany, Marta; Ginebra Molins, Josep
    Competitive project

     Share

  • Computational comparison of three local likelihood density estimators

     Delicado Useros, Pedro Francisco
    INTERNATIONAL SEMINAR ON NONPARAMETRIC INFERENCE (ISNI 2005)
    Presentation's date: 2005-07-13
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Constant Coefficient Tests for Random Coefficient Regression

     Delicado Useros, Pedro Francisco
    Congreso Conjunto de Matemáticas RSME-SCM-SEIO-SEMA
    Presentation's date: 2005-02-02
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Estimating parliamentary composition through electoral polls

     Udina, F.; Delicado Useros, Pedro Francisco
    Journal of the Royal Statistical Society. Series A, statistics in society
    Vol. 168, p. 387-399
    Date of publication: 2005-03
    Journal article

     Share Reference managers Reference managers Open in new window

  • Remarks on local likelihood density estimation

     Delicado Useros, Pedro Francisco
    6th World Congress of the Bernoulli Society for Mathemathical Statistics and Probability
    Presentation's date: 2004-07-26
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Fitting Principal Curves as mixtures of simple nonlinear models

     Delicado Useros, Pedro Francisco
    ISBA 2004 World Meeting
    Presentation's date: 2004-05-23
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window

  • Aplicación del análisis de datos funcionales en la probabilidad de morir por edad en Catalunya

     Navarro, Valenti; Puig Oriol, Xavier; Delicado Useros, Pedro Francisco
    XXII REUNIÓN CIENTÍFICA DE LA SOCIEDAD ESPAÑOLA DE EPIDEMIOLOGÍA (SEE)
    Presentation's date: 2004-10-27
    Presentation of work at congresses

     Share Reference managers Reference managers Open in new window