Person:
Portela García-Miguel, Javier

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First Name
Javier
Last Name
Portela García-Miguel
URI
https://hdl.handle.net/20.500.14352/77436
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
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Now showing 1 - 10 of 18
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    Differentiated models in the collaborative transport economy: a mixture analysis for Blablacar and Uber
    (2021) Quirós Romero, Cipriano; Portela García-Miguel, Javier; Marín Sanz, Raquel; Dabić, Marina; Griffy-Brown, Charla
    The collaborative economy has become one of the fastest-growing areas since the great recession of 2008, with passenger transport activities being of particular importance. Based on on-demand ride services, in which passengers are connected with community drivers through a smartphone app, these collaborative transport activities are not all of a homogeneous nature, and need to be differentiated according to the type of service provided to understand the socioeconomic and environmental characteristics that determine their widespread use. The objective of this paper is to analyze the determinants of use of the two main online platforms for transport in Europe: Blablacar (ride-sharing) and Uber (ride-hailing), representing two different business models for shared mobility. Our contribution is an empirical analysis emphasizing the role of digital skills and employing a mixture analysis technique that permits the distinction between these two platforms models. Our results show that beyond their strong linkage to the digital environment, the determinants of using both platforms differ. In the case of Blablacar, the results show a closed user profile influenced by age, educational level, live as a couple or urban environment. However, the user profile for Uber is open and more diffuse, with a preference for female population.
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    Project number: 390
    Aprendizaje virtual de las matemáticas utilizando distintas TICs
    (2021) Riomoros Callejo, María Isabel; Medina Sánchez, María Ángeles; Ávila Tejera, Juan Julián; Belope Nguema, Sabina; García Ruiz, Yolanda; García Villalba, Luis Javier; Portela García-Miguel, Javier; Blanco García, Susana; Miguel Vicente, Carmen; García Pineda, María Pilar; Sandoval Orozco, Ana Lucila
    Proyecto para ayudar al estudiantado en el aprendizaje de las Matemáticas y promover su aprendizaje autónomo. Todo ello, con materiales más visuales como vídeos, píldoras educativas, clases en modo síncrono, ejemplos con GeoGebra y cuestionarios.
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    Project number: 104
    Las Matemáticas Empresariales en el marco Erasmus Mundus
    (2017) García Pineda, María Pilar; Heras Martínez, Antonio José; Blanco García, Susana; Balbás Aparicio, Raquel; García Villalba, Luis Javier; Riomoros Callejo, María Isabel; Portela García-Miguel, Javier; Sandoval Orozco, Ana Lucila; Rebollo Castillo, Francisco Javier
    La creciente importancia de los métodos cuantitativos en las ciencias económicas y empresariales nos motiva a proponer una revisión detallada de los syllabus de las materias de matemáticas que se imparten en el Grado de Administración y Dirección de Empresas, con el objetivo de Investigar las correspondencias entre nuestros syllabus y los de las mas importantes universidades a nivel internacional (en el marco Erasmus Mundus). La investigación que proponemos llevará a cabo comparaciones exhaustivas de los temarios de esta categoría de asignaturas y sus metodologías docentes, y detectará las posibles discrepancias existentes en este tipo de estudios dependiendo de la universidad que los imparte. En una segunda fase, estudiaremos las causas de las posibles diferencias detectadas y, finalmente, produciremos un sistema capaz de sugerir medidas concretas que solventen los posibles problemas detectados.
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    Clustering using ordered weighted averaging operator and 2-tuple linguistic model for hotel segmentation: the case of TripAdvisor
    (Expert Systems with Applications, 2023) Shu, Ziwei; Carrasco González, Ramón Alberto; Portela García-Miguel, Javier; Sanchez-Montañés, Manuel; Lin, Binshan
    With the growth of online tourism, it is important to analyze the reviews left by numerous customers on social networks to improve the hotel’s online reputation. Hotel segmentation based on online reviews has attracted an increasing interest from many academics. The problem is that many hotel segmentation models overlook the fact that some customers focus on positive reviews when choosing a hotel, while others focus on negative ones. To address this shortcoming, this paper develops a novel approach to classify hotels using the ordered weighted averaging (OWA) operator, the 2-tuple linguistic model, and K-means clustering. The proposed approach has been evaluated with a real dataset from TripAdvisor, which contains more than 50 million customer online reviews on eight aspects of the hotel. The results show that the proposed model can produce denser and more separated clusters than the model without linguistic quantifiers. From a business point of view, this model enables hotels to distinguish customers’ perceptions (from the less demanding to the most demanding) about their eight aspects, allowing them to specify which of them need to be improved and develop strategies more quickly. At the same time, it introduces a new way of ranking hotels online, allowing customers to create personalized rankings of hotels based on their degree of demand for various hotel aspects (better location, cleaner rooms, etc.) rather than the average ratings, so that they can select the most suitable hotels more quickly.
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    Implementation of a Robust Bayesian Method
    (Journal of Statistical Computation and Simulation, 2004) Portela García-Miguel, Javier; Gómez Villegas, Miguel Ángel
    In this work we study robustness in Bayesian models through a generalization of the Normal distribution. We show new appropriate techniques in order to deal with this distribution in Bayesian inference. Then we propose two approaches to decide, in some applications, if we should replace the usual Normal model by this generalization. First, we pose this dilemma as a model rejection problem, using diagnostic measures. In the second approach we evaluate model’s predictive efficiency. We illustrate those perspectives with a simulation study, a non linear model and a longitudinal data model.
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    Multiple scenarios of quality of life index using fuzzy linguistic quantifiers: the case of 85 countries in Numbeo
    (Mathematics, 2022) Shu, Ziwei; Carrasco González, Ramón Alberto; Portela García-Miguel, Javier; Manuel Sánchez-Montañés, Manuel; Chiclana, Francisco
    In economic development, in addition to comparing the gross domestic product (GDP) between nations, it is critical to assess the quality of life to gain a holistic perspective of their different aspects. However, the quality of life index (QOLI) is a subjective term that can be difficult to quantify. Although this composite index is typically calculated using universal weights proposed by experts to aggregate indicators, such as safety indexes, healthcare indexes, pollution indexes, and housing indicators, it is complicated to balance multiple dimensions whose weights are adjusted to account for different countries’ circumstances. Therefore, this paper aims to construct various scenarios of the QOLI, using linguistic quantifiers of the ordered weighted averaging (OWA) operator, and the 2-tuple linguistic model. Numbeo, one of the largest quality of life information databases, was used in this paper to estimate the QOLI in 85 countries. Uncertainty and sensitivity analyses were employed to assess the robustness of the QOLI. The results of the proposed model are compared with those obtained using the Numbeo formulation. The results show that the proposed model increases the linguistic interpretability of the QOLI, and obtains different QOLIs, based on diverse country contexts.
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    A Bayesian Test For The Mean Of The Power Exponential Distribution
    (Communications in statistics. Theory and methods, 2008) Gómez Villegas, Miguel Ángel; Portela García-Miguel, Javier; Sanz San Miguel, Luis
    In this article, we deal with the problem of testing a point null hypothesis for the mean of a multivariate power exponential distribution. We study the conditions under which Bayesian and frequentist approaches can match. In this comparison it is observed that the tails of the model are the key to explain the reconciliability or irreconciliability between the two approaches.
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    Aplicación de métodos numéricos en inferencia bayesiana : implementación de un método bayesiano robusto
    (2004) Portela García-Miguel, Javier; Gómez-Villegas, Miguel Ángel
    El objetivo de este trabajo es desarrollar técnicas para la aplicación de la familia de distribuciones Potencial Exponencial, dentro del marco de la Inferencia Bayesiana, con especial incidencia en el problema de selección de modelos bayesianos. En particular, se presenta una generalización de esta familia, y se desarrollan un método Monte-Carlo, un método de simulación vía muestreo de Gibbs y un método de simulación que utiliza una representación en mixturas de esta familia, para establecer inferencias sobre las distribuciones a posteriori surgidas del planteamiento bayesiano. A través del parámetro de control de curtosis puede plantearse un contraste bayesiano de hipótesis nula puntual para contrastar normalidad de los datos en el marco de esta familia. Se plantea este contraste desde un enfoque basado en medidas de discrepancia, presentando una medida basada en el cálculo de regiones de máxima densidad a posteriori y haciendo un estudio de simulación. Finalmente se aplican las técnicas desarrolladas anteriormente en el marco de modelos bayesianos, concretamente en modelos lineales, modelos no lineales, y modelos longitudinales, poniendo de relieve el interés de la utilización de esta familia en problemas de robustez en modelos bayesianos
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    Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks
    (Sensors, 2016) Portela García-Miguel, Javier; García Villalba, Luis Javier; Silva Trujillo, Alejandra Guadalupe; Sandoval Orozco, Ana Lucila; Kim, Tai-Hoon
    Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.
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    Project number: 118
    Análisis de la diferencia de género en el rendimiento académico en Matemáticas en los grados de ADE y FBS
    () García Pineda, María Pilar; Almaraz Luengo, Elena Salome; Blanco García, Susana; De Frutos Espinosa, María Cristina; García Villalba, Luis Javier; Martínez Hernández, Luis Alberto; Pérez Arteaga, Sandra; Portela García-Miguel, Javier; Povedano Álvarez, Daniel; Rodríguez Palanquex, María Cruz; Sandoval Orozco, Ana Lucila; Turrado García, Fernando
    El objetivo es analizar con evidencias empíricas, obtenidas mediante herramientas estadísticas e informáticas, las posibles diferencias de género en el rendimiento académico en las asignaturas de Matemáticas, en grados no STEM, como son ADE y FBS