Centro de Gestión de la Calidad y del Cambio
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- PublicationRisk Scoring Models for Trade Credit in Small and Medium Enterprises(Springer International Publishing, 2015-05) Terrádez Gurrea, Manuel; Kizys, Renatas; Juan Pérez, Ángel Alejandro; Debón Aucejo, Ana María; Sawik, Bartosz; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Centro de Gestión de la Calidad y del Cambio; National Science Centre, Polonia; AGH University of Science and Technology, PoloniaTrade credit refers to providing goods and services on a deferred payment basis. Commercial credit management is a matter of great importance for most small and medium enterprises (SMEs), since it represents a significant portion of their assets. Commercial lending involves assuming some credit risk due to exposure to default. Thus, the management of trade credit and payment delays is strongly related to the liquidation and bankruptcy of enterprises. In this paper we study the relationship between trade credit management and the level of risk in SMEs. Despite its relevance for most SMEs, this problem has not been sufficiently analyzed in the existing literature. After a brief review of existing literature, we use a large database of enterprises to analyze data and propose a multivariate decision-tree model which aims at explaining the level of risk as a function of several variables, both of financial and non-financial nature. Decision trees replace the equation in parametric regression models with a set of rules. This feature is an important aid for the decision process of risk experts, as it allows them to reduce time and then the economic cost of their decisions.
- PublicationDesarrollo de una metodología para la formación y evaluación “continua” en pensamiento crítico(Editorial Universitat Politècnica de València, 2018-09-26) Vidal Puig, Santiago; Barceló Cerdá, Susana; Calduch Llosa, Ángeles; Debón Aucejo, Ana María; Calduch Losa, Maria de los Angeles; Villa Juliá, María Fulgencia; Instituto Universitario Mixto de Tecnología de Informática; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Instituto de Diseño para la Fabricación y Producción Automatizada; Centro de Gestión de la Calidad y del Cambio; Escuela Técnica Superior de Ingeniería Informática; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Grupo de Ingeniería Estadística Multivariante GIEM[EN] In this study, we shall describe a teaching experience carried out by a group of lecturers in the Statistics Department. These lecturers are involved in the training and assessment of “critical thinking” skills as part of the institutional project centred on generic skills at the Universitat Politècnica de València. The objective of this experience was to promote the understanding, development and application of the critical thinking skills in the students. Different activities linked to the abilities involved in critical thinking are proposed to the students throughout the academic year. The activities require ongoing assessment from the formative point of view. Thus, the students are aware of their own progress. Additionally, students are evaluated in the exams with questions in different formats (PoliformaT exams, tests and peer review). Suitable materials and activities for training and assessment of critical thinking have been developed. Finally the teaching staff and the students’ opinions have been collected through surveys.
- PublicationExploring essential variables for successful and unsuccessful football teams in the "Big Five" with multivariate supervised techniques(Università del Salento, 2022-05) Malagón-Selma, María del Pilar; Debón Aucejo, Ana María; Ferrer Riquelme, Alberto José; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería Industrial; Centro de Gestión de la Calidad y del Cambio; Grupo de Ingeniería Estadística Multivariante GIEM; Universitat Politècnica de València[EN] This research proposes multivariate techniques for discovering the game actions that contribute to the final ranking of football teams. This study uses data from the "Big Five" teams that competed in the Bundesliga First Division, Premier League, LaLiga, Ligue 1, and Serie A in the 2018-2019 season. The principal component analysis is used for outlier detection and for providing an overall preliminary insight. The statistically significant game actions of the top and bottom teams were studied using three supervised multivariate techniques, namely the partial least squares discriminant analysis, random forest and logistic regression. The partial least squares discriminant analysis model best identifies the variables with the most statistically significant contribution to a team's success or failure. The results were compared with those obtained using two-sample univariate tests (such as the Student's t-test or the Mann-Whitney test), demonstrating the advantages of multivariate approaches over univariate approaches. The results indicate that the top teams have both offensive and defensive power, and emphasise the high number of attacking actions; in contrast, the bottom teams have weak defences and few offensive actions.
- PublicationStatistical methods to compare mortality for a group with non-divergent populations. Application to Spanish regions(Springer Verlag (Germany), 2011-12-06) Debón Aucejo, Ana María; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Gestión de la Calidad y del Cambio; Ministerio de Ciencia e Innovación[EN] This paper develops a model to compare geographical differences in the mortality of related regions, taking into account the interdependence between them. Additionally, the model allows us to provide an adequate solution for studying the mortality of a group pertaining to a larger population. It should therefore be possible to improve the mortality analysis for the regions in a country by taking into account the patterns within that country. Using official data from the Spanish National Institute of Statistics (Instituto Nacional de Estadística, INE), we applied a modification of the Lee¿Carter model to Spanish regions. The results of this model were then compared with other similar models such as the logit Brass, Li and Lee and Russolillo¿Giordano¿Haberman. One interesting feature of our model is its simplicity, as the comparison of mortality patterns is accomplished by means of a simple index.
- PublicationModelos de Machine Learning y estadística multivariante para predecir la posición de los equipos de primera división(Universitat de València, 2022) Malagón-Selma, María del Pilar; Debón Aucejo, Ana María; Ferrer Riquelme, Alberto José; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería Industrial; Centro de Gestión de la Calidad y del Cambio; Grupo de Ingeniería Estadística Multivariante GIEM; UNIVERSIDAD POLITECNICA DE VALENCIA[EN] This research aims to find which models of Machine Learning and Multivariate Statistics have a greater predictive capacity when deciding what the team's classification will be at the end of the season. The teams that competed in the first division of the Bundesliga, Premier League, LaLiga, Ligue 1 and Serie A throughout the 2018-2019 season have been studied. The badly classified teams by the best of the models, the Random Forest with balanced data, were analyzed in-depth to determine the game's actions that caused the classification error. The results indicate that, generally, the effectiveness in front of goal and the possession of the ball are the statistics in which badly classified teams differ the most with the average of their real position. In conclusion, this research shows how Machine Learning and Multivariate Statistical techniques can be used successfully to discriminate between Top and Bottom teams competing in the best leagues in the world
- PublicationFault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data(Elsevier, 2012-04) Debón Aucejo, Ana María; García Díaz, Juan Carlos; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería Industrial; Centro de Gestión de la Calidad y del Cambio; Universitat Politècnica de València[EN] Advanced statistical models can help industry to design more economical and rational investment plans. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing. Increasingly stringent quality requirements in the automotive industry also require ongoing efforts in process control to make processes more robust. Robust methods for estimating the quality of galvanized steel coils are an important tool for the comprehensive monitoring of the performance of the manufacturing process. This study applies different statistical regression models: generalized linear models, generalized additive models and classification trees to estimate the quality of galvanized steel coils on the basis of short time histories. The data, consisting of 48 galvanized steel coils, was divided into sets of conforming and nonconforming coils. Five variables were selected for monitoring the process: steel strip velocity and four bath temperatures. The present paper reports a comparative evaluation of statistical models for binary data using Receiver Operating Characteristic (ROC) curves. A ROC curve is a graph or a technique for visualizing, organizing and selecting classifiers based on their performance. The purpose of this paper is to examine their use in research to obtain the best model to predict defective steel coil probability. In relation to the work of other authors who only propose goodness of fit statistics, we should highlight one distinctive feature of the methodology presented here, which is the possibility of comparing the different models with ROC graphs which are based on model classification performance. Finally, the results are validated by bootstrap procedures.
- PublicationA minimally invasive methodology based on morphometric parameters for day 2 embryo quality assessment(Elsevier, 2014) Molina Botella, María Inmaculada; Lázaro Ibáñez, Elisa; Pertusa, José; Debón Aucejo, Ana María; Martinez Sanchis, Juan Vicente; Pellicer Bofill, Antonio Joaquin; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Gestión de la Calidad y del Cambio[EN] The risk of multiple pregnancy to maternal fetal health can be minimized by reducing the number of embryos transferred. New tools for selecting embryos with the highest implantation potential should be developed. The aim of this study was to evaluate the ability of morphological and morphometric variables to predict implantation by analysing images of embryos. This was a retrospective study of 135 embryo photographs from 112 IVF ICSI cycles carried out between January and March 2011. The embryos were photographed immediately before transfer using Cronus 3 software. Their images were analysed using the public program ImageJ. Significant effects (P < 0.05), and higher discriminant power to predict implantation were observed for the morphometric embryo variables compared with morphological ones. The features for successfully implanted embryos were as follows: four cells on day 2 of development; all blastomeres with circular shape (roundness factor greater than 0.9), an average zona pellucida thickness of 13 µm and an average of 17695.1 µm2 for the embryo area. Embryo size, which is described by its area and the average roundness factor for each cell, provides two objective variables to consider when predicting implantation. This approach should be further investigated for its potential ability to improve embryo scoring.
- PublicationOn the use of Statistical Process Control in Monitoring Mortality. An Application to European Countries(Instituto Nacional de Estadística, 2016) Giner Bosch, Vicent; Cabrerizo Cabanos, Majarlika María; Debón Aucejo, Ana María; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería Industrial; Centro de Gestión de la Calidad y del Cambio; Ministerio de Economía y Competitividad[EN] The evolution of mortality is a key global concern from both an economic and social point of view. In particular, being able to detect and predict changes in mortality compared to its expected behaviour as accurately as possible is a desirable goal. In this context, the standardized mortality ratio (SMR) is commonly used in order to measure the mortality of a country with regard to its neighbouring countries at a given moment in time. In this work, we address the study of the evolution of the SMR of a country over time, modelled as a time series. The joint use of time series and statistical process control (SPC) techniques to model and monitor the behaviour of the SMR is explored. Both approaches are relevant and complementary. On one hand, time series are an appropriate tool to study and characterize the evolution of SMR over time and to forecast it. On the other hand, SPC permits detection of significant changes in the trend of the variable being monitored. More precisely, we suggest monitoring the residuals of the fitted time series model using control charts. We present and discuss the results of applying our proposal to mortality data for European countries in a 20-year period. These results show the relevance of our approach and delineate our next research steps. Finally, the use of other approaches combining time series and SPC techniques is also outlined.
- PublicationVerificación de la evolución de la mortalidad a través de los años(Asociación Española de Profesores Universitarios para la Economía y la Empresa, 2004) Debón Aucejo, Ana María; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Gestión de la Calidad y del Cambio[ES] Típicos enfoques de análisis y graduación de la mortalidad se basan en la no dinamicidad, y por tanto estabilidad de ésta, para periodos largos de tiempo. Por el contrario, este artículo está enfocado sobre un factor relevante en la evolución de la misma, como es el tiempo cronológico. Así pues, el objetivo de este trabajo es analizar la influencia que tiene el tiempo cronológico en las probabilidades anuales de muerte de un individuo de edad x, qx, cuando las probabilidades están tanto graduadas (suavizadas) como sin graduar (sin suavizar). Para ello, se calculan las estimaciones de dichas probabilidades con datos del INE de la Comunidad Valenciana, referidos estos a diferentes periodos de tiempo. Los resultados del estudio empírico parecen confirmar la existencia de diferencias entre las experiencias de mortalidad y comportamientos correspondientes a periodos de tiempo cronológico distintos tanto para hombres como para mujeres. Estas conclusiones ratifican una vez más, la utilidad de las tablas de mortalidad dinámicas en el ámbito de las operaciones actuariales
- PublicationProyección de los indicadores de mortalidad para España(Instituto Nacional de Estadística, 2015) Debón Aucejo, Ana María; Martínez Ruiz, Francisco; Montes Suay, Francisco; Moshuk, Marta; Facultad de Administración y Dirección de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Gestión de la Calidad y del Cambio; Ministerio de Economía y Competitividad[ES] El presente estudio expone los resultados obtenidos al aplicar el modelo Lee- Carter original y sus extensiones (con dos términos y con efecto cohorte) a las probabilidades de muerte para la población española entre los años 1991 y 2010. Estos modelos se ajustaron a los datos elaborados por el INE separadamente para varones y mujeres. Por otra parte, se calcularon los índices generales de mortalidad y sus proyecciones a futuro por medio de series temporales ARIMA entre los años 2011 y 2030. A partir de la comparación de los modelos con medidas de bondad de ajuste se constató el modelo de Lee-Carter con efecto cohorte proporciona mejores resultados de la predicción de las probabilidades de muerte que el modelo de Lee- Carter original o el modelo con dos términos. La comparación muestra que, a pesar de la mayor complejidad de los modelos extendidos, éstos pueden explicar de mejor modo las tendencias pasadas y, por tanto, las futuras. También se calcularon dos indicadores de mortalidad: la esperanza de vida y el índice de Gini. La mejora de ambos refleja de modo directo el incremento en el estándar de vida en la población española durante las últimas décadas.