Repositorio Institucional Universidad EAFIT ::Examinando por Autor "Laniado H."

Examinando por Autor "Laniado H."

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Airline choice model for an international round-trip flight considering outbound and return flight schedules
(Warsaw University of Technology, 2020-01-01) Munoz C.; Laniado H.; Córdoba J.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
This paper quantified the impact of outbound and return flight schedule preferences on airline choice for international trips. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and flight schedule. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. Therefore, this study introduces attributes related to return flight characteristics and round-trip flight schedule interaction into the airline choice models, which have not previously been reported in the literature. We developed a stated preference survey that includes round-trip fares based on flight schedule combinations and the number of days prior to departure fares was purchased. We applied modelling techniques using a set of stated preference data. A mixed logit model was tested for the presence of heterogeneity in passengers' preferences. Our results indicated that models with attributes related to return flight and its interaction with outbound flight attributes have a superior fit compared with models only based on attributes reported in the literature review. The model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flight are significantly affecting passenger choice behaviour in international round-trip flights. Sensitivity analysis of airline service characteristics and their marketing implications are conducted. The analysis reports seven policies with the greatest impact on each airline choice probabilities. It shows that by reducing travel time and airfare and by adopting an afternoon and night schedule preference for outbound and return flight, respectively, the highest probability on airline choice would be reached. This research contributes to the current literature by enhancing the understanding of how passengers choose airlines, considering both outbound and inbound journey characteristics. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions. © 2020 Warsaw University of Technology. All rights reserved.
Airline choice model for an international round-trip flight considering outbound and return flight schedules
(Warsaw University of Technology, 2020-01-01) Munoz C.; Laniado H.; Córdoba J.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
This paper quantified the impact of outbound and return flight schedule preferences on airline choice for international trips. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and flight schedule. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. Therefore, this study introduces attributes related to return flight characteristics and round-trip flight schedule interaction into the airline choice models, which have not previously been reported in the literature. We developed a stated preference survey that includes round-trip fares based on flight schedule combinations and the number of days prior to departure fares was purchased. We applied modelling techniques using a set of stated preference data. A mixed logit model was tested for the presence of heterogeneity in passengers' preferences. Our results indicated that models with attributes related to return flight and its interaction with outbound flight attributes have a superior fit compared with models only based on attributes reported in the literature review. The model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flight are significantly affecting passenger choice behaviour in international round-trip flights. Sensitivity analysis of airline service characteristics and their marketing implications are conducted. The analysis reports seven policies with the greatest impact on each airline choice probabilities. It shows that by reducing travel time and airfare and by adopting an afternoon and night schedule preference for outbound and return flight, respectively, the highest probability on airline choice would be reached. This research contributes to the current literature by enhancing the understanding of how passengers choose airlines, considering both outbound and inbound journey characteristics. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions. © 2020 Warsaw University of Technology. All rights reserved.
An alternative model to explain the vectorial capacity using as example Aedes aegypti case in dengue transmission
(Elsevier BV, 2019-01-01) Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
Vectorial capacity (VC), as a concept that describes the potential of a vector to transmit a pathogen, has had historical problems related to lacks in dimensional significance and high error propagation from parameters that take part in the model to output. Hence, values estimated with those equations are not sufficiently reliable to consider in control strategies or vector population study. In this paper, we propose a new VC model consistent at dimensional level, i.e., the definition and the equation of VC have same and consistent units, with a parameter estimation method and mathematical structure that reduces the uncertainty in model output, using as a case of study an Aedes aegypti population of the municipality of Bello, Colombia. After a literature review, we selected one VC equation following biological, measurability and dimensional criteria, then we rendered a local and global sensitivity analysis, identifying the mortality rate of mosquitoes as a target component of the equation. Thus, we studied the Weibull and Exponential distributions as probabilistic models that represent the expectation of mosquitoes infective life, intending to include the best distribution in a selected VC structure. The proposed mortality rate estimation method includes a new parameter that represents an increase or decrease in vector mortality, as it may apply. We noticed that its estimation reduces the uncertainty associated with the expectation of mosquitoes' infective life expression, which also reduces the output range and variance in almost a half. Virology; Applied mathematics; Health sciences; Epidemiology; Infectious disease; Mortality; Uncertainty analysis; Vectorial capacity; Sensitivity analysis; Dengue © 2019 The Authors
An alternative model to explain the vectorial capacity using as example Aedes aegypti case in dengue transmission
(Elsevier BV, 2019-01-01) Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y Aplicaciones
Vectorial capacity (VC), as a concept that describes the potential of a vector to transmit a pathogen, has had historical problems related to lacks in dimensional significance and high error propagation from parameters that take part in the model to output. Hence, values estimated with those equations are not sufficiently reliable to consider in control strategies or vector population study. In this paper, we propose a new VC model consistent at dimensional level, i.e., the definition and the equation of VC have same and consistent units, with a parameter estimation method and mathematical structure that reduces the uncertainty in model output, using as a case of study an Aedes aegypti population of the municipality of Bello, Colombia. After a literature review, we selected one VC equation following biological, measurability and dimensional criteria, then we rendered a local and global sensitivity analysis, identifying the mortality rate of mosquitoes as a target component of the equation. Thus, we studied the Weibull and Exponential distributions as probabilistic models that represent the expectation of mosquitoes infective life, intending to include the best distribution in a selected VC structure. The proposed mortality rate estimation method includes a new parameter that represents an increase or decrease in vector mortality, as it may apply. We noticed that its estimation reduces the uncertainty associated with the expectation of mosquitoes' infective life expression, which also reduces the output range and variance in almost a half. Virology; Applied mathematics; Health sciences; Epidemiology; Infectious disease; Mortality; Uncertainty analysis; Vectorial capacity; Sensitivity analysis; Dengue © 2019 The Authors
Author Correction: Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks (Scientific Reports, (2018), 8, 1, (6955), 10.1038/s41598-018-24874-2)
(Nature Publishing Group, 2019-01-01) Azcorra A.; Chiroque L.F.; Cuevas R.; Anta A.F.; Laniado H.; Lillo R.E.; Romo J.; Sguera C.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
The original version of this Article contained an error in Affiliation 3, which was incorrectly given as ‘Department of Mathematical Sciences, Universidad EAFIT, Universidad Nacional de Colombia, Medellín, Colombia’. The correct affiliation is listed below: Department of Mathematical Sciences, Universidad EAFIT, Medellín, Colombia This error has now been corrected in the HTML and PDF versions of the Article and in the accompanying Supplementary Material file. © 2019, The Author(s).
Estimación robusta de la matriz de covarianza para la selección óptima de portafolios de inversión
(UNIV NAC COLOMBIA, FAC NAC MINAS, 2018-01-01) Gutiérrez-Sepúlveda D.; Laniado H.; Medina-Hurtado S.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
The selection of portfolios under the Media-Variance (M-V) model work bad when it is exposed to the presence of atypical data that generate error estimation of the parameters In order to minimize this estimation error, we investigate new robust methodologies and their financial performance in terms off the ratio Sharpe, of the turnover index and of the variance. The estimation of the covariance matrix parameter is done with three different robust methods that seek to minimize the instability generated by atypical data, the first is the great contribution of this research, which consists in shrinking the covariance matrix with a cut-out to the mean, the second and third methods are chi-square cut-outs in the distance of Mahalanobis and Minimum Determinant of the Covariance Matrix (MCD) respectively. © The author; licensee Universidad Nacional de Colombia.
Multivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimators
(Springer Verlag, 2019-01-01) Cabana E.; Lillo R.E.; Laniado H.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
A collection of robust Mahalanobis distances for multivariate outlier detection is proposed, based on the notion of shrinkage. Robust intensity and scaling factors are optimally estimated to define the shrinkage. Some properties are investigated, such as affine equivariance and breakdown value. The performance of the proposal is illustrated through the comparison to other techniques from the literature, in a simulation study and with a real dataset. The behavior when the underlying distribution is heavy-tailed or skewed, shows the appropriateness of the method when we deviate from the common assumption of normality. The resulting high true positive rates and low false positive rates in the vast majority of cases, as well as the significantly smaller computation time show the advantages of our proposal. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
On the estimation of extreme directional multivariate quantiles
(Marcel Dekker Inc., 2019-01-01) Torres R.; Di Bernardino E.; Laniado H.; Lillo R.E.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
In multivariate extreme value theory (MEVT), the focus is on analysis outside of the observable sampling zone, which implies that the region of interest is associated to high risk levels. This work provides tools to include directional notions into the MEVT, giving the opportunity to characterize the recently introduced directional multivariate quantiles (DMQ) at high levels. Then, an out-sample estimation method for these quantiles is given. A bootstrap procedure carries out the estimation of the tuning parameter in this multivariate framework and helps with the estimation of the DMQ. Asymptotic normality for the proposed estimator is provided and the methodology is illustrated with simulated data-sets. Finally, a real-life application to a financial case is also performed. © 2019, © 2019 Taylor & Francis Group, LLC.
Robust regression based on shrinkage with application to Living Environment Deprivation
(Springer, 2020-01-01) Cabana E.; Lillo R.E.; Laniado H.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
A robust estimator is proposed for the parameters that characterize the linear regression problem. It is based on the notion of shrinkages, often used in Finance and previously studied for outlier detection in multivariate data. A thorough simulation study is conducted to investigate: the efficiency with Normal and heavy-tailed errors, the robustness under contamination, the computational time, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socioeconomic data-set about the Living Environment Deprivation of areas in Liverpool (UK), are studied. The results from the simulations and the real data examples show the advantages of the proposed robust estimator in regression. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
Robust regression based on shrinkage with application to Living Environment Deprivation
(Springer, 2020-01-01) Cabana E.; Lillo R.E.; Laniado H.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
A robust estimator is proposed for the parameters that characterize the linear regression problem. It is based on the notion of shrinkages, often used in Finance and previously studied for outlier detection in multivariate data. A thorough simulation study is conducted to investigate: the efficiency with Normal and heavy-tailed errors, the robustness under contamination, the computational time, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socioeconomic data-set about the Living Environment Deprivation of areas in Liverpool (UK), are studied. The results from the simulations and the real data examples show the advantages of the proposed robust estimator in regression. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers
(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.
Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers
(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.
Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers
(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.
S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem
(Public Library of Science, 2018-11-27) Duque J.C.; Laniado H.; Polo A.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP. © 2018 Duque et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem
(Public Library of Science, 2018-11-27) Duque J.C.; Laniado H.; Polo A.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP. © 2018 Duque et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks
(Nature Publishing Group, 2018-05-03) Azcorra A.; Chiroque L.F.; Cuevas R.; Fernández Anta A.; Laniado H.; Lillo R.E.; Romo J.; Sguera C.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
Billions of users interact intensively every day via Online Social Networks (OSNs) such as Facebook, Twitter, or Google+. This makes OSNs an invaluable source of information, and channel of actuation, for sectors like advertising, marketing, or politics. To get the most of OSNs, analysts need to identify influential users that can be leveraged for promoting products, distributing messages, or improving the image of companies. In this report we propose a new unsupervised method, Massive Unsupervised Outlier Detection (MUOD), based on outliers detection, for providing support in the identification of influential users. MUOD is scalable, and can hence be used in large OSNs. Moreover, it labels the outliers as of shape, magnitude, or amplitude, depending of their features. This allows classifying the outlier users in multiple different classes, which are likely to include different types of influential users. Applying MUOD to a subset of roughly 400 million Google+ users, it has allowed identifying and discriminating automatically sets of outlier users, which present features associated to different definitions of influential users, like capacity to attract engagement, capacity to attract a large number of followers, or high infection capacity. © 2018 The Author(s).

Examinando por Autor "Laniado H."

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