Research

At IBiDat, we perform both fundamental and applied research across many different areas: Business, Computer Science, Machine Learning, Mathematics and Statistics. Our team is comprised of interdisciplinary researchers. Below you can find our publications.

Títle Authors Journal
Fuel management operations planning in fire management: A bileveloptimisation approach Liberatore, Federico , et al. Safety Science 137 (2021): 105181
Characterization of the summer surface mesoscale dynamics at Dome F, Antarctica González, S. , Vasallo, F., Sanz, P., Quesada, A. and Justel, A. Atmospheric Research 259 (2021): 105699 doi.org/10.1016/j.atmosres.2021.105699
Local meteorological conditions,shapeand desiccation influence dispersal capabilities for airborne microorganisms Galbán, S., Justel, A. , González, S. and Quesada, A. Science of The Total Environment 780 (2021):  146653 doi.org/10.1016/j.scitotenv.2021.146653
Heterogeneity of Microbial Communities in SoilsFromthe Antarctic Peninsula Region Almela, P., Justel, A. and Quesada, A. Frontiers in Microbiology (2021) doi.org/10.3389/fmicb.2021.628792
Circulant singular spectrum analysis: A new automated procedure for signal extraction Bogalo, J., Poncela, P. and Senra, E.
Signal Processing 179 (2021): 107824
Title Authors Journal
A class of Itô diffusions with known terminal value and specified optimal barrier D’Auria,B. and Ferriero, A.  Mathematics, 8(1), p. 123-135 (2020)
Is managerial entrenchment always bad and corporate social responsibility always good?A cross-national examination of their combined influence on shareholder value Surroca, J.A., Aguilera,R.V., Desender,K. and Tribó, J.A. Strategic Managent Journal , 1-30 (2020)
Robust regression based on shrinkage with application to Living Environment Deprivation Cabana, E., Laniado H. and Lillo, R.E Stoch Environ Res Risk Assess (2020). https://doi.org/10.1007/s00477-020-01774-4
Blood transfusion prediction using restricted Boltzmann machines Cifuentes, J., Yao,Y., Yan, M. and Zheng, B. Computer Methods in Biomechanics and Biomedical Engineering (2020), DOI: 10.1080/10255842.2020.1742709
A Mathematical Pre-Disaster Model with Uncertainty and Multiple Criteria for Facility Location and Network Fortification Monzón, J., Liberatore, F. and Vitoriano, B. Mathematics 2020, 8, 529
Advanced Statistical Techniques for Noninvasive Hyperglycemic States Detection in Mice Using Millimeter-Wave Spectroscopy Moreno-Oyervides. A., Aguilera-Morillo, M.C., Larcher, F., Krozer, V. and Acedo, P. IEEE Transactions on Terahertz Science and Technology, 10(3), pp. 237-245 (2020)
Wind Power Long-Term Scenario Generation Considering Spatial-Temporal Dependencies in Coupled Electricity Markets Marulanda, G., Bello, A., Cifuentes, J. and Reneses, J. Energies 2020, 13, 3427
Air Temperature Forecasting Using Machine Learning Techniques: A Review. Cifuentes, J., Marulanda, G., Bello, A., and Reneses, J. Energies 2020, 13(16), 4215
Detection of Barriers to Mobility in the Smart City Using Twitter Sánchez-Ávila M., Mouriño-García M.A., Fisteus, J.A. and Sánchez Fernández, L. IEEE Access, vol. 8, pp. 168429-168438, 2020, doi: 10.1109/ACCESS.2020.3022834.
Cooperation, social norm internalization, and hierarchical societies Lozano P.,Gavrilets, S. and Sánchez, A. Sci Rep 10, 15359 (2020). https://doi.org/10.1038/s41598-020-71664-w
Optimal classification of Gaussian processes in homo- and heteroscedastic settings Torrecilla, J.L, Ramos-Carreño, C., Sánchez-Montañés, M. and Suárez,A. Stat Comput 30, 1091–1111 (2020). https://doi.org/10.1007/s11222-020-09937-7
The turning point and end of an expanding epidemic cannot be precisely forecast Castro. M., Ares, S.,Cuesta, J.A. and Manrubia, S. Proceedings of the National Academy of Sciences Oct 2020, 202007868; DOI: 10.1073/pnas.2007868117
Complex networks to understand the past: the case of roads in Bourbon Spain Pablo‑Martí, F., Alañón‑Pardo, A. and Sánchez A. Cliometrica DOI:https://doi.org/10.1007/s11698-020-00218-x/td>
A Portfolio Perspective on the Multitude of Firm Characteristics Martin-Utrera,A., DeMiguel,V., Nogales, F.J. and Uppal, R. Review of Financial Studies, 33(5), pp. 2180-2222, 2020
Hierarchical Clustering for Smart Meter Electricity Loads based on Quantile Autocovariances Alonso, A.M., Nogales, F.J. and Ruiz, C. IEEE Transactions on Smart Grid, 11(5), pp. 4522-4530, 2020
Shuffle, Cut, and Learn: Crypto Go, A Card Game for Teaching Cryptography González-Tablas, A.I., González Vasco, M.I., Cascos, I., and Planet Palomino, A Mathematics, 8(11), 1993
Competing for congestible goods: experimental evidence on parking choice Pereda,M., Ozaita,J.,Stavrakakis, I. and Sánchez, A./td> Scientific Reports volume 10, Article number: 20803 (2020)
Gait-Based Identification Using Deep Recurrent Neural Networks and Acceleration Patterns Peinado-Contreras, A. and Munoz-Organero, M./td> Sensors 2020, 20(23), 6900; https://doi.org/10.3390/s20236900
Title Authors Journal
Large-Scale Analysis of User Exposure to Online Advertising on Facebook Arrate Galán, A., José González Cabañas J., Cuevas A., María Calderón M. and Cuevas Rumin R. IEEE Access ( Volume 7) pp11959 – 11971 (2019)
Group size effects and critical mass in public goods games Valerio Capraro, M.Pand Sánchez Sánchez, A. Scientific Reports volume 9, Article number: 5503 (2019)
Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model. Virbickaite, A., Lopes, H., Ausín, M.C. and Galeano, P. Econometrics Reviews (2019), DOI: 10.1080/07474938.2018.1514022.
Parallel Bayesian inference for high dimensional dynamic factor copulas. Nguyen,H., Ausín, M.C. and Galeano, P. Journal of Financial Econometrics, 1, 118-151. (2019)
Disentangling the role of variance and covariance information in portfolio selection problems. Santos, A.P. Quantitative Finance, 19(1),(2019)
An Iterative Sparse-Group Lasso. Laria, J.C., Aguilera-Morillo, M.C. and Lillo, R.E. Journal of Computational and Graphical Statistics, (2019) DOI: 10.1080/10618600.2019.1573687
Fitting procedure for the two-state Batch Markov modulated Poisson process. Yera, Y.G.,Lillo, R.E. and Ramírez-Cobo, P. European Journal of Operational Research, (2019) DOI: 10.1016/j.ejor.2019.04.018
An experimental study of network effects on coordination in asymmetric games Broere, J., Buskens,V., Henk Stoof, H. and Sánchez, A. Scientific Reports, Volume 9, Article number: 6842 (2019)
A Kendall correlation coefficient between functional data Valencia, D., Lillo, R.E and Romo, J. Advances in Data Analysis and Classification (2019)
DOI:10.1007/s11634-019-00360-z
Outlier Detection in Wearable Sensor Data for Human Activity Recognition (HAR) Based on DRNNs Muñoz, M. IEEE (2019)
DOI 10.1109/ACCESS.2019.2921096
Evolution and study of a copycat effect in intimate partner homicides: A lesson from Spanish femicides Torrecilla, J.L.,Quijano-Sánchez,L.,Liberatore F.,López-Ossorio, J.J. and González-Álvarez, J.L PLOS ONE (2019)
https://doi.org/10.1371/journal.pone.0217914
Clustering time series by linear dependency Alonso A. M and Peña D. Statistics and Computing (2019) 29:655–676
https://doi.org/10.1007/s11222-018-9830-6
Carbon pathways through the food web of a microbial mat from Byers Peninsula, Antarctica Almela, P., Velázquez, D., Rico, E., Justel ,A. and Quesada, A. Frontiers in Microbiology (2019)
doi.org/10.3389/fmicb.2019.00628
Using Recurrent Neural Networks to Compare Movement Patterns in
ADHD and Normally Developing Children Based on Acceleration Signals from the Wrist and Ankle
Muñoz-Organero M. , Powell L. , Heller B., Harpin V. and Jack Parker J. Sensors 2019, 19(13), 2935;
https://doi.org/10.3390/s19132935
Optimal sales-mix and generation plan in a two-stage electricity market Falbo, P. and Ruiz, C. Energy Economics
Volume 78, February 2019, Pages 598-614
Large scale and information effects on cooperation in public good games Pereda, M.,Tamarit, I., Antonioni, A., Cuesta, J.A., Hernández, P. and Sánchez, A. Scientific Reports volume 9, Article number: 15023 (2019)
Detecting and Monitoring Hate Speech in Twitter Pereira-Kohatsu, J.C., Quijano-Sánchez,L., Federico Liberatore, F. and Camacho-Collados, M. Sensors 2019, 19(21), 4654; https://doi.org/10.3390/s19214654
Weather Observations of Remote Polar Areas Using an AWS Onboard a Unique Zero-Emissions Polar Vehicle. Gonzalez, S., Bañon, M., Albero, J.V., Larramendi, R., Moreno, H., Vasallo, F., Sanz, P., Quesada, A., and Justel, A. Bulletin of the American Meteorological Association https://doi.org/10.1175/BAMS-D-19-0110.1
On Optimal Tests for Rotational Symmetry Against New Classes of Hyperspherical Distributions. García-Portugués, E., Paindaveine , D.and Verdebout, T. Journal of the American Statistical Association https://doi.org/10.1080/01621459.2019.1665527
Data science, big data and statistics. Galeano, P. and Peña,D. TEST 28, 289–329 (2019). https://doi.org/10.1007/s11749-019-00651-9
Empirical Dynamic Quantiles for Visualization of High-Dimensional Time Series. Peña,D, Tsay, R.S.and Zamar, R. Technometrics, 61:4, 429-444, DOI: 10.1080/00401706.2019.1575285
Forecasting Multiple Time Series With One-Sided Dynamic Principal Components. Peña,D, Smucler, E. and Yohai, V.J Journal of the American Statistical Association, 114:528, 1683-1694, DOI: 10.1080/01621459.2018.1520117
Rank tests for functional data based on the epigraph, the hypograph and associated graphical representations Franco-Pereira, A. and Lillo R.E. Advances in Data Analysis and Classification(2019) https://doi.org/10.1007/s11634-019-00380-9
Early, Non-Invasive Sensing of Sustained Hyperglycemia in Mice Using Millimeter-Wave Spectroscopy Moreno-Oyervides, A., Martín-Mateos, P., Aguilera-Morillo, M.C., Ulisse, G., Arriba, M.C, Durban, M., Del Rio, M., Larcher, F. Krozer, V. and Acedo, P. Sensors, 19(15). pii: E3347. doi: 10.3390/s19153347. (2019)
Title Authors Journal
Measurement Errors in R Ucar, I., Pebesma, E., Azcorra, A. The R Journal, 10 (2), 549–557.
Resource heterogeneity leads to unjust effort distribution in climate change mitigation Vicens, J., Bueno-Guerra,N., Gutierrez-Roig, M., Gracia-Lázaro, C., Gómez-Gardeñes, J., Perelló, J., Sánchez, A., Moreno, Y. and Duch, J. PLOS ONE 13(10): e0204369 (2018).
Cognitive Resource Allocation Determines the Organization of Personal Networks Tamarit, I., Cuesta, J.A., Dunbar R.I.M. and Sánchez, A. Proceedings of the National Academy of Sciences of the USA 115 (33) 8316-8321 (2018).
Portfolio Selection with Proportional Transaction Costs and Predictability Mei, X.and Nogales, F.J. Journal of Banking and Finance, 94, pp 131-151, 2018
Retail Competition with Switching Consumers in Electricity Markets Ruiz, C., Nogales, F.J. and Prieto F.J. Networks and Spatial Economics, 18(1), pp. 145-180, 2018
Using Deep Convolutional Neural Network for Emotion Detection on a Physiological Signals Dataset (AMIGOS) Santamaria Granados, L., Muñoz Organero, M., Ramírez Gonzalez G., Abdulhay, E. and Arunkumar N. IEEE Access, vol. 7, pp. 57-67, 2019.
Human Activity Recognition based on Single Sensor Square HV Acceleration Images and Convolutional Neural Networks Muñoz Organero, M. IEEE Sensors Journal, vol. 19, no. 4, pp. 1487-1498, 15 Feb.15, 2019.
Collaborative hierarchy maintains cooperation in asymmetric games Antonioni, A., Pereda, M., Cronin, K.A., Tomassini, M. and Sánchez, A. Scientific Reports Vol 8, Article 5375 (2018)
Unsupervised scalable statistical method for identifying influential users in online social networks Azcorra, A., Chiroque, L.F., Cuevas, R., Fernández Anta, A., Laniado, H., Lillo, R.E., Romo, J. and Sguera, C. Scientific Reports Vol 8, Article 6955 (2018)
Adding levels of complexity enhances robustness and evolvability in a multilevel genotype-phenotype map Catalá,P., Wagner, A., Manrubia, S. and Cuesta, J.A. Journal of the Royal Society Interface Vol 15, 20170516 (2018)
Quantitative account of social interactions in a mental health care ecosystem: cooperation, trust and collective action Cigarini, A., Vicens, J., Duch, J., Sánchez, A. and Perelló, J. Scientific Reports Vol 8, Article 3794 (2018)
Goodness of fit test for the funtional linear model based on randomly projected empirical processed Cuesta-Albertos, J.A., García-Portugués, E., Febrero-Bande, M., and González-Manteiga, W. Annals of Statistics (2018)
Equal status in Ultimatum Games promotes rational sharing Han, X., Cao, S., Bao, J.Z., Wang, W.X., Zang, B., Gao, Z.Y. and Sánchez, A. Scientific Reports Vol 8, Article 1222 (2018)
Cooperation on dynamic networks within an uncertain reputation environment Lozano, P., Antonioni, A., Tomassini, M. and Sánchez, A. Scientific Reports Vol 8, Article 9093 (2018)
Assessment of skills and adaptive learning for parametric exercises combining knowledge spaces and item response theory Muñoz-Merino, P. J., González Novillo, R., and Delgado Kloos, C: Applied Soft Computing, 68, 110-124.(2018)
Applying automatic text-based detection of deceptive language to police reports: extracting behavioral patterns from a multi-step classification model to understand how we lie to the Police Quijano Sánchez, L., Liberatore, F., Camacho-Collados, J. and Camacho-Collados, M. Knowledge-Based Systems. Vol 149 pp 155-168 (2018)
Bayesian analysis of the stationary MAP2 Ramírez-Cobo, P., Lillo, R.E. and Wiper, M. Bayesian Analysis. 12(4), 1163-1194 (2017)
Physics of human cooperation: experimental evidence and theoretical models Sánchez, A. Journal of Statistical Mechanics: Theory and Experiment.Vol 2018, 024001 (2018)
Cognitive resource allocation determines the organization of personal networks Tamarit, I., Cuesta, J.A., Dunbar, R.I.M and Sánchez, A. Proceedings of the National Academy of Sciences (USA) 115, 8316-8321 (2018)
Multi-dimensional risk in a non-stationary climate: joint probability of increasingly severe warm and dry conditions Gómez, M, Ausín, M.C and Domínguez, M.C Stochastic Environmental Research and Risk Assessment, 32, 2787–2807 (2018)
Vine copula models for predicting water flow discharge at King George Island, Antarctica Sarhadi, A., Ausín, M.C, Wiper,M.P., Touma,D. and Diffenbaugh, N.S. Science Advances, vol 4, no. 11(2018)
VA Large-Scale Analysis of Facebook’s User-Base and User Engagement Growth Mitike Kassa Y., Cuevas R. and Cuevas A. IEEE Access ( Volume 6) pp 78881 – 78891(2018)
Yield curve forecast combinations based on bond portfolio performancea> Moura, G.V., Caldeira, J.F. and Santos A.P. Journal of Forecasting, 31(1),(2018)
Lotka’s law for the Brazilian scientific output published in journals da Silva, S., Perlin,M., Matsushita, R., Santos A.P., Imasato, T. and Borestein, D. Journal of Information Science.(2018) https://doi.org/10.1177/0165551518801813
A divisive clustering method for functional data with special consideration of outliers Justel, A. and Svarc, M. Advances in Data Analysis and Classification (2018) número 12, paginas 637-656.
Title Authors Journal
Copying@ Scale: Using harvesting accounts for collecting correct answers in a MOOC☆ Alexandron, G., Ruipérez-Valiente, J. A., Chen, Z., Muñoz-Merino, P.J., and Pritchard, D. E Computers & Education, Vol 108, pp 96-114 (2017)
Improving the Graphical Lasso Estimation for the Precision Matrix Through Roots of the Sample Covariance Matrix☆ Avagyan, V., Alonso,A.M., and Nogales, F.J. Journal of Computational and Graphical Statistics Vol 26, Issue 4, pp 865-872 (2017)
High-fat diet induces metabolic changes and reduces oxidative stress in female mouse hearts☆ Barba, I., Miró-Casas, E., Torrecilla, J.L., Pladevall, E., Tejedor, S., Sebastián-Pérez , R., Ruiz-Meana, M., Berrendero, J.R. , Cuevas,A. and García-Dorado, D. Journal of Nutritional Biochemistry, Vol. 40, Pages 187-193 (2017)
An Efficient Industrial Big-data Engine Basanta-Val, P. IEEE Transactions, on Industrial Informatics Vol. PP Issue: 99, (2017)
Patterns for Distributed Real-Time Stream Processing Basanta-Val, P., Fernández-García, N., Sánchez-Fernández,L. and Arias-Fisteus, J. IEEE Transactions on Parallel and Distributed Systems, Vol. 28, Issue: 11 (2017)
Predictable remote invocations for distributed stream processing Basanta-Val, P., Fernández-García, N. and Sánchez-Fernández,L. Future Generation , DOI. 10.1016/j.future.2017.08.023, (2017)
Distance-weighted discrimination of face images for gender classification Benito, M., García-Portugués , E., Marron, J. S. and Peña, D. JStat Vol 6, pp 231–240 (2017)
On the use of reproducing kernel Hilbert spaces in functional classification Berrendero, J.R., Cuevas, A. and Torrecilla, J.L. Journal of the American Statistical Association, DOI: 10.1080/01621459.2017.1320287, (2017)
Modelling Electricity Swaps with Stochastic Forward Premium Models Blanco, I., Peña, J.I. and Rodriguez R. Energy Journal Issue, Vol. 39, no 2(2017)
Humans expect generosity Brañas-Garza, P., Rodríguez-Lara, I. and Sánchez, A. Scientific Reports, 7, Article number: 42446 (2017)
Combining Multivariate Volatility Forecasts: An Economic-Based Approach Caldeira, J.F., Moura, G.V., Nogales, F.J. and Santos A.P. Journal of Financial Econometrics Vol 15, Issue 2, pp 247-285 (2017)
Control charts based on parameter depths Cascos, I. and López Díaz, M. Applied Mathematical Modelling, Vol 53, pp 487–509 (2018)
Adaptive multiscapes: an up-to-date metaphor to visualize molecular adaptation Catalán, P., Arias,C.F. , Cuesta, J. and Manrubia, S. Biology Direct, 12:7 (2017)
T-Hoarder: A framework to process Twitter data streams Congosto, M., Basanta-Val, P. and Sanchez-Fernandez, L. Journal of Network and Computer Applications, Vol. 83, Pages 28-39 (2017)
Functional Principal Component Regression and Functional Partial Least-squares Regression: An Overview and a Comparative Study Febrero-Bande, M., Galeano, P. and González-Manteiga, W. International Statistical Review Vol 85, Issue 1, pp 61–83 (2017)
Langevin diffusions on the torus: estimation and applications Garcia Portugués, E., Sørensen M., Mardia, K.V. and Hamelryck, T. Statistics and Computing, pp 1–22, (2017)
Disentangling the effects of selection and loss bias on gene dynamics Iranzo J., Cuesta,J.A, Manrubia,S., Mikhail I. Katsnelson, and Koonin, E. V. Proceedings of the National Academy of Sciences (USA), Early Edition, vol. 114 no. 28 (2017)
The BIG CHASE: A decision support system for client acquisition applied to financial networks Liberatore F. and Quijano-Sánchez L. Decision Support Systems, Vol. 98, Pages 49-58 (2017)
What do we really need to compute the Tie Strength? An empirical study applied to Social Networks Liberatore F. and Quijano-Sánchez L. Computer Communications, Volume 110, Pages 59-74 (2017)
Distribution of genotype networks sizes in sequence-to-structure genotype-phenotype maps Manrubia S. and Cuesta J. A. Journal of the Royal Society Interface, Vol. 14, issue 129 (2017)
Equilibria, information and frustration, in heterogeneous network games with conflicting preferences Mazzoli,M. and Sánchez, A Journal of Statistical Mechanics: Theory and Experiment, DOI: 10.1088/1742-5468/aa9347 (2017)
Detecting Steps Walking at very Low Speeds Combining Outlier Detection, Transition Matrices and Autoencoders from Acceleration Patterns Munoz-Organero, M. and Ruiz-Blaquez, R. Sensors, 17(10), 2274 (2017)
Automatic detection of traffic lights, street crossings and urban roundabouts combining outlier detection and deep learning classification techniques based on GPS traces while driving Munoz-Organero, M., Ruiz-Blaquez, R. and Sánchez-Fernández, L. Computers Environment and Urban Systems. DOI: 10.1016/j.compenvurbsys.2017.09.005 (2017)
Improving transportation networks: Effects of population structure and decision making policies Pablo-Martí, F.and Sánchez, A. Scientific Reports, 7, Article number: 4498 (2017)
The emergence of altruism as a social norm Pereda, M., Brañas-Garza,P., Rodríguez-Lara,I. and Sánchez, A. Scientific Reports 7, Article number: 9684 (2017)
Fast and robust estimators of variance components in the nested error model Pérez, B., Molina, I., Thieler, A., Fried , R. and Peña, D. Statistics and Computing Vol 27, Issue 6, pp 1655–1675 (2017)
Make it personal: A social explanation system applied to group recommendations Quijano-Sanchez, L., Sauer, C., Recio-Garcia, J.A. and Diaz-Agudo, B. Expert Systems with Applications, Vol. 76, Pages 36-48 (2017)
Bayesian Analysis of the Stationary MAP Ramírez-Cobo, P, Lillo, R.E. and Wiper, M.P. Bayesian Aalysis Vol 12, Number 4, pp. 1163–1194 (2017)
Directional multivariate extremes in environmental phenomena Torres, R., De Michele, C., Laniado, H. and Lillo, R.E. Environmetrics Vol 28 (2017)
Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics Gómez, M., Ausín, M.C., and Domínguez, M.C Stochastic Environmental Research and Risk Assessment, 31, 1107-1121. (2017 )
Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics Zhihan Lv, Houbing Song, Basanta-Val,P., Steed, A. and Minho Jo IEEE Transactions on Industrial Informatics Vol. 13, Issue: 4, (Aug. 2017 )
Can we predict the financial markets based on Google’s search queries? Perlin, M., Caldeira, J.F.,Santos, A.P. and Pontuschka, M. Journal of Forecasting, 36(4),(2017)
Combining multivariate volatility forecasts: an economic-based approach Moura, G.V., Caldeira, J.F., Nogales, F.J. and Santos, A.P. Journal of Financial Econometrics, 15(2),(2017)
Title Authors Journal
D-trace estimation of a precision matrix using adaptive Lasso penalties Avagyan, V., Alonso,A.M., and Nogales, F.J. Advances in Data Analysis and Classification DOI: https://doi.org/10.1007/s11634-016-0272-8 (2016)
Stock Return Serial Dependence and Out- of-Sample Portfolio Performance. DeMiguel, A.V., Nogales,F.J. and Uppal, R. The Review of Financial Studies,Vol. 27, Issue 4, Pages 1031–1073 (2014) .
Dating multiple change points in the correlation matrix Galeano, P. and Dominik Wied, D. Sociedad de Estadística e Investigación Operativa (2016) DOI 10.1007/s11749-016-0513-3
Multiperiod portfolio optimization with multiple risky assets and general transaction costs Mei, X., De Miguel, V and Nogales, F.J. Journal of Banking & Finance Vol 69, pp 108-120, (2016)
Common Seasonality in Multivariate Time Series Nieto, F.H. Peña,D. and Saboyá, D. Statistica Sinica, 26, 1389-1410, 2016.
Monitoring multivariate variance changes Pape, K., Dominik Wied, D. and Galeano, P. Journal of Empirical Finance Vol 39, pp 54-68 (2016)
Generalized Dynamic Principal Components Peña,D. and Yohai, V.J. The Journal of American Statistical Association, 111,515, 1121-1131, 2016.
Dependence patterns for modeling simultaneous events. Rodríguez, J., Lillo, R.E. and Ramírez Cobo, P. (2016). Reliability Engineering & System Safety, 154, 19-30.
Analyzing the Impact of Using Optional Activities in Self-Regulated Learning Ruipérez-Valiente, J.A. Muñoz-Merino, P.J.,Delgado Kloos,C.,Niemann,K.,Schefeld,M. and Wolpers, M. IEEE Transactions on Learning Technologies, Volume: 9, Issue: 3, July-Sept. 1 2016
Functional outlier detection by a local depth with application to NO x levels Sguera, C, Galeano, P y Lillo, R.E Stochastic Environmental Research and Risk Assessment, Volume 30, Issue 4, pp 1115–1130 (2016)
A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model with Application to Portfolio Selection. Virbickaite, A, Ausín, M.C and Galeano, P. Computational Statistics and Data Analysis, 100, 814-829.(2016)
Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula. Sarhadi, A., Burn, D.H., Ausín, M.C and Wiper,M.P. Water Resources Research, 52, 2327–2349.(2016)
A New Time-varying Concept of Risk in a Changing Climate. Sarhadi, A., Burn, D.H., Ausín, M.C and Wiper,M.P. Scientific Reports, 6, Article number: 35755.(2016)
Bond portfolio optimization using dynamic factor models Moura, G.V., Caldeira, J.F. and Santos, A.P. Journal of Empirical Finance, 37, (2016)
Predicting the yield curve using forecast combinations Moura, G.V., Caldeira, J.F. and Santos, A.P. Computational Statistics & Data Analysis, 100,(2016)
The Brazilian scientific output published in journals: A study based on a large CV database Perlin, M., Santos, A.P., da Silva, S., Imasato, T. and Borestein, D. Journal of Informetrics, 11(1).(2016)
Title Authors Journal
Daily rhythms in mobile telephone communication Aledavood, T., López, E., Roberts, S., Reed-Tsochas, F., Moro, E., Dunbar, R. and Saramäki, J. PLoS ONE 10, e0138098 (2015)
Short-Range Mobility and the Evolution of Cooperation: An Experimental Study Antonioni, A., Tomassini, M. and Sánchez, A. Scientific Reports 5, 10282 (2015).
Time series segmentation procedures to detect, locate and estimate change- points Badagian, A.L., Kaiser, R. and Peña, D. In festschrift for Prof. Heiler, Empirical Economic and Financial Research – Theory, Methods and Practice, Beran, J., Feng, Y. and Hebbel, H. (eds.) Springer, Berlin. 2015.
Revealing patterns of local species richness along environmental gradients with a novel network tool. Baudena, M., Sánchez, A.,Georg, C.P., Ruíz-Benito, P., Zavala, M.A., Rodríguez, M.A. and Rietkerk, M.G./td> Scientific Reports 5, 11561 (2015).
Reputation drives cooperative behaviour and network formation in human groups Cuesta, J.A., Gracia-Lázaro, C., Ferrer, A., Moreno, Y. and Sánchez, A. Scientific Reports 5, 7843 (2015).
Performance of Social Network Sensors During Hurricane Sandy. Kryvasheyeu, Y., Chen, H., Moro, E., Van Hentenryck, P. and Cebrian, M. PLoS ONE 10, 0117288 (2015)
Detection and evaluation of emotions in Massive Open Online Courses. Leony, D., Muñoz-Merino, P.J., Ruipérez-Valiente, J.A., Pardo, A., Arellano, D. and Delgado kloos, C. Journal of Universal Computer Science, vol. 21, no. 5, pp. 638-655 (2015)
Social Media Fingerprints of Unemployment. Llorente, A., García-Herranz, M., Cebrián, M. and Moro, E. PLoS ONE 10, 0128692 (2015)
Precise effectiveness strategy for analyzing the effectiveness of students with educational resources and activities in MOOCs Muñoz-Merino, P.J., Ruipérez-Valiente, J.A., Alario-Hoyos, C., Pérez-Sanagustín, M. and Delgado kloos, C. Computers in Human Behavior, vol. 47, pp. 108-118 (2015)
A Software Engineering Model for the Development of Adaptation Rules and its Application in a Hinting Adaptive E-learning System Muñoz-Merino, P.J., Delgado kloos, C., Muñoz-Organero, M. and Pardo, A. Computer Science and Information Systems, vol. 12, no. 1 (2015), pp. 203–231.
Rethinking Statistics with Big Data: learning from George Box Peña, D. Quality Technology &Quantitative Management 12, 1, 2015.
ALAS-KA: A learning analytics extension for better understanding the learning process in the Khan Academy platform Ruipérez-Valiente, J.A., Muñoz-Merino, P.J., Leony, D. and Delgado kloos, C. Computers in Human Behavior, vol. 47, pp. 139-148, (2015).
Theory must be informed by experiments (and back) – Comment on “Universal scaling for the dilemma strength in evolutionary games”, by Z. Wang et al. Sánchez, A. Physics of Life Reviews 14, 52-53 (2015).
From seconds to months: an overview of multi-scale dynamics of mobile telephone calls Saramäki, J. and Moro, E. Eur. Phys. J. B 88, 164 (2015).
Bayesian nonparametric models of circular variables based on Dirichlet process mixtures of normal distributions. Núñez-Antonio, G, Ausín, M.C and Wiper, M.P. Journal of Agricultural, Biological, and Environmental Statistics, 20, 47-64 (2015)
Bayesian inference methods for univariate and multivariate GARCH models: a survey Virbickaite, A., Ausín, M.C and Galeano, P. Journal of Economic Surveys, 29, 76-96(2015)
Hedging against embarrassment Goulart, M.,Costa Jr., N., Andrade, E. and Santos, A.P. Journal of Economic Behavior and Organization, 116, (2015)
Measuring risk in fixed income portfolios using yield curve modelst Moura, G.V., Caldeira, J.F. and Santos, A.P Computational Economics. 46(1),(2015)
Monetary policy surprises and jumps in interest rates: evidence from Brazil Meurer,R.Santos, A.P and Turatti, D.E. Journal of Economic Studies, Vol. 42 Issue: 5, pp.893-907 (2015), https://doi.org/10.1108/JES-07-2014-0113