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  • Aguilera Morillo, M. Carmen; Aguilera del Pino, Ana M; Preda, Cristian. Penalized versions of Functional PLS Regression. Chemometrics and Intelligent Laboratory Systems, (In press). DOI:10.1016/j.chemolab.2016.03.013
  • Aguilera Morillo, M. Carmen; Durbán Reguera, María; Aguilera del Pino, Ana M.; (2016). Prediction of functional data with spatial dependence: a penalized approach. Stochastic Environmental Research and Risk Assessment, (In press)DOI 10.1007/s00477-016-1216-8
  • Alonso-Revenga, J. M.; Martín, N.; Pardo, L. (2016) : New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes. Statistics and Computing . (In press) DOI: 10.1007/s11222-015-9616-z
  • Cabras, Stefano and Tena, J. D. (2016). A Bayesian nonparametric modelling to estimate student response to ICT investment. Journal of Applied Statistics. (In press).
  • Maharaj, E.A., Alonso, A.M. and D’Urso, P. (2016). Clustering Seasonal Time Series Using Extreme Value Analysis: An Application to Spanish Temperature Time Series, Communications in Statistics – Case Studies and Data Analysis, (In press).
  • Nieto, F. Peña,D. and D. Saboyá (2016). “Common Seasonality in Multivariate Time Series” Statistica Sinica, (In press).
  • Peña , D. and Yohai, V. (2016) “Generalized Dynamic Principal Components” (con V. Yohai). The Journal of American Statistical Association, (In press)
  • Velilla, S. (2016) A note on collinearity diagnostics and centering. The American Statistician, (In revision).
  • Armero C, Cabras S, Castellanos ME, Perra S, Quirós A, Oruezábal MJ6, Sánchez-Rubio J. (2016) Bayesian analysis of a disability model for lung cancer survival. Statistical Methods in Medical Research. 21-1, pp.336-351. DOI: 10.1177/0962280212452803.
  • Adan, I; D’Auria, B. (2016). Sojourn time in a single server queue with threshold service rate control. SIAM Journal on Applied Mathematics (SIAP), 76(1), p. 197–216
  • Bahamonde, N. y Veiga, H. (2016). A robust closed-form estimator for the GARCH(1,1) model, Journal of Statistical Computation and Simulation, 86(8), 1605-1619.
  • Barbosa, S., Gouveia, S., Scotto, M. and Alonso, A.M. (2016) Wavelet-based Clustering of Sea Level Records, Mathematical Geosciences, 48 (2), 149-162.
  • Basu, A.; Mandal, A.; Martín, N.; Pardo, L. (2016) Generalized Wald-type tests based on minimum density power divergence estimators. Statistics: A Journal of Theoretical and Applied Statistics, 50 (1) 1-26. DOI: 10.1080/02331888.2015.1016435
  • Batsidis, A.; Martín, N.; Pardo, L.; Zografos, K. (2016) f-divergence based procedure for parametric change-point problems. Methodology and Computing in Applied Probability (18), 21-35. DOI: 10.1007/s11009-014-9398-3
  • Cabras, Stefano. (2016). A Markov Chain Representation of the Multiple Testing problem. Statistical Methods in Medical Research. (On Line First).
  • Cascos Fernández, Ignacio; López Díaz, Miguel; (2016). On the uniform consistency of the zonoid depth, Journal of multivariate analisys, (Academic press) 143, 394-397.DOI: 10.1016/j.jmva.2015.09.020
  • de la Cruz, Rolando; Meza, Cristian; Arribas-Gil, Ana and Carroll, Raymond J. (2016) Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements. Journal of Multivariate Analysis, 143, 94-106. 
  • García Lara, J.M; García Osma, B and Penalva, F. (2016) Accounting Conservatism and Firm Investment Efficiency . Journal of Accounting and Economics. Vol. 61(1). DOI: 10.1016/j.jacceco.2015.07.003
  • Martín Barragán, B.; Lillo, R. and Romo, J. (2016) Functional boxplots based on epigraphs and hypograph . Journal of Applied Statistics, 43(6), 1088-1103. DOI: 10.1080/02664763.2015.1092108
  • Martin, N.; Mata, R.; Pardo, L. (2016) Wald type and phi-divergence based test-statistics for isotonic binomial proportions. Mathematics and Computers in Simulation (120) 31-49. DOI: 10.1016/j.matcom.2015.06.008
  • Pino, G., Tena, J. D., and Espasa, A. (2016). Geographical disaggregation of sectoral inflation. Econometric modelling of the Euro area and Spanish economies. Applied Economics, 48(9), 799-815. DOI: 10.1080/00036846.2015.1088141


  • Huffman, Jennifer; Cabras, Stefano; et al. 2015. Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans. PLOS ONE. (In press).
  • Aguilera Morillo, M. Carmen; Aguilera, Ana M. (2015). P-spline estimation of functional classification methods for improving the quality in the food industry. Communications in Statistics - Simulation and Computation, 44 (10), 2513-2534.
  • Alonso, A.M., Pérez, R.H. and Silva, E. (2015) Forecasting Mortality Rates: Mexico 2001-2010, Communications in Statistics – Case Studies and Data Analysis, 1 (1), 22-38.
  • Arribas-Gil, Ana; de la Cruz, Rolando; Lebarbier, Emilie and Meza, Cristian. (2015) Classification of longitudinal data through a semiparametric mixed-effects model based on lasso-type estimators. Biometrics, 71(2), 333-343.
  • Arribas-Gil, Ana and Romo, Juan. (2015) Discussion of "Multivariate Functional Outlier Detection" by M. Hubert, P. Rousseeuw and P. Segaert. Statistical Methods and Applications, 24(2), 236-267. DOI: 10.1007/s10260-015-0328-5
  • Badagian, Ana Laura; Kaiser Regina and Peña, Daniel. (2015). Time Series Segmentation Procedures to Detect, Locate and Estimate Change-Point. Empirical Economic and Financial Research. Springer. 45-60.
  • Balakrishnan, N.; Martín, N.; Pardo, L. (2015) Empirical phi-divergence test statistics for testing simple and composite null hypotheses. Statistics: A Journal of Theoretical and Applied Statistics, 49 (5) 951-977. DOI: 10.1080/02331888.2014.957702
  • Bertolino, F.; Cabras, S. et al. (2015). Unscaled Bayes Factors for Multiple Hypothesis Testing in Microarray Experiments. Statistical Methods in Medical Research. 24-6, pp.1030-1043.
  • Blanco, B.; García Lara, J.M. and Ttribó, J.A. (2015) Segment Disclosure and Cost of Capital. Journal of Business Finance and Accounting, Vol. 42(3&4), 367-411. DOI: 10.1111/jbfa.12106
  • Cabras, S.; Castellanos, M.E.; Staffetti, E. (2015). A Random Forest application to Contact-State Classification for Robot Programming by Human Demonstration. Applied Stochastic Models in Business and Industry. Wiley.
  • Cabras, S.; Castellanos M.E.; Perra Silvia. (2015). A new minimal training sample scheme for intrinsic bayes factors in censored data. Computational Statistics and Data Analysis. 81, pp.52-63.
  • Cabras, S.; Castellanos M.E.; Ruli, E. (2015). Approximate Bayesian computation by modelling summary statistics in a quasi-likelihood framework. Bayesian Analysis. Int. Soc. of Bayesian Analysis (ISBA). 10-2, pp.411-439.
  • Cabras, S.; Comandini, O.; Marini, E. (2015). Birth registration and child undernutrition in sub-Saharan Africa. Public Health Nutrition. Cambridge University Press.
  • Cabras, S.; Racugno, W.; Ventura, L. (2015). Higher-order asymptotic compu- tation of bayesian significance tests for precise null hypotheses in the presence of nui- sance parameters. Journal of Statistical Computation and Simulation. 85-15, pp.2989-3001.
  • D'Auria, B; Kanta, S. (2015). Pure threshold strategies for a two-node tandem network under partial information. Operations Research Letters, 43(5), p. 467-470. 
  • Febrero-Bande, M., Galeano, P. and González-Manteiga, W. (2015) Functional principal component regression and functional partial least squares regression: an overview and a comparative study. International Statistical Review, forthcoming.
  • Fidrmuc, J., & Tena, J. D. (2015). Friday the 13th: The Empirics of Bad Luck. Kyklos, 68(3), 317-334. DOI: 10.1111/kykl.12085
  • Flores, R., Forrest, D., Pablo, C. D., & Tena, J. D. (2015). What is a good result in the first leg of a two-legged football match?. European Journal of Operational Research, 247(2), 641-647. DOI: 10.1016/j.ejor.2015.05.076
  • Galán, J., Veiga, H. y Wiper, M. (2015). Dynamic Effects in Inefficiency: Evidence from the Colombian Banking Sector, European Journal of Operational Research, 20(2), 562-575.
  • Galeano, P., Joseph, E. and Lillo, R. E. (2015) The Mahalanobis distance for functional data with applications to classification. Technometrics, 57, 281-291.
  • Gouveia, S., Scotto, M., Monteiro, A. and Alonso, A.M. (2015) Wavelets-based Clustering of Air Quality Monitoring Sites, Environmental Monitoring and Assessment, 187 (11), 1-14.
  • Jara, M., Paolini, D., & de Dios Tena Horrillo, J. (2015). Management efficiency in football: An empirical analysis of two extreme cases. Managerial and Decision Economics, 36(5), 286-298. DOI: 10.1002/mde.2668
  • Leonti, M., Staub, P.O., Cabras, S., Castellanos, ME and Casu, L. (2015). From cumulative cultural transmission to evidence-based medicine: Evolution of medicinal plant knowledge in Southern Italy. Frontiers in Pharmacology.
  • Mandal, A.; Basu, A.; Martín, N.; Pardo, L. (2015) Robust tests for the equality of two normal means based on the density power divergence. Metrika. 78 (5) 611-634. DOI: 10.1007/s00184-014-0518-4
  • Martín-Barragán, B., Ramos, S. y Veiga, H. (2015). Correlations between oil and stock markets: A wavelet-based approach, Economic Modelling, 50, 212-227.
  • Martín, N. (2015) Diagnostics in a simple correspondence analysis model: an approach based on the Cook's distance for log-linear models. Journal of Multivariate Analysis (136) 175-189. DOI: 10.1016/j.jmva.2015.01.008
  • Martín, N. (2015). Using the Cook's distance in Polytomous Logistic Regression. British Journal of Mathematical and Statistical Psychology. 68(1) 84-115. DOI: 10.1111/bmsp.12036
  • Merino A. & Albacete R. (2015). “Evolución y predicción a corto plazo de la demanda de productos petrolíferos en España”. ICE Información Comercial Española Revista de Economía volumen 886, Transformación en los mercados energéticos, 37-57.
  • Peña D. (2015) “Rethinking Statistics with Big Data: learning from George Box” Quality Technology &Quantitative Management, QTQM Special Issue Vol. 12, No. 1, 4-7. DOI:10.1080 /16843703.2016.1169671
  • Sguera, C., Galeano, P. and Lillo, R. E. (2015) Functional outlier detection by a local depth with application to NOx levels. Stochastic Environmental Research and Risk Assessment, forthcoming.
  • Virbickaite, A., Ausín, M. C. and Galeano, P. (2015) A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection. Computational Statistics and Data Analysis, forthcoming.
  • Virbickaite, A., Ausín, M. C. and Galeano, P. (2015) Bayesian inference methods for univariate and multivariate GARCH models: a survey. Journal of Economic Surveys, 29, 76-96.


  • Cabras, S.; Castellanos, M. E.; Ruli, E. (2014). A Quasi likelihood approximation of posterior distributions for likelihood-intractable complex models. Metron. pp. (In press).
  • Dessi, C.; Cabras, S. et al. (2014). How Small Family-owned Businesses May Compete with Retail Superstores: Tacit Knowledge and Perceptive Concordance among Owner-managers and Customers. Journal of Small Business and Enterprise Development. (In press).
  • Alonso, A.M., Casado, D., Lopez-Pintado, S. and Romo, J. (2014) Robust Functional Classification for Time Series, Journal of Classification, 31, 325-350. DOI: 10.1007/s00357-014-9163-x
  • Alonso, A.M., de Zea Bermudez, P. and Scotto, M. (2014) Comparing Generalized Pareto models fitted to extreme observations: An application to the largest temperatures in Spain, Stochastic Environmental Research and Risk Assessment, 28, 1221-1233.
  • Arribas-Gil, Ana; Bertin, Karine; Meza, Cristian and Rivoirard, Vincent. (2014) Lasso-type estimators for Semiparametric Nonlinear Mixed-Effects Models Estimation.. Statistics and Computing, 24(3), 443-460.
  • Arribas-Gil, Ana and Müller, Hans-Georg. (2014) Pairwise Dynamic Time Warping for Event Data. Computational Statistics and Data Analysis, 69, 255-268.
  • Arribas-Gil, Ana and Romo, Juan. (2014) Shape Outlier Detection and Visualisation for Functional Data: the Outliergram. Biostatistics, 15(4), 603-619. 
  • Ausín, M. C., Galeano, P. and Ghosh, P. (2014) A semiparametric Bayesian approach to the analysis of financial time series with applications to Value at Risk estimation. European Journal of Operational Research, 232, 350-358.
  • Batsidis, A.; Martín, N.; Pardo, L.; Zografos, K.; (2014) A necessary power divergence-type family of tests for testing elliptical symmetry. Journal of Statistical Computation and Simulation. 84 (1) 57-83. DOI: 10.1080/00949655.2012.694437
  • Blanco, B.; García Lara, J.M. and Tribó, J.A. (2014). The Relation between Segment Disclosure and Earnings Quality. Journal of Accounting and Public Policy. Vol. 33, 449-469. DOI:10.1016/j.jaccpubpol.2014.06.002
  • Cabras, S.; Castellanos, ME.; Perra, S. (2014). Comparison of objective bayes factors for variable selection in parametric regression models for survival analysis. Statistics in Medicine.
  • Cascos Fernández, Ignacio; Molchanov Ilya; (2014) Multivariate risk measures: a constructive approach based on selections, Mathematical finance, 34 pages. DOI: 10.1111/mafi.12078
  • Escabias, Manuel; Aguilera, Ana M.; Aguilera Morillo, M. Carmen (2014). Functional PCA and base-line logit models. Journal of Classification, 31 (3), 296-324.
  • Firinu, D.; Cabras, S. et al. (2014). TH17 cells are increased in the peripheral blood of patients with SAPHO syndrome. Autoimmunity, pp.1-6.  DOI: 10.3109/08916934.2014.906582
  • Galán, J., Veiga, H. y Wiper, M. (2014).Bayesian estimation of inefficiency heterogeneity in stochastic frontier models, Journal of Productivity Analysis, 42(1), 85-101.
  • Galeano, P. and Wied, D. (2014) Multiple break detection in the correlation structure of random variables. Computational Statistics and Data Analysis, 76, 262-282.
  • García Lara, J.M.; García Osma, B. and Penalva, F. (2014) Information Consequences of Accounting Conservatism. European Accounting Review. Vol. 23(2), 173-198.
  • Grané, A. y Veiga, H. (2014). Outliers, GARCH-type models and risk measures: A comparison of several approaches, Journal of Empirical Finance, 26, 26-40.
  • Jiménez, R. and Hidalgo, M.(2014)  Forensic Analysis of Venezuelan Elections during the Chávez Presidency. DOI:10.1371/journal.pone.0100884
  • Maharaj, E.A. and Alonso, A.M. (2014) Discriminant analysis of multivariate time series: Application to diagnosis based on ECG signals, Computational Statistics and Data Analysis, 70, 67-87.
  • Marques, H., Pino, G., & de Dios Tena Horrillo, J. (2014). Regional inflation dynamics using space–time models. Empirical Economics, 47(3), 1147-1172. DOI: 10.1007/s00181-013-0763-9
  • Marron, J.S. and Alonso, A.M. (2014) Overview of object oriented data analysis, Biometrical Journal, 56, 732–753.
  • Martín Barragán, B.; Lillo, R. and Romo, J. (2014) Interpretable support vector machines for functional data. European Journal of Operational Research, 232 (1), 146-155. DOI: 10.1016/j.ejor.2012.08.0170.1016/j.ejor.2012.08.017
  • Martín, N.; Pardo, L.; (2014) A new influence measure in Polytomous Logistic Regression Models based on Phi-divergence measures. Communications in Statistics-Theory and Methods. 43 (10-12) 2311-2321. DOI: 10.1080/03610926.2013.839038
  • Martín, N.; Pardo, L.; (2014) Comments on: Extensions of some classical methods in change point analysis. TEST 23 (2) 279-282 . DOI: 10.1007/s11749-014-0372-8
  • Martín, N.; Mata, R.; Pardo, L.; (2014) Phi-divergence statistics for the likelihood ratio order: an approach based on log-linear models. Journal of Multivariate Analysis. (130) 387–408. DOI: 10.1016/j.jmva.2014.06.004
  • Mayordomo, S.; Peña, J.I. and Romo, J. (2014) Testing for statistical arbitrage in credit derivatives markets. Journal of Empirical Finance, 26, 59-75. DOI: 10.1016/j.jempfin.2014.02.002
  • Moreno, M. and Romo, J. (2014) Robust unit roots tests with autoregressive errors. Communications in Statistics. DOI:10.1080/03610926.2014.955114
  • Pérez, D. Molina, I and Peña, D. (2014) “Outlier Detection and Robust Estimation in Linear Regression Models with Fixed Group Effects” Journal of Statistical Computation and Simulation, 84, 2652-2669.
  • Sguera, C., Galeano, P. and Lillo, R. E. (2014) Spatial Depth-based classification for functional data. TEST, 23, 725-750.
  • Veerman, J.J.P. and Prieto, Francisco J. (2014) On Rank Driven Dynamical Systems, Journal of Statistical Physics, 156 (3), 455-472. DOI: 10.1007/s10955-014-1012-0
  • Velilla, S. On the behaviour of the SAVE directions. (2014). Communications in Statistics - Theory and Methods, Volume: 43, (21) 4612 – 4627.



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