sample of publications

• articles 

  • Testing for linearity in scalar¿on¿function regression with responses missing at random.  COMPUTATIONAL STATISTICS.  39:3405-3429. 2024
  • Sequential detection of parameter changes in dynamic conditional correlation models.  APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY.  37:475-495. 2021
  • Variational inference for high dimensional structured factor copulas.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  151:1-23. 2020
  • Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction.  Energy Economics.  92. 2020
  • A robust procedure to build dynamic factor models with cluster structure.  Journal of Econometrics.  216:35-52. 2020
  • Parallel bayesian inference for high-dimensional dynamic factor copulas.  Journal of Financial Econometrics.  17:118-151. 2019
  • Rejoinder on: Data science, big data and statistics.  TEST.  28:363-368. 2019
  • Data science, big data and statistics.  TEST.  28:289-329. 2019
  • Estimation, imputation and prediction for the functional linear model with scalar response with responses missing at random.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  131:91-103. 2019
  • Las nuevas oportunidades del Big Data para las instituciones financieras.  Papeles de economía española.  78-97. 2019
  • Particle learning for Bayesian semi-parametric stochastic volatility model.  Econometric Reviews.  38:1007-1023. 2019
  • Dating multiple change points in the correlation matrix.  TEST.  26:331-332. 2017
  • Functional Principal Component Regression and Functional Partial Least-squares Regression: An Overview and a Comparative Study.  INTERNATIONAL STATISTICAL REVIEW.  85:61-83. 2017
  • Monitoring multivariate variance changes.  Journal of Empirical Finance.  39:54-68. 2016
  • A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  100:814-829. 2016
  • Functional outlier detection by a local depth with application to NOx levels.  STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT.  30:1115-1130. 2016
  • The Mahalanobis Distance for Functional Data With Applications to Classification.  TECHNOMETRICS.  57:281-291. 2015
  • Bayesian inference methods for univariate and multivariate GARCH Models: a Survey.  JOURNAL OF ECONOMIC SURVEYS.  29:76-96. 2015
  • Spatial depth-based classification for functional data.  TEST.  23:725-750. 2014
  • Multiple break detection in the correlation structure of random variables.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  76:262-282. 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. 2014
  • Monitoring correlation change in a sequence of random variables.  Journal of Statistical Planning and Inference.  143:186-196. 2013
  • Comments on: Some recent theory for autoregressive count time series by Dag Tjostheim. DISCUSSION.  TEST.  21:455-458. 2012
  • The Gaussian Mixture Dynamic Conditional Correlation Model: Parameter Estimation, Value at Risk Calculation, and Portfolio Selection.  JOURNAL OF BUSINESS & ECONOMIC STATISTICS.  28:559-571. 2010
  • Measures of Influence in the Functional Linear Model with Scalar Response.  JOURNAL OF MULTIVARIATE ANALYSIS.  101:305-490. 2010
  • Shifts in Individual Parameters of a GARCH Model.  Journal of Financial Econometrics.  8:122-153. 2010
  • Outlier Detection in Functional Data by Depth Measures with Application to Identify Abnormal NOx Levels.  ENVIRONMETRICS.  19:331-345. 2008

• book chapters 

  • Una aplicación del análisis de series temporales funcionales a los precios horarios de la electricidad en el mercado MIBEL. In: Análisis Econométrico y Big Data.  FUNCAS. 163-189. 2021
  • Parameter estimation of the functional linear model with scalar response with responses missing at random. In: Functional statistics and related fields.  SPRINGER. 105-111. 2017
  • Finding outliers in linear and nonlinear time series. In: Robustness and complex data structures.  SPRINGER. 243-260. 2013
  • Additive Outlier Detection in Seasonal ARIMA Models by a Modified Bayesian Information Criterion. In: Economic Time Series: Modeling and Seasonality.  CRC Press & IEEE. 317-336. 2012
  • Principal Components Selection for Estimating the Functional Linear Model with Scalar Response. In: Statistical Methods for the Analysis of Large Data-Sets.  CLEUP. 223-226. 2009
  • An Unified Approach to Model Selection, Discrimination, Goodness of Fit and Outliers in Time Series. In: Advances in Mathematical and Statistical Modeling.  Birkhauser. 267-278. 2008
  • Influence in the Functional Linear Model with Scalar Response. In: Functional and Operational Statistics.  SPRINGER. 165-171. 2008

• conference contributions 

  • Una introducción a las seriestemporales funcionales 2020
  • Estimation, imputation and prediction for the functional linear model with scalar response with missing responses.  218. 2018
  • Variational inference for high dimensional structured factor copulas.  202. 2018
  • Cleaning a large set of time series for common, cluster and specific outliers 2017
  • Parameter estimation of the functional linear model with scalar response with responses missing at random.  105-111. 2017
  • Approximate bayesian computation for phase-type distributions 2016
  • Inferencia bayesiana para modelos GARCH con errores SNI 2016
  • Modelling high dimensional stock dependence using factor copulas 2016
  • Outlier detection in high-dimensional time series 2016
  • Outlier detection in high-dimensional time series 2016
  • Big data analysis from a statistical perspective: opportunities and challenges 2015
  • Dating multiple change points in time series correlations with applications to financial returns 2015
  • Functional outlier detection with a local spatial depth 2015
  • Statistical analysis of networks with R 2015
  • Dating multiple change points in the correlation matrix 2014
  • Particle learning for Bayesian non-parametric Markov switching stochastic volatility model 2014
  • Particle learning for Bayesian non-parametric Markov switching stochastic volatility model 2014
  • Particle learning for Bayesian nonparametric stochastic volatility model 2014
  • The Mahalanobis distance for functional data with applications to classification 2014
  • A bayesian non-parametric approach to asymmetric dynamis conditional correlation model with application to portfolio selection 2013
  • Multiple break detection in the correlation structure of random variables 2013
  • Particle learning for bayesian non-parametric Markov switching stochastic volatility models with financial applications 2013
  • Spatial depth-based outlier detection for functional data 2013
  • Spatial depth-based outlier detection for functional data 2013
  • The Mahalanobis distance for functional data with applications to classification 2013
  • The Mahalanobis distance for functional data with applications to classification 2013
  • Bayesian Non-Parametric Portfolio Allocation and Hedging Risk with Multivariate Asymmetric GARCH 2012
  • Multiple Break Detection in the Correlation Structure of Time Series 2012
  • Robust Classification for Functional Data Via Spatial Depth-Based Methods 2012
  • Spatial Depth-Based Classification for Functional Data 2012
  • Spatial Depth-Based Classification for Functional Data 2012
  • The Estimation of Prediction Error in Functional Settings through Bootstrap Methods 2012
  • A Semiparametric Bayesian Approach to the GARCH Model with Application to Value at Risk Estimation 2011
  • Aspectos generales sobre la presencia de adtos atípicos en series temporales 2011
  • Classification and Discriminant Procedures for Dependent Data 2011
  • Selection of Eigenfunctions in the Fucntional Linear Model with Scalar Response 2008
  • The Gaussian Mixture Conditional Correlation Model: Parameter Estimation, Value at Risk Calculation and Portfolio Selection 2008

• working papers 

  • Variational Inference for high dimensional structured factor copulas 2018
  • Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas 2017
  • Two-sample Hotelling's T² statistics based on the functional Mahalanobis semi-distance 2015
  • Dating multiple change points in the correlation matrix 2015
  • Monitoring multivariate variance changes 2015
  • Particle learning for Bayesian non-parametric Markov Switching Stochastic Volatility model 2014
  • Bayesian estimation of a Dynamic Conditional Correlation model with multivariate Skew-Slash innovations 2014
  • Functional outlier detection with a local spatial depth 2014
  • A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection 2013
  • The Mahalanobis distance for functional data with applications to classification 2013
  • Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection 2013
  • Modeling financial time series with the skew slash distribution 2012
  • Spatial depth-based classification for functional data 2012
  • A Semiparametric Bayesian Approach to the Analysis of Financial Time Series with Applications to value at Risk 2010