Journal articles

  1. Dependency evolution in Spanish disabled population : a functional data analysis approach. Irene Albarrán, Pablo Alonso and Ana Arribas-Gil. Journal of the Royal Statistical Society, Series A, in press, 2016.

  1. Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements. Rolando de la Cruz, Cristian Meza, Ana Arribas-Gil and Raymond J. Carroll. Journal of Multivariate Analysis, 143, 94-106, 2016. (ArXiv link) (Journal link)

  1. Discussion of "Multivariate Functional Outlier Detection" by M. Hubert, P. Rousseeuw and P. Segaert. Ana Arribas-Gil and Juan Romo. Statistical Methods and Applications, 24(2), 236-267, 2015. (Journal link)

  1. Classification of longitudinal data through a semiparametric mixed-effects model based on lasso-type estimators. Ana Arribas-Gil, Rolando de la Cruz, Emilie Lebarbier and Cristian Meza. Biometrics, 71(2), 333-343, 2015. (Journal link)

  1. Shape Outlier Detection and Visualisation for Functional Data: the Outliergram. Ana Arribas-Gil and Juan Romo. Biostatistics, 15(4), 603-619, 2014. (ArXiv link) (Journal link) (R code and examples)

  1. Pairwise Dynamic Time Warping for Event Data. Ana Arribas-Gil and Hans-Georg Müller. Computational Statistics and Data Analysis, 69, 255-268, 2014. (ArXiv link) (Journal link)

  1. Lasso-type estimators for Semiparametric Nonlinear Mixed-Effects Models Estimation. Ana Arribas-Gil, Karine Bertin, Cristian Meza and Vincent Rivoirard. Statistics and Computing, 24(3), 443-460, 2014. (ArXiv link) (Journal link)

  1. A context dependent pair hidden Markov model for statistical alignment. Ana Arribas-Gil and Catherine Matias. Statistical Applications in Genetics and Molecular Biology, 11(1), 1-29, 2012. (Journal link)

  1. Robust depth-based estimation in the time warping model. Ana Arribas-Gil and Juan Romo. Biostatistics, 13(3): 398-414, 2012. (Journal link) (R code and examples)

  1. Parameter estimation in multiple hidden i.i.d. models from biological multiple alignment. Ana Arribas-Gil. Statistical Applications in Genetics and Molecular Biology, 9(1), Article 10, 2010. (Journal link)

  1. Statistical alignment with a sequence evolution model allowing rate heterogeneity along the sequence. Ana Arribas-Gil, Dirk Metzler and Jean-Louis Plouhinec. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6(2), 281-295, 2009. (Journal link)

  1. Parameter estimation in pair hidden Markov models. Ana Arribas-Gil, Elisabeth Gassiat and Catherine Matias. Scandinavian Journal of Statistics, 33(4), 651-671, 2006. (Journal link)

Working papers

A time warping approach to multiple sequence alignment. Ana Arribas-Gil and Catherine Matias, 2016. (ArXiv link)

Book chapters

Can Personal Dependency Paths Help to Estimate Life Expectancy Free of Dependency? Irene Albarrán, Pablo Alonso, Ana Arribas-Gil and Aurea Grané. In Mathematical and Statistical Methods for Actuarial Sciences and Finance, Cira Perna and Marilena Sibillo (Eds.), Springer, 2014 (ISBN 978-3-319-05014-0). (Publisher link)

PhD Thesis

Estimation dans des modèles à variables cachées. Alignement de séquences biologiques et modèles d'évolution. (pdf, 1.2 MB)