Dr. Sara Lopez-Pintado's research focuses on developing non-parametric tools for analyzing complex data, such as functional data. In many research areas, and particularly in medicine and biology, there is a growing need for the statistical analysis of curves. Dr. Lopez-Pintado has proposed a new robust methodology for ordering curves and extended the notions of median, ranks, and outliers to functional data. She is currently interested in epidemiological cohort studies (i.e. growth curves of children) where the time observations are sparse and irregularly spaced. Dr. Lopez-Pintado has also worked in proposing new robust ways of classifying high-dimensional data, in particular gene-expression data.
Honors & Awards
Lopez-Pintado, S., Romo, J. and Torrente, A. Robust depth-based analysis of gene expression data Biostatistics 2010
Lopez-Pintado, S. and Romo, J. On the concept of depth for functional data Journal of the American Statistical Association 104 486-503 2009
Lopez-Pintado, S. and Romo, J. Depth-based inference for functional data Computational Statistics and Data Analysis 51 4957-4968 2007
Lopez-Pintado, S. and Jornsten, R. Functional analysis via extensions of the band depth IMS Lecture Notes-Monograph Series. IMS 54 103-120 2007
Lopez-Pintado, S. and Romo, J. Depth-based classification for functional data DIMACS Series in Discrete Mathematics and Theoretical Computer Science. Data Depth: Robust Multivariate Analysis, Computational Geometry and Appliations. American Mathematical Society. 72 103-120 2006