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Daniel Gervini

  • Professor, Mathematical Sciences
  • BSDS Program Coordinator, Mathematical Sciences
  • Undergraduate Chair, Data Science

Education

  • Postdoc, Department of Biostatistics, University of Zürich, 2001-2004
  • Research Fellow, Department of Mathematics, University of Buenos Aires, 1996-1999
  • PhD Mathematics, University of Buenos Aires, 1999
  • MS Mathematics, University of Buenos Aires, 1995

Research Interests

  • Functional Data Analysis (i.e. statistical analysis of samples of functions)
  • Robust Statistics (i.e. outlier-resistant estimation methods)
  • Nonparametric Statistics
  • Multivariate Analysis

Selected Service and Projects

  • Robust functional estimation using the spatial median and spherical principal components.Biometrika 95 (2008), 587-600.
  • Choosing principal components: a new graphical method based on Bayesian model selection.Communications in Statistics - Simulation and Computation, 37 (2008), 962-977, with P. Auer.
  • Logistic discrimination with total variation regularization. Communications in Statistics - Simulation and Computation, 37 (2008), 1825-1838, with R. Rühlicke.

Selected Publications

Gervini, Daniel, and Baur, Tyler J.“Joint models for grid point and response processes in longitudinal and functional data” Statistica Sinica().
Gervini, Daniel, and Khanal, Manoj. “Exploring patterns of demand in bike sharing systems via replicated point process models” Journal of the Royal Statistical Society Series C: Applied Statistics68. (2019): 585-602.
Gervini, Daniel, and . “Independent component models for replicated point processes” Spatial Statistics18. (2016): 474-488.
Gervini, Daniel. “Dynamic retrospective regression for functional data” Technometrics 57. (2015): 26-34.
Gervini, Daniel. “Warped functional regression” Biometrika 102. (2015): 1-14.
Gervini, Daniel. “Analysis of Aneurisk65 data: warped logistic discrimination” Electronic Journal of Statistics 8. (2014): 1930-1936.
Gervini, Daniel. “Warped Functional Analysis of Variance” Biometrics 70. (2014): 526-535.
Gervini, Daniel. “Outlier detection and trimmed estimation for general functional data” Statistica Sinica 22. (2012): 1639-1660.

UWM Land Acknowledgement: We acknowledge in Milwaukee that we are on traditional Potawatomi, Ho-Chunk and Menominee homeland along the southwest shores of Michigami, North America’s largest system of freshwater lakes, where the Milwaukee, Menominee and Kinnickinnic rivers meet and the people of Wisconsin’s sovereign Anishinaabe, Ho-Chunk, Menominee, Oneida and Mohican nations remain present.   |   To learn more, visit the Electa Quinney Institute website.