The Nonparametric Statistics Workshop, entitled “Integration of Theory, Methods and Applications” will be held on the University of Michigan campus at Ann Arbor on October 6 and 7, 2016.

The main goal of the workshop is to bring together researchers who are interested in the development of nonparametric theory and methods or innovative applications from different sub-fields of statistics for stimulating interactions. This workshop covers various topics, which include, but are not limited to, high-dimensional data analysis, functional and image data analysis, smoothing, semi-parametric approaches, network analysis, shape-constrained nonparametric models, spatial analysis, astronomy, economics, neuroimaging and nutrition.

Attendance at the workshop is open to all interested participants (subject to space limitations). Please register if you would like to attend this workshop.

Organizing Committee:

Naisyin Wang (Co-Chair), University of Michigan

Xuming He (Co-Chair), University of Michigan

Elizaveta Levina, University of Michigan

Mary Meyer, Colorado State University

Jean Opsomer, Colorado State University

Harrison Zhou, Yale University

Local Committee:

Naisyin Wang, University of Michigan

Elizaveta Levina, University of Michigan

Naveen Narisetty, University of Illinois at Urbana–Champaign

Kerby Shedden, University of Michigan

Stilian Stoev, University of Michigan

Ji Zhu, University of Michigan



The organizers gratefully acknowledge the support from:

The National Science Foundation

Institute of Mathematical Statistics

Section on Nonparametric Statistics – American Statistical Association

Department of Statistics, University of Michigan, Ann Arbor

College of Literature, Science, and the Arts, University of Michigan, Ann Arbor

Horace H. Rackham School of Graduate Studies, University of Michigan

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