Home

 

Welcome to the Nonparametric Statistics Section

American Statistical Association

 

The objective of this section is to provide a forum for the ASA members with interests in flexible statistical methods that make only minimal assumptions on the underlying population or modeling structure. Focus areas include, but are not limited to, distribution free, nonparametric and semiparametric methods, and methods for high-dimensional and functional data. The section embraces the myriad of methodologies, philosophies and applications that comprise contemporary nonparametric statistics, seeks to promote research, education and training in them and to build cooperative relationships within and outside the ASA with those who have interest in nonparametrics.


Latest News:

Congratulations to the newly elected officers of the Section!
  • Chair-Elect 2025: Lily Wang, George Mason University.
  • Program Chair-Elect 2025: Hao Chen, University of California at Davis.
  • Treasurer 2025 (Rotates to Secretary in 2026): Tianying Wang, Colorado State University.
  • Publications Officer 2024-2026: Hongyuan Cao, Florida State University.
  • Council of Sections Representative 2024-2026: Limin Peng, Emory University.

C
ongratulations to the winners of the 2024 Student Paper Awards of the Section! 
2024 Student Paper Award Winners (alphabetical order): 
  • Mao Hong, Johns Hopkins University
  • Xindi Lin, University of Wisconsin, Madison
  • Yin Tang, Penn State University
Other finalists (alphabetical order): 
  • Yi Han, UC Davis
  • Haoran Lu, University of Georgia
  • Wookyeong Song, UC Davis
They presented in a special topic-contributed session at JSM 2024. In addition, the best presentation award winner went to Wookyeong Song. 

Upcoming Events 

2025 Joint Statistical Meeting, 

The conference will be held from August 2-7, 2025. For more information, see https://ww2.amstat.org/meetings/jsm/2025/

Latest Discussions

Log in to see this information

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.