Due to the COVID-19 Pandemic, the University has instruction to cancel all in-person events through the Spring semester to adhere to city and state orders limiting public gatherings. Events still running must now take place Online— listed events will include a link in which one may access the Online webspace:

To view Ms. Ashrafi’s defense, enter her Online chatroom via Microsoft Team’s at 10:00 am on Thursday, April 23, 2020.

Functional Data Analysis in Non-Linear Space

Ms. Syeda Ashrafi
University of Wisconsin-Milwaukee
PhD Graduate Student – Teaching Assistant

“Functional data are essentially high dimensional and thus become a vast source of information that gives wide opportunities for research and data analysis. However, in many situations, these functions belong to non-linear spaces and might have certain restrictions. Our aim is to redefine the original problem such that our function to be estimated becomes unconstrained. We will consider two cases of non-linear spaces: 1) Monotone increasing function and 2) Probability density functions. The warping function approach will be used for monotone increasing function. The data has been used is Knee variable of gait data for warping function and income variable of socioeconomic household data (from Family expenditure survey of Great Britain) for the density function approach.”

Committee Members:
Profs. Daniel Gervini (Advisor); Vytaras Brazauskas, David Spade, Wei Wei & Chao Zhu

*Click to view the event flyer