Rate My Professor Fang Li

Fang Li is an Associate Professor in the Department of Mathematical Sciences at the School of Science, Indiana University Indianapolis. Her principal research interests focus on the inference of stochastic processes, including long-range dependence and time series analysis. She develops nonparametric kernel estimations for regression, autoregressive models, density functions, and heteroscedastic error variance functions. Professor Li's work also encompasses comparing multiple time series with applications in economics and finance. In collaboration with biological research groups, she applies nonparametric and general linear mixed models to real-life data. Additionally, she extends nonparametric approaches to survival and longitudinal data analysis.

Professor Li has contributed key publications to the field of statistics. These include 'Testing for the equality of two autoregressive functions using quasi residual' published in Communications in Statistics-Theory and Methods in 2009, 'DTU: A Decision Tree for Uncertain Data' presented at the Pacific-Asia Conference on Knowledge Discovery and Data Mining in 2009, 'Asymptotic properties of some kernel smoothers' (preprint, 2008), 'Limiting average availability of a system supported by several spares and several repair facilities' in Journal of Statistics & Probability Letters in 2006, 'Testing for the equality of the two nonparametric regression curves with long memory errors' in Communications in Statistics-Simulation and Computation in 2006, 'Model diagnosis for SETAR time series' in Statistica Sinica in 2005, and 'Testing for superiority among two time series' in Statistical Inference for Stochastic Processes in 2005. Her research demonstrates significant advancements in statistical methodologies applicable to diverse scientific domains.