Fang Li

Research

Prof. Li's principal research interest focuses on inference of stochastic processes including long-range dependence and time series, in which nonparametric kernel estimations are explored to estimate regression, autoregressive, density, and heteroschadastic error variance functions. Some of her ongoing projects involve comparing multiple time series, which has diverse applications in economics and finance. In collaboration with research groups from biological fields, she is applying nonparametric and general linear mixed models to real life data. Additionally, she has strong interest in extending the nonparametric approaches to survival and longitudinal data analysis.

Publications & Professional Activity

Li, F. (2009). Testing for the equality of two autoregressive functions using quasi residual. Communications in Statistics-Theory and Methods, 38 (9), 1404 - 1421.

Qin, B., Xia, Y. and Li, F. (2009). DTU: A Decision Tree for Uncertain Data. the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 4-15, Bangkok, Thailand, 2009.

Li, F. (2008) Asymptotic properties of some kernel smoothers. Preprint #pr08-03, Department of Mathematical Sciences, Indiana University Purdue University Indianapolis.

Sarkar, J. and Li, F. (2006). Limiting average availability of a system supported by several spares and several repair facilities. Journal of Statistics & Probability Letters, 76, 1965-1974.

Li, F. (2006) Testing for the equality of the two nonparametric regression curves with long memory errors. Communications in Statistics-Simulation and Computation, 35, No. 3, 621-643.

Koul, H.L., Stute, W. and Li, F. (2005). Model diagnosis for SETAR time series. Statistica Sinica, 15, 795-817.

Koul, H.L. and Li, F. (2005). Testing for superiority among two time series. Statistical Inference for Stochastic Processes, 8, 109-135.

Affiliations

Statistics Consulting Center