Abstract: The perspectives and methods of functional data analysis and longitudinal data analysis for smoothing are contrasted and compared. Topics include kernel methods and random effects models for smoothing, basis function methods, and examination of correlates of curve shapes. Some directions in which methodology might advance are identified.
Key words and phrases: Functional data analysis, longitudinal data analysis, nonparametric curve estimation.