Yi Sun's journal club session, where she will present the paper "Applied Functional Data Analysis Methods and Case Studies (Ramsay, J. O. and Silverman B.W, 2002)"
The field of Functional Data Analysis (FDA) has seen rapid development over the last two decades. FDA refers to a collection of methods for analysing data over a curve, surface or continuum. It is very much involved with computational statistics. FDA has been applied to quite broadly in medicine, business and engineering.
In this talk, Yi will introduce the basic idea of FDA using a case study presented in the paper: zooming in on human growth.
“Human growth is not at all the simple process that one might imagine at first sight… Collecting records is time-consuming and expensive, because children have to be measured accurately and tracked for a long period of their lives.
[We] consider how to make this sort of record into a useful functional datum to incorporate into further analyses. A smooth curve drawn through the points is commonly called a growth curve, but growth is actually the rate of increase of the height of the child. In children this is necessarily positive… [We] develop a monotone smoothing method that takes this sort of consideration into account and yields a functional datum that picks out important stages in a child’s growth."