Analysis of a process with continuous sample curves can be carried out in a manner similar to principal components analysis of vector processes. By appropriate definition of a best linear model in the continuous case, we show that principal modes of variation consist of eigenfunctions of the process covariance functionC(s,t). Procedures for estimation of these eigenfunctions from a finite sample of observed curves are given, and results are compared with principal components analysis of the same data.