Major changes made on fpca.sc to address following issues:
1. The main input Y will be either a matrix of observed functions (as it is now) or in long format, a data frame with columns .obs, .ind and .value as in pffr.
2. A new argument random.int will be added. If TRUE (not the default), the mean will be estimated by gamm4 with random intercepts, instead of by gam treating all the data as independent.
3. Another new argument, index (or argvals? Does anyone have a preference?), will be added for inputting the function arguments. The function arguments will be set to 1:D (as in the current code) only if Y is a matrix of functions and if this new argument is NULL (the default). 
4. Instead of using cov.sum/cov.count (see the code) as the raw covariance estimate for Cov[y(s1),y(s2)], Rayman will try smoothing the entire set of y(s1)y(s2) values. This will give greater weight to points (s1,s2) with more data. 

git-svn-id: svn://svn.r-forge.r-project.org/svnroot/refund@155 edb9625f-4e0d-4859-8d74-9fd3b1da38cb