Evaluates the gradient of a monotone function with respect to the coefficients defining the log-first derivative $W(t)$ at each of a set of argument values.
mongrad(x, Wfdobj, basislist=vector("list",JMAX),
returnMatrix=FALSE)A matrix with as many rows as argument values and as many columns as basis functions defining $W$.
A numerical vector at which function and derivative are evaluated.
A functional data object.
A list containing values of basis functions.
logical: If TRUE, a two-dimensional is returned using a special class from the Matrix package.
J. O. Ramsay
Ramsay, James O., Hooker, G. and Graves, S. (2009), Functional Data Analysis with R and Matlab, Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.
monfn,
monhess,
landmarkreg,
smooth.morph