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| 1 | +\name{mongrad} |
| 2 | +\alias{mongrad} |
| 3 | +\title{ |
| 4 | +Evaluate the gradient of a monotone function |
| 5 | +} |
| 6 | +\description{ |
| 7 | +Evaluates the gradient of a monotone function with respect to the coefficients defining |
| 8 | +the log-first derivative $W(t)$ at each of a set of argument values.} |
| 9 | +\usage{ |
| 10 | +mongrad(x, Wfdobj, basislist=vector("list",JMAX), |
| 11 | + returnMatrix=FALSE) |
| 12 | +} |
| 13 | +%- maybe also 'usage' for other objects documented here. |
| 14 | +\arguments{ |
| 15 | + \item{x}{A numerical vector at which function and derivative are |
| 16 | + evaluated.} |
| 17 | + \item{Wfdobj}{A functional data object.} |
| 18 | + \item{basislist}{A list containing values of basis functions.} |
| 19 | + \item{returnMatrix}{ |
| 20 | + logical: If TRUE, a two-dimensional is returned using a |
| 21 | + special class from the Matrix package.} |
| 22 | +} |
| 23 | +\value{ |
| 24 | +A matrix with as many rows as argument values and as many columns as basis functions |
| 25 | +defining $W$. |
| 26 | +} |
| 27 | +\references{ |
| 28 | + Ramsay, James O., Hooker, G. and Graves, S. (2009), \emph{Functional |
| 29 | + Data Analysis with R and Matlab}, Springer, New York. |
| 30 | + |
| 31 | + Ramsay, James O., and Silverman, |
| 32 | + Bernard W. (2005), \emph{Functional |
| 33 | + Data Analysis, 2nd ed.}, Springer, New York. |
| 34 | + |
| 35 | + Ramsay, James O., and Silverman, |
| 36 | + Bernard W. (2002), \emph{Applied |
| 37 | + Functional Data Analysis}, Springer, New York. |
| 38 | +} |
| 39 | +\author{ |
| 40 | + J. O. Ramsay |
| 41 | +} |
| 42 | +\seealso{ |
| 43 | + \code{\link{monfn}}, |
| 44 | + \code{\link{monhess}}, |
| 45 | + \code{\link{landmarkreg}}, |
| 46 | + \code{\link{smooth.morph}}, |
| 47 | + \code{\link{smooth.morph2}} |
| 48 | +} |
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