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% $Id: SSgompertz.Rd,v 1.1 2003/12/11 07:16:06 ripley Exp $\name{SSgompertz}\title{Gompertz Growth Model}\usage{SSgompertz(x, Asym, b2, b3)}\alias{SSgompertz}\arguments{\item{x}{a numeric vector of values at which to evaluate the model.}\item{Asym}{a numeric parameter representing the asymptote.}\item{b2}{a numeric parameter related to the value of the function at\code{x = 0}}\item{b3}{a numeric parameter related to the scale the \code{x} axis.}}\description{This \code{selfStart} model evaluates the Gompertz growth modeland its gradient. It has an \code{initial} attribute thatcreates initial estimates of the parameters \code{Asym},\code{b2}, and \code{b3}.}\value{a numeric vector of the same length as \code{input}. It is the value ofthe expression \code{Asym*exp(-b2*b3^x)}. If all ofthe arguments \code{Asym}, \code{b2}, and \code{b3} arenames of objects the gradient matrix with respect to these names is attached asan attribute named \code{gradient}.}\author{Douglas Bates}\seealso{\code{\link{nls}}, \code{\link{selfStart}}}\examples{DNase.1 <- subset(DNase, Run == 1)SSlogis(log(DNase.1$conc), 4.5, 2.3, 0.7) # response onlyAsym <- 4.5; b2 <- 2.3; b3 <- 0.7SSgompertz(log(DNase.1$conc), Asym, b2, b3 ) # response and gradientgetInitial(density ~ SSgompertz(log(conc), Asym, b2, b3),data = DNase.1)## Initial values are in fact the converged valuesfm1 <- nls(density ~ SSgompertz(log(conc), Asym, b2, b3),data = DNase.1)summary(fm1)}\keyword{models}