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% $Id: SSlogis.Rd,v 1.1.10.2 1999/12/26 10:41:13 ripley Exp $\name{SSlogis}\title{Logistic Model}\usage{SSlogis(input, Asym, xmid, scal)}\alias{SSlogis}\arguments{\item{input}{a numeric vector of values at which to evaluate the model.}\item{Asym}{a numeric parameter representing the asymptote.}\item{xmid}{a numeric parameter representing the \code{x} value at theinflection point of the curve. The value of \code{SSlogis} will be\code{Asym/2} at \code{xmid}.}\item{scal}{a numeric scale parameter on the \code{input} axis.}}\description{This \code{selfStart} model evaluates the logisticfunction and its gradient. It has an \code{initial} attribute thatcreates initial estimates of the parameters \code{Asym},\code{xmid}, and \code{scal}.}\value{a numeric vector of the same length as \code{input}. It is the value ofthe expression \code{Asym/(1+exp((xmid-input)/scal))}. If all ofthe arguments \code{Asym}, \code{xmid}, and \code{scal} arenames of objects the gradient matrix with respect to these names is attached asan attribute named \code{gradient}.}\author{Jose Pinheiro and Douglas Bates}\seealso{\code{\link{nls}}, \code{\link{selfStart}}}\examples{library(nls)data( ChickWeight )Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ]SSlogis( Chick.1$Time, 368, 14, 6 ) # response onlyAsym <- 368; xmid <- 14; scal <- 6SSlogis( Chick.1$Time, Asym, xmid, scal ) # response and gradientgetInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)## Initial values are in fact the converged valuesfm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)summary(fm1)}\keyword{models}