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% $Id: SSbiexp.Rd,v 1.1 1999/11/12 13:34:35 bates Exp $\name{SSbiexp}\title{Biexponential model}\usage{SSbiexp(input, A1, lrc1, A2, lrc2)}\alias{SSbiexp}\arguments{\item{input}{a numeric vector of values at which to evaluate the model.}\item{A1}{a numeric parameter representing the multiplier of the firstexponential.}\item{lrc1}{a numeric parameter representing the natural logarithm ofthe rate constant of the first exponential.}\item{A2}{a numeric parameter representing the multiplier of the secondexponential.}\item{lrc2}{a numeric parameter representing the natural logarithm ofthe rate constant of the second exponential.}}\description{This \code{selfStart} model evaluates the biexponential model functionand its gradient. It has an \code{initial} attribute thatcreates initial estimates of the parameters \code{A1}, \code{lrc1},\code{A2}, and \code{lrc2}.}\value{a numeric vector of the same length as \code{input}. It is the value ofthe expression\code{A1*exp(-exp(lrc1)*input)+A2*exp(-exp(lrc2)*input)}.If all of the arguments \code{A1}, \code{lrc1}, \code{A2}, and\code{lrc2} are names of objects, the gradient matrix with respect tothese names is attached as an attribute named \code{gradient}.}\author{Jose Pinheiro and Douglas Bates}\seealso{\code{\link{nls}}, \code{\link{selfStart}}}\examples{library( nls )data( Indometh )Indo.1 <- Indometh[Indometh$Subject == 1, ]SSbiexp( Indo.1$time, 3, 1, 0.6, -1.3 ) # response onlyA1 <- 3; lrc1 <- 1; A2 <- 0.6; lrc2 <- -1.3SSbiexp( Indo.1$time, A1, lrc1, A2, lrc2 ) # response and gradientgetInitial(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)## Initial values are in fact the converged valuesfm1 <- nls(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)summary(fm1)}\keyword{models}