\Header{SSbiexp}{Biexponential model}
\keyword{models}{SSbiexp}
\begin{Description}\relax
This \code{selfStart} model evaluates the biexponential model function
and its gradient.  It has an \code{initial} attribute that 
creates initial estimates of the parameters \code{A1}, \code{lrc1},
\code{A2}, and \code{lrc2}.\end{Description}
\begin{Usage}
\begin{verbatim}
SSbiexp(input, A1, lrc1, A2, lrc2)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{input}] a numeric vector of values at which to evaluate the model.
\item[\code{A1}] a numeric parameter representing the multiplier of the first
exponential.
\item[\code{lrc1}] a numeric parameter representing the natural logarithm of
the rate constant of the first exponential.
\item[\code{A2}] a numeric parameter representing the multiplier of the second
exponential.
\item[\code{lrc2}] a numeric parameter representing the natural logarithm of
the rate constant of the second exponential.
\end{ldescription}
\end{Arguments}
\begin{Value}
a numeric vector of the same length as \code{input}.  It is the value of
the 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 to
these names is attached as an attribute named \code{gradient}.\end{Value}
\begin{Author}\relax
Jose Pinheiro and Douglas Bates\end{Author}
\begin{SeeAlso}\relax
\code{\Link{nls}}, \code{\Link{selfStart}}\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
library( nls )
data( Indometh )
Indo.1 <- Indometh[Indometh$Subject == 1, ]
SSbiexp( Indo.1$time, 3, 1, 0.6, -1.3 )  # response only
A1 <- 3; lrc1 <- 1; A2 <- 0.6; lrc2 <- -1.3
SSbiexp( Indo.1$time, A1, lrc1, A2, lrc2 ) # response and gradient
getInitial(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)
## Initial values are in fact the converged values
fm1 <- nls(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)
summary(fm1)
\end{ExampleCode}
\end{Examples}

