.\" -*- nroff -*- generated from .Rd format
.BG
.FN SSbiexp
.TL
Biexponential model
.DN
This `selfStart' model evaluates the biexponential model function
and its gradient.  It has an `initial' attribute that 
creates initial estimates of the parameters `A1', `lrc1',
`A2', and `lrc2'.
.CS
SSbiexp(input, A1, lrc1, A2, lrc2)
.RA
.AG input
a numeric vector of values at which to evaluate the model.
.AG A1
a numeric parameter representing the multiplier of the first
exponential.
.AG lrc1
a numeric parameter representing the natural logarithm of
the rate constant of the first exponential.
.AG A2
a numeric parameter representing the multiplier of the second
exponential.
.AG lrc2
a numeric parameter representing the natural logarithm of
the rate constant of the second exponential.
.RT
a numeric vector of the same length as `input'.  It is the value of
the expression `A1*exp(-exp(lrc1)*input)+A2*exp(-exp(lrc2)*input)'.
If all of the arguments `A1', `lrc1', `A2', and `lrc2' are names of
objects, the gradient matrix with respect to these names is attached
as an attribute named `gradient'.

.SA
`nls', `selfStart'
.EX
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
.KW models
.WR
