SSbiexp {stats} | R Documentation |
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
.
SSbiexp(input, A1, lrc1, A2, lrc2)
input |
a numeric vector of values at which to evaluate the model. |
A1 |
a numeric parameter representing the multiplier of the first exponential. |
lrc1 |
a numeric parameter representing the natural logarithm of the rate constant of the first exponential. |
A2 |
a numeric parameter representing the multiplier of the second exponential. |
lrc2 |
a numeric parameter representing the natural logarithm of the rate constant of the second exponential. |
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
.
Jose Pinheiro and Douglas Bates
nls
, selfStart
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)