1-27206531-0-90000491 <domi at sun11.ukl.uni-freiburg.de> writes:
I use:
platform i386-pc-mingw32
arch x86
os Win32
system x86, Win32
status
major 1
minor 4.1
year 2002
month 01
day 30
language R
Thank you for providing that information.
I try to fit a 2 compartment model. The compartments are open, connected
to each other and are filled via constant input and a time depended
function as well. Data describes increasing of Apo B after dialysis. Aim
of the analysis is to test the hypothesis whether the data could described
by two simple disconnected one compartment modes ore the "saturated
model" holds? The first order differential equation for the saturated
model:
db5 = - (k50+k56)*b5 + k56*b6 + c*g(t) + h
db6 = + k65*b5 - (k60+k65)*b6 + d
db5, db6 are the first derivatives, b5, b6 are the functions to be
fitted. The remaining parameters are unknown and should follow from the
fit.
assuming that g(t) has the functional form: b4i + (b40-b4i)*exp(-k4*t)
(after calculations of 2 papers of A4) follows the solution:
L5L6 <- function(b40, b4i, k4, t, p50, p56, p60, p65, pc, ph, pd, pb50,
pb60) {
k50 <- exp(p50)
k56 <- exp(p56)
k60 <- exp(p60)
k65 <- exp(p65)
c <- exp(pc)
h <- exp(ph)
d <- exp(pd)
b50 <- exp(pb50)
b60 <- exp(pb60)
a <- (k50+k56)
b <- k65
e <- k56
f <- (k60+k65)
z1 <- (-(a+f)/2 - sqrt((a+f)^2/4 - a*f + b*e))
z2 <- (-(a+f)/2 + sqrt((a+f)^2/4 - a*f + b*e))
K <- ((z1+a)/(z2-z1))
B1 <- (b/(z2-z1)*b60 - K*b50)
A1 <- (b50-B1)
X1 <- (b*d/(z2-z1)-K*(c*b4i+h))
X2 <- (K*c*(b4i-b40))
X3 <- (c*b4i + h - X1)
X4 <- (c*(b40-b4i)- X2)
C1E <- (X3/(-z1)*(1-exp(z1*t)) +
X4/(-(k4+z1))*(exp(-k4*t)-exp(z1*t)))
C2E <- (X1/(-z2)*(1-exp(z2*t)) +
X2/(-(k4+z2))*(exp(-k4*t)-exp(z2*t)))
b5 <- (A1*exp(z1*t) + B1*exp(z2*t) + C1E + C2E)
b6 <- ((z1+a)/b * A1*exp(z1*t) + (z2+a)/b * B1*exp(z2*t) +
(z1+a)/b * C1E + (z2+a)/b * C2E)
y <- f5*b5 + f6*b6
return(y)
}
I am in the lucky circumstances having starting values, because a nlr-fit
succeeds, the graphical presentation of the fits looks quite nice. The nlr
function is part of Lindsey's library(gnlm), but now I would like to apply
Pinheiro and Bates library(nlme) and I have got an error:
m2 <- nls(y ~ L5L6(b40, b4i, k4, t, p50, p56, p60, p65, pc, ph, pd,
pb50, pb60),
+ data=help, start=c(p50=0.008678954, p56=-0.595153967,
+ p60=-4.602990518, p65=-0.625732096,
+ pc=-0.128657978, ph=0.708033556, pd=1.140357461, pb50=1.311141424,
+ pb60=1.270852258))
Error in numericDeriv(form[[3]], names(ind), env) :
Missing value or an Infinity produced when evaluating the model
If somebody feel that he can help me, I could send him my R- code and
data file as well.
It is likely that the iterative algorithm is progressing to values of
the parameters that don't make sense physically. I suggest that you
add trace = TRUE to your call to nls. This will provide a record of the
parameter values, the residual sum of squares, and the convergence
criterion throughout the iterations.
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