Hi everyone,

I'm trying to perform a bi exponential Fit with the package NLS. the
plinear algorithm seems to be a good choice

see:

p<-3000
q<-1000
a<--0.03
b<--0.02
t<-seq(0:144);t
y<-p*exp(a*t) + q*exp(b*t)+rnorm(t,sd=0.3*(p*
exp(a*t) + q*exp(b*t)))
fittA <- nls(y~cbind(exp(a*t), exp(b*t)),
algorithm="plinear",start=list(a=-.1, b=-0.2), data=list(y=y, t=t),
trace=FALSE);fittA

#          a          b         .lin1      .lin2
# -0.003074   -2.777     4512     -2399

fittB <- nls(y~cbind(exp(a*t), exp(b*t)),
algorithm="plinear",start=list(a=-.1, b=-0.3), data=list(y=y, t=t),
trace=FALSE);fittB

#        a              b          .lin1           .lin2
#  -0.02248   -0.04684 2414.86017 2052.96601


but

1 - the initial condition is very sensitive, is there any way to find a
good start for the parameters?
2 - I would like to havre .lin1 >0 ans .lin2 >0 , is there a way to do that?


thx a lot

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