This is my experimental data:
data = {{0, 5.5455}, {1, 5.561}, {3, 5.6075}, {10, 5.5455}, {30,
5.4835}, {100, 5.0965}, {300, 4.6935}, {1000, 4.438}, {14462,
4.012}, {23082, 3.9345}};
I need to fit to this model
model = 4.00 + p1 Exp[-(t/tau1)^mu1] + p2 Exp[-(t/tau2)^mu2];
with these conditions:
4.6 <=
p1 <=
5.5
4.0 <=
p2 <=
4.7
0<=
mu1<=
1
0<=
mu2<=
1
mi code is:
NonlinearModelFit[data, model, {p1, p2, tau1, tau2, mu1, mu2}, t]
But it gives this error:
FindFit::fitm: Unable to solve for the fit parameters; the design matrix is nonrectangular, non-numerical, or could not be inverted.
Power::indet: Indeterminate expression 0.^0. encountered.
Power::indet: Indeterminate expression 0.^0. encountered.
NonlinearModelFit::nrjnum: The Jacobian is not a matrix of real numbers at {p1,p2,tau1,tau2,mu1,mu2} = {1.,1.,1.,1.,1.,1.}.
I try this, but is nothing do
With[{4.6 <= p1 <= 5.5, 4.0 <= p2 <= 4.3, 0 <= mu1 <= 1,
0 <= mu2 <= 1, 3.85 <= p0 <= 4.0},
NonlinearModelFit[data, model, {p0, p1, p2, tau1, tau2, mu1, mu2},
t]]