matlab curve fitting: restrictions on parameters - algorithm

Question

I have 5 non-parametric models all with 5 to 8 parameters. This models are used to fit longitudinal data y(t) with t being time. Every datafile is fitted by all 5 models for comparison. The model itself cannot be altered.
For fitting starting values are used and these are fitted into a lsqcurvefit model using a levenberg-marquardt algortihm. So I've written a script for several models and one function for curvefitting
if i perform the curve fitting a lot of the starting values are wandering off to extreme values. This is the thing I want to avoid since these parameters should stay in the proximity off it's starting values and should only change between a well defined range or so that only curve fits within a standard deviation are included.Important to note here is that this restrictions should be imposed during the curve fitting (iterative numerization techique) and not afterwards.
The function I've written to fit models into height:
% Fit a specific model for all valid persons
try
opts = optimoptions(#lsqcurvefit, 'Algorithm', 'levenberg-marquardt');
[personalParams,personalRes,personalResidual] = lsqcurvefit(heightModel,initialValues,personalData(:,1),personalData(:,2),[],[],opts);
catch
x=1;
end
The function I've written for one of my models
elseif strcmpi(model,'jpss')
% y = h_1(1-(1/(1+((t+0.75)^c_1/d_1)+((t+0.75)^c_2/d_2)+((t+0.75)^c_3/d_3)))
% heightModel = #(params,ages) params(1).*(1-1./(1+((ages+0.75).^params(2))./params(3) + ((ages+0.75).^params(4))./params(5) + ((ages+0.75).^params(6))./params(7)));
heightModel = #(params,ages) params(1).*(1-1./(1+(((ages+0.75)./params(3)).^params(2)) + (((ages+0.75)./params(5)).^params(4)) + ((ages+0.75)./params(7)).^params(6))); % Adapted 25/07
modelStrings = {'h1','c1','d1','c2','d2','c3','d3'};
% Define initial values
if strcmpi('male',gender)
initialValues = [174.8 0.6109 2.9743 3.614 9.88 22.393 13.59];
else
initialValues = [162.7 0.6546 2.43 4.011 8.579 18.394 11.846];
end
What I would like to do:
Is it possible to place restrictions on every startingvalue #initial values? Putting restrictions on lsqcurvefit wouldn't be a good idea I think since there are different models with different starting values and different ranges that are allowed.
I had 2 things in my mind:
1. using range and place this between the initial values
initialValues = [162.7 0.6546 2.43 4.011 8.579 18.394 11.846]`
if range a1=[150,180]; range a2=[0.3,0.8] and so one
place lb and ub restrictions seperatly on all my initialvalues between lsqcurvefit
if Heightmodel='name model'
initial value* 1.2 and lb = initial value* 0.8
Can someone give me some hints or pointers because I can't make it work.
Thanks in advance
Lucy
Could somebody help me out

Answer 1

You state: there are different models with different starting values and different ranges that are allowed. This is where you can use ub and lb. How to do this is outlined in the lsqcurvefit documentation:
X=LSQCURVEFIT(FUN,X0,XDATA,YDATA,LB,UB) defines a set of lower and
upper bounds on the design variables, X, so that the solution is in the
range LB <= X <= UB. Use empty matrices for LB and UB if no bounds
exist. Set LB(i) = -Inf if X(i) is unbounded below; set UB(i) = Inf if
X(i) is unbounded above.
For instance in the following example the parameters are constrained within limits during the fit. The lower bound (lb) and upper bound (ub) are set to 20% below and above the starting values, respectively.
heightModel = #(params,ages) abs(params(1).*(1-1./(1+(params(2).* (ages+params(8) )).^params(5) +(params(3).* (ages+params(8) )).^params(6) +(params(4) .*(ages+params(8) )).^params(7) )));
initialValues = [161.92 0.4173 0.1354 0.090 0.540 2.87 14.281 0.3701];
lb = 0.8*initialValues; % <-- lower bound is 20% smaller than initial par values
ub = 1.2*initialValues;
[parsout,resnorm,residual] = lsqcurvefit(heightModel,initialValues,t,ht,lb,ub);