MATLAB: Generalized Non-Linear Mixed Model with Matlab

binary datalogistic regressionmixed modelStatistics and Machine Learning Toolbox

Hello everyone,

I know that the fitglme function is very useful to run a Generalized Linear Mixed Model

However, is there any function able to perform a Generalized Non-Linear Mixed Model with matlab ?

Thank you,

Vincent

Best Answer

Generalized non linear mixed model feature is not present as of now.

I have brought this issue to the concerned people and it might be considered in any future release

Related Solutions

MATLAB: Non-linear FRF

If you have Simulink, you can model this equation ( look at the documentation for the demo model 'vdp' for reference ).

Then, use the linear analysis tool for FRF. This blog posting might be helpful: http://blogs.mathworks.com/seth/2010/02/26/how-to-estimate-the-frequency-response-of-a-simulink-model/

MATLAB: Non-linear solver

See if this does what you want:

F=96485; 
T=298; 
R=8.314;
% % % i=a*exp(-c*F*E/(R*T))+b*exp(-d*F*E/(R*T));                % Original Equation
% % % a = p(1),  b = p(2),  c = p(3),  d = p(4)                 % Define Parameters
fcn = @(p,E,i) p(1).*exp(-p(3)*F*E/(R*T)) + p(2).*exp(-p(4)*F*E/(R*T)) - i;
E = 42;                                                         % Use Correct Value

i = 24;                                                         % Use Correct Value
p0 = rand(4,1)*1E-6;
[Params,fval] = fsolve(@(p)fcn(p,E,i), p0)

If you have vectors of values for ‘E’ and ‘i’, use a nested loop to iterate through them:

E = [...];
i = [...];
for k1 = 1:numel(E)
    for k2 = 1:numel(i);
        Params{k1,k2} = fsolve(@(p)fcn(p,E(k1),i(k2)), p0);
    end
end

Best Answer

Related Solutions

MATLAB: Non-linear FRF

MATLAB: Non-linear solver

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