Plotting with lsqnonlin regression

Hello,

I wrote a function that uses lsqnonlin to generate predictions but I'm wondering how I can use those predictions to make plots and visulaize them? Should I be using lsqcurvefit instead? Any and all suggestions are welcome! The function lsq calls errFun and I've included them below for reference. Thank you in advance for your help!

function results = lsq(M) % takes Nx3 matrix where columns are Lx, Ly, gap
results = table(); 
tempTable = table(); 
idx = nchoosek(1:size(M,1), 3);  % Nx3 matrix of all index trios
a = [];
Lx = [];
Ly = [];
gap = [];
for k = 1:size(idx, 1)
    ix = idx(k ,:); % current idx trio, row vector
    Lx = M(ix,1)';
    Ly = M(ix,2)';
    gap = M(ix,3);  
    L = sqrt((M(ix,1).^2 + M(ix,2).^2)/2);
    % Here is where I'm having trouble. I passed the four arguments and the
    % errors says "Too many input argumetns".
    lsq = lsqnonlin(@(coeff) errFun(coeff, L, M(ix,3)), [0; 1; 1]);
    a(k) = lsq(1);
    
    tempTable.Lx = Lx(:)';
    tempTable.Ly = Ly( :)';
    tempTable.L = L(:)';
    tempTable.Prediction = a(k)';
    results = [results;tempTable];
end
results.PercentErr = abs((results.Prediction - 4.5670) ./ 4.5670) * 100;
end

function fErr = errFun(coeff, xdata, ydata) 
    %parameters
    a = coeff(1);
    b = coeff(2);
    c = coeff(3);
    % calculate prediction from model
    yModel = a + b*exp(-c .* xdata);
    fErr = yModel - ydata;
end

Answer 1

[Gaurav Garg]

Hi Valeria,

You can look at the examples here to check how to plot and visualize the results.