Matlab curve fitter error with exponential form with 2 terms
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Briana Canet
el 11 de Nov. de 2023
Comentada: Torsten
el 11 de Nov. de 2023
I am trying to curve fit the following data using the following exponetial form with two terms. I was expecting a concave curve along the points, but it is not producting that.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1536505/image.png)
Please help. I am trying to curve fit the following points.
clc;
clear;
close all;
% Interior Square Footage
sqftL = [1500 1600 1750 1930 2250];
sqftUtilityL = [0 0.25 0.5 0.75 1];
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Respuesta aceptada
Matt J
el 11 de Nov. de 2023
Editada: Matt J
el 11 de Nov. de 2023
% Interior Square Footage
x = [1500 1600 1750 1930 2250];
y = [0 0.25 0.5 0.75 1];
theFit=fit(x' , y', 'exp2','Lower',[0 0 -inf -inf],'Upper',[inf 0 0 0 ])
plot(theFit , x , y)
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Torsten
el 11 de Nov. de 2023
% Interior Square Footage
x = [1500 1600 1750 1930 2250];
y = [0 0.25 0.5 0.75 1];
theFit=fit(x' , y', 'poly1')
plot(theFit , x , y)
Más respuestas (2)
Sulaymon Eshkabilov
el 11 de Nov. de 2023
It does work very well if the initial conditions are given. Here is how it can be attained:
% Interior Square Footage
sqftL = [1500 1600 1750 1930 2250];
sqftUtilityL = [0 0.25 0.5 0.75 1];
FModel = @(b,x)(b(1)*exp(b(2)*x));
b0=[0.1, 0.001]; % Initial guess for b
opts = statset('Display','iter','TolFun',1e-10);
beta = nlinfit(sqftL,sqftUtilityL, FModel,b0, opts);
x = linspace(min(sqftL), max(sqftL));
FModel_Vals = (beta(1)*exp(beta(2)*x));
plot(sqftL, sqftUtilityL, 'rd', 'MarkerSize',9, 'MarkerFaceColor','y')
hold on
plot(x, FModel_Vals, 'k', 'LineWidth',2)
legend('Data', 'Fit Model: a*exp(b*x)', 'Location', 'best')
xlabel('sqftL')
ylabel('sqftUtilityL & Fit Model')
grid on
1 comentario
Sulaymon Eshkabilov
el 11 de Nov. de 2023
It is better to fit with log fit.
% Interior Square Footage
sqftL = [1500 1600 1750 1930 2250];
sqftUtilityL = [0 0.25 0.5 0.75 1];
FModel = @(b,x)(b(1)*log(x)+b(2));
b0=[1, -1]; % Initial guess for b
opts = statset('Display','iter','TolFun',1e-10);
beta = nlinfit(sqftL,sqftUtilityL, FModel,b0, opts);
x = linspace(min(sqftL), max(sqftL));
FModel_Vals = (beta(1)*log(x)+beta(2));
plot(sqftL, sqftUtilityL, 'rd', 'MarkerSize',9, 'MarkerFaceColor','y')
hold on
plot(x, FModel_Vals, 'k', 'LineWidth',2)
legend('Data', 'Fit Model: a*log(x)+b', 'Location', 'best')
xlabel('sqftL')
ylabel('sqftUtilityL & Fit Model')
grid on
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