exponential regression functions with error in input values
显示 更早的评论
Hi, I am trying to fit a regression model that should look like something of the form y = e^(a-bx) for some positive constants a and b. I have been perviously using the linear least squares method after taking the log of both sides and then fitting a linear model and this works. However, due to some erros in my input data this will not work for the occasion where y = 0 for obvious reasons. The issue is I need to fit an exponential line that follows the points for example [4,100], [25,50], [100,0]. This line should remain postive although the point [100,0] is where the failure arises. Any help would be greatly appreciated!
采纳的回答
you can use lsqnonlin or lsqcurvefit
clear variables, close all
% data
x = [4 25 100];
y = [100 50 0];
% fitting function
yfit = @(p,x) exp(p(1)-p(2)*x);
% nonlin problem
f = @(p) yfit(p,x)-y;
% initial guess
p0 = [1 1];
% use lsqnonlin
pfit1 = lsqnonlin(f,p0);
% use built-in lsqcurvefit
pfit2 = lsqcurvefit(yfit,p0,x,y);
% plot
figure,hold on;
plot(x,y,'o')
xfit = linspace(min(x),max(x),100);
plot(xfit,yfit(pfit1,xfit))
plot(xfit,yfit(pfit2,xfit))
更多回答（1 个）
x = [4; 25; 100];
y = [100; 50; 0];
% objfcn = @(b,x) b(1) .* exp(b(2) - b(3).*x);
objfcn = @(b,x) exp(b(1) - b(2).*x);
[B,nres] = fminsearch(@(b)norm(y - objfcn(b,x)), rand(2,1))
xv = linspace(min(x), max(x), 50);
figure
plot(x, y, 'p')
hold on
plot(xv, objfcn(B,xv), '-r')
hold off
grid
The fitnlm function is more robust and provides statistics on the fit. Use the predict function to return the fitted curve and confidence region on the fit.
.
类别
在 帮助中心 和 File Exchange 中查找有关 Get Started with Curve Fitting Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
