MATLAB: Linear regression : estimate the parameters

linear regression

Hello! How can I estimate the parameters (beta1 and beata2) of the following model : y=beta1+beta2*x+epsilon Thanks.

Best Answer

p = polyfit(x,y,1); 
beta1 = p(2); 
beta2 = p(1);

Related Solutions

MATLAB: Gradient of the fit with uncertainty and R

See the section in the polyfit (link) documentation on Output Arguments, specifically R (link). It is the ‘Triangular factor from a QR decomposition of the Vandermonde matrix of x’.

Since ‘R’ is a field of ‘bint’ (in the example you posted), there is nothing further you need to do, since ‘R’ is calculated for you. (If I remember correctly, the ‘R’ field is the covariance matrix. It has been a while since I explored polyfit.)

MATLAB: How to plot this implicit function

Try symbolic expression

clc,clear
alpha=1.5; A=0.0207; gamma=0.25;
syms beta eps
x = (beta-alpha*(beta-gamma)+sqrt((beta-alpha*(beta-gamma)).^2+4*alpha*beta*gamma*A))./(2*beta);
y =  x.*(1-x).*beta/gamma;
t =  -x+x.*y.*(alpha-eps*beta)./((A+x+y).^2);
d =  eps*beta.*x.*y.*(x.^2+(A+x).*x+A*alpha)./((A+x+y).^3);
    % convert symbolic expression to function handle
F = matlabFunction(t.^2 - d,'vars',[beta eps]);
ezplot(F,[0,1,0,1]);

Best Answer

Related Solutions

MATLAB: Gradient of the fit with uncertainty and R

MATLAB: How to plot this implicit function

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