Linear Least Squares Regression

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A
A 2022-12-9
评论： A 2022-12-10
Ran in:
x = [2, -2, 3, -3];
y = [7, 8, 19, 17];
N = length(x);
X = 'ones (N, 1), x';
Y = y;
J='inv(X.*X)*X*Y';
plot(x,y,'bs',[0, 5],J(1)+J(2)*[0, 5]+J(3)*[0, 5]);
hold on
how can i turn this graph into this graph

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回答（1 个）

Bora Eryilmaz
Bora Eryilmaz 2022-12-9
编辑：Bora Eryilmaz 2022-12-9
Ran in:
% Original data
x = [2, -2, 3, -3];
y = [7, 8, 19, 17];
% Take tranposes.
x = x';
y = y';
% Find coefficients of a quadratic polynomial fit using linear least
% squares method.
C = [x.^2 x ones(size(x))] \ y
C = 3×1
2.1000 0.1538 -0.9000
% Get interpolated values on the polynomial.
xi = (-4:0.1:4)';
yi = C(1)*xi.^2 + C(2)*xi + C(3);
% Plot results.
plot(x,y, 'r*')
hold on
plot(xi,yi,'b-')

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