Writing my own polyfit function
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How would one write their own polyfit function using only mldivide and for loops?
I have a basic idea:
function [A,e] = MyPolyRegressor(x, y, n)
c=ones(n,1);
for i=1:n;
c(:,i)=x.^(i-1);
end
A=c\y
e=c*A-y
But it doesnt quite work.
3 comentarios
Jan
el 26 de Oct. de 2012
Editada: Jan
el 26 de Oct. de 2012
Because you didn't format your code properly (please learn how to do this...), it is not possible to find out, which one is the "line 4".
But with some guessing: "ones(n,1)" and even "ones(size(x))" create vectors, while the required Vandermonde-matrix needs the dimensions [length(x), n+1].
Respuesta aceptada
Jan
el 26 de Oct. de 2012
Editada: Jan
el 26 de Oct. de 2012
function p = fPolyFit(x, y, n)
% Construct Vandermonde matrix:
x = x(:);
V = ones(length(x), n + 1);
for j = n:-1:1
V(:, j) = V(:, j + 1) .* x;
end
% Solve least squares problem:
[Q, R] = qr(V, 0);
p = transpose(R \ (transpose(Q) * y(:)));
% Equivalent: (V \ y)'
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Más respuestas (1)
Vrushabh Bhangod
el 19 de Mayo de 2018
Editada: Walter Roberson
el 10 de Jun. de 2018
function [p,mu,f] = plofit(x,y,n)
% x = input samples
% y = output function,n = order
m = length(x); %number of rows in the Vandermonde Matrix
V = zeros(m,n);
a = n;
for i = 1:m
v = zeros(1,n);
for j = a:-1:1
v(n+1-j) = realpow(x(i),j);
end
V(i,:) = v;
end
V(:,n+1)=ones(m,1);% adding 1 column to ones to the vandermonde matrix
%%QR method to compute the least squares solution for the coefficients,'p'
[Q,R] = qr(V,0);
p = transpose(R \ (transpose(Q) * y'));
f = polyval(p,x);
%%to find mean
mean = sum(x)/length(x);
sq = 0;
for i =1:length(x)
sq = sq + (x(i)-mean)^2;
end
sd = (sq/length(x))^0.5;
mu = [mean;sd];
end
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