Least Squares method code

X =input('Enter list of abscissas: ');

Unable to run the 'fevalJSON' function because it calls the 'input' function, which is not supported for this product offering.

Y = input('Enter list of ordinates: ');
F = input('Enter 1 for linear fit, 2 for parabolic: ');
n = length(X);
N = F+1;
A= zeros(N,N);
for i=1:N
   for j=1:N
  A(i,j) = sum(X.^(i+j-2));
   end
end
B= zeros(N,1);
for k=1:N
   B(k) = sum((X.^(k-1)).*Y);
end
U=A\B;
% hien thi parabol
disp('Your polynomial is:')
grid on
for k=N:-1:2
   fprintf('+(%.(4fx^%d)',U(k),k-1)
end
fprintf('+(%.4f)\n', U(1))
%plotting
P = flip(U);
x = linspace(X(1),X(n),100);
y = polyval(P,x);
plot (x,y,'r')
hold on
plot(x,y,'o')

can someone turn that picture into something like this picture

or like a line when i choose F=1

[Image Analyst]

What values did you type in?

[A]

x = [0.8; 1.4; 2.7; 3.8; 4.8; 4.9]

y = [0.69; 1.0; 2.02; 2.39; 2.34; 2.83]

Answer 1

[William Rose]

@A,

[edit: I adjusted the fprintf() lines to produce better output.]

X = [0.8; 1.4; 2.7; 3.8; 4.8; 4.9];
Y = [0.69; 1.0; 2.02; 2.39; 2.34; 2.83];
%F = input('Enter 1 for linear fit, 2 for parabolic: ');
F=2;
n = length(X);
N = F+1;
A= zeros(N,N);
for i=1:N
    for j=1:N
        A(i,j) = sum(X.^(i+j-2));
    end
end
B= zeros(N,1);
for k=1:N
    B(k) = sum((X.^(k-1)).*Y);
end
U=A\B;
% hien thi parabol
disp('Your polynomial is:')

Your polynomial is:

for k=N:-1:2
   fprintf('%+.4f x^%d ',U(k),k-1)
end

-0.0947 x^2 +1.0215 x^1 

fprintf(' %+.4f \n', U(1))

 -0.1283 

%plotting
P = flip(U);
x = linspace(X(1),X(n),100);
y = polyval(P,x);
plot (x,y,'-r',X,Y,'b*')
legend('Fit','Data')

The above code uses F=2, i.e. parabolic fit. Good luck.