[ÇóÖú] matlabÇúÏßÄâºÏ basic fitting Óëpolyfit

function [th,err,yi]=polyfits(x,y,N,xi,r)
%x,y  :Êý¾ÝµãϵÁÐ
%N    :¶àÏîʽÄâºÏµÄϵͳ
%r    :¼ÓȨϵÊýµÄÄæ¾ØÕó

M=length(x);
x=x(:);
y=y(:);

%Åжϵ÷Óú¯ÊýµÄ¸ñʽ£¬¿¼ÂÇȨÕó
if nargin==4
%µ±Óû§µ÷Óú¯Êý¸ñʽΪ(x,y,N,r)
    if length(xi)==M
        r=xi;
        xi=x;
%µ±Óû§µ÷Óú¯Êý¸ñʽΪ(x,y,N, xi)£¬È¨ÕóΪ1
    else r=1;
    end
%µ±Óû§µ÷Óú¯Êý¸ñʽΪ(x,y,N)£¬²»¿¼ÂÇȨÕó
elseif nargin==3
    xi=x;
    r=1;
end
%Çó½âϵÊý¾ØÕó
A(:,N+1)=ones(M,1);
for n=N:-1:1
    A(:,n)=A(:,n+1).*x;
end

if length(r)==M
    for m=1:M
        A(m,:)=A(m,:)/r(m);
        y(m)=y(m)/r(m);
    end
end

%¼ÆËãÄâºÏϵÊý
th=(A\y)';
ye=polyval(th,x);
err=norm(y-ye)/norm(y);
yi=polyval(th,xi);

clear;
clf;
x=input('ÇëÊäÈëxÖµ:');
y=input('ÇëÊäÈëyÖµ:');
% x=[ 10.5  13  13.8  16  18  19 20.8];
% y=[1190  1040 1000 800 600 430 200];
% eb=[0.2*ones(5,1);ones(5,1)];
[x,i]=sort(x);
y=y(i);
xi=min(x)+[0:100]/100*(max(x)-min(x));
for i=1:4
N=2*i-1;
[th,err1,yi]=polyfits(x,y,N,xi);
  subplot(220+i);
plot(x,y,'k*')
hold on
plot(xi,yi,'g:','LineWidth',1.5)
title(['The ',num2str(N),'th Polynomial Curve Fitting'])
grid on
end