Matlab least square fitting

1、 Content abstract

A little
414- Can communicate 、 consulting 、 Answering question

2、 Content description

A little

3、 Simulation analysis

close all
clear
clc
x=2:15;
y=[6.42,8.20,9.58,9.50,9.70,10.00,9.93,9.99,10.49,10.59,10.60,10.80,10.60,10.9];
p = polyfit(x,y,6);
x1 = 2:0.01:15;
y1 = polyval(p,x1);
figure
plot(x,y,'*',x1,y1,'r')
xlabel 'x  Axis ' 
ylabel 'y  Axis ' 
title(' least square polyfit Fitting diagram ') 
figure
bar(x,polyval(p,x)-y)
xlabel 'x  Axis ' 
ylabel ' residual ' 
title(' least square polyfit Fitting diagram ') 

k = length(x); 
X=[ones(k,1) x' x.^2' x.^3']; 
[b, bint, r, rint, stats] = regress(y',X);
x2 = 2:0.01:15;
y2 = b(1)+b(2)*x2+x2.^2*b(3)+x2.^3*b(4);
figure
plot(x,y,'*',x2,y2,'r')
xlabel 'x  Axis ' 
ylabel 'y  Axis ' 
title(' least square regress Fitting diagram ') 
figure
bar(x,r)
xlabel 'x  Axis ' 
ylabel ' residual ' 
title(' least square regress Fitting diagram ') 

4、 Reference paper

A little