gistfile1.txt

clear all; close all; clc

%% Exercise 3-1A

% find reasonable best-fit polynomial for data1 and data2

data1 = load('data1.txt');
data2 = load('data2.txt');
data3 = load('data3.txt');

x1 = data1(:,1);
y1 = data1(:,2);

x2 = data2(:,1);
y2 = data2(:,2);

P1 = polyfit(x1,y1,1);
P2 = polyfit(x2,y2,2);

save -ASCII A1.dat P1;
save -ASCII A2.dat P2;

% find root mean square error for data1 and data2

poly1 = polyval(P1,x1);

rms1 = sqrt((mean(y1-poly1)).^2);

poly2 = polyval(P2,x2);

rms2 = sqrt((mean(y2-poly2)).^2);

ans3 = [rms1 rms2];

save -ASCII A3.dat ans3;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% Exercise 3-1B

%Compute the best-fit polynomial for data3 for each polynomial order between 1 and 10. Also compute the RMS error between each polynomial fit and the data. Evaluate the 7-th order polynomial at locations .03:.03:3, and store as a row vector Fvals.

x=zeros(10,11)
for i = 1:10;
   x(i) = polyfit(data3(:,1),data3(:,2),i)
end




%for x = .03:.03:3
%   y = polyval(p3_3,x)
%end