% lsftest - Program for testing least squares fit routines
clear; help lsftest; % Clear memory and print header
N = 50; % Number of data points
randn('seed',0); % Initialize random number generator
fprintf('Enter the coefficients of the quadratic \n');
fprintf(' Y(x) = c(1) + c(2)*x + c(3)*x^2 \n');
c = input('as [c(1) c(2) c(3)] - ');
alpha = input('Enter estimated error bar - ');
x = 1:N;
r = alpha*randn(1,N); % Gaussian distributed random vector
y = c(1) + c(2)*x + c(3)*x.^2 + r;
sigma = alpha*ones(1,N); % Constant error bar
%%% Linear regression (Straight line) fit
M = 2; % Number of fit parameters (M=2 is straight line)
[a_fit sig_a yy chisqr] = linreg(x,y,sigma);
%%% Polynomial fit
%%% M = 3; % Number of fit parameters (M=3 is quadratic)
%%% [a_fit sig_a yy chisqr] = pollsf(x,y,sigma,M);
fprintf('Fit parameters:\n');
for i=1:M
fprintf(' a(%g) = %g +/- %g \n',i,a_fit(i),sig_a(i));
end
fprintf('Chi square = %g, N-M = %g \n',chisqr,N-M);
plot(x,y,'o',x,yy,'-');
hold on; % Freeze the plot to place error bars
errorbar(x,y,sigma)
xlabel('x'); ylabel('y');
title('Data (circle); fit (solid line)');
hold off; % Unfreeze the plot
