%% Fit Linear Interpolant Models Using the fit Function
% This example shows how to use the fit function to fit linear interpolant models to data.
%% Interpolant Fitting Methods
% Specify the interpolant model method when calling the fit function using one of the options outlined in Interpolant Model Names. None of the interpolant methods has any additional fit option parameters.
%% Fit a Linear Interpolant Model
% Load data and fit a linear interpolant model using the 'linearinterp' option.

load census
f = fit(cdate,pop,'linearinterp');
plot(f,cdate,pop);

%
%% Compare Linear Interpolant Models
% Load data and create both nearest neighbor and pchip interpolant fits using the 'nearestinterp' and 'pchip' options.

load carbon12alpha
f1 = fit(angle,counts,'nearestinterp');
f2 = fit(angle,counts,'pchip');

%
% Compare the fitted curves f1 and f2 on a plot.

p1 = plot(f1,angle,counts);
xlim([min(angle),max(angle)])
hold on

p2 = plot(f2,'b');
hold off
legend([p1;p2],'Counts per Angle','Nearest Neighbor','pchip',...
    'Location','northwest')

% For an alternative to 'cubicinterp' or 'pchipinterp', you can use other spline functions that give you greater control over what you create. See About Splines in Curve Fitting Toolbox.
% Copyright 2012 The MathWorks, Inc.