%get the residual
d_res=d_data-d_model;

%plot the data, fitted values, and residual in the same plot
figure(1);
clf;
subplot(3, 1, 1);
plot(d_data);
axis tight;
ylabel('Data', 'FontSize', 18);
title(['Two Parameters Estimation C=' num2str(C) ', K=' num2str(K)]);

subplot(3, 1, 2);
plot(d_model, 'r');
axis tight;
ylabel('Model', 'FontSize', 18);

subplot(3, 1, 3);
plot(d_res, 'g');
axis tight;
ylabel('Residual', 'FontSize', 18);

%plot them in the same plot
figure(2);
clf;
plot(d_data);
hold on;
plot(d_model, 'r--');
plot(d_res, 'g:');
hold off;
legend('experimental data','model displacement', 'Residual');
xlabel('Time','FontSize', 18);
ylabel('Displacement');
axis tight;

%just plot the residual vs time
%this is to check the dependence structure

figure(3);
clf;
plot(d_res, 'g.');
axis tight;
ylabel('Residual', 'FontSize', 18);
xlabel('Time', 'FontSize', 18);

%checking the residuals have the same variance or not
%plot the residual vs. the fitted values

figure(4);
clf;
plot(d_model, d_res, 'o');
axis tight;
xlabel('Fitted Value', 'FontSize', 18);
ylabel('Residual', 'FontSize', 18);

%check whether the residuals are truly from Normal distribution
%1. quantile-quantile plot

figure(5);
clf;
qqplot(d_res);

%2. normality-probablity plot

figure(6);
clf;
normplot(d_res);