MATLAB: Extrapolate best-fit line

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Hello,

This is a section of one of my plots. I am estimating the slope of the "crosses data", i.e. the star is not included in that estimation (I am just using it as a reference value). I want to show that my best fit of the crosses also passes through that star. How can I extrapolate this without having to include the star in my estimate? Thanks

Best Answer

If you have the coefficients c(1) and c(2) of the fit line l(x)=c(1)+c(2)*x, just evaluate the equation at the x-coordinate of the star point and compare with the y-coordinate of the star point.

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MATLAB: Fitting data into a quadratic curve

To force ‘b’ and ‘c’ to be zero:

B = volume_flow_rate1(:).^2 \ influence(:)                              % Estimate Regression Parameter
vfrv = linspace(min(volume_flow_rate1), max(volume_flow_rate1));        % Vector For Regression Evaluation

inflv = vfrv(:).^2 * B;                                                 % Evaluate Regression

figure();
plot(volume_flow_rate1,influence, '--r*' );
hold on
plot(vfrv, inflv, '-.k')                                                % Plot Regression

hold off
xlabel ('Q (uL/s)');
ylabel ('P(Pa)');
legend ('Via');
text(25, 1200, sprintf('y = %.6f\\cdotx^2', B))                         % Regression Equation

The regression parameter is:

B =
        0.0266527362537937

To force only ‘c’ to be zero:

B = [volume_flow_rate1(:).^2, volume_flow_rate1(:)] \ influence(:);     % Estimate Regression Parameters
vfrv = linspace(min(volume_flow_rate1), max(volume_flow_rate1));        % Vector For Regression Evaluation
inflv = [vfrv(:).^2, vfrv(:)] * B;                                      % Evaluate Regression
figure();
plot(volume_flow_rate1,influence, '--r*' );
hold on
plot(vfrv, inflv, '-.k')                                                % Plot Regression
hold off
xlabel ('Q (uL/s)');
ylabel ('P(Pa)');
legend ('Via');
text(25, 1200, sprintf('y = %.6f\\cdotx^2  %+.6f\\cdotx', B))           % Regression Equation

The regression parameter estimates are:

B =
        0.0304986880886496
        -0.722814145120915

MATLAB: Logarithmic best-fit line

No. You have negative y data, and logarithmic fit of that would go complex valued.

If you only want the x to be logarithmic, then either use semilogx() or else plot in your normal way and the set the XScale property of the axes to 'log'

Best Answer

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MATLAB: Fitting data into a quadratic curve

MATLAB: Logarithmic best-fit line

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