fitting data into a quadratic curve

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Hadi Data
Hadi Data 2019-10-4
评论： Star Strider 2019-10-15
Hello,
I have some data that can be fitted into a quadratic curve of y=ax^2 + bx + c. My data passes through the origin, and has a horizontal slope near the origin too. So my question is how do i force b and c to be zero in the qudratic equation ? while doing that i want to estimate the error too, so how do i keep track of the error if i have more than one quadratic equation.
I tried using fittype and polyval, and i am familiar with them, but that doesn't do my task.
I attached my data for better understanding.
Thanks for any help.

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Star Strider
Star Strider 2019-10-4
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
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Hadi Data
Hadi Data 2019-10-15
Perfect, that worked as i wanted. And yes i am using different data.
Thank you again and again :D , I learned alot from you.
Star Strider
Star Strider 2019-10-15
As always, my pleasure!
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