While there are many regression tools in matlab, there are few that do all the types of calculations typically needed by analytical chemists for performing linear regression and error calculations for unknowns measured with a calibration curve, all in one spot.
The function takes two vectors X and Y, which must be the same length, and which contain the calibration data. Optional inputs include a matrix of unknown measurements and whether results should be dumped to the screen or not. Unknowns must be provided with different samples in columns, replicate measurements in rows. If samples have different numbers of replicate measurements, pad the missing values with NaNs
Results are reported back in two simple structures, one with regression stats and one with results for any measured unknowns.
There are much more powerful tools out there, but this is one that any undergrad chemist just getting into MATLAB can use to handle their data.
James Harynuk (2021). Calibration curve (https://www.mathworks.com/matlabcentral/fileexchange/71623-calibration-curve), MATLAB Central File Exchange. Retrieved .
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