Version 8.5 adds two new peak shapes and changes IQR (Interquatrile range) reported in the bootstrap method to
IQR/1.34896, which equals the relative standard deviation without outliers for a normal distribution.
Updated summary
Version 7.9: April, 2016, Added shapes 38=variable time constant ExpLorentzian; 40=sine wave; 41=rectangle;
42=flattened Gaussian; 43=Gompertz function (3 variable logistic); 44=1-exp(-k*x). "extra" defaults to 1 if not specified in input arguments.
Edited discription
August, 2015, Allows fixed width models (shapes 11 ands 12)
to have different fixed widths for each peak (specified by a vector);
also adds a fixed-height Gaussian model (shape 34) with heights specified
by a vector (input argument 10)
Version 5.7: August, 2014. Adds minimum width constraint as 13th input argument (See example 19); Can be a vector for multiple peak shapes. The default if not specified is the independent variable (x) interval.
Version 4.2 ,corrects some bugs, adds an additional autozero mode that subtracts a flat baseline without requiring that the signal return to the baseline at both ends of the signal segment, and adds a Voigt profile peak shape.
Version 3.51: January, 2013. Improved accuracy of linear autozero calculation. Improved calculation of default "start" guess when not specified in the input arguments.
Version 3.3: September, 2012. Added 11th input argument ('plots') to turn plotting OFF (plots=0) or on (plots=1); added Gaussian/Lorentzian blend, bifurcated (asymmetrical) Gaussian and Lorentzian.
Editor's Note: This file was selected as MATLAB Central Pick of the Week
peakfit(signal,center,window,NumPeaks,peakshape,extra,NumTrials,start,autozero,fixedparameters,plots,bipolar,minwidth,DELTA,clipheight)
A command-line peak fitting program for time-series signals, written as a self-contained Matlab function in a single m-file. Uses a non-linear optimization algorithm to decompose a complex, overlapping-peak signal into its component parts. The objective is to determine whether your signal can be represented as the sum of fundamental underlying peaks shapes. Accepts signals of any length, including those with non-integer and non-uniform x-values. Fits any number of peaks of 44 different shapes, including models with multiple shapes. This is a command line version, usable from a remote terminal. It is capable of making multiple trial fits with sightly different starting values and taking the one with the lowest mean fit error, and it can estimate the standard deviation of peak parameters from a single signal using the bootstrap method.
Cite As
Tom O'Haver (2022). peakfit.m (https://www.mathworks.com/matlabcentral/fileexchange/23611-peakfit-m), MATLAB Central File Exchange.
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