- To determine the number of Gaussian components needed to fit the data optimally you may make use of the Akaike Information Criteria (AIC) statistic. AIC gives the optimized loglikelihood values. You may try fitting the spectrum with different models by varying the number of Gaussian components in the “fitgmdist()” function. Select the model with the lowest value of AIC.
- In addition to the above, you may also try regularization by setting the “RegularizationValue” parameter in the “fitgmdist()” function.
Deconvolution of fluorescence spectra
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Kristoffer Linder on 20 Aug 2019
I want to make a deconvolution of a fluorescence spectra into its Gaussian components. I am not sure how many components there are, and I want to do it in Matlab. I tried "fitgmdist" but I did not manage to do it so i tried to do it manually generating three gaussian distribution and I adjusted the mean and standard deviation to get the image image below. It is just that I don't know how to adjust the parameter to get a correct estimaton, and I want to implement a algorithm that could do it automatically.
Jyothis Gireesh on 23 Aug 2019
I am assuming that you want to create an algorithm which can automatically determine the optimal number of Gaussian components needed to fit the given data.
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You may also make use of the following documentation for further clarification.