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Using the Voigt line shape function requires a lot of intense computations for every iteration made, therefore approximations to the Voigt line shape can be implemented to solve the peak parameters. Two of the most common line shapes used are the Mixture of Gaussian and Lorentzian line shapes and the Pearson VII. Even though these functions do not solve the form of the true line shape exactly, they do approximate it, using far fewer calculations per iteration. The Mixture of both the Gaussian and Lorentzian line shapes within a function simulates the Voigt function while decreasing the computation time. Therefore this model is used to fit line shapes that are Voigt in nature. The parameters found from fitting this function to the data can be related to the proportion of the Lorentzian to Gaussian contribution to the line broadening. From which line width parameters due to the various broadening interactions can be calculated.
where M = mixture (% Lorz) | 
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