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I have a dataset of a random variable whose probability density function can be fitted/modelled as a sum of N probability density functions of normal distributions:

[itex]

F_X(x) = p(\mu_1,\sigma_1^2)+p(\mu_2,\sigma_2^2)+\ldots+p({\mu}_x,\sigma_x^2)

[/itex]

I am interested in a fitting method can robustly determine the values of [itex]\mu_1,\sigma_1,\mu_2,\sigma_2,[/itex] etc

Note this is NOT convolution of normal distributions.

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# Curve fitting of summed normal distributions

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