I'm pretty new to Bayesian statistics and I want to use Bayesian regression on a 2D data set (frequency on x-axis and measurement data on the y-axis) to quantify the uncertainties. The model is a simple sum of multiple Gaussians (number of Gaussians = 10) with unknown parameters (amplitude, position, and width of the Gaussians). I am trying my hands on Bayesian Inference for Gaussian mixture models using PyMC3.
I am not sure if this is the right approach to proceed. Any leads on the same would be highly appreciated. Thanks.