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Using Kernel Density Estimation for Model Development?
The way that I have seen kernel density estimation be used in particular is for model development. So we're talking about the distribution of each of our parameters. That's something that we're interested in understanding in a continuous sense. Do you mind to start to apply something with kernel density estimations so I can understand how this would be better?