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Dec 18, 2017 at 17:24 comment added Miguel Intuitively, I'd say that if your target distribution doesn't have fat tails, that is a good ansatz, but I don't have any theory to back that up. I guess you could try different strategies and cross-validate them across as much data as you can get your hands on.
Dec 18, 2017 at 16:38 comment added llxxee Thank you, kernel density estimation solves the first part of my question, but when we can choose which points to observe, how do we make the decision? Say we know all the data frequency in a data set $f_1,f_2,...f_n$, but we can only observe $k$ points in the dataset to do the density estimation, what should be our strategy? Should we choose the data points with the highest frequency?
Dec 18, 2017 at 15:05 history edited Miguel CC BY-SA 3.0
Mention histograms
Dec 18, 2017 at 14:22 history notice added Tim Needs detailed answers
Dec 18, 2017 at 14:14 history answered Miguel CC BY-SA 3.0