Abstract:Nonparametric density estimation methods are designed to estimate the density function
f
that generates a sample of observations, without assuming a parametric form for
f
. Rather,
f
is only assumed to be smooth, where smoothness is defined as the condition that at least a specified number of derivatives are square integrable. Penalized maximum likelihood estimators accomplish this by maximizing a penalized form of the log‐likelihood, wher… Show more
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