Probability Density Estimation
For observational data, (1.5) of Example 1.2 defines penalized likelihood density estimation. Of interest are the selection of smoothing parameters, the computation of the estimates, and the asymptotic behavior of the estimates. Variants of (1.5) are also called for to accommodate data subject to selection bias and data from conditional distributions.
KeywordsSmoothing Parameter Unity Constraint Conditional Density Reproduce Kernel Hilbert Space Side Condition
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