Correction of Density Estimators that are not Densities

By I. Glad, Nils Lid Hjort, N. Ushakov. 2003

83 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A bias-reduced approach to density estimation using Bernstein polynomials (2010, background): “Glad, Hjort, and Ushakov (2003) present an interesting solution to this that always improves the performance of the resulting estimator.”
Self‐consistent method for density estimation (2009, methodology): “Those can be corrected without any error cost by translating the estimate downwards until the positive part is normalized to 1, and setting to 0 the negative part (Glad et al., 2003; Ushakov, 1999).”
Bandwidth Selection in Kernel Density Estimation (2010, methodology): “A method for correcting density estimates that are not densities can be found in Glad, Hjort and Ushakov (2003), [7], but this problem will not be addressed in this report.”
Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting (2016, methodology): “For an overview and theoretical guarantees, we refer the reader to Hall and Murison (1993), Efromovich (1999), Glad, Hjort, and Ushakov (2003), and Wasserman (2006).”