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• W2007242302 abstract "Abstract For the density estimation problem the global window width kernel density estimator does not perform well when the underlying density has features that require different amounts of smoothing at different locations. In this article we propose to transform the data with the intention that a global window width is more appropriate for the density of the transformed data. The density estimate of the original data is the “back-transform” by change of variables of the global window width estimate of the transformed data's density. We explore choosing the transformation from suitable parametric families. Data-based selection rules for the choice of transformations and the window width are discussed. Application to real and simulated data demonstrates the usefulness of our proposals." @default.
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• W2007242302 date "1991-06-01" @default.
• W2007242302 modified "2023-10-18" @default.
• W2007242302 title "Transformations in Density Estimation" @default.
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• W2007242302 doi "https://doi.org/10.1080/01621459.1991.10475041" @default.
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