Two-dimensional density estimation using smooth invertible transformations |
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Authors: | Ethan Anderes |
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Institution: | a Statistics Department, University of California at Davis, One Shields Avenue, Davis, CA 95616, USA b Department of Health Research and Policy (Biostatistics), Stanford University, 259 Campus Dr., Stanford, CA 94305, USA |
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Abstract: | We investigate the problem of estimating a smooth invertible transformation f when observing independent samples X1,…,Xn∼P°f where P is a known measure. We focus on the two-dimensional case where P and f are defined on R2. We present a flexible class of smooth invertible transformations in two dimensions with variational equations for optimizing over the classes, then study the problem of estimating the transformation f by penalized maximum likelihood estimation. We apply our methodology to the case when P°f has a density with respect to Lebesgue measure on R2 and demonstrate improvements over kernel density estimation on three examples. |
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Keywords: | Smooth invertible transformation Deformation Density estimation Quasiconformal map Optimization |
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