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Published in 2022 at "Electronic Journal of Statistics"
DOI: 10.1214/21-ejs1975
Abstract: We prove minimax bounds for estimating Gaussian location mixtures on $\mathbb{R}^d$ under the squared $L^2$ and the squared Hellinger loss functions. Under the squared $L^2$ loss, we prove that the minimax rate is upper and…
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Keywords:
minimax bounds;
loss;
location mixtures;
gaussian location ... See more keywords