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- W4309155282 abstract "The aim of this paper is to establish non-asymptotic minimax rates of testing for goodness-of-fit hypotheses in a heteroscedastic setting. More precisely, we deal with sequences $(Y_j)_{jin J}$ of independent Gaussian random variables, having mean $(theta_j)_{jin J}$ and variance $(sigma_j)_{jin J}$. The set $J$ will be either finite or countable. In particular, such a model covers the inverse problem setting where few results in test theory have been obtained. The rates of testing are obtained with respect to $l_2$ and $l_{infty}$ norms, without assumption on $(sigma_j)_{jin J}$ and on several functions spaces. Our point of view is completely non-asymptotic." @default.
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- W4309155282 date "2009-12-12" @default.
- W4309155282 modified "2023-10-13" @default.
- W4309155282 title "Non asymptotic minimax rates of testing in signal detection with heterogeneous variances" @default.
- W4309155282 doi "https://doi.org/10.48550/arxiv.0912.2423" @default.
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