This article demonstrates a wavelet thresholding method for density estimation in finite mixtures, highlighting asymptotic performance under weak dependence.
In this article, we construct an adaptive wavelet thresholding estimator for the density in a finite mixture model. Our sample is drawn from an almost periodically correlated process under a weak dependence assumption. We assess the asymptotic performance of our estimator by establishing an upper bound for the integrated mean squared error over a Besov ball.
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Koné et al. (2025) studied this question.
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