A flexible and robust approach to univariate Gaussian splitting using parameterised Gaussian mixtures

Fuente: arXiv
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Auteurs principaux: Mikhin, Dmitry, Xiourouppa, Athena
Format: Preprint
Publié: 2026
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author Mikhin, Dmitry
Xiourouppa, Athena
author_facet Mikhin, Dmitry
Xiourouppa, Athena
contents We consider approximation of a Gaussian distribution with a mixture of homoscedastic Gaussians of smaller variance. The solution is obtained by minimising the $L^2$ norm between the original Gaussian and the mixture, which is parameterised to reduce the complexity of the optimisation problem. The developed technique is straightforward, sufficiently robust and yields Gaussian Mixtures that rapidly approach the original function as the number of mixands is increased. The proposed solution is examined for multiple special cases of input parameters resulting in further simplifications. Extension of the proposed method for approximating non-Gaussian distributions is discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2606_01530
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A flexible and robust approach to univariate Gaussian splitting using parameterised Gaussian mixtures
Mikhin, Dmitry
Xiourouppa, Athena
Statistics Theory
We consider approximation of a Gaussian distribution with a mixture of homoscedastic Gaussians of smaller variance. The solution is obtained by minimising the $L^2$ norm between the original Gaussian and the mixture, which is parameterised to reduce the complexity of the optimisation problem. The developed technique is straightforward, sufficiently robust and yields Gaussian Mixtures that rapidly approach the original function as the number of mixands is increased. The proposed solution is examined for multiple special cases of input parameters resulting in further simplifications. Extension of the proposed method for approximating non-Gaussian distributions is discussed.
title A flexible and robust approach to univariate Gaussian splitting using parameterised Gaussian mixtures
topic Statistics Theory
url https://arxiv.org/abs/2606.01530