Abstract
We introduce a novel approach to estimate the parameters of a mixture of two distributions. The method combines a grid approach with the method of moments and can be applied to a wide range of two-component mixture models. The grid approach enables the use of parallel computing and the method can easily be combined with resampling techniques. We derive the method for the special cases when the data are described by the mixture of two Weibull distributions or the mixture of two normal distributions, and apply the method on gene expression data from 409 \(ER+\) breast cancer patients.
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Acknowledgments
This work was supported by grants from the Swedish Research Council, Dnr 340-2013-5185 (P. R.), the Kempe Foundations, Dnr JCK-1315 (D. K., P. R.), and the Faculty of Science and Technology, Umeå University (Yu. B., D. K., P. R.).
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Belyaev, Y., Källberg, D., Rydén, P. (2017). The HRD-Algorithm: A General Method for Parametric Estimation of Two-Component Mixture Models. In: Rykov, V., Singpurwalla, N., Zubkov, A. (eds) Analytical and Computational Methods in Probability Theory. ACMPT 2017. Lecture Notes in Computer Science(), vol 10684. Springer, Cham. https://doi.org/10.1007/978-3-319-71504-9_41
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DOI: https://doi.org/10.1007/978-3-319-71504-9_41
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