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The HRD-Algorithm: a general method for parametric estimation of two-component mixture models
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. (Patrik Rydén)
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
2017 (engelsk)Inngår i: Lecture Notes in Computer Science, ISSN 978-3-319-71504-9, Vol. 10684, s. 497-508Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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+" role="presentation" style="box-sizing: border-box; display: inline-table; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">ER+ER+ breast cancer patients.

sted, utgiver, år, opplag, sider
Springer, 2017. Vol. 10684, s. 497-508
Emneord [en]
Mixture models, Parameter estimation, Method of moments Grid-approach, Resampling, Cluster analysis Variable selection, High-dimensional data
HSV kategori
Forskningsprogram
matematisk statistik
Identifikatorer
URN: urn:nbn:se:umu:diva-144646DOI: 10.1007/978-3-319-71504-9_41OAI: oai:DiVA.org:umu-144646DiVA, id: diva2:1181482
Konferanse
Analytical and Computational Methods in Probability Theory. ACMPT 2017.
Forskningsfinansiär
Swedish Research Council, 340-2013-5185Tilgjengelig fra: 2018-02-08 Laget: 2018-02-08 Sist oppdatert: 2018-10-15bibliografisk kontrollert

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