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A unified approach to estimation of noncentrality parameters, the multiple correlation coefficient, and mixture models

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Abstract

We consider a class of mixture models for positive continuous data and the estimation of an underlying parameter θ of the mixing distribution. With a unified approach, we obtain classes of dominating estimators under squared error loss of an unbiased estimator, which include smooth estimators. Applications include estimating noncentrality parameters of chi-square and F-distributions, as well as ρ 2/(1 − ρ 2), where ρ is amultivariate correlation coefficient in a multivariate normal set-up. Finally, the findings are extended to situations, where there exists a lower bound constraint on θ.

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Correspondence to T. Kubokawa, É. Marchand or W. E. Strawderman.

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Kubokawa, T., Marchand, É. & Strawderman, W.E. A unified approach to estimation of noncentrality parameters, the multiple correlation coefficient, and mixture models. Math. Meth. Stat. 26, 134–148 (2017). https://doi.org/10.3103/S106653071702003X

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  • DOI: https://doi.org/10.3103/S106653071702003X

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