Saddlepoint approximation for data in simplices: a review with new applications

Gatto, Riccardo (2019). Saddlepoint approximation for data in simplices: a review with new applications. Stats, 2(1), pp. 121-147. MPDI 10.3390/stats2010010

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This article provides a review of the saddlepoint approximation for a M-statistic of a sample of nonnegative random variables with fixed sum. The sample vector follows the multinomial, the multivariate hypergeometric, the multivariate Polya or the Dirichlet distributions. The main objective is to provide a complete presentation in terms of a single and unambiguous notation of the common mathematical framework of these four situations: the simplex sample space and the underlying general urn model. Some important applications are reviewed and special attention is given to recent applications to models of circular data. Some novel applications are developed and studied numerically

Item Type:

Journal Article (Review Article)

Division/Institute:

08 Faculty of Science > Department of Mathematics and Statistics > Institute of Mathematical Statistics and Actuarial Science

UniBE Contributor:

Gatto, Riccardo

Subjects:

300 Social sciences, sociology & anthropology > 360 Social problems & social services
500 Science > 510 Mathematics

ISSN:

2571-905X

Publisher:

MPDI

Language:

English

Submitter:

Riccardo Gatto

Date Deposited:

02 Apr 2020 08:10

Last Modified:

02 Apr 2020 08:10

Publisher DOI:

10.3390/stats2010010

BORIS DOI:

10.7892/boris.142970

URI:

https://boris.unibe.ch/id/eprint/142970

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