Authors:
- Uses a flexible class of probability distributions for modeling data with skewness behavior, discrepant observations and population heterogeneity instead nonparametric methods
- Explores methods that are implemented in the R package mixsmsn
- Enhances the spread of ideas that are currently trickling through the literature of mixture models
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
Part of the book sub series: SpringerBriefs in Statistics - ABE (BRIEFSABE)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
About this book
This work is a useful reference guide for researchers analyzing heterogeneous data, as well as a textbook for a graduate-level course in mixture models. The tools presented in the book make complex techniques accessible to applied researchers without the advanced mathematical background and will have broad applications in fields like medicine, biology, engineering, economic, geology and chemistry.
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Authors and Affiliations
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Department of Statistics, University of Connecticut, Storrs Mansfield, USA
Víctor Hugo Lachos Dávila
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Department of Statistics, Federal University of Amazonas, Manaus, Brazil
Celso Rômulo Barbosa Cabral
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Department of Statistics, Federal University of Juiz de Fora, Juiz de Fora, Brazil
Camila Borelli Zeller
About the authors
Celso Rômulo Barbosa Cabral is a Professor at the Federal University of Amazonas, Brazil, where he graduated in Statistics (1987). He received his Master’s degree from the National Association of Pure and Applied Mathematics, IMPA, Brazil (1991) and his PhD (2000) in Statistics from the University of São Paulo, Brazil. His research focuses mainly on asymmetric distributions, measurement error models and finite mixtures of distributions.
Camila Borelli Zeller is a Professor at the Federal University of Juiz de Fora, Brazil. She holds a Master’s degree (2006) and a PhD (2009) in Statistics, from the University of Campinas, Brazil. The main focus of her research is asymmetric distributions, linear models and finite mixtures of distributions.
Bibliographic Information
Book Title: Finite Mixture of Skewed Distributions
Authors: Víctor Hugo Lachos Dávila, Celso Rômulo Barbosa Cabral, Camila Borelli Zeller
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-319-98029-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-319-98028-7Published: 20 November 2018
eBook ISBN: 978-3-319-98029-4Published: 12 November 2018
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: X, 101
Number of Illustrations: 17 b/w illustrations, 5 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Life Sciences, Medicine, Health Sciences, Statistics and Computing/Statistics Programs