Archive for handbook of mixture analysis

handbook of mixture analysis [review]

Posted in Books, R, Statistics with tags , , , , , , , , , on March 19, 2021 by xi'an

“In my opinion, the editors have done an excellent job when selecting the contents of the handbook and putting the different chapters together. For instance, this can be appreciated by the fact that, despite the large number of authors and contributions, all chapters have kept the same notation. Furthermore, in addition to a sound description of the underlying theory and methods, several chapters include information about how to fit the presented models using the R programming language. However, I missed pointers to repositories to download the code and datasets for some of the examples used in the book. To sum up, this is an excellent reference book on mixture models.” Virgilio Gómez-Rubio, JRSS A, 2021

an elegant book [review]

Posted in Books, Statistics, University life with tags , , , , , , , on December 28, 2020 by xi'an

“Handbook of Mixture Analysis is an elegant book on the mixture models. It covers not only statistical foundations but also extensions and applications of mixture models. The book consists of 19 chapters (each chapter is an independent paper), and collectively, these chapters weave into an elegant web of mixture models” Yen-Chi Chen (U. Washington)

estimation exam [best of]

Posted in Books, Kids, Statistics with tags , , , , , , , , on January 29, 2019 by xi'an

Yesterday, I received a few copies of our CRC Press Handbook of Mixture Analysis, while grading my mathematical statistics exam 160 copies. Among the few goodies, I noticed the always popular magical equality


that must have been used in so many homeworks and exam handouts by now that it should become a folk theorem. More innovative is the argument that E[1/min{X¹,X²,…}] does not exist for iid U(0,θ) because it is the minimum and thus is the only one among the order statistics with the ability to touch zero. Another universal shortcut was the completeness conclusion that when the integral

\int_0^\theta \varphi(x) x^k \text{d}x

was zero for all θ’s then φ had to be equal to zero with no further argument (only one student thought to take the derivative). Plus a growing inability in the cohort to differentiate even simple functions… (At least, most students got the bootstrap right, as exemplified by their R code.) And three stars to the student who thought of completely gluing his anonymisation tag, on every one of his five sheets!, making identification indeed impossible, except by elimination of the 159 other names.

a book and three chapters on ABC

Posted in Statistics with tags , , , , , , , , , , on January 9, 2019 by xi'an

In connection with our handbook on mixtures being published, here are three chapters I contributed to from the Handbook of ABC, edited by Scott Sisson, Yanan Fan, and Mark Beaumont:

6. Likelihood-free Model Choice, by J.-M. Marin, P. Pudlo, A. Estoup and C.P. Robert

12. Approximating the Likelihood in ABC, by  C. C. Drovandi, C. Grazian, K. Mengersen and C.P. Robert

17. Application of ABC to Infer about the Genetic History of Pygmy Hunter-Gatherers Populations from Western Central Africa, by A. Estoup, P. Verdu, J.-M. Marin, C. Robert, A. Dehne-Garcia, J.-M. Cornuet and P. Pudlo

a book and two chapters on mixtures

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , on January 8, 2019 by xi'an

The Handbook of Mixture Analysis is now out! After a few years of planning, contacts, meetings, discussions about notations, interactions with authors, further interactions with late authors, repeating editing towards homogenisation, and a final professional edit last summer, this collection of nineteen chapters involved thirty-five contributors. I am grateful to all participants to this piece of work, especially to Sylvia Früwirth-Schnatter for being a driving force in the project and for achieving a much higher degree of homogeneity in the book than I expected. I would also like to thank Rob Calver and Lara Spieker of CRC Press for their boundless patience through the many missed deadlines and their overall support.

Two chapters which I co-authored are now available as arXived documents:

5. Gilles Celeux, Kaniav Kamary, Gertraud Malsiner-Walli, Jean-Michel Marin, and Christian P. Robert, Computational Solutions for Bayesian Inference in Mixture Models
7. Gilles Celeux, Sylvia Früwirth-Schnatter, and Christian P. Robert, Model Selection for Mixture Models – Perspectives and Strategies

along other chapters

1. Peter Green, Introduction to Finite Mixtures
8. Bettina Grün, Model-based Clustering
12. Isobel Claire Gormley and Sylvia Früwirth-Schnatter, Mixtures of Experts Models
13. Sylvia Kaufmann, Hidden Markov Models in Time Series, with Applications in Economics
14. Elisabeth Gassiat, Mixtures of Nonparametric Components and Hidden Markov Models
19. Michael A. Kuhn and Eric D. Feigelson, Applications in Astronomy