Global implicit function theorems and the online expectation–maximisation algorithm-Reference-Cited by-同舟云学术

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Global implicit function theorems and the online expectation–maximisation algorithm

Published:2022-01-24 Issue:2 Volume:64 Page:255-281
ISSN:1369-1473
Container-title:Australian & New Zealand Journal of Statistics
language:en
Short-container-title:Aus NZ J of Statistics

Author:

Nguyen Hien Duy¹²^ORCID,Forbes Florence³

Affiliation:

1. School of Mathematics and Physics University of Queensland St. Lucia 4067QLDAustralia

2. Department of Mathematics and Statistics La Trobe University Bundoora VIC3086Australia

3. Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK 38000Grenoble France

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/anzs.12356

Reference48 articles.

1. Family of mean-mixtures of multivariate normal distributions: Properties, inference and assessment of multivariate skewness

2. Remarks on the non-identifiability of mixtures of distributions

3. A new class of stochastic EM algorithms. Escaping local maxima and handling intractable sampling

4. Application of Methods of Ordinary Differential Equations to Global Inverse Function Theorems

5. The fully visible Boltzmann machine and the Senate of the 45th Australian Parliament in 2016

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1. Towards Frugal Unsupervised Detection of Subtle Abnormalities in Medical Imaging;Lecture Notes in Computer Science;2023

2. Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors;Statistics and Computing;2022-10

3. A Festschrift for Geoff McLachlan;Australian & New Zealand Journal of Statistics;2022-06

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