Multivariate approximation in total variation, II: Discrete normal approximation

AD Barbour; MJ Luczak; A Xia

Journal article

Multivariate approximation in total variation, II: Discrete normal approximation

AD Barbour, MJ Luczak, A Xia

Annals of Probability | INST MATHEMATICAL STATISTICS | Published : 2018

DOI: 10.1214/17-AOP1205

Abstract

The paper applies the theory developed in Part I to the discrete normal approximation in total variation of random vectors in Zd . We illustrate the use of the method for sums of independent integer valued random vectors, and for random vectors exhibiting an exchangeable pair. We conclude with an application to random colourings of regular graphs.

University of Melbourne Researchers

Andrew Barbour Author

Aihua Xia Author

Related Projects (4)

Random Discrete Structures: Approximations and Applications

The behaviour of many real world systems can be modelled by random discrete structures evolving over time. For example, the sizes of populat..

MEASURE-VALUED ANALYSIS OF STOCHASTIC POPULATIONS

The project aims to develop new mathematical models and tools for the rigorous analysis of very general stochastic populations that are subj..

Random Network Models with Applications in Biology

Complex biological systems consist of a large number of interacting agents or components, and so can be studied using mathematical random ne..

STOCHASTIC POPULATIONS: THEORY AND APPLICATIONS

The project aims to study models of evolution and cancer development. It will produce new mathematical results and open up new applications..

Grants

Awarded by Engineering and Physical Sciences Research Council

Funding Acknowledgements

[ "Work begun while ADB was Saw Swee Hock Professor of Statistics at the National University of Singapore, carried out in part at the University of Melbourne and at Monash University, and supported in part by Australian Research Council Grants Nos. DP120102728, DP120102398, DP150101459 and DP150103588.", "Work carried out in part at the University of Melbourne, and supported by an EPSRC Leadership Fellowship, grant reference EP/J004022/2, and in part by Australian Research Council Grants Nos. DP120102398 and DP150101459.", "Work supported in part by Australian Research Council Grants Nos. DP120102398 and DP150101459." ]