A Conversation with Chris Heyde

@article{Glasserman2006ACW,
  title={A Conversation with Chris Heyde},
  author={Paul Glasserman and Steven Kou},
  journal={Statistical Science},
  year={2006},
  volume={21},
  pages={286-298}
}
Born in Sydney, Australia, on April 20, 1939, Chris Heyde shifted his interest from sport to mathematics thanks to inspiration from a schoolteacher. After earning an M.Sc. degree from the University of Sydney and a Ph.D. from the Australian National University (ANU), he began his academic career in the United States at Michigan State University, and then in the United Kingdom at the University of Sheffield and the University of Manchester. In 1968, Chris moved back to Australia to teach at ANU… 
6 Citations

Figures from this paper

Christopher Charles Heyde 1939 - 2008

An account of the Heyde family is followed by a description of Chris's childhood, schooling and university training at Sydney and the ANU. Chris spent most of his academic career at the ANU, CSIRO

Some American Exceptional Contributions in Finance

This chapter provides discussion on the financial theories of American contributors that are exceptional. We visit some names that are popular in economics as well. In those cases where the authors

Notes on stochastic processes Paul Keeler

A stochastic process is a type of mathematical object studied in mathematics, particularly in probability theory, which can be used to represent some type of random evolution or change of a system.

Notes on stochastic processes

A stochastic process is a type of mathematical object studied in mathematics, particularly in probability theory, which shows some type of a randomness. There are many types of stochastic processes

Recent publications

Readers' attention is particularly drawn to the special issue of Paedagogica Historica, 42 (2006), on the history of mathematics teaching: the Proceedings of Thematic Study Group 29 at ICME 10 in

A Cautionary Note on Model Choice and the Kullback-Leibler Information

The Kullback-Leibler information has found application in many areas of statistical science. It typically arises in model choice and model dimension questions in a way which suggests its use as a

References

SHOWING 1-10 OF 10 REFERENCES

The Lucky Country

With an introduction by Hugh Mackay 'Australia is a lucky country, run mainly by second-rate people who share its luck.' The phrase 'the lucky country' has become part of our lexicon; it's forever

On Limit Theorems for Quadratic Functions of Discrete Time Series

In this paper it is shown how martingale theorems can be used to appreciably widen the scope of classical inferential results concerning autocorrelations in time series analysis. The object of study

On a Property of the Lognormal Distribution

In this paper it is established that the lognormal distribution is not determined by its moments. Some brief comments are made on the set of distributions having the same moments as a lognormal

Multiple Time Series

In medical investigations, it is not uncommon to record observations on two or more time series. For example, blood pressure and weight may be regularly monitored on a sample of patients. The

The lucky country : Australia in the sixties

Martingales: A case for a place in the statistician's repertoire (invited paper)

  • Austral. J. Statist
  • 1972

Martingales: A case for a place in the statistician's repertoire (invited paper)

  • Austral. J. Statist
  • 1972