Peter Green (statistician)

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Peter James Green
Born (1950-04-28) 28 April 1950 (age 71)
Solihull, England
Alma materUniversity of Oxford
University of Sheffield
Known forReversible-jump Markov chain Monte Carlo
AwardsGuy Medal (Bronze, 1987) (Silver, 1999)
Scientific career
InstitutionsUniversity of Bath
University of Bristol
University of Durham
University of Wisconsin–Madison
University of Technology, Sydney
Doctoral advisorDouglas P. Kennedy
Websitewww.bristol.ac.uk/maths/people/peter-j-green

Peter Green, FRS (born 28 April 1950)[1] is a British Bayesian statistician. He is Emeritus Professor and Professorial Research Fellow at the University of Bristol, and a Professor at the University of Technology, Sydney. He is distinguished for his contributions to computational statistics, in particular his contributions to spatial statistics and semi-parametric regression models and also his development of reversible-jump Markov chain Monte Carlo.

Green was born in Solihull and attended Solihull School.[1] He studied mathematics at Oxford University before moving to the University of Sheffield for postgraduate study, where he was awarded an MSc in probability and statistics and a PhD in applied probability.[2]

He was elected a Fellow of the Royal Society in 2003. He served as President of the Royal Statistical Society from 2001 to 2003,[3] having previously been awarded its Guy Medal in both Bronze (1987) and Silver (1999).[4] He held a Royal Society Wolfson Research Merit Award from 2006 to 2011. He was President of the International Society for Bayesian Analysis for the year 2007.

He is editor of the journal Statistical Science for 2014-2016.[citation needed]

References[]

  1. ^ Jump up to: a b Prof Peter Green at Debrett's People of Today. Accessed 2011-01-23.
  2. ^ "Prof Peter Green". University of Bristol. Retrieved 13 June 2014.
  3. ^ Past Presidents Archived 2007-10-06 at the Wayback Machine. Royal Statistical Society. Accessed 2009-04-26.
  4. ^ Honours & Awards: Previous Recipients Archived 2007-09-28 at the Wayback Machine. Royal Statistical Society. Accessed 2009-04-26.
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