prospectus
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
238<br />
www.kent.ac.uk/smsas<br />
analysis by classical, likelihood<br />
and Bayesian methodologies.<br />
Often new computational methods<br />
are the key to analysing complex<br />
big data problems.<br />
Nonparametric statistics<br />
In order to describe the data, it<br />
is common in statistics to assume<br />
a specific probability model.<br />
Unfortunately, in many practical<br />
applications (for instance in<br />
economics, population genetics<br />
and social networks) it is not<br />
possible to identify a specific<br />
structure for the data.<br />
Nonparametric methods provide<br />
statistical tools for addressing<br />
inference in these situations.<br />
Economics and finance<br />
At Kent there is particular interest<br />
in the use of nonparametric<br />
methods including quantile<br />
regression and Bayesian<br />
nonparametric approaches.<br />
Application areas include<br />
modelling of business cycle and<br />
capacity utilisation, calculating<br />
sovereign credit ratings, modelling<br />
of stock return data, and<br />
predicting inflation.<br />
Academic staff<br />
For details of individual<br />
staff research interests, see<br />
www.kent.ac.uk/smsas/our-people<br />
Dr Diana Cole: Senior Lecturer<br />
in Statistics<br />
Professor David Fletcher:<br />
Professor of Statistics<br />
Professor Jim Griffin: Professor<br />
of Statistics<br />
Dr Alfred Kume: Senior Lecturer<br />
in Statistics<br />
Dr Fabrizio Leisen: Senior<br />
Lecturer in Statistics<br />
Dr Eleni Matechou: Lecturer<br />
in Statistics<br />
Dr Rachel McCrea: Lecturer<br />
in Statistics<br />
Professor Martin Ridout:<br />
Professor of Applied Statistics<br />
Dr Christiano Villa: Lecturer<br />
in Statistics<br />
Dr Xue Wang: Lecturer<br />
in Statistics<br />
Professor Jian Zhang: Professor<br />
of Statistics<br />
Location<br />
Canterbury<br />
Entry requirements<br />
Usually, a minimum 2.1<br />
(or equivalent) in a relevant<br />
subject. For specific details,<br />
see www.kent.ac.uk/pg<br />
English language<br />
requirements<br />
See p244<br />
Fees<br />
See www.kent.ac.uk/pg<br />
Funding<br />
www.kent.ac.uk/pgfunding<br />
National ratings<br />
REF 2014, mathematical<br />
sciences:<br />
• 100% of our research<br />
judged to be of<br />
international quality<br />
• 25th for research power<br />
Applications<br />
Taught programmes<br />
Online at www.kent.ac.uk/<br />
courses/postgrad/apply<br />
Research programmes<br />
See p260 or contact the<br />
School for further details.<br />
Further information<br />
T: +44 (0)1227 824133<br />
E: smsaspgadmin@<br />
kent.ac.uk
Change language