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Details of Grant 

EPSRC Reference: GR/T17908/01
Title: Bayesian Analysis Of Skewed Longitudinal Data
Principal Investigator: Steel, Professor M
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Statistics
Organisation: University of Warwick
Scheme: Standard Research (Pre-FEC)
Starts: 10 January 2005 Ends: 09 January 2008 Value (£): 150,611
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Financial Services
Related Grants:
Panel History:  
Summary on Grant Application Form
in many fields of application of statistics the usual distributional assumptions (such as Normality) are often in conflict with the data. We have worked in the development of more flexible classes of distributions, which is now a rapid growth area for modelling cross-section at data. We now intend toinvestigate the use of flexible distributions for modelling longitudinal data, where we will allow for distribution al shapes to change over time. The statistical paradigm used in this research will be Bayesian, which will allow us to formally deal with model uncertainty. The latter is a very relevant concept given the large collection of possible distributional shapes but we also consider uncertainty regarding the modelling of the dynamics and the choice of covarlates in regression modelling. We will also tackle the issue of missing observations. Fast inference methods based on Markov chain Monte Carlo algorithms will be developed and made available to applied researchers in the field. In addition, we plan to conduct substantive applications to two areas of topical interest in economics: the distribution of firm sizes and the growth of countries or regions.
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Project URL: http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/steel/steel_homepage/epsrc
Further Information:  
Organisation Website: http://www.warwick.ac.uk