Mathematical Sciences: Predictive Likelihood
{'Code': '03040300', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
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This project is concerned with studying methods of                         prediction based on the likelihood function alone.  Determining                 the extent to which these predictive likelihoods may be sensibly                used and the extent to which they may be inerpreted as pivotals                 is an important theoretical objective of this project.  The close               connection between these likelihoods and the parametric                         likelihoods allows for a study of the interrelationship between                 predictivism and estimation from a likelihood perspective.                           Prediction or forecasting is useful and important in all                   areas of science and is often the underlying reason for                         formulating and fitting statistical models in the first place.                  This research addresses the question of how a predictive                        likelihood should be extracted from an assumed statistical model.
{'FirstName': 'Ronald', 'LastName': 'Butler', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ronald W Butler', 'EmailAddress': 'rbutler@smu.edu', 'NSF_ID': '000272336', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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