Mathematical Sciences: Abstract Gambling Theory Bayesian    Statistics and Probability
{'Code': '03040107', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Alan Izenman', 'PO_EMAI': None, 'PO_PHON': None}
Research is proposed in three related areas.  The principal                investigator has a long record of distinguished research in the                 area of abstract gambling theory.  In this project he will                      investigate certain fundamental problems of both discrete and                   continuous gambling theory such as countably additive theory and                measurability.  Specific gambling problem to be considered is of                minimizing the expected time to goal in a Bayesian framework.                   The second project will explore the relationship of coherent                    inference to the theory of admissible inference in Bayesian                     statistics and will develop a family of tractable priors with                   required properties.  The last project deals with optimal                       stopping and its relation with abstract gambling theory.
{'FirstName': 'William', 'LastName': 'Sudderth', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William D Sudderth', 'EmailAddress': 'bill@stat.umn.edu', 'NSF_ID': '000376121', 'StartDate': '06/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1269', 'Text': 'STATISTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8801085.xml'}