Mathematical Sciences: Probability and Statistics
{'Code': '03040107', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Peter Arzberger', 'PO_EMAI': None, 'PO_PHON': None}
The research will deal with the general areas of                           reconstruction, estimation and reliability.  Reconstruction of an               integrable function via a few of its projections leads to a class               of solutions.  From the point of view of the applications, it is                important to know the size of this solution set.  The principal                 investigator will study the extreme points of this set.  For the                estimation problems, a notion of compact admissibility is                       introduced.  A decision is compactly admissible if it becomes                   admissible when the sample space is replaced by a compact subset.               Dr. Kemperman will study the compact admissibility and other                    properties of estimators in exponential families.  Reliability                  properties of a distribution function will be explored through                  the convex hull of all moment points.
{'FirstName': 'Johannes', 'LastName': 'Kemperman', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Johannes H Kemperman', 'EmailAddress': None, 'NSF_ID': '000288053', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1263', 'Text': 'PROBABILITY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8802557.xml'}