Mathematical Sciences: Stochastic Compartmental Systems
{'Code': '03040107', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'William Y. Velez', 'PO_EMAI': None, 'PO_PHON': None}
This project will continue the analysis of the compartmental               models.  The fundamental assumption in compartmental models is                  that the system is divided in to distinct coponents with outside                input as well as feedback from the system itself.  Most of the                  work so far has assumed deterministic processes governing the                   particles.  Such models are used in pharmacokinetics, biological                systems and in manpower planning systems.                                            The research will study linear semi markov compartmental                   systems.  Using marginal maximum likelihood, estimators of the                  parameters of the system will be found.  The methods will be                    extended to copmartmental volumes.
{'FirstName': 'Peter', 'LastName': 'Purdue', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Peter Purdue', 'EmailAddress': None, 'NSF_ID': '000289333', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Naval Postgraduate School', 'CityName': 'MONTEREY', 'ZipCode': '939435098', 'PhoneNumber': '8316562271', 'StreetAddress': '1 UNIVERSITY CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'CA19', 'ORG_UEI_NUM': 'CEPCN5K7EKU8', 'ORG_LGL_BUS_NAME': 'NAVAL POSTGRADUATE SCHOOL', 'ORG_PRNT_UEI_NUM': 'NW2RJN8TQQW1'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1263', 'Text': 'PROBABILITY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8706496.xml'}