Mathematical Sciences: Problems in Stochastic Analysis
{'Code': '03040107', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Peter Arzberger'}
The principal investigator will continue the study of                      measure-valued population processes and multi-level branching                   diffusions.  The major motivation for the project is to create                  models to fit the hypothesis and then to use the acceptable                     models to predict the future behavior.  The classes of stochastic               processes to be studied have been shown as appropriate models for               analysis of allelic frequency data.  Measure-valued branching                   processes trace not only the numbers of particles but also their                distributions over the time.  Thus the measure-valued aspect of                 the processes make them particularly attractive models in                       epidemiological spread of communicable disease or economic wealth               of various populations.  Mathematically, the stochastic measure                 diffusion process is the continuous analogue of an infinite                     particle branching Markov system.  The project will address three               specific aspects of these processes: properties of the                          topological support of the associated random measure, including                 the coherence or dispersiveness, clustered nature or                            scatteredness, and singularity or absolute continuity of such                   random measures.
{'FirstName': 'S. Brent', 'LastName': 'Morris', 'EmailAddress': None, 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'National Security Agency', 'CityName': 'Fort George G Meade', 'ZipCode': '207556643', 'PhoneNumber': None, 'StreetAddress': '9800 Savage Road', 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD'}
{'Code': '1263', 'Text': 'PROBABILITY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8800289.xml'}