Mathematical Sciences: Probability in Banach Spaces
{'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}
This research will explore sample path properties of certain               stochastic processes.  Stochastic processes serve as models in                  many areas of interest such as weather, economic indices,                       epidemics etc.  The suitability of the models for specific                      questions of interest depends on the sample path properties of                  the models themselves.  The study of these properties uses highly               mathematical tools.                                                                  This research will study three interdependent problems.  The               first will compare sample path properties of stochastic processes               represented as certain Fourier transforms with those of random                  Fourier series with independent infinitely divisible                            coefficients.  The second problem is continuation of the study                  with M. Talagrand of sharp estimates for certain random stable                  tensor products.  The third will continue to study, in                          association with M. Weber, the tail probability distribution of                 Gaussian vectors.
{'FirstName': 'Michael', 'LastName': 'Marcus', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael B Marcus', 'EmailAddress': 'mbmarcus@optonline.net', 'NSF_ID': '000139856', 'StartDate': '05/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'CUNY City College', 'CityName': 'NEW YORK', 'ZipCode': '100319101', 'PhoneNumber': '2126505418', 'StreetAddress': '160 CONVENT AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'L952KGDMSLV5', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '126300', 'Text': 'PROBABILITY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8706285.xml'}