Mathematical Sciences: Multilinear Analysis of SpectroscopicData
{'Code': '03040107', 'Directorate': {'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Alan Izenman'}
This collaborative project between a statistician and a                    biophysical chemist will refine and extend analyses of                          spectroscopic data.  Spectroscopy is the measurement of the                     absorption or emission of particles from a specimen.  The                       fluorescence spectra of proteins are highly sensitive to many                   different elements, and are frequently severely overlapping.  The               novel feature of the spectroscopic data is its high signal-to-                  noise ratio.  The new statistical techniques will make use of the               special features of the data and address the analysis to specific               questions of interest.  In standard factor analysis, the                        expectation of the response variable is assumed to be a linear                  function of unknown parameters.  The nature of the spectroscopic                data make it necessary to use non-linear functions of the                       parameters.
[{'FirstName': 'Robert', 'LastName': 'Ross', 'EmailAddress': None, 'StartDate': '07/15/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sue', 'LastName': 'Leurgans', 'EmailAddress': None, 'StartDate': '07/15/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
{'Name': 'Ohio State University Research Foundation -DO NOT USE', 'CityName': 'Columbus', 'ZipCode': '432101016', 'PhoneNumber': '6146888734', 'StreetAddress': '1960 KENNY RD', 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH'}
{'Code': '1269', 'Text': 'STATISTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8805402.xml'}