Mathematical Sciences: Transformation Techniques in         Regression
{'Code': '03040107', 'Directorate': {'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Alan Izenman'}
This research focuses on transformations in regression                     analysis when there is a theoretical model for the median                       response, but the error distribution must be modeled empirically.               The purposes of the transformation are to stabilize the variance                and to induce symmetrically distributed errors.  Estimating such                timation of parameters in the theoretical model.  It can also                   help model the random nature of the physical system from which                  the data arose.     This reseach in statistical science is in the               general area of regression analysis.  Mathematical theory in this               area deals with measuring the degree of association between                     variables and assessing the nature of such associations.  This                  work extends the flexibility of the mathematical models available               for making such assessments and thus will permit a richer variety               of relationships to be discovered and characterized.
{'FirstName': 'David', 'LastName': 'Ruppert', 'EmailAddress': 'dr24@cornell.edu', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Cornell University', 'CityName': 'Ithaca', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '373 Pine Tree Road', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY'}
{'Code': '1269', 'Text': 'STATISTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8800294.xml'}