Mathematical Sciences: Comparing Two or More Populations    With Nonparametric or Semiparametric Approach
{'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 research will extend existing parametric and                          nonparametric regression methods.  Regression analysis is widely                used on data to determine relationship of two or more variables                 of interest.  New methods need to be invented to take in to                     account various characters of the data.                                              The research will study biased estimators of parameters in a               partial spline model.  This model can be used to compare two or                 more populations.  The investigator will also look at test                      statistic to compare "mean curves" with or without the help of                  the covariates.
{'FirstName': 'Jyh-Jen', 'LastName': 'Shiau', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jyh-Jen Shiau', 'EmailAddress': None, 'NSF_ID': '000228330', 'StartDate': '06/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Missouri-Columbia', 'CityName': 'COLUMBIA', 'ZipCode': '652113020', 'PhoneNumber': '5738827560', 'StreetAddress': '121 UNIVERSITY HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MO04', 'ORG_UEI_NUM': 'SZPJL5ZRCLF4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1263', 'Text': 'PROBABILITY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8709977.xml'}