Mathematical Sciences: Strong Approximations of the         Distributions of Estimators in Linear Stochastic Models
{'Code': '03040107', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Alan Izenman', 'PO_EMAI': None, 'PO_PHON': None}
The research for this project is directed at establishing                  suitable approximations to the distributions of estimators of                   parameters in linear stochastic models.  By approximations,                     Berry.Essen bounds and asymptotic expansions are also included.                 The method that will be used will be different from the usual                   method of characteristic functions and will also give                           approximations uniformly over all Borel subsets, which is also                  one of the aims of the project.                                                      Some specific statistical models that will be considered in                detail include nonlinear regression, autoregression, regression                 with lagged dependent variables.  Robust versions of the                        estimators in these models will be considered in addition to the                least squares estimators.
{'FirstName': 'Paramaraj', 'LastName': 'Jeganathan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paramaraj Jeganathan', 'EmailAddress': 'jegan@stat.lsa.umich.edu', 'NSF_ID': '000438385', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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{'Code': '1269', 'Text': 'STATISTICS'}
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