Mathematical Sciences: Advanced Methods in Semiparametric   and Nonlinear Model Building
{'Code': '03040300', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Sallie Keller-McNulty', 'PO_EMAI': None, 'PO_PHON': None}
This research project is to provide theoretical and advanced               computational methods for linear and nonlinear model building in                both a parametric and a semiparametric context, with both large                 and small data sets.  Partial and interaction splines and                       combining the problems of non-Gaussian data, nonlinear                          observation functionals and apriori inequality constraints will                 be used in large scale multivariate semi-parametric model                       building.  Part of the emphasis will be on sequential                           semiparametric model building techniques suitable for very large                data sets with several concomitant variables.  Certain model                    fitting problems in multivariate density estimation will also be                considered, as will methods for approximating and displaying                    likelihood contours for nonlinear statistical models and the                    application of these techniques to the investigation of                         multiparameter interactions in several types of non-linear model                formulations.                                                                        This research is in the general area of semi-parametric                    statistical methods.  Such methods incorporate fewer assumptions                than embodied in pure parametric methods but retain critical                    aspects of their structure.  Results with significance for both                 the statistical sciences community and the general science and                  engineering community are expected.
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{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 North Park Street', 'StreetAddress2': 'Suite 6301', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_DUNS_NUM': '161202122', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_DUNS_NUM': '041188822'}
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