Mathematical Sciences: Canonical Analysis of Multivariate   Time Series
{'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 project will develop methodology for multivariate time                 series analysis.  Multivariate model building is a very important               and current topic for research in the time series area.  The                    proposed methods will be based on the canonical representation of               the process and have the potential of revealing hidden                          simplifying structures of the process.  This will be useful in                  obtaining an appropriate linear model for the process under                     study.  The main tool used will be canonical analysis of vector                 processes, including lagged variables.  The investigator has                    already significant results in the area and has excellent                       experience in applying the procedures to real-world problems.                   Since the research is primarily concerned with canonical                        analysis, many results obtained will have applicability beyond                  time series analysis.
{'FirstName': 'Ruey', 'LastName': 'Tsay', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruey S Tsay', 'EmailAddress': 'ruey.tsay@gsb.uchicago.edu', 'NSF_ID': '000268514', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_ORG': 'PA18', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}
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{'Code': '1269', 'Text': 'STATISTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8702854.xml'}