Although data are most often recorded as observations at a single point, on many occasions the data are actually curves, for example a motion or a growth pattern or a development process occurring over time. The goal of this research is to develop statistical procedures which draw inferences from curves or estimated curves directly. In particular, this research is concerned with multivariate methods addressing problems in principal components analysis, canonical correlation, discriminant analysis and prediction.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Application #
9108295
Program Officer
Sallie Keller-McNulty
Project Start
Project End
Budget Start
1991-09-01
Budget End
1994-08-31
Support Year
Fiscal Year
1991
Total Cost
$30,000
Indirect Cost
Name
University of California Davis
Department
Type
DUNS #
City
Davis
State
CA
Country
United States
Zip Code
95618