Statistical Methods for Valley Elevation Cross-Profiles
Document Type
Presentation Abstract
Presentation Date
4-7-2005
Abstract
Functional data analysis methods including functional cluster analysis and functional linear modeling are discussed. The methods are used to describe and compare the shape of elevation cross-profiles taken from three Himalayan valleys. Typical methods for the analysis of these profiles are discussed in a nonlinear regression framework along with the use of model selection criteria. Curve registration is used to align important features in the profiles. Functional cluster analysis is used to group profiles by shape, with the shape based on the estimated curvature of each profile. Functional linear models are then used to explain the variability in the observed shapes of the profiles.
No particular mathematical or negotiation skills are required. This talk is open to everyone.
Recommended Citation
Greenwood, Mark, "Statistical Methods for Valley Elevation Cross-Profiles" (2005). Colloquia of the Department of Mathematical Sciences. 193.
https://scholarworks.umt.edu/mathcolloquia/193
Additional Details
Thursday, 7 April 2005
4:10 p.m. in Math 109