Functional data analysis with application to MS and cervical vertebrae data

• Author / Creator

  Yaraee, Kate

• Functional data analysis (FDA) is a fast-growing area in statistics with the aim of
  estimating a set of related functions or curves rather than focusing on a single entity,
  like estimating a point, as in classical statistics. FDA has a wide range of applications
  in different fields such as biological sciences, geology, psychology, economics, image
  data, etc. In fact, discrete data points collected over a continuum can be thought
  of as a function that is assumed to be a reasonably smooth mechanism giving rise
  to those discrete observed points. This continuum is not necessarily a physical time
  point, but rather attributes such as age, spatial location, seasons, or temperature.

• Subjects / Keywords

  • Cervical Vertebrae
  • Functional data analysis
  • Multiple Sclerosis

• Graduation date

  Fall 2011

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3H944

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.