Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach

Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach

abstract: This paper investigates a relatively new analysis method for longitudinal data in the framework of functional data analysis. This approach treats longitudinal data as so-called sparse functional data. The first section of the paper introduces functional data and the general ideas of functi...

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Bibliographic Details
Other Authors: Ward, Kimberly (Author)
Format: Dissertation
Language:English
Published: 2016
Subjects:
Psychology
Functional Data Analysis
Longitudinal Data
Mixed Models
Online Access:http://hdl.handle.net/2286/R.I.40749

Internet

http://hdl.handle.net/2286/R.I.40749

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