Estimating Growth in Height from Limited Longitudinal Growth Data Using Full-Curves Training Dataset: A Comparison of Two Procedures of Curve Optimization—Functional Principal Component Analysis and SITAR

Estimating Growth in Height from Limited Longitudinal Growth Data Using Full-Curves Training Dataset: A Comparison of Two Procedures of Curve Optimization—Functional Principal Component Analysis and SITAR

A variety of models are available for the estimation of parameters of the human growth curve. Several have been widely and successfully used with longitudinal data that are reasonably complete. On the other hand, the modeling of data for a limited number of observation points is problematic and requ...

Full description

Bibliographic Details
Main Authors: Miroslav Králík, Ondřej Klíma, Martin Čuta, Robert M. Malina, Sławomir Kozieł, Lenka Polcerová, Anna Škultétyová, Michal Španěl, Lubomír Kukla, Pavel Zemčík
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Children
Subjects:
human growth
growth modelling
functional data analysis
Sitar
Online Access:https://www.mdpi.com/2227-9067/8/10/934

Similar Items

Similar Items