Functional data analysis tools for the livestock science researcher

2011

Falzon, Gregory

Trotter, Mark

Lamb, David

Schneider, Derek

Editor(s): Thomas Banhazi and Chris Saunders

Conference Publication

en

Publication

Australian Society for Engineering in Agriculture

Barton, Australia

une:10341

Livestock tracking technology has the potential to collect large amounts of data on the position of each animal that is tagged. The assimilation and interpretation of such data in a rigorous manner can be both computationally demanding and mathematically challenging. A range of statistical methodologies could be applied to livestock tracking data and it is often difficult for the livestock scientist to determine the most appropriate method to use for a particular application. This paper focuses on the method of functional data analysis, which promises to be a very useful approach for describing vast amounts of spatio-temporal tracking data by using relatively few transform coefficients. The functional data analysis approach also captures the inherent spatiotemporal correlations in the tracking record thereby ensuring that potentially critical information is retained in the analysis. The background and basic concepts of functional data analysis will be introduced followed by the analysis of data that compares sheep with and without parasite burden.

link

Book of Abstracts of the Biennial Conference of the Australian Society for Engineering in Agriculture (SEAg), p. 92-92

9780858259904

92

92