Allometric Extension for Multivariate Regression

  • Tarpey T
  • Ivey C
N/ACitations
Citations of this article
25Readers
Mendeley users who have this article in their library.

Abstract

In multivariate regression, interest lies on how the response vector depends on a set of covariates. A multivariate regression model is proposed where the covariates explain variation in the response only in the direction of the first principal component axis. This model is not only parsimonious, but it provides an easy interpretation in allometric growth studies where the first principal component of the log-transformed data corresponds to constants of allometric growth. The proposed model naturally generalizes the two-group allometric extension model to the situation where groups differ according to a set of covariates. A bootstrap test for the model is proposed and a study on plant growth in the Florida Everglades is used to illustrate the model.

Cite

CITATION STYLE

APA

Tarpey, T., & Ivey, C. T. (2021). Allometric Extension for Multivariate Regression. Journal of Data Science, 4(4), 479–495. https://doi.org/10.6339/jds.2006.04(4).287

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free