Choosing Regression Models for Biomass Prediction Equations

Abstract

This paper briefly describes the underlying assumptions and inherent drawbacks of logarithmic regression models commonly used to develop biomass prediction equations. Superiority of simple nonlinear models over both the logarithmic and multiple linear regression models is discussed and demonstrated on two data sets.