BI-LOGISTIC GROWTH

The S-shaped logistic growth model has been extensively studied and applied to a wide range of biological and socio-technical systems. A model, the Bi-logistic, is presented for the analysis of systems that experience two phases of logistic growth, either overlapping or sequentially. A nonlinear least-squares algorithm is described that provides Bi-logistic parameter estimates from time-series growth data. Model sensitivity and robustness are discussed in relation to error structure in the data. A taxonomy and some examples of systems that exhibit Bi-logistic growth are presented. The Bi-logistic model is shown to be superior to the simple logistic model for representing many growth processes.