Performance of the Weibull individual growth model for weight at age data

Introduction: Knowledge of different functions associated with a probability distribution, as well as their properties, can be translated into functions that provide information about different characteristics of the growth process under study. Objectives: To analyze the relationship between individual growth models and the cumulative distribution functions of continuous random variables. Methods: We compare the flexibility and goodness of fit of the Weibull-type model against the von Bertalanffy weight growth model. We fit these two growth models into two very different sets of age-weight data taken from the literature; the first comprises 22 pairs of Pacific halibut mean weight at age, and the second 900 pairs of striped bass weight-age-data. Results: The Weibull-type growth model had greater flexibility and neglected less information available in the data sets than the von Bertalanffy model. Conclusions: The Weibull model, derived from cumulative probability distribution, is a good choice to fit weight-at-age data as it is more flexible than the commonly used von Bertalanffy model.