ABSTRACT
Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model growth rate. One of the reasons for the lack of accuracy is that most matrix-based models implicitly assume a specific degree of variability in development times for the organism. Because the variability is implicit, the implied variances are often not verified with experimental data. In this paper, we shall present extensions to the stage-classified matrix models so that organisms with arbitrary means and standard deviations of development times can be modeled.
