Alternative Nonlinear Growth Models for Biological Processes - Oyamakin, Oluwafemi
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The work modified the source differential forms of the Malthusian perspective and its variants and came up with five new growth models as alternative to the existing Exponential, Monomolecular, Gompertz, Richards and Von Bertalanffy growth models using Hyperbolic sine function. The developed models provided boundedness for the exponetial growth model and improved the growth processes in the other models through the allometry parameter that controls the shape of the growth curve. Data from different sources were used to validate the effectiveness of the developed model so as to determine its…mehr

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Produktbeschreibung
The work modified the source differential forms of the Malthusian perspective and its variants and came up with five new growth models as alternative to the existing Exponential, Monomolecular, Gompertz, Richards and Von Bertalanffy growth models using Hyperbolic sine function. The developed models provided boundedness for the exponetial growth model and improved the growth processes in the other models through the allometry parameter that controls the shape of the growth curve. Data from different sources were used to validate the effectiveness of the developed model so as to determine its suitability and validity. Furthermore, the developed models along with the existing ones were subjected to violation of assumptions so as to test how robust they are to outliers or shocks. At various degree of contamination of outliers ranging from 50%, 100% and 500% of the highest and lowest values were considered and the developed models demonstrated a better ability to accommodate shocks over the existing ones. Hence, I recommend usage of our developed models when study that requires the use of growth models is being carried out
Autorenporträt
Dr. Oyamakin Oluwafemi is currently a lecturer in the (Biometry Unit) Department of Statistics, University of Ibadan with passion for teaching and conducting research in Forestry and Public Health. He is also a GradStat, CStat and CSci of the Royal Statistical Society, United Kingdom.