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[The description of growth course using a generalized logistic growth function].
Gegenbaurs Morphologisches Jahrbuch
|January 1, 1979
Summary
This study introduces a generalized logistic function for quantifying growth patterns. An ALGOL program system effectively adjusts this function to real-world data, improving approximation accuracy.
Area of Science:
- Mathematical modeling
- Quantitative biology
- Statistical analysis
Context:
- Growth processes require accurate quantitative descriptions.
- Existing logistic functions may have limitations in capturing complex growth dynamics.
- Accurate modeling is crucial for understanding biological and economic growth patterns.
Purpose:
- To introduce and analyze the generalized logistic function for describing measured growth courses.
- To explore the numerical properties and computational adjustment of this function.
- To demonstrate the effectiveness of a specialized ALGOL program for nonlinear approximation.
Summary:
- The generalized logistic function, derived from VERHULST's logistic function, is proposed for quantitative growth description.
- The study discusses numerical properties and computerized adjustment methods for this function.
- An ALGOL program system for nonlinear approximation is presented, demonstrating effective adjustment of the generalized logistic function to growth data.
- Improved approximation quality is shown for models including an adjustable absolute term.
Impact:
- Provides a more versatile mathematical tool for analyzing diverse growth phenomena.
- Enhances the accuracy of growth modeling through improved approximation techniques.
- Facilitates the application of advanced computational methods in biological and economic growth studies.