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Logistic function for the mathematical model used in Population dynamics that adjusts growth rate based on how close it is to the maximum a system can support; Albert Allen Bartlett – a leading proponent of the Malthusian Growth Model; Exogenous growth model – related growth model from economics; Growth theory – related ideas from economics
Often the independent variable is time. Described as a function, a quantity undergoing exponential growth is an exponential function of time, that is, the variable representing time is the exponent (in contrast to other types of growth, such as quadratic growth). Exponential growth is the inverse of logarithmic growth.
The function also adheres to the sigmoid function, which is the most widely accepted convention of generally detailing a population's growth. Moreover, the function makes use of initial growth rate, which is commonly seen in populations of bacterial and cancer cells, which undergo the log phase and grow rapidly in numbers.
Relative growth rate (RGR) is growth rate relative to size - that is, a rate of growth per unit time, as a proportion of its size at that moment in time. It is also called the exponential growth rate, or the continuous growth rate.
The formula can be read as follows: the rate of change in the population (dN/dt) is equal to growth (rN) that is limited by carrying capacity (1 − N/K). From these basic mathematical principles the discipline of population ecology expands into a field of investigation that queries the demographics of real populations and tests these results ...
The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.
One of the simplest of macroscale models: an ordinary differential equation describing continuous exponential growth. N ( t ) {\displaystyle N(t)} is the size of the population at the time t {\displaystyle t} and d N ( t ) / d t {\displaystyle dN(t)/dt} is the rate of change through time in a single dimension N {\displaystyle N} .
Verhulst developed the logistic function in a series of three papers between 1838 and 1847, based on research on modeling population growth that he conducted in the mid 1830s, under the guidance of Adolphe Quetelet; see Logistic function § History for details. [1] Verhulst published in Verhulst (1838) the equation: