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  2. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    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.

  3. Generalised logistic function - Wikipedia

    en.wikipedia.org/wiki/Generalised_logistic_function

    The generalized logistic function or curve is an extension of the logistic or sigmoid functions. Originally developed for growth modelling, it allows for more flexible S-shaped curves. The function is sometimes named Richards's curve after F. J. Richards, who proposed the general form for the family of models in 1959.

  4. Logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Logistic_distribution

    As the logistic distribution, which can be solved analytically, is similar to the normal distribution, it can be used instead. The blue picture illustrates an example of fitting the logistic distribution to ranked October rainfalls—that are almost normally distributed—and it shows the 90% confidence belt based on the binomial distribution.

  5. Hyperbolastic functions - Wikipedia

    en.wikipedia.org/wiki/Hyperbolastic_functions

    Cumulative Distribution Function of Hyperbolastic Type I, Logistic, and Hyperbolastic Type II PDF of H1, Logistic, and H2. Hyperbolastic regressions are statistical models that utilize standard hyperbolastic functions to model a dichotomous or multinomial outcome variable. The purpose of hyperbolastic regression is to predict an outcome using a ...

  6. Beverton–Holt model - Wikipedia

    en.wikipedia.org/wiki/Beverton–Holt_model

    The Beverton–Holt model is a classic discrete ... of the continuous-time logistic equation for population growth ... population dynamics" (PDF ...

  7. Pierre François Verhulst - Wikipedia

    en.wikipedia.org/wiki/Pierre_François_Verhulst

    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:

  8. Population dynamics - Wikipedia

    en.wikipedia.org/wiki/Population_dynamics

    Using these techniques, Malthus' population principle of growth was later transformed into a mathematical model known as the logistic equation: = (), where N is the population size, r is the intrinsic rate of natural increase, and K is the carrying capacity of the population.

  9. Population model - Wikipedia

    en.wikipedia.org/wiki/Population_model

    One of the most basic and milestone models of population growth was the logistic model of population growth formulated by Pierre François Verhulst in 1838. The logistic model takes the shape of a sigmoid curve and describes the growth of a population as exponential, followed by a decrease in growth, and bound by a carrying capacity due to ...