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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. Logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Logistic_distribution

    Its cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks. It resembles the normal distribution in shape but has heavier tails (higher kurtosis). The logistic distribution is a special case of the Tukey lambda distribution.

  4. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    An explanation of logistic regression can begin with an explanation of the standard logistic function. The logistic function is a sigmoid function, which takes any real input , and outputs a value between zero and one. [2] For the logit, this is interpreted as taking input log-odds and having output probability. The standard logistic function ...

  5. Logistic equation - Wikipedia

    en.wikipedia.org/wiki/Logistic_equation

    Logistic equation can refer to: Logistic function, a common S-shaped equation and curve with applications in a wide range of fields. Logistic map, a nonlinear recurrence relation that plays a prominent role in chaos theory; Logistic regression, a regression technique that transforms the dependent variable using the logistic function

  6. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A sigmoid function is any mathematical function whose graph has a characteristic S-shaped or sigmoid curve. A common example of a sigmoid function is the logistic function, which is defined by the formula: [1] = + = + = ().

  7. Logit - Wikipedia

    en.wikipedia.org/wiki/Logit

    If p is a probability, then p/(1 − p) is the corresponding odds; the logit of the probability is the logarithm of the odds, i.e.: ⁡ = ⁡ = ⁡ ⁡ = ⁡ = ⁡ (). The base of the logarithm function used is of little importance in the present article, as long as it is greater than 1, but the natural logarithm with base e is the one most often used.

  8. Hubbert linearization - Wikipedia

    en.wikipedia.org/wiki/Hubbert_linearization

    The Hubbert curve [2] is the first derivative of a logistic function, which has been used for modeling the depletion of crude oil in particular, the depletion of finite mineral resources in general [3] and also population growth patterns. [4] Example of a Hubbert Linearization on the US Lower-48 crude oil production.

  9. Maximum sustainable yield - Wikipedia

    en.wikipedia.org/wiki/Maximum_sustainable_yield

    The logistic model (or logistic function) is a function that is used to describe bounded population growth under the previous two assumptions. The logistic function is bounded at both extremes: when there are not individuals to reproduce, and when there is an equilibrium number of individuals (i.e., at carrying capacity).