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  2. 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.

  3. Generalized logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_logistic...

    For other families of distributions that have also been called generalized logistic distributions, see the shifted log-logistic distribution, which is a generalization of the log-logistic distribution; and the metalog ("meta-logistic") distribution, which is highly shape-and-bounds flexible and can be fit to data with linear least squares.

  4. Tidyverse - Wikipedia

    en.wikipedia.org/wiki/Tidyverse

    The tidyverse is a collection of open source packages for the R programming language introduced by Hadley Wickham [1] and his team that "share an underlying design philosophy, grammar, and data structures" of tidy data. [2] Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging piping. [3 ...

  5. Kaniadakis logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Kaniadakis_Logistic...

    The Kaniadakis Logistic distribution (also known as κ-Logisticdistribution) is a generalized version of the Logistic distribution associated with the Kaniadakis statistics. It is one example of a Kaniadakis distribution .

  6. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    OpenMx – A package for structural equation modeling running in R (programming language) OpenNN – A software library written in the programming language C++ which implements neural networks, a main area of deep learning research; Orange, a data mining, machine learning, and bioinformatics software

  7. STAR model - Wikipedia

    en.wikipedia.org/wiki/STAR_model

    Logistic transition function for the ESTAR model with varying from -10 to +10 and - from 0 to 1. Calculated using GNU R package. Three basic transition functions and the name of resulting models are: first order logistic function - results in Logistic STAR (LSTAR) model:

  8. 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.

  9. 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.