Search results
Results from the WOW.Com Content Network
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.
Another generalized log-logistic distribution is the log-transform of the metalog distribution, in which power series expansions in terms of are substituted for logistic distribution parameters and . The resulting log-metalog distribution is highly shape flexible, has simple closed form PDF and quantile function , can be fit to data with linear ...
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.
In the logistic map, r is a parameter, and x is a variable. ... The frequency distribution of the logistic map with r = 4 has high density near both sides of [0, 1 ...
The logit and probit are both sigmoid functions with a domain between 0 and 1, which makes them both quantile functions – i.e., inverses of the cumulative distribution function (CDF) of a probability distribution. In fact, the logit is the quantile function of the logistic distribution, while the probit is the quantile function of the normal ...
The shifted log-logistic distribution is a probability distribution also known as the generalized log-logistic or the three-parameter log-logistic distribution. [1] [2] It has also been called the generalized logistic distribution, [3] but this conflicts with other uses of the term: see generalized logistic distribution.
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.
the uniform distribution over any convex set, the logistic distribution, the extreme value distribution, the Laplace distribution, the chi distribution, the hyperbolic secant distribution, the Wishart distribution, if n ≥ p + 1, [4] the Dirichlet distribution, if all parameters are ≥ 1, [4] the gamma distribution if the shape parameter is ...