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In probability and statistics, the Kumaraswamy's double bounded distribution is a family of continuous probability distributions defined on the interval (0,1). It is similar to the beta distribution, but much simpler to use especially in simulation studies since its probability density function, cumulative distribution function and quantile functions can be expressed in closed form.
In probability theory, the Modified Kumaraswamy (MK) distribution is a two-parameter continuous probability distribution defined on the interval (0,1). It serves as an alternative to the beta and Kumaraswamy distributions for modeling double-bounded random variables.
The Kumaraswamy distribution is as versatile as the Beta distribution but has simple closed forms for both the cdf and the pdf. The logit metalog distribution , which is highly shape-flexible, has simple closed forms, and can be parameterized with data using linear least squares.
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Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; Appearance. ... Kumaraswamy distribution; L. Landau distribution;
If has an NEF-QVF distribution and μ has a conjugate prior distribution then the marginal distributions are well-known distributions. [1] These properties together with the above notation can simplify calculations in mathematical statistics that would normally be done using complicated calculations and calculus.
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In decision theory, if all alternative distributions available to a decision-maker are in the same location–scale family, and the first two moments are finite, then a two-moment decision model can apply, and decision-making can be framed in terms of the means and the variances of the distributions.