Kumaraswamy’s distribution: A beta-type distribution with some tractability advantages

By M. Chris Jones. 2009

534 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/60c7e907d60c1fb5c85c991a3610d5422ee3ccfe

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In Global and Planetary Change

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Citations in the corpus

Risk-averse stochastic programming approach for microgrid planning under uncertainty (2017, methodology): “Advantages of using Kumaraswamy distribution over the beta distribution are [20]:”
Stacking species distribution models and adjusting bias by linking them to macroecological models (2014, methodology): “In Appendix S2, we assume the parent distribution is a Kumaraswamy distribution (an alternative to the beta distribution, which is more mathematically tractable for this analysis; Jones, 2009), and then prove by counterexample that Eqn 6 cannot generally be satisfied, even in the simplified case of ”
Improved point estimation for the Kumaraswamy distribution (2011, methodology): “Further, according to Jones [2], the beta distribution has the following advantages over the Kum distribution: simpler formulae for moments and moment-generating function; a one-parameter sub-family of symmetric distributions; simpler moment estimation and more ways of generating the distribution vi”
Approximate Inference for Deep Latent Gaussian Mixtures (2016, background): “We assume the posterior factorizes as q(π, z|xi) = q(π|xi)q(z|πi,xi) = ∏ K−1 Kumar(ai,k, bi,k) ∑K k=1 πi,kNθk(z|xi) where Kumar(a,b) denotes the Kumaraswamy distribution [4].”
Fast Threshold Tests for Detecting Discrimination (2017, methodology): “An early example of this was the Kumaraswamy distribution (Jones, 2009; Kumaraswamy, 1980), developed as an alternative to the beta distribution for its simpler CDF.”
Estimation of reliability of multicomponent stress–strength for a Kumaraswamy distribution (2017, methodology): “The basic properties of this distribution have been discussed by Jones (2009).”
New Properties of the Kumaraswamy Distribution (2013, unknown): “However, in spite of the fact that the Kumaraswamy distribution was introduced in 1980, further theoretical research on the distribution was not developed until very recently (Garg, 2008; Jones, 2009; Mitnik, 2009; Nadarajah, 2008).”
The Kumaraswamy-Log-Logistic Distribution (2012, background): “Jones (2009) advocated the Kum distribution as a generator instead of the beta generator, since its quantile function takes a simple form.”
General results for the Marshall and Olkin's family of distributions (2013, unknown): “This distribution, introduced by Kumaraswamy (1980), was well investigated by Jones (2009); see also Lemonte (2011).”
Exponentiated $T$-$X$ Family of Distributions with Some Applications (2013, methodology): “An extension of the beta-generated method was proposed in Jones (2009) and Cordeiro and de Castro (2011) by using the Kumaraswamy distribution (Kumaraswamy, 1980), as a generator instead of beta distribution.”
The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation (2012, unknown): “It also illustrates a series of properties of the re-parameterized versions of the distribution that can be derived rather directly from known properties of the distribution in its standard parameterization (for these latter properties, see Jones 2009, Sect.”
The Kumaraswamy modified Weibull distribution: theory and applications (2014, background): “However, Jones [15] explored the background and genesis of the Kw distribution and, more importantly, highlighted some advantages and disadvantages of the beta and Kw distributions.”
Transmuted Kumaraswamy Distribution (2016, methodology): “Jones (2009) investigated not only properties of the Kumaraswamy distribution but also some similarities and differences between the beta and Kw distributions.”