WEIBULL-LOMAX DISTRIBUTION: PROPERTIES AND APPLICATIONS
By Gauss Moutinho Cordeiro, Muhammad Mansoor, Muhammad Zubair, Muhammad Hussain Tahir. 2014
208 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/9f47e63d999580fbc9f48ac2f3e8bbef748f62fc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Morad Alizadeh
- Haitham M. Yousof
- Ibrahim Elbatal
- Edwin M. M. Ortega
- Ahmed Z. Afify
- G. Hamedani
- Gauss Moutinho Cordeiro
- Nadeem Shafique Butt
In Computer Vision and Pattern Recognition
In Molecular Biology
Citations in the corpus
- Sine Topp-Leone-G family of distributions: Theory and applications (2020, methodology): “[72], Kumaraswamy Lomax (KwL) model derived by Shams [66], beta Lomax (BL) model derived by Eugene et al.”
- The generalized odd Burr III family of distributions: properties, applications and characterizations (2019, methodology): “We fit the above data sets by the GOBIII-Lx model along with the other well-known lifetime distributions namely; transmuted Weibull Lomax (TWLx) [18], modified betaWeibull (MBW) [19],Macdonald Lomax (Mc-Lx) [20] and Weibull Lomax (WLx) [21] distributions.”
- The Transmuted Exponentiated Generalized-G Family of Distributions (2015, methodology): “We compare the fit of the TExGW distribution with those of the transmuted Weibull Lomax (TWL) (Afify et al., 2015), McDonald Weibull (McW) (Cordeiro et al., 2014), McDonald modified Weibull (McMW) (Merovci and Elbatal, 2013), Kw-TEMW, generalized transmuted Lindley (GT-Li) (Nofal et al., 2015),…”
- A New Generalization of the Lomax Distribution with Increasing, Decreasing, and Constant Failure Rate (2017, methodology): “Modified and extended versions of the Lomax distribution have been studied; examples include theweighted Lomax distribution [4], exponential Lomax distribution [5], exponentiated Lomaxdistribution [6], gammaLomaxdistribution [7], transmuted Lomax distribution [8], Poisson Lomax distribution [9], McD”
- The four-parameter Burr XII distribution: Properties, regression model, and applications (2018, background): “…(BEBXII) (Mead, 2014), transmuted exponentiated generalized Weibull (TExGW) (Yousof et al. 2015), Weibull Fréchet (WFr) (Afify et al., 2016), Weibull Lomax (WL) (Tahir et al., 2015), and beta Burr XII (BBXII) (Paranaíba et al., 2014) with corresponding densities (for x > 0) given in the Appendix.”