TY  - JOUR
Y1  - 2023///
JF  - Frontiers in Applied Mathematics and Statistics
A1  - Ishaq, A.I.
A1  - Suleiman, A.A.
A1  - Daud, H.
A1  - Singh, N.S.S.
A1  - Othman, M.
A1  - Sokkalingam, R.
A1  - Wiratchotisatian, P.
A1  - Usman, A.G.
A1  - Abba, S.I.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176587855&doi=10.3389%2ffams.2023.1258961&partnerID=40&md5=c9e5f27b1975658000f7e88665782d8c
VL  - 9
AV  - none
N2  - This article aimed to present a new continuous probability density function for a non-negative random variable that serves as an alternative to some bounded domain distributions. The new distribution, termed the log-Kumaraswamy distribution, could faithfully be employed to compete with bounded and unbounded random processes. Some essential features of this distribution were studied, and the parameters of its estimates were obtained based on the maximum product of spacing, least squares, and weighted least squares procedures. The new distribution was proven to be better than traditional models in terms of flexibility and applicability to real-life data sets. Copyright © 2023 Ishaq, Suleiman, Daud, Singh, Othman, Sokkalingam, Wiratchotisatian, Usman and Abba.
N1  - cited By 2
ID  - scholars19062
TI  - Log-Kumaraswamy distribution: its features and applications
ER  -