TY - JOUR
T1 - The odd power generalized Weibull-G power series class of distributions
T2 - properties and applications
AU - Oluyede, Broderick
AU - Moakofi, Thatayaone
AU - Chipepa, Fastel
N1 - Publisher Copyright:
© 2022 Glowny Urzad Statystyczny. All rights reserved.
PY - 2022/3
Y1 - 2022/3
N2 - We develop a new class of distributions, namely, the odd power generalized Weibull-G power series (OPGW-GPS) class of distributions. We present some special classes of the proposed distribution. Structural properties, have also been derived. We conducted a simulation study to evaluate the consistency of the maximum likelihood estimates. Moreover, two real data examples on selected data sets, to illustrate the usefulness of the new class of distributions. The proposed model outperforms several non-nested models on selected data sets.
AB - We develop a new class of distributions, namely, the odd power generalized Weibull-G power series (OPGW-GPS) class of distributions. We present some special classes of the proposed distribution. Structural properties, have also been derived. We conducted a simulation study to evaluate the consistency of the maximum likelihood estimates. Moreover, two real data examples on selected data sets, to illustrate the usefulness of the new class of distributions. The proposed model outperforms several non-nested models on selected data sets.
UR - http://www.scopus.com/inward/record.url?scp=85140794922&partnerID=8YFLogxK
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U2 - 10.2478/stattrans-2022-0006
DO - 10.2478/stattrans-2022-0006
M3 - Article
AN - SCOPUS:85140794922
SN - 1234-7655
VL - 23
SP - 89
EP - 108
JO - Statistics in Transition New Series
JF - Statistics in Transition New Series
IS - 1
ER -