TY - JOUR
T1 - A new heavy-tailed exponentiated generalised-G family of distributions
T2 - properties and applications
AU - Lekono, Gomolemo Jacqueline
AU - Oluyede, Broderick
AU - Gabaitiri, Lesego
N1 - Publisher Copyright:
Copyright © 2024 Inderscience Enterprises Ltd.
PY - 2024
Y1 - 2024
N2 - In this paper, we introduce a new family of heavy-tailed distributions called the type-I heavy-tailed exponentiated generalised-G (TIHTEG-G) family of distributions. A special model of the proposed family, namely the type-I heavy-tailed exponentiated generalised-log-logistic (TIHTEG-LLoG) model is studied in detail. Statistical properties of the new family of distributions are presented. These include, among others, the hazard rate function, quantile function, moments, distribution of order statistics and Rényi entropy. The maximum likelihood method of estimation is used for estimating the model parameters and Monte Carlo simulation is conducted to examine the performance of the model. Actuarial measures are also derived and simulation study for these measures is done to show that the proposed TIHTEG-LLoG model is a heavy-tailed model. Real datasets are analysed to illustrate the usefulness of the proposed model.
AB - In this paper, we introduce a new family of heavy-tailed distributions called the type-I heavy-tailed exponentiated generalised-G (TIHTEG-G) family of distributions. A special model of the proposed family, namely the type-I heavy-tailed exponentiated generalised-log-logistic (TIHTEG-LLoG) model is studied in detail. Statistical properties of the new family of distributions are presented. These include, among others, the hazard rate function, quantile function, moments, distribution of order statistics and Rényi entropy. The maximum likelihood method of estimation is used for estimating the model parameters and Monte Carlo simulation is conducted to examine the performance of the model. Actuarial measures are also derived and simulation study for these measures is done to show that the proposed TIHTEG-LLoG model is a heavy-tailed model. Real datasets are analysed to illustrate the usefulness of the proposed model.
KW - actuarial measures
KW - applications
KW - exponentiated generalised-G
KW - family of distributions
KW - heavy-tailed
KW - properties
KW - simulation
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U2 - 10.1504/IJMOR.2024.136860
DO - 10.1504/IJMOR.2024.136860
M3 - Article
AN - SCOPUS:85186495799
SN - 1757-5850
VL - 27
SP - 1
EP - 34
JO - International Journal of Mathematics in Operational Research
JF - International Journal of Mathematics in Operational Research
IS - 1
ER -