The Markov Bernoulli Lomax with Applications Censored and COVID-19 Drought Mortality Rate Data. Mohammed, B., I., Tashkandy, Y., A., El-Raouf, M., M., A., Hossain, M., M., & Bakr, M., E. Axioms, 12(5):439, 2023. doi abstract bibtex In this article, we present a Markov Bernoulli Lomax (MB-L) model, which is obtained by a countable mixture of Markov Bernoulli and Lomax distributions, with decreasing and unimodal hazard rate function (HRF). The new model contains Marshall- Olkin Lomax and Lomax distributions as a special case. The mathematical properties, as behavior of probability density function (PDF), HRF, rth moments, moment generating function (MGF) and minimum (maximum) Markov-Bernoulli Geometric (MBG) stable are studied. Moreover, the estimates of the model parameters by maximum likelihood are obtained. The maximum likelihood estimation (MLE), bias and mean squared error (MSE) of MB-L parameters are inspected by simulation study. Finally, a MB-L distribution was fitted to the randomly censored and COVID-19 (complete) data.
@article{
title = {The Markov Bernoulli Lomax with Applications Censored and COVID-19 Drought Mortality Rate Data},
type = {article},
year = {2023},
keywords = {Markov Bernoulli Lomax distribution,Markov Bernoulli geometric model,P-P plot,censored data,countable mixture,model selections},
pages = {439},
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abstract = {In this article, we present a Markov Bernoulli Lomax (MB-L) model, which is obtained by a countable mixture of Markov Bernoulli and Lomax distributions, with decreasing and unimodal hazard rate function (HRF). The new model contains Marshall- Olkin Lomax and Lomax distributions as a special case. The mathematical properties, as behavior of probability density function (PDF), HRF, rth moments, moment generating function (MGF) and minimum (maximum) Markov-Bernoulli Geometric (MBG) stable are studied. Moreover, the estimates of the model parameters by maximum likelihood are obtained. The maximum likelihood estimation (MLE), bias and mean squared error (MSE) of MB-L parameters are inspected by simulation study. Finally, a MB-L distribution was fitted to the randomly censored and COVID-19 (complete) data.},
bibtype = {article},
author = {Mohammed, Bahady I and Tashkandy, Yusra A and El-Raouf, Mohmoud M Abd and Hossain, Md. Moyazzem and Bakr, Mahmoud E},
doi = {10.3390/axioms12050439},
journal = {Axioms},
number = {5}
}
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