@article{
 title = {The exponential pareto power series distribution: Theory and applications},
 type = {article},
 year = {2017},
 keywords = {Exponential pareto distribution,Maximum likelihood estimation,Moments,Power series distribution},
 pages = {603-615},
 volume = {13},
 id = {5b11bf34-463d-368b-ba19-908cb52aa686},
 created = {2021-08-31T15:29:47.008Z},
 file_attached = {true},
 profile_id = {49efd9d1-b84a-3562-b8db-36e64ac7ba81},
 last_modified = {2021-08-31T15:48:13.363Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Elbatal2017},
 folder_uuids = {4cfcf1ef-e8a1-481b-9768-92f271f79e14},
 private_publication = {false},
 abstract = {A new lifetime class of distributions is introduced by compounding the exponential Pareto and power series distributions. The compounding procedure follows the same set-up carried out by Adamidis and Loukas (1998). We obtain several properties of the new class including ordinary and conditional, mean deviations, Bonferroni and Lorenz curves, residual and reversed residual lifes and order statistics. The maximum likelihood estimation procedure is carried out to estimate the model parameters. We present three special models of the proposed class.},
 bibtype = {article},
 author = {Elbatal, I. and Zayed, Mohamed and Rasekhi, Mahdi and Butt, Nadeem Shafique N.S.},
 doi = {10.18187/pjsor.v13i3.2072},
 journal = {Pakistan Journal of Statistics and Operation Research},
 number = {3}
}

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