@article{
 title = {The transmuted exponentiated generalized-G family of distributions},
 type = {article},
 year = {2015},
 keywords = {Exponentiated generalized-g family,Generating function,Maximum likelihood,Order statistic,Transmuted-G family},
 pages = {441-464},
 volume = {11},
 publisher = {University of the Punjab, College of Statistical & Actuarial Science},
 id = {799e379c-5b16-3631-8528-bd2bb0e84584},
 created = {2020-09-18T15:01:45.324Z},
 file_attached = {true},
 profile_id = {49efd9d1-b84a-3562-b8db-36e64ac7ba81},
 last_modified = {2021-03-09T11:50:39.216Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Yousof2015},
 source_type = {JOUR},
 folder_uuids = {5ddc3a8d-55b4-43f0-b1b2-dbebf8b6daac},
 private_publication = {false},
 abstract = {We introduce a new class of continuous distributions called the transmuted exponentiated generalized-G family which extends the exponentiated generalized-G class introduced by Cordeiro et al. (2013). We provide some special models for the new family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Rényi and Shannon entropies, order statistics and probability weighted moments are derived. The estimation of the model parameters is performed by maximum likelihood. The flexibility of the proposed family is illustrated by means of an application to a real dataset.},
 bibtype = {article},
 author = {Yousof, Haitham M. and Afify, Ahmed Z. and Alizadeh, Morad and Butt, Nadeem Shafique and Hamedani, G. G. and Ali, M. Masoom},
 doi = {10.18187/pjsor.v11i4.1164},
 journal = {Pakistan Journal of Statistics and Operation Research},
 number = {4}
}

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