The transmuted geometric-weibull distribution: Properties, characterizations and regression models. Nofal, Z., M., Gebaly, Y., M., Altun, E., Alizadeh, M., & Butt, N., S. Pakistan Journal of Statistics and Operation Research, 13(2):395-416, 2017.
The transmuted geometric-weibull distribution: Properties, characterizations and regression models [pdf]Paper  abstract   bibtex   
We propose a new lifetime model called the transmuted geometric-Weibull distribution. Some of its structural properties including ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Renyi and q-entropies and order statistics are derived. The maximum likelihood method is discussed to estimate the model parameters by means of Monte Carlo simulation study. A new location-scale regression model is introduced based on the proposed distribution. The new distribution is applied to two real data sets to illustrate its flexibility. Empirical results indicate that proposed distribution can be alternative model to other lifetime models available in the literature for modeling real data in many areas.
@article{
 title = {The transmuted geometric-weibull distribution: Properties, characterizations and regression models},
 type = {article},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {Goodness of fit,Lifetime data,Maximum likelihood,Moment,Order statistic,Regression model},
 pages = {395-416},
 volume = {13},
 id = {378fd383-7d60-399c-b434-cb04ae370103},
 created = {2020-09-18T15:01:45.104Z},
 file_attached = {true},
 profile_id = {49efd9d1-b84a-3562-b8db-36e64ac7ba81},
 last_modified = {2021-03-09T11:50:38.855Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Nofal2017},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {We propose a new lifetime model called the transmuted geometric-Weibull distribution. Some of its structural properties including ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Renyi and q-entropies and order statistics are derived. The maximum likelihood method is discussed to estimate the model parameters by means of Monte Carlo simulation study. A new location-scale regression model is introduced based on the proposed distribution. The new distribution is applied to two real data sets to illustrate its flexibility. Empirical results indicate that proposed distribution can be alternative model to other lifetime models available in the literature for modeling real data in many areas.},
 bibtype = {article},
 author = {Nofal, Zohdy M. and Gebaly, Yehia M.El and Altun, Emrah and Alizadeh, Morad and Butt, Nadeem Shafique},
 journal = {Pakistan Journal of Statistics and Operation Research},
 number = {2}
}
Downloads: 0