In this paper mathematical and statistical properties including moment generating function, mean deviations about mean and median, order statistics, Bonferroni and Lorenz curves, Renyi entropy and stress strength reliability of quasi Lindley distribution (QLD) introduced by Shanker and Mishra (2013 a) have been derived and discussed. The goodness of fit of QLD over exponential and Lindley distributions have been illustrated with five real lifetime data-sets and found that QLD provides better fit than exponential and Lindley distributions.
Published in | International Journal of Statistical Distributions and Applications (Volume 2, Issue 1) |
DOI | 10.11648/j.ijsd.20160201.11 |
Page(s) | 1-7 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Mean Deviations, Order Statistics, Bonferroni and Lorenz Curves, Renyi Entropy Measure, Stress-Strength Reliability, Goodness of Fit
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APA Style
Rama Shanker, Hagos Fesshaye, Shambhu Sharma. (2016). On Quasi Lindley Distribution and Its Applications to Model Lifetime Data. International Journal of Statistical Distributions and Applications, 2(1), 1-7. https://doi.org/10.11648/j.ijsd.20160201.11
ACS Style
Rama Shanker; Hagos Fesshaye; Shambhu Sharma. On Quasi Lindley Distribution and Its Applications to Model Lifetime Data. Int. J. Stat. Distrib. Appl. 2016, 2(1), 1-7. doi: 10.11648/j.ijsd.20160201.11
AMA Style
Rama Shanker, Hagos Fesshaye, Shambhu Sharma. On Quasi Lindley Distribution and Its Applications to Model Lifetime Data. Int J Stat Distrib Appl. 2016;2(1):1-7. doi: 10.11648/j.ijsd.20160201.11
@article{10.11648/j.ijsd.20160201.11, author = {Rama Shanker and Hagos Fesshaye and Shambhu Sharma}, title = {On Quasi Lindley Distribution and Its Applications to Model Lifetime Data}, journal = {International Journal of Statistical Distributions and Applications}, volume = {2}, number = {1}, pages = {1-7}, doi = {10.11648/j.ijsd.20160201.11}, url = {https://doi.org/10.11648/j.ijsd.20160201.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20160201.11}, abstract = {In this paper mathematical and statistical properties including moment generating function, mean deviations about mean and median, order statistics, Bonferroni and Lorenz curves, Renyi entropy and stress strength reliability of quasi Lindley distribution (QLD) introduced by Shanker and Mishra (2013 a) have been derived and discussed. The goodness of fit of QLD over exponential and Lindley distributions have been illustrated with five real lifetime data-sets and found that QLD provides better fit than exponential and Lindley distributions.}, year = {2016} }
TY - JOUR T1 - On Quasi Lindley Distribution and Its Applications to Model Lifetime Data AU - Rama Shanker AU - Hagos Fesshaye AU - Shambhu Sharma Y1 - 2016/04/14 PY - 2016 N1 - https://doi.org/10.11648/j.ijsd.20160201.11 DO - 10.11648/j.ijsd.20160201.11 T2 - International Journal of Statistical Distributions and Applications JF - International Journal of Statistical Distributions and Applications JO - International Journal of Statistical Distributions and Applications SP - 1 EP - 7 PB - Science Publishing Group SN - 2472-3509 UR - https://doi.org/10.11648/j.ijsd.20160201.11 AB - In this paper mathematical and statistical properties including moment generating function, mean deviations about mean and median, order statistics, Bonferroni and Lorenz curves, Renyi entropy and stress strength reliability of quasi Lindley distribution (QLD) introduced by Shanker and Mishra (2013 a) have been derived and discussed. The goodness of fit of QLD over exponential and Lindley distributions have been illustrated with five real lifetime data-sets and found that QLD provides better fit than exponential and Lindley distributions. VL - 2 IS - 1 ER -