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Quasi Lindley Geometric Distribution

by L. S. Diab, Hiba Z. Muhammed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 13
Year of Publication: 2014
Authors: L. S. Diab, Hiba Z. Muhammed
10.5120/16652-6628

L. S. Diab, Hiba Z. Muhammed . Quasi Lindley Geometric Distribution. International Journal of Computer Applications. 95, 13 ( June 2014), 9-16. DOI=10.5120/16652-6628

@article{ 10.5120/16652-6628,
author = { L. S. Diab, Hiba Z. Muhammed },
title = { Quasi Lindley Geometric Distribution },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 13 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number13/16652-6628/ },
doi = { 10.5120/16652-6628 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:20.616047+05:30
%A L. S. Diab
%A Hiba Z. Muhammed
%T Quasi Lindley Geometric Distribution
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 13
%P 9-16
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we introduce a new class of lifetime distributions which is called the Quasi Lindley Geometric (QLG) distribution. This distribution obtained by compounding the Quasi Lindley and geometric distributions. Some structural properties of the proposed new distribution are discussed, including probability density function and explicit algebraic formulas for its survival and hazard functions, moment , moment generating function and mean deviations. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

References
  1. Adamidis K. , Dimitrakopoulou,T. , Loukas,S. (2005). On ageneralization of the exponential- geometric distribution. Statistics & Probability Letters, 73,259-269.
  2. Adamidis K. ,Loukas,S. (1998). A lifetime distribution with decreasing failure rate. Statistics & Probability Letters, 39, 35-42.
  3. Aarset M. V. (1987). How to identify bathtub hazard rate, IEEET ransactions Reliability, 36,106-108.
  4. Barreto-Souza,W, Silva,R. Band Cordeiro,G. M (2010) A new distribution with decreasing, increasing and upside- down bathtub failure rate,Comput. Statist. DataAnal. 54pp. 935-944.
  5. Barreto-Souza,W. ,Cribari-Neto, F. (2009). Ageneralization of the exponential- Poisson distribution. Statistics& Probability Letters,79, 2493-2500.
  6. Chahkandi, M. , Ganjali, M. (2009). On some life time distributions with decreasing failure rate. Computational Statistics &Data Analysis,53,4433-4440.
  7. Ghitany, M. E. , Atieh, B. , and Nadarajah, S. (2008). Lindley distribution and its application . Mathematics and Computers in Simulation, 78,493-506.
  8. Gupta, P. L. and Gupta, R. C. (1983). On the moments of residual life in reliability and some characterization results. Comm. Statist. Theory Methods 12(4),449-461.
  9. Johnson,N. L, Kotz, S. and Balakrishnan, N. (1995). Continuous Univariate Distributions. volume1. JohnWiley& Sons, NewYork.
  10. Kenney, J. F. and Keeping, E. S. (1962). Mathematics of statistics, pp. 101-102, Part1, 3rded. Princeton,NJ.
  11. Kundu,C. and Nanda ,A. K, (2010) Some reliability properties of the inactivity time ,Communications in Statistics-Theory and Methods 39899-911.
  12. Kus, C. (2007). A new lifetime distribution. Computational Statistics & Data Analysis, 51, 4497-4509.
  13. Lee, E. T. and Wang, J. W. Statistical Methods for Survival Data Analysis, 3 rded. ,Wiley, New York, 2003.
  14. Lindley, D. V. (1958). Fiducial distributions and Bayes theorem, J. Royal Stat. Soc. Series B,20102-107.
  15. Lu,W. , Shi,D. (2011). A new compounding life distribution: the Weibull- Poisson distribution. Journal of Applied Statistics, DOI:10. 1080/02664763. 2011. 575126.
  16. MazucheliJ and AchcarJ. A. (2011). The Lindley distribution applied to competing risks lifetime data. Comput. Methods Programs Biomed. 104 (2):188-192.
  17. Morais, A. L. ,Barreto- Souza,W. (2011). A Compound Class of Weibull and Power Series Distributions. Computational Statistics & Data Analysis,55,1410-1425.
  18. Moors, J. J . A. (1998). Aquantile alternative for kurtosis. Journal of the Royal Statistical Society Ser. D. ,The Statistician, 37,25-32.
  19. Nanda, A. K. , Singh, H. Misra, N. Paul, P. (2003). Reliability properties of reversed residual lifetime, Communications in Statistics- Theory and Methods 322031-2042.
  20. Rama, S. and Mishra A. (2013) . Aquasi Lindley distribution . African Journal of Mathematics and Computer Science Research. 6(4), 64-71.
  21. Swain. J, S. Venkatraman. S, and Wilson . J(1988). Least squares estimation of distribution function in Johnson stranslation system. Journal of Statistical Computation and Simulation,29,271- 297.
  22. Tahmasbi,R. , Rezaei,S. (2008). Atwo-parameter lifetime distribution with decreasing failure rate. Computational Statistics. & Data Analysis, 52, 3889-3901.
  23. Zakerzadeh, H. andMahmoudi, E. (2012). A new two parameter lifetime distribution: model and properties. arXiv:1204. 4248[stat. CO.
Index Terms

Computer Science
Information Sciences

Keywords

Quasi Lindley distribution Geometric distribution Moments Maximum likelihood.

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