How to cite this paper
Denthet, S & Promin, P. (2019). The negative binomial-weighted Lindley distribution.Decision Science Letters , 8(3), 317-322.
Refrences
Arnold, T. B., & Emerson, J. W. (2011). Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions. R Journal, 3(2), 34-39.
Ghitany, M. E., Atieh, B., & Nadarajah, S. (2008). Lindley distribution and its application. Mathematics and Computers in Simulation, 78(4), 493-506.
Gómez-Déniz, E., Sarabia, J. M., & Calderín-Ojeda, E. (2008). Univariate and multivariate versions of the negative binomial-inverse Gaussian distributions with applications. Insurance: Mathematics and Economics, 42(1), 39-49.
Hamid, H. (2014). Integrated Smoothed Location Model and Data Reduction Approaches for Multi Variables Classification (Unpublished doctoral dissertation). Universiti Utara Malaysia, Kedah, Malaysia.
Haight, F. (1967). Handbook of the Poisson distribution. John Wiley and Sons, New York.
Klugman,S., Panjer, H. and Willmot, G. (2008). Loss models: from data to decisions. 3rd. John Wiley and Sons.
Kongrod, S., Bodhisuwan, W., & Payakkapong, P. (2014). The negative binomial-Erlang distribution with applications. International Journal of Pure and Applied Mathematics, 92(3), 389-401.
Lindley, D. V. (1958). Fiducial distributions and Bayes' theorem. Journal of the Royal Statistical Society. Series B (Methodological), 20(1), 102-107.
Pudprommarat, C., Bodhisuwan, W., & Zeephongsekul, P. (2012). A new mixed negative binomial distribution. Journal of Applied Sciences(Faisalabad), 12(17), 1853-1858.
Rainer,W. (2008). Econometric analysis of count data. Library of congress control, New York.
Team, R.C. (2015). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria.
Zamani, H., & Ismail, N. (2010). Negative binomial-Lindley distribution and its application. Journal of Mathematics and Statistics, 6(1), 4-9.
Ghitany, M. E., Atieh, B., & Nadarajah, S. (2008). Lindley distribution and its application. Mathematics and Computers in Simulation, 78(4), 493-506.
Gómez-Déniz, E., Sarabia, J. M., & Calderín-Ojeda, E. (2008). Univariate and multivariate versions of the negative binomial-inverse Gaussian distributions with applications. Insurance: Mathematics and Economics, 42(1), 39-49.
Hamid, H. (2014). Integrated Smoothed Location Model and Data Reduction Approaches for Multi Variables Classification (Unpublished doctoral dissertation). Universiti Utara Malaysia, Kedah, Malaysia.
Haight, F. (1967). Handbook of the Poisson distribution. John Wiley and Sons, New York.
Klugman,S., Panjer, H. and Willmot, G. (2008). Loss models: from data to decisions. 3rd. John Wiley and Sons.
Kongrod, S., Bodhisuwan, W., & Payakkapong, P. (2014). The negative binomial-Erlang distribution with applications. International Journal of Pure and Applied Mathematics, 92(3), 389-401.
Lindley, D. V. (1958). Fiducial distributions and Bayes' theorem. Journal of the Royal Statistical Society. Series B (Methodological), 20(1), 102-107.
Pudprommarat, C., Bodhisuwan, W., & Zeephongsekul, P. (2012). A new mixed negative binomial distribution. Journal of Applied Sciences(Faisalabad), 12(17), 1853-1858.
Rainer,W. (2008). Econometric analysis of count data. Library of congress control, New York.
Team, R.C. (2015). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria.
Zamani, H., & Ismail, N. (2010). Negative binomial-Lindley distribution and its application. Journal of Mathematics and Statistics, 6(1), 4-9.