Maximum Entropy Empirical Likelihood Methods Based on Laplace Transforms for Nonnegative Continuous Distribution with Actuarial Applications

ISSN Print: 2161-718X
ISSN Online: 2161-7198
www.scirp.net/journal/ojs
E-mail: [email protected]

Citations

"Maximum Entropy Empirical Likelihood Methods Based on Laplace Transforms for Nonnegative Continuous Distribution with Actuarial Applications"
written by Andrew Luong,
published by Open Journal of Statistics, Vol.7 No.3, 2017

has been cited by the following article(s):

[1]	Generalized Method of Moments and Generalized Estimating Functions Based on Probability Generating Function for Count Models
	2020

[2]	Méthode d'inférence utilisant la vraisemblance empirique basée sur l'entropie pour les modèles de diffusion avec sauts
	2019

[3]	Simulated Minimum Quadratic Distance Methods Using Grouped Data for Some Bivariate Continuous Models
	2018

[4]	Maximum Entropy Empirical Likelihood Methods Based on Bivariate Laplace Transforms and Moment Generating Functions
	2018

[1]	Generalized Method of Moments and Generalized Estimating Functions Based on Probability Generating Function for Count Models Open Journal of Statistics, 2020 DOI:10.4236/ojs.2020.103031

[2]	Simulated Minimum Quadratic Distance Methods Using Grouped Data for Some Bivariate Continuous Models Open Journal of Statistics, 2018 DOI:10.4236/ojs.2018.82024

[3]	Maximum Entropy Empirical Likelihood Methods Based on Bivariate Laplace Transforms and Moment Generating Functions Open Journal of Statistics, 2018 DOI:10.4236/ojs.2018.82017

Top