Abstract
The discrete skewed Laplace distribution is a flexible distribution with integer domain and simple closed form that can be applied to model count data. Parameters are estimated under empirical Bayes (EB) analysis and comparison are made between the Bayesian parameter estimation and classical parameter estimation, i.e. the maximum likelihood (ML) approach. The results show that the Bayesian parameter estimations are preferable.
DOI
10.22237/jmasm/1478003880
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
