An estimation of size-biased generalized logarithmic series distribution

This paper sets out to introduce a Size-biased Generalized Logarithmic Series Distribution (SBGLSD). An attempt is also made at obtaining the estimates of the parameters of SBGLSD by employing the method of moments and a proposed new method using the non-zero frequency of a variable up to a finite value. Comparison is also made among different estimation methods by means of Pearson’s Chi-square, Akaike Information Criterion (AIC) and Bayesian Information Criterion Techniques (BIC). It was observed that the proposed estimator gives better results in comparison to moment estimators. This suggested method has an advantage over the method of moments.