New method predicts unknown parameters with precision as sample size grows.
Method-of-quantiles estimators match real-life and theoretical quantiles to estimate unknown parameters. The study looks at how these estimators behave with large sample sizes. Different examples are examined, and the best probability level for matching quantiles is determined. The method-of-quantiles estimators are compared to method-of-moments estimators to see how they converge.
