{"id":512,"date":"2017-09-24T06:19:37","date_gmt":"2017-09-24T06:19:37","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&p=512"},"modified":"2017-09-24T06:19:44","modified_gmt":"2017-09-24T06:19:44","slug":"quantile-estimation-two-parameter-gamma-distribution","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/quantile-estimation-two-parameter-gamma-distribution\/","title":{"rendered":"Quantile estimation in the two-parameter gamma distribution"},"content":{"rendered":"
The gamma distribution is applicable in situations where intervals between events
\nare considered as well as where a skewed distribution is appropriate. Estimation
\nof parameters is revisited in the two-parameter gamma distribution. The method
\nof quantile estimates is implemented to this distribution. A comparative study
\nbetween the method of moments, the maximum likelihood method, the method of
\nproduct spacings, and the method of quantile estimates is performed using simulation.
\nFor the scale parameter, the maximum likelihood estimate performs better
\nand for the shape parameter, the product spacings estimate performs better.<\/p>\n