Shrinkage Estimators for Shape Parameter of Gompertz Distribution

This study introduces shrinkage estimators for determining the shape parameter within the Gompertz distribution, employing two distinct shrinkage techniques. Investigation into the mean squared error characteristics of said estimator has been undertaken, and its outcomes have been derived. To provide a thorough examination, a comparative analysis between these newly proposed classes of estimators and their corresponding conventional unbiased counterparts is conducted, utilizing mean squared error metrics in a simulation study. Observations from said simulation illustrate that the shrinkage estimators yield markedly smaller values for mean squared error when juxtaposed against existing unbiased estimators. Furthermore, the suggested estimators exhibit superior performance as the sample size increases.