Abstract:
The parameter estimator discussed is the parameter estimator of the Dagum
distribution with the k-loss function and the entropy loss function using the Bayes
method. To get the Bayes estimator from the scale parameter of the Dagum distribution,
the Jeffrey’s non-informative prior distribution is used based on the maximum
likelihood function and the loss function for the k-loss function and the entropy loss
function to obtain an efficient estimator. Determinant of the best estimator is done by
comparing the variance values generated from each estimator. An estimator that uses
the entropy loss function is the best method for estimating the parameters of the Dagum
distribution of the data population with efficient conditions met.
