Comparison of methods for estimating the parameters of the asymmetric Laplace distribution using the quadratic loss function and the maximum possibility method


The asymmetric Laplace distribution (AL) has a fundamental and important role in developing mathematics and statistics and applying its properties in the financial field. Quadratic, assuming gamma and exponential precedence functions for each of the parameters of skew and scaling, respectively. Whereas the maximal potential estimators and Lindley approximation were used efficiently in the Bayesian estimation. Based on the simulation method to generate random samples with four different sample sizes (n = 15, 30, 60, 100 and recurrence). The value of L=1000 with taking default values of the two parameters k, \sigma and initial values for a, b, c, depending on the mean integral error squares (IMSE), where the comparison was made between the squared error loss function and the method of greatest possibility, where the results showed that the estimator of Baseline for the parameters of skewness and measurement under the squared error loss function is better than the method of greatest possibility.