A new estimation for probability distributions using $L_2$ optimization

Abstract

Many probability distributions belong to a location-scale family. One such an example is a normal distribution. Probability distributions of the family possess many desirable merits and have colossal amount of real-world application. In this paper, we propose a novel method to estimate both location and scale parameters of probability distributions and investigate its asymptotic properties. After examining theoretical aspects of the proposed estimators, we will empirically demonstrate that they compares favorably with other estimators through simulation studies.

Cited by in corpus (1)

• Robust estimation of parameters in logistic regression via solving the Cramer-von Mises type L2 optimization problem