Improved parameter estimation for a family of exponential distributions

08/04/2023
by   S. B. Kologrivova, et al.
0

In this paper, we consider the problem of parameter estimating for a family of exponential distributions. We develop the improved estimation method, which generalized the James–Stein approach for a wide class of distributions. The proposed estimator dominates the classical maximum likelihood estimator under the quadratic risk. The estimating procedure is applied to special cases of distributions. The numerical simulations results are given.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/07/2020

A Generalized One Parameter Polynomial Exponential Generator Family of Distributions

A new class of distributions, called Generalized One Parameter Polynomia...
research
10/11/2020

Distributionally Robust Parametric Maximum Likelihood Estimation

We consider the parameter estimation problem of a probabilistic generati...
research
07/29/2021

Sparse estimation for generalized exponential marked Hawkes process

We have established a sparse estimation method for the generalized expon...
research
06/07/2018

Estimation of Mittag-Leffler Parameters

We propose a procedure for estimating the parameters of the Mittag-Leffl...
research
11/30/2017

A simple and efficient profile likelihood for semiparametric exponential family

Semiparametric exponential family proposed by Ning et al. (2017) is an e...
research
12/09/2021

Times Square sampling: an adaptive algorithm for free energy estimation

Estimating free energy differences, an important problem in computationa...
research
03/13/2022

Estimating a regression function in exponential families by model selection

Let X_1=(W_1,Y_1),…,X_n=(W_n,Y_n) be n pairs of independent random varia...

Please sign up or login with your details

Forgot password? Click here to reset