Work

A Sequential Learning Procedure for Estimating Coefficients in Linear Regression With Applications to Online Sales Examination

Year: 2024

Type: article

Abstract: ABSTRACT In this paper, we consider the problem of estimating coefficients in a linear regression model. We propose a sequential learning procedure to determine the sample size for achieving a given small estimation risk, under the widely used Gauss‐Markov setup with independent normal errors. The procedure is proven to enjoy the second‐order efficiency and risk‐efficiency properties, which are validated through Monte Carlo simulation studies. Using e‐commerce data, we implement the procedure to examine the influential factors of online sales.

Source: Applied Stochastic Models in Business and Industry

DOI: 10.1002/asmb.2903

Authors: Jun Hu, Yan Zhuang, Shunan Zhao

Institutions: Oakland University, Connecticut College

Language: English

Topic: Advanced Statistical Methods and Models

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4404328616

FWCI: 0.343

Cites: 24

Cited by: 1

Related to: 10