A Sequential Learning Procedure with Applications to Online Sales Examination
Methodology
2023-11-07 v1
Abstract
In this paper, we consider the problem of estimating parameters 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.
Cite
@article{arxiv.2311.02273,
title = {A Sequential Learning Procedure with Applications to Online Sales Examination},
author = {Jun Hu and Yan Zhuang and Shunan Zhao},
journal= {arXiv preprint arXiv:2311.02273},
year = {2023}
}