School of Statistics, East China Normal University, Shanghai, People's Republic of China
Department of Statistics, University of Wisconsin, Madison, WI, USA
xwang2587@wisc.edu
We consider maximum likelihood estimation with two or more datasets sampled from different populations with shared parameters. Although more datasets with shared parameters can increase statistical accuracy, this paper shows how to handle heterogeneity among different populations for correctness of estimation and inference. Asymptotic distributions of maximum likelihood estimators are derived under either regular cases where regularity conditions are satisfied or some non-regular situations. A bootstrap variance estimator for assessing performance of estimators and/or making large sample inference is also introduced and evaluated in a simulation study.
To cite this article: Jun Shao & Xinyan Wang (2023) MLE with datasets from populations having shared parameters, Statistical Theory and Related Fields, 7:3, 213-222, DOI: 10.1080/24754269.2023.2180185 To link to this article: https://doi.org/10.1080/24754269.2023.2180185