Asymptotic Distribution of the Correlation Matrix in a Monotone Incomplete Sample

Data with missing values are often obtained using multivariate statistical analyses. It is crucial to study how to estimate parameters and test hypotheses using such data. There exists a step monotone incomplete sample as a simple model of data, which includes such missing values. In this study, we derive the asymptotic distribution of the estimator for the correlation matrix and propose a hypothesis testing method for it in a three-step monotone incomplete sample. Further, we investigate the accuracy of our results by numerical simulation.

Automated summary

This study investigates the asymptotic distribution of the estimator for the correlation matrix and proposes a hypothesis testing method in a three-step monotone incomplete sample, which is validated by numerical simulation.