Confidence interval for correlation estimator between latent processes

Abstract

Kimura and Yoshida [26] treated a model in which the finite variation part of a two-dimensional semimartingale is expressed by time-integration of latent processes. They proposed a correlation estimator between the latent processes and proved its consistency and asymptotic mixed normality. In this paper, we discuss the confidence interval of the correlation estimator to detect the correlation. We propose two types of estimators for asymptotic variance of the correlation estimator and prove their consistency in a high frequency setting. Our model includes doubly stochastic Poisson processes whose intensity processes are correlated Itô processes. We compare our estimators based on the simulation of the doubly stochastic Poisson processes.

Clinical Epidemiological Studies of Colorectal Cancer by Record Linkage of Cancer Registries and Biospecimen Data: A Systematic Review

“…In contrast, the obstacles to record linkage for biospecimen data with databases maintained in other hospitals or governments are very challenging in Japan without a law like the Biobank Act (Kimura, et al, 2020). This is because consent must be obtained separately from participants when providing data to an outside organization for record linkage (Ministry of Health, Labour and Welfare., 2022).…”