Inference of partial correlations of a multivariate Gaussian time series
成果类型：
Article
署名作者：
Dilernia, A. S.; Fiecas, M.; Zhang, L.
署名单位：
Grand Valley State University; University of Minnesota System; University of Minnesota Twin Cities
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asae012
发表日期：
2024
页码：
14371444
关键词：
摘要：
We derive an asymptotic joint distribution and novel covariance estimator for the partial correlations of a multivariate Gaussian time series given mild regularity conditions. Using our derived asymptotic distribution, we develop a Wald confidence interval and testing procedure for inference of individual partial correlations for time series data. Through simulation we demonstrate that our proposed confidence interval attains higher coverage rates, and our testing procedure attains false positive rates closer to the nominal levels than approaches that assume independent observations when autocorrelation is present.