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Kashif Yousuf & Yang Feng. (2022) Targeting Predictors Via Partial Distance Correlation With Applications to Financial Forecasting. Journal of Business & Economic Statistics 40:3, pages 1007-1019.
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Virginia Lacal & Dag Tjøstheim. (2019) Estimating and Testing Nonlinear Local Dependence Between Two Time Series. Journal of Business & Economic Statistics 37:4, pages 648-660.
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Germán G. Creamer & Chihoon Lee. (2019) A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures. Quantitative Finance 19:9, pages 1531-1542.
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Jingren Chen, Xuejun Ma & Yue Chao. Testing independence for multivariate time series via auto multivariate distance covariance. Communications in Statistics - Theory and Methods 0:0, pages 1-13.
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Raffaele Bolla, Roberto Bruschi, Franco Davoli, Chiara Lombardo, Alireza Mohammadpour, Riccardo Trivisonno & Wint Yi Poe. (2023) Adaptive Reliability for the Automated Control of Human–Robot Collaboration in Beyond-5G Networks. IEEE Transactions on Network and Service Management 20:3, pages 2489-2503.
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Themistoklis Koutsellis, Alexandros Nikas, Stylianos Choumas, Christopher Ververidis, Thomas Papapolyzos, Anastasios Bitsikas, Ioanna Makarouni & Haris Doukas. (2023) Exploring the Impact of the Signal-to-Noise Ratio Assumption on the Time Series Bootstrap Pairwise Dependence Hypothesis Test. Exploring the Impact of the Signal-to-Noise Ratio Assumption on the Time Series Bootstrap Pairwise Dependence Hypothesis Test.
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