cellMR provides robust multivariate regression for casewise and cellwise outliers, missing data, and high dimensions, with cellBoot delivering asymptotically valid robust inference via indirect bootstrap.
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A framework connects separable-covariance functional data to matrix-variate MMCD estimation and linear-complexity Shapley decompositions to deliver robust and explainable outlier detection.
Cellwise outliers can contaminate over half the cases even at low proportions, necessitating specialized robust techniques for location, covariance, regression, PCA, and tensor data that differ from casewise approaches.
citing papers explorer
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Cellwise and Casewise Robust Multivariate Regression with Inference
cellMR provides robust multivariate regression for casewise and cellwise outliers, missing data, and high dimensions, with cellBoot delivering asymptotically valid robust inference via indirect bootstrap.
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Explainable Outlier Detection for Multivariate Functional Data
A framework connects separable-covariance functional data to matrix-variate MMCD estimation and linear-complexity Shapley decompositions to deliver robust and explainable outlier detection.
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Cellwise Outliers
Cellwise outliers can contaminate over half the cases even at low proportions, necessitating specialized robust techniques for location, covariance, regression, PCA, and tensor data that differ from casewise approaches.