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Theory of angular depth for classification of directional data
Stanislav Nagy, Houyem Demni, Davide Buttarazzi and Giovanni C. Porzio Advances in Data Analysis and Classification 18(3) 627 (2024) https://doi.org/10.1007/s11634-023-00557-3
Depth-based reconstruction method for incomplete functional data
Integrated Depths for Partially Observed Functional Data
Antonio Elías, Raúl Jiménez, Anna M. Paganoni and Laura M. Sangalli Journal of Computational and Graphical Statistics 32(2) 341 (2023) https://doi.org/10.1080/10618600.2022.2070171
A high dimensional functional time series approach to evolution outlier detection for grouped smart meters
Detecting and classifying outliers in big functional data
Oluwasegun Taiwo Ojo, Antonio Fernández Anta, Rosa E. Lillo and Carlo Sguera Advances in Data Analysis and Classification 16(3) 725 (2022) https://doi.org/10.1007/s11634-021-00460-9
On depth-based fuzzy trimmed means and a notion of depth specifically defined for fuzzy numbers
Evaluating Proxy Influence in Assimilated Paleoclimate Reconstructions—Testing the Exchangeability of Two Ensembles of Spatial Processes
Trevor Harris, Bo Li, Nathan J. Steiger, Jason E. Smerdon, Naveen Narisetty and J. Derek Tucker Journal of the American Statistical Association 116(535) 1100 (2021) https://doi.org/10.1080/01621459.2020.1799810
Flexible integrated functional depths
Stanislav Nagy, Sami Helander, Germain Van Bever, Lauri Viitasaari and Pauliina Ilmonen Bernoulli 27(1) (2021) https://doi.org/10.3150/20-BEJ1254
A Decomposition of Total Variation Depth for Understanding Functional Outliers
GENERALIZED EXPONENTIAL SMOOTHING IN PREDICTION OF HIERARCHICAL TIME SERIES
Daniel Kosiorowski, Dominik Mielczarek, Jerzy P. Rydlewski and Małgorzata Snarska Statistics in Transition New Series 19(2) 331 (2018) https://doi.org/10.21307/stattrans-2018-019
Depth-Based Recognition of Shape Outlying Functions