{"doi":"10.1007/978-3-0348-8201-9_26","title":"Multivariate Trimmed Means Based on Data Depth","abstract":null,"journal":"Statistical Data Analysis Based on the L1-Norm and Related Methods","year":2002,"id":605778,"datarank":0.31191623125197543,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.0,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1554801,"name":"Yijun Zuo","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Multivariate Trimmed Means Based on Data Depth","abstract":"Multivariate analogues of the univariate median have been successfully introduced based on data depth. Like their univariate counterpart, these multivariate medians in general are quite robust but not very efficient. Univariate trimmed means, which can keep a desirable balance between robustness and efficiency, are known to be the alternatives to the univariate median. Multivariate analogues of univariate trimmed means can also be introduced based on data depth. In this article, we study multivariate depth trimmed means with a main focus on their limiting distribution, robustness, and efficiency.","is_dataset_classified":null,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"23304386","pmcid":null,"openalex_id":"https://openalex.org/W2176526134","authors":[],"funders":[],"total_grants":0,"fwci":1.5196,"citation_percentile":0.83383085,"influential_citations":0,"citation_trend":[{"year":2012,"count":1},{"year":2015,"count":1},{"year":2021,"count":1},{"year":2025,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://link.springer.com/content/pdf/10.1007/978-3-0348-8201-9_26","host_type":"publisher"},{"url":"https://doi.org/10.1007/978-3-0348-8201-9_26","host_type":"ebook platform"}],"fields_of_study":["Advanced Statistical Methods and Models","Advanced Statistical Process Monitoring","Advanced Measurement and Detection Methods"],"mesh_terms":[],"keywords":["Univariate","Multivariate statistics","Truncated mean","Multivariate analysis","Robustness (evolution)","Statistics","Univariate analysis","Computer science","Limiting","Mathematics","Engineering","Chemistry"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-30T03:13:14.603081Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}