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http://purl.uniprot.org/citations/26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://purl.uniprot.org/core/Journal_Citation
http://purl.uniprot.org/citations/26761909http://www.w3.org/2000/01/rdf-schema#comment"We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly)."xsd:string
http://purl.uniprot.org/citations/26761909http://purl.org/dc/terms/identifier"doi:10.1109/jbhi.2016.2515993"xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/author"Bayar B."xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/author"Bouaynaya N."xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/author"Shterenberg R."xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/date"2017"xsd:gYear
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/name"IEEE J Biomed Health Inform"xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/pages"573-581"xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/title"SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation."xsd:string
http://purl.uniprot.org/citations/26761909http://purl.uniprot.org/core/volume"21"xsd:string
http://purl.uniprot.org/citations/26761909http://www.w3.org/2004/02/skos/core#exactMatchhttp://purl.uniprot.org/pubmed/26761909
http://purl.uniprot.org/citations/26761909http://xmlns.com/foaf/0.1/primaryTopicOfhttps://pubmed.ncbi.nlm.nih.gov/26761909
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http://purl.uniprot.org/uniprot/#_A4V1N8-mappedCitation-26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/26761909
http://purl.uniprot.org/uniprot/#_A4V1N9-mappedCitation-26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/26761909
http://purl.uniprot.org/uniprot/#_B9EQV5-mappedCitation-26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/26761909
http://purl.uniprot.org/uniprot/#_E1JJP0-mappedCitation-26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/26761909
http://purl.uniprot.org/uniprot/#_M9MSG3-mappedCitation-26761909http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/26761909