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Author Correction: Genetics of 35 blood and urine biomarkers in the UK Biobank.
Sinnott-Armstrong N, Tanigawa Y, Amar D, Mars N, Benner C, Aguirre M, Venkataraman GR, Wainberg M, Ollila HM, Kiiskinen T, Havulinna AS, Pirruccello JP, Qian J, Shcherbina A; FinnGen; Rodriguez F, Assimes TL, Agarwala V, Tibshirani R, Hastie T, Ripatti S, Pritchard JK, Daly MJ, Rivas MA. Sinnott-Armstrong N, et al. Among authors: tibshirani r. Nat Genet. 2021 Nov;53(11):1622. doi: 10.1038/s41588-021-00956-2. Nat Genet. 2021. PMID: 34608296 No abstract available.
Flexible covariate effects in the proportional hazards model.
Hastie T, Sleeper L, Tibshirani R. Hastie T, et al. Among authors: tibshirani r. Breast Cancer Res Treat. 1992;22(3):241-50. doi: 10.1007/BF01840837. Breast Cancer Res Treat. 1992. PMID: 1391990 Clinical Trial.
Generalized additive models for medical research.
Hastie T, Tibshirani R. Hastie T, et al. Among authors: tibshirani r. Stat Methods Med Res. 1995 Sep;4(3):187-96. doi: 10.1177/096228029500400302. Stat Methods Med Res. 1995. PMID: 8548102
Supervised harvesting of expression trees.
Hastie T, Tibshirani R, Botstein D, Brown P. Hastie T, et al. Among authors: tibshirani r. Genome Biol. 2001;2(1):RESEARCH0003. doi: 10.1186/gb-2001-2-1-research0003. Epub 2001 Jan 10. Genome Biol. 2001. PMID: 11178280 Free PMC article.
Missing value estimation methods for DNA microarrays.
Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB. Troyanskaya O, et al. Among authors: tibshirani r. Bioinformatics. 2001 Jun;17(6):520-5. doi: 10.1093/bioinformatics/17.6.520. Bioinformatics. 2001. PMID: 11395428
Regularized linear discriminant analysis and its application in microarrays.
Guo Y, Hastie T, Tibshirani R. Guo Y, et al. Among authors: tibshirani r. Biostatistics. 2007 Jan;8(1):86-100. doi: 10.1093/biostatistics/kxj035. Epub 2006 Apr 7. Biostatistics. 2007. PMID: 16603682
This method generalizes the idea of the "nearest shrunken centroids" (NSC) (Tibshirani and others, 2003) into the classical discriminant analysis. The SCRDA method is specially designed for classification problems in high dimension low sample size situations, for example, …
This method generalizes the idea of the "nearest shrunken centroids" (NSC) (Tibshirani and others, 2003) into the classical discrimin …
339 results