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Theory and Methods - Prediction by Supervised Principal Components
Bair, Eric; Hastie, Trevor; Paul, Debashis; Tibshirani, … - In: Journal of the American Statistical Association : JASA 101 (2006) 473, pp. 119-137
Persistent link: https://www.econbiz.de/10006604430
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Flexible Discriminant Analysis by Optimal Scoring
Hastie, Trevor; Tibshirani, Robert; Buja, Andreas - In: Journal of the American Statistical Association : JASA 89 (1994) 428, pp. 1255-1270
Persistent link: https://www.econbiz.de/10006636517
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SpurseNet: Coordinate Descent With Nonconvex Penalties
Mazumder, Rahul; Friedman, Jerome H; Hastie, Trevor - In: Journal of the American Statistical Association : JASA 106 (2011) 495, pp. 1125-1139
Persistent link: https://www.econbiz.de/10009797124
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Discussion - On Consistency and Sparsity for Principal Components Analysis in High Dimensions
Witten, Daniela M.; Hastie, Trevor; Tibshirani, Robert - In: Journal of the American Statistical Association : JASA 104 (2009) 486, pp. 698-699
Persistent link: https://www.econbiz.de/10008263765
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Improved semiparametric time series models of air pollution and mortality
Dominici, Francesca; McDermott, Aidan; Hastie, Trevor - In: Journal of the American Statistical Association : JASA 99 (2004) 468, pp. 938-948
Persistent link: https://www.econbiz.de/10002500441
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Prediction by supervised principal components
Bair, Eric; Hastie, Trevor; Paul, Debashis; Tibshirani, … - In: Journal of the American Statistical Association : JASA 101 (2006), pp. 119-137
Persistent link: https://www.econbiz.de/10003309492