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Efficient global approximation of generalized nonlinear l1-regularized solution paths and its applications
Yuan, Ming
;
Zou, Hui
- In:
Journal of the American Statistical Association : JASA
104
(
2009
)
488
,
pp. 1562-1574
Persistent link: https://www.econbiz.de/10003993050
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2
Hidden Markov models for microarray time course data in multiple biological conditions
Yuan, Ming
;
Kendziorski, Christina
- In:
Journal of the American Statistical Association : JASA
101
(
2006
),
pp. 1323-1334
Persistent link: https://www.econbiz.de/10003406566
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3
Efficient empirical bayes variable selection and estimation in linear models
Yuan, Ming
;
Forrest, Jeffrey Yi-Lin
- In:
Journal of the American Statistical Association : JASA
100
(
2005
)
472
,
pp. 1215-1225
Persistent link: https://www.econbiz.de/10003241605
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4
Theory and Methods - Efficient Empirical Bayes Variable Selection and Estimation in Linear Models
Yuan, Ming
;
Lin, Yi
- In:
Journal of the American Statistical Association : JASA
100
(
2005
)
472
,
pp. 1215-1225
Persistent link: https://www.econbiz.de/10006605493
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5
Applications and Case Studies - Rejoinder - Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions
Yuan, Ming
;
Kendziorski, Christina
- In:
Journal of the American Statistical Association : JASA
101
(
2006
)
476
,
pp. 1338-1340
Persistent link: https://www.econbiz.de/10007398024
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6
Applications and Case Studies - Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions
Yuan, Ming
;
Kendziorski, Christina
- In:
Journal of the American Statistical Association : JASA
101
(
2006
)
476
,
pp. 1323-1331
Persistent link: https://www.econbiz.de/10007398027
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7
Minimax and Adaptive Prediction for Functional Linear Regression
Cai, T. Tony
;
Yuan, Ming
- In:
Journal of the American Statistical Association : JASA
107
(
2012
)
499
,
pp. 1201-1217
Persistent link: https://www.econbiz.de/10010028431
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8
Maximum Likelihood Estimation of the Multivariate Normal Mixture Model
Yuan, Ming
;
Zou, Hui
- In:
Journal of the American Statistical Association : JASA
104
(
2009
)
488
,
pp. 1539-1550
Persistent link: https://www.econbiz.de/10008376193
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