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Li, Runze
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Biometrics
Journal of the American Statistical Association : JASA
21
Journal of the American Statistical Association
13
Computational Statistics & Data Analysis
9
Discussion papers of interdisciplinary research project 373
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Econometric theory
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Journal of econometrics
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Discussion paper / Humboldt-Universität zu Berlin, Sonderforschungsbereich 373 Quantifikation und Simulation Ökonomischer Prozesse
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Journal of Business & Economic Statistics
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Journal of Time Series Analysis
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The journal of technology transfer
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China political economy
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Discussion Papers / Department of Economics and Related Studies, University of York
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Econometric Theory
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Journal of Applied Statistics
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Macroeconomic forecasting in the era of big data : theory and practice
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Efficient Statistical Inference Procedures for Partially Nonlinear Models and their Applications
Li, Runze
;
Nie, Lei
- In:
Biometrics
64
(
2008
)
3
,
pp. 904-911
Persistent link: https://www.econbiz.de/10010947299
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2
Weighted Wilcoxon-Type Smoothly Clipped Absolute Deviation Method
Wang, Lan
;
Li, Runze
- In:
Biometrics
65
(
2009
)
2
,
pp. 564-571
Persistent link: https://www.econbiz.de/10010948361
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3
Quadratic Inference Functions for Varying-Coefficient Models with Longitudinal Data
Qu, Annie
;
Li, Runze
- In:
Biometrics
62
(
2006
)
2
,
pp. 379-391
Persistent link: https://www.econbiz.de/10010948535
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4
Prediction-Based Structured Variable Selection through the Receiver Operating Characteristic Curves
Wang, Yuanjia
;
Chen, Huaihou
;
Li, Runze
;
Duan, Naihua
; …
- In:
Biometrics
67
(
2011
)
3
,
pp. 896-905
Persistent link: https://www.econbiz.de/10011036115
Saved in:
5
Partially Linear Structure Selection in Cox Models with Varying Coefficients
Lian, Heng
;
Lai, Peng
;
Liang, Hua
- In:
Biometrics
69
(
2013
)
2
,
pp. 348-357
Persistent link: https://www.econbiz.de/10010683880
Saved in:
6
Two-Component Mixture Cure Rate Model with Spline Estimated Nonparametric Components
Wang, Lu
;
Du, Pang
;
Liang, Hua
- In:
Biometrics
68
(
2012
)
3
,
pp. 726-735
Persistent link: https://www.econbiz.de/10010684073
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