Stein-rule M-estimation in sparse partially linear models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s42081-023-00231-0.pdf
Reference24 articles.
1. Ahmed, S. E. (2014). Penalty, Shrinkage and Pretest Strategies: Variable Selection and Estimation. New York, USA: Springer.
2. Ahmed, S. E., Ahmed, F., & Yüzbaşı, B. (2023). Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data. Boca Raton, USA: CRC Press.
3. Ahmed, S. E., Doksum, K. A., Hossain, S., & You, J. (2007). Shrinkage, pretest and absolute penalty estimators in partially linear models. Australian & New Zealand Journal of Statistics, 49, 435–454.
4. Ahmed, S. E., & Fallahpour, S. (2012). Shrinkage estimation strategy in quasi-likelihood models. Statistics & Probability Letters, 82(12), 2170–2179.
5. Ahmed, S. E., Hussein, A. A., & Sen, P. K. (2006). Risk comparison of some shrinkage M-estimators in linear models. Nonparametric Statistics, 18, 401–415.
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