REGULARISASI REGRESI LINIER BERGANDA PADA DATA BERDIMENSI TINGGI UNTUK MENGATASI EFEK MULTIKOLINEARITAS
Abstract
Keywords
Full Text:
PDF (Bahasa Indonesia)References
Amaratunga, D., & Cabrera, J. (2016). High-dimensional data. 44(1), 3–9.
Bickel, P. J., & Li, B. (2006). Regularization in statistics. Test, 15(2), 271–344. https://doi.org/10.1007/BF02607055
Hastie, T., Tibshirani, R., Hastie, M. W., Tibshirani, @bullet, & Wainwright, @bullet. (2016). Statistical Learning with Sparsity Monographs on Statistics and Applied Probability 143 143 copy to come from copywriter for review. Crc, 362.
Hussain, J. N. (2020). High dimensional data challenges in estimating multiple linear regression. Journal of Physics: Conference Series, 1591(1). https://doi.org/10.1088/1742-6596/1591/1/012035
James, G., Witten, & R, T. (2013). An Introduction Learning with Applications in R. Springer.
Jiawei Han, M. K. and J. P. (2012). Data Mining: Concepts and Techniques (Third Edit). Morgan Kaufmann. https://doi.org/https://doi.org/10.1016/C2009-0-61819-5
Kim, Y., Hao, J., Mallavarapu, T., Park, J., & Kang, M. (2019). Hi-LASSO: High-Dimensional LASSO. IEEE Access, 7, 44562–44573. https://doi.org/10.1109/ACCESS.2019.2909071
Pourahmadi, M. (2013). High-Dimensional Covariance Estimation (D. J. et al Balding (ed.)). Wiley.
DOI: https://doi.org/10.30743/mes.v10i1.9469
Refbacks
- There are currently no refbacks.