A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates
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DOI: 10.1007/s00362-018-1013-1
Abstract: In this paper, a new robust and efficient estimation approach based on local modal regression is proposed for partially linear models with large-dimensional covariates. We show that the resulting estimators for both parametric and nonparametric… read more here.
Keywords: large dimensional; efficient estimation; robust efficient; models large ... See more keywords
Theoretical Performance of Low Rank Adaptive Filters in the Large Dimensional Regime
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DOI: 10.1109/taes.2019.2906418
Abstract: This paper proposes a new approximation of the theoretical signal to interference plus noise ratio (SINR) loss of the low-rank (LR) adaptive filter built on the eigenvalue decomposition of the sample covariance matrix. This new… read more here.
Keywords: large dimensional; low rank; rank adaptive; dimensional regime ... See more keywords
Risk Convergence of Centered Kernel Ridge Regression With Large Dimensional Data
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DOI: 10.1109/tsp.2020.2975939
Abstract: This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call centered kernel ridge regression (CKRR), also known in the literature as kernel ridge regression with offset. This… read more here.
Keywords: regression; risk; large dimensional; kernel ridge ... See more keywords