scholarly journals Sliced Inverse Regression for High-dimensional Time Series

2003 ◽  
pp. 3-11 ◽  
Author(s):  
C. Becker ◽  
R. Fried
Keyword(s):  
Time Series ◽  
Sliced Inverse Regression ◽  
High Dimensional ◽  
Inverse Regression

On Sliced Inverse Regression With High-Dimensional Covariates

2006 ◽  
Vol 101 (474) ◽  
pp. 630-643 ◽  
Author(s):  
Lixing Zhu ◽  
Baiqi Miao ◽  
Heng Peng
Keyword(s):  
Sliced Inverse Regression ◽  
High Dimensional ◽  
Inverse Regression

scholarly journals Analysis of microarray right-censored data through fused sliced inverse regression

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jae Keun Yoo
Keyword(s):  
Dimension Reduction ◽  
Censored Data ◽  
Sliced Inverse Regression ◽  
High Dimensional ◽  
Sufficient Dimension Reduction ◽  
Inverse Regression ◽  
Right Censored Data ◽  
Practical Advantage ◽  
Linear Projection ◽  
Lower Dimensional

Abstract Sufficient dimension reduction (SDR) for a regression pursue a replacement of the original p-dimensional predictors with its lower-dimensional linear projection. The so-called sliced inverse regression (SIR; [5]) arguably has the longest history in SDR methodologies, but it is still one of the most popular one. The SIR is known to be easily affected by the number of slices, which is one of its critical deficits. Recently, a fused approach for SIR is proposed to relieve this weakness, which fuses the kernel matrices computed by the SIR application from various numbers of slices. In the paper, the fused SIR is applied to a large-p-small n regression of a high-dimensional microarray right-censored data to show its practical advantage over usual SIR application. Through model validation, it is confirmed that the fused SIR outperforms the SIR with any number of slices under consideration.

scholarly journals A convex formulation for high-dimensional sparse sliced inverse regression

Biometrika ◽  
2018 ◽  
Author(s):  
Kean Ming Tan ◽  
Zhaoran Wang ◽  
Tong Zhang ◽  
Han Liu ◽  
R Dennis Cook
Keyword(s):  
Sliced Inverse Regression ◽  
High Dimensional ◽  
Inverse Regression ◽  
Convex Formulation

scholarly journals Inference of breakpoints in high-dimensional time series

2021 ◽  
pp. 1-33
Author(s):  
Likai Chen ◽  
Weining Wang ◽  
Wei Biao Wu
Keyword(s):  
Time Series ◽  
High Dimensional

scholarly journals Time Series-Analysis Based Engineering of High-Dimensional Wide-Area Stability Indices for Machine Learning

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Raoult Teukam Dabou ◽  
Innocent Kamwa ◽  
C. Y. Chung ◽  
C. F. Mugombozi
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Time Series Analysis ◽  
Wide Area ◽  
High Dimensional ◽  
Series Analysis ◽  
Stability Indices
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