Results 181 to 190 of about 2,014 (224)

Rapid dynamics of dorsal raphe serotonin neurons regulate the strength of visual attention. [PDF]

Nat Commun
Lehnert J, Cha K, Forestell J, Yang K, Ma X, Shariff S, Britt JP, Khadra A, Cook EP, Krishnaswamy A.   +9 more
europepmc   +1 more source

Relaxed Doubly Robust Estimation in Causal Inference. [PDF]

Stat Theory Relat Fields
Xu T, Zhao J.
europepmc   +1 more source

Testing an inverse link between limbic alpha-synucleinopathy and myelin markers in mice and humans. [PDF]

NPJ Parkinsons Dis
Clark RN, Landes RE, Abbas M, Mistretta VG, Jhaveri JR, DeLoatch KA, Franks J, Chen J, Luk KC, Hu X, Leak RK.   +10 more
europepmc   +1 more source

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Sparse Sliced Inverse Regression

Technometrics, 2006
Sliced inverse regression (SIR) is an innovative and effective method for dimension reduction and data visualization of high-dimensional problems. It replaces the original variables with low-dimensional linear combinations of predictors without any loss of regression information and without the need to prespecify a model or an error distribution ...
Lexin Li, Christopher J Nachtsheim
exaly   +2 more sources

Graph informed sliced inverse regression

Computational Statistics and Data Analysis, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andreas Artemiou, Eugen Pircalabelu
exaly   +2 more sources

Sliced Inverse Regression with Regularizations

Biometrics, 2008
SummaryIn high‐dimensional data analysis, sliced inverse regression (SIR) has proven to be an effective dimension reduction tool and has enjoyed wide applications. The usual SIR, however, cannot work with problems where the number of predictors,p, exceeds the sample size,n, and can suffer when there is high collinearity among the predictors.
Lexin Li
exaly   +4 more sources

On the optimality of sliced inverse regression in high dimensions [PDF]

Annals of Statistics, 2021
The central subspace of a pair of random variables $(y,x) \in \mathbb{R}^{p+1}$ is the minimal subspace $\mathcal{S}$ such that $y \perp \hspace{-2mm} \perp x\mid P_{\mathcal{S}}x$. In this paper, we consider the minimax rate of estimating the central space of the multiple index models $y=f(β_{1}^τx,β_{2}^τx,...,β_{d}^τx,ε)$ with at most $s$ active ...
Xinran Li, Jun S Liu, Dongming Huang
exaly   +7 more sources

An Asymptotic Theory for Sliced Inverse Regression

Annals of Statistics, 1992
Sliced inverse regression is a nonparametric method for achieving dimension reduction in regression problems. It is assumed that the conditional distribution of response \(Y\) given predictors \(X\) depends only on \(K\) linear combinations of \(X\).
, Tailen Hsing
exaly   +3 more sources

Fréchet kernel sliced inverse regression

Journal of Multivariate Analysis, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yushen Dong, Yichao Wu
openaire   +1 more source