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Partial sufficient variable screening, which aims to reduce the predictive set of primary interest without loss of regression information in the presence of ...
The method provides for detecting nonrelevant predictor variables and collaps ing the table over them. The procedure is applied to data presented by van Alstyne ...
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Abstract: Variable screening for ultrahigh-dimensional data has attracted extensive attention in the past decade. In many applications, researchers.
May 26, 2023 · Variable screening as a fast and effective dimension reduction tool plays an important role in analyzing ultrahigh dimensional data.
In this paper, we propose a model-free variable screening paradigm that allows for high-dimensional controls and applies to either continuous or categorical ...
In this paper, a novel two-stage sufficient variable screening procedure, especially when the response is categorical is proposed. This procedure is very ...
We propose two sufficient variable selection procedures, i.e., one- and two-stage approaches using independence measures for continuous response, ...
Dec 14, 2023 · The paper is about partial sufficient variable screening with categorical controls. The provided paper does not mention the PHQ variable.
controls were simulated. SNPs with MAF less than 0.01 were removed. This left around 280. SNPs in the fine mapping region. The simulation study was designed ...
Oct 18, 2023 · Hello, I am building a partial least squares (PLS) model with categorical independent variables. I understand that the CLASS statement is useful ...
Missing: sufficient screening controls.