Variable screening using factor analysis for high-dimensional data with multicollinearity
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866915577689276416 |
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| author | Tanaka, Shuntaro Matsui, Hidetoshi |
| author_facet | Tanaka, Shuntaro Matsui, Hidetoshi |
| contents | Screening methods are useful tools for variable selection in regression analysis when the number of predictors is much larger than the sample size. Factor analysis is used to eliminate multicollinearity among predictors, which improves the variable selection performance. We propose a new method, called Truncated Preconditioned Profiled Independence Screening (TPPIS), that better selects the number of factors to eliminate multicollinearity. The proposed method improves the variable selection performance by truncating unnecessary parts from the information obtained by factor analysis. We confirmed the superior performance of the proposed method in variable selection through analysis using simulation data and real datasets. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2306_05702 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Variable screening using factor analysis for high-dimensional data with multicollinearity Tanaka, Shuntaro Matsui, Hidetoshi Methodology Computation 62J05, 62J07 G.3 Screening methods are useful tools for variable selection in regression analysis when the number of predictors is much larger than the sample size. Factor analysis is used to eliminate multicollinearity among predictors, which improves the variable selection performance. We propose a new method, called Truncated Preconditioned Profiled Independence Screening (TPPIS), that better selects the number of factors to eliminate multicollinearity. The proposed method improves the variable selection performance by truncating unnecessary parts from the information obtained by factor analysis. We confirmed the superior performance of the proposed method in variable selection through analysis using simulation data and real datasets. |
| title | Variable screening using factor analysis for high-dimensional data with multicollinearity |
| topic | Methodology Computation 62J05, 62J07 G.3 |
| url | https://arxiv.org/abs/2306.05702 |