Model validation and influence diagnostics for regression models with missing covariates.
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DOI: 10.1002/sim.7584
Abstract: Missing covariate values are prevalent in regression applications. While an array of methods have been developed for estimating parameters in regression models with missing covariate data for a variety of response types, minimal focus has… read more here.
Keywords: regression; validation; regression models; missing covariates ... See more keywords
Testing for parametric component of partially linear models with missing covariates
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DOI: 10.1007/s00362-016-0848-6
Abstract: This paper considers the testing problem of partially linear models with missing covariates. The inverse probability weighted restricted estimator for the parametric component under linear constraint is derived and proven to share asymptotically normal distribution.… read more here.
Keywords: parametric component; partially linear; linear models; missing covariates ... See more keywords
Modified Multi-Direction Iterative Algorithm for Separable Nonlinear Models With Missing Data
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DOI: 10.1109/lsp.2022.3204408
Abstract: Multi-direction iterative (MUL-DI) algorithm is an efficient algorithm for large-scale models, and it establishes a theoretical linkage between least squares (LS) and gradient descent (GD) algorithms. However, it involves Givens transformation and dense matrix calculation… read more here.
Keywords: models missing; direction iterative; algorithm; separable nonlinear ... See more keywords