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mixgb  

Multiple Imputation Through 'XGBoost'
View on CRAN: Click here


Download and install mixgb package within the R console
Install from CRAN:
install.packages("mixgb")

Install from Github:
library("remotes")
install_github("cran/mixgb")

Install by package version:
library("remotes")
install_version("mixgb", "2.2.3")



Attach the package and use:
library("mixgb")
Maintained by
Yongshi Deng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-07
Latest Update: 2025-04-06
Description:
Multiple imputation using 'XGBoost', subsampling, and predictive mean matching as described in Deng and Lumley (2023) . Our method utilizes the capabilities of XGBoost, a highly efficient implementation of gradient boosted trees, to capture interactions and non-linear relations automatically. Moreover, we have integrated subsampling and predictive mean matching to minimize bias and reflect appropriate imputation variability. This package supports various types of variables and offers flexible settings for subsampling and predictive mean matching. Additionally, it includes diagnostic tools for evaluating the quality of the imputed values.
How to cite:
Yongshi Deng (2022). mixgb: Multiple Imputation Through 'XGBoost'. R package version 2.2.3, https://cran.r-project.org/web/packages/mixgb. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1.0 (2022-06-07 10:40), 1.0.2 (2023-02-16 12:00), 1.5.2 (2024-12-02 10:20), 1.5.3 (2025-04-07 01:30), 2.0.3 (2025-12-07 12:30)
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Complete documentation for mixgb
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