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BlockMissingData  

Integrating Multi-Source Block-Wise Missing Data in Model Selection
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BlockMissingData", "0.1.0")



Attach the package and use:
library("BlockMissingData")
Maintained by
Fei Xue
[Scholar Profile | Author Map]
First Published: 2023-09-12
Latest Update: 2023-09-12
Description:
Model selection method with multiple block-wise imputation for block-wise missing data; see Xue, F., and Qu, A. (2021) .
How to cite:
Fei Xue (2023). BlockMissingData: Integrating Multi-Source Block-Wise Missing Data in Model Selection. R package version 0.1.0, https://cran.r-project.org/web/packages/BlockMissingData. Accessed 10 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited BlockMissingData R package
View BlockMissingData citation profile
Other R packages that BlockMissingData depends, imports, suggests or enhances
Complete documentation for BlockMissingData
Functions, R codes and Examples using the BlockMissingData R package
Some associated functions: MBI . imputeglm.predict . 
Some associated R codes: MBI.R . imputeglm.predict.R .  Full BlockMissingData package functions and examples
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