Description
Linear Regression Based on 'ILSE' for Missing Data.
Description
Linear regression when covariates include missing values by embedding the correlation information between covariates. Especially for block missing data, it works well. 'ILSE' conducts imputation and regression simultaneously and iteratively. More details can be referred to Huazhen Lin, Wei Liu and Wei Lan. (2021) <doi:10.1080/07350015.2019.1635486>.
README.md
ILSE
Linear Regression by Iterative Least Square Estimation When Covariates Include Missing Values. In ILSE package, we also provide Full Information Maximum Likelihood for Linear Regression fimlreg that can handle missing Covariates or missing Response variables.
Please see our new paper for model details:
Installation
To install the the packages 'ILSE' from 'Github', firstly, install the 'remotes' package.
install.packages("remotes")
remotes::install_github("feiyoung/ILSE")
Or install the the packages "ILSE" from 'CRAN'
install.packages("ILSE")
Website of ILSE package
We set up a package website to illustrate the usage of this package. For examples of typical ILSE usage, please see our Package Website for a demonstration and overview of the functions included in ILSE.