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Iterative Least Square Estimation or Full Information Maximum Likelihood Estimation for Linear Regression When Data Include Missing Values.

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ILSE

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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:

Huazhen Lin, Wei Liu, & Wei Lan (2021). Regression Analysis with individual-specific patterns of missing covariates. Journal of Business & Economic Statistics, 39(1), 179-188.

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")

Usage

For usage examples and guided walkthroughs, check the vignettes directory of the repo.

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.

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Iterative Least Square Estimation or Full Information Maximum Likelihood Estimation for Linear Regression When Data Include Missing Values.

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