Learn R Programming

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:

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")

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.

Copy Link

Version

Install

install.packages('ILSE')

Monthly Downloads

53

Version

1.1.7

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Wei Liu

Last Published

January 31st, 2022

Functions in ILSE (1.1.7)

kern

Kernel Function
ilse

Linear Regression by Iterative Least Square Estimation
fimlreg

Full Information Maximum Likelihood Linear Regression
cov.mat

Generate Two Type of Covariance Matrix
print

Print the Information of FIML or ILSE methods
nhanes

NHANES example - all variables numerical
Coef

Extracts Regression Coefficients
cor.mat

Generate Two Type of Correlation Matrix
summary

Summarizing the inference information for ILSE or FIML methods