GCE

GCEstim: Generalized Cross Entropy linear models in R.

Recent/release notes

• Major updates.

Features

• Estimates linear regression coefficients using Generalized Cross Entropy.

Overview

GCEstim provides tools for estimating linear regression models using Generalized Cross Entropy (GCE) and related information-theoretic estimators. The package is particularly useful in situations involving multicollinearity, small sample sizes, ill-conditioned design matrices, or when prior information is available.

The package includes estimation, model selection, support-space construction, cross-validation, bootstrap inference, and diagnostic tools.

Examples

res.lmgce.v01 <-
  lmgce(
    formula = y ~ X001 + X002 + X003 + X004,
    data = dataThesis,
    boot.B = 100,
    boot.method = "residuals")

summary(res.lmgce.v01)
plot(res.lmgce.v01)

Installation

• Development version from Github:

devtools::install_github("jorgevazcabral/GCEstim",
                         build_vignettes = TRUE,
                         build_manual = TRUE,
                         dependencies=TRUE)

• Stable version from CRAN:

install.packages("GCEstim")

Development Status

GCEstim is under active development. Bug reports, feature requests, and pull requests are welcome through GitHub Issues.

Links

• CRAN: https://cran.r-project.org/package=GCEstim
• GitHub: https://github.com/jorgevazcabral/GCEstim
• Issues: https://github.com/jorgevazcabral/GCEstim/issues

References

Golan, Judge and Miller (1996). Maximum Entropy Econometrics.

Golan (2018). Foundations of Info-Metrics.

Cabral et al. (2025). GCEstim: Regression Coefficients Estimation Using the Generalized Cross Entropy.

Citation

In case you want / have to cite this package, please use citation('GCEstim') for citation information.