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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.

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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.

GCE