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pmlsp: Partial Maximum Likelihood Estimation of Spatial Probit Models

Estimate spatial autoregressive nonlinear probit models with and without autoregressive disturbances using partial maximum likelihood estimation. Estimation and inference regarding marginal effects is also possible. For more details see Bille and Leorato (2020) <doi:10.1080/07474938.2019.1682314>.

Version: 1.0.1
Depends: R (≥ 3.5)
Imports: abind, Matrix, matrixcalc, maxLik, methods, minqa, mvtnorm, numDeriv, qrng, spatialreg, spdep, stats, utils
Suggests: testthat (≥ 3.0.0)
Published: 2026-01-31
DOI: 10.32614/CRAN.package.pmlsp (may not be active yet)
Author: Daniele Spinelli [aut, cre], Anna Gloria Bille' [aut], Samantha Leorato [aut]
Maintainer: Daniele Spinelli <daniele.spinelli at unimib.it>
BugReports: https://github.com/d-spinelli/pmlsp/issues
License: GPL (≥ 3)
URL: https://github.com/d-spinelli/pmlsp
NeedsCompilation: no
CRAN checks: pmlsp results

Documentation:

Reference manual: pmlsp.html , pmlsp.pdf

Downloads:

Package source: pmlsp_1.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: pmlsp_1.0.1.zip, r-oldrel: not available
macOS binaries: r-release (arm64): pmlsp_1.0.1.tgz, r-oldrel (arm64): pmlsp_1.0.1.tgz, r-release (x86_64): pmlsp_1.0.1.tgz, r-oldrel (x86_64): pmlsp_1.0.1.tgz

Linking:

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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.