# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "glsm" in publications use:' type: software license: MIT title: 'glsm: Saturated Model Log-Likelihood for Multinomial Outcomes' version: 0.0.0.6 identifiers: - type: doi value: 10.32614/CRAN.package.glsm abstract: 'When the response variable Y takes one of R > 1 values, the function ''glsm()'' computes the maximum likelihood estimates (MLEs) of the parameters under four models: null, complete, saturated, and logistic. It also calculates the log-likelihood values for each model. This method assumes independent, non-identically distributed variables. For grouped data with a multinomial outcome, where observations are divided into J populations, the function ''glsm()'' provides estimation for any number K of explanatory variables.' authors: - family-names: Villalba given-names: Jorge email: jvillalba@utb.edu.co orcid: https://orcid.org/0000-0002-2888-9660 - family-names: Llinas given-names: Humberto email: hllinas@uninorte.edu.co orcid: https://orcid.org/0000-0002-2976-5109 - family-names: Borja given-names: Jorge email: jborjaa@uninorte.edu.co orcid: https://orcid.org/0009-0006-4824-5199 - family-names: Tilano given-names: Jorge email: jtilano@uninorte.edu.co orcid: https://orcid.org/0009-0005-5793-4183 preferred-citation: type: manual title: 'glsm: Estimation of the Log-Likelihood in the Saturated Model When the Response Variable Takes One of R > 1 Values' authors: - family-names: LlinĂ¡s given-names: Humberto J. - family-names: Villalba given-names: Jorge L. - family-names: Borja given-names: Jorge A. - family-names: Tilano given-names: Jorge J. year: '2025' notes: R package version 0.0.0.6 repository: https://cran.r-universe.dev commit: b8569e9f4a2c7446dcd1799ca901d0533dfed8da date-released: '2025-07-09' contact: - family-names: Villalba given-names: Jorge email: jvillalba@utb.edu.co orcid: https://orcid.org/0000-0002-2888-9660