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glsm

Saturated Model Log-Likelihood for Multinomial Outcomes

v0.0.0.6 · Jul 14, 2025 · MIT + file LICENSE

Description

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.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies dplyr ggplot2 VGAM plyr glsm

Version History

new 0.0.0.6 Mar 10, 2026