Contingency Table Analysis Based on ML Fitting of MPH Models

Contingency table analysis is performed based on maximum likelihood (ML) fitting of multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models. See Lang (2004) and Lang (2005) for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood- based (cell- and link-specific) residuals; and cell probability and expected count estimates along with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood, score, power-divergence--confidence intervals for contingency table estimands, when table probabilities are potentially subject to equality constraints. For test-inversion intervals, see Lang (2008) and Zhu (2020) .


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1.3.0 by Qiansheng Zhu, 5 months ago

Browse source code at

Authors: Joseph B. Lang [aut] , Qiansheng Zhu [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports intervals, numDeriv, limSolve, methods

Suggests vcd, MASS

See at CRAN