binve: Inverts a marginal log-linear parametrization
In ggm: Graphical Markov Models with Mixed Graphs

Description Usage Arguments Details Value Note Author(s) References See Also

Inverts a marginal log-linear parametrization.

1	binve(eta, C, M, G, maxit = 500, print = FALSE, tol = 1e-10)

`eta`	a vector of dimension `t-1` where `t` is the number of cells of a contingency table.
`C`	A contrast matrix.
`M`	A marginalization matrix.
`G`	G is the model matrix of the loglinear parameterization with no constant term.
`maxit`	an integer, specifying the maximum number of iterations. Default 500.
`print`	a logical value: if `TRUE`, prints the criterion after each cycle.
`tol`	A small value specifying the tolerance for the convergence criterion. Default: `1e-10`.

A marginal log-linear link is defined by η = C (M \log p). See Bartolucci et al. (2007).

A vector of probabilities p.

From a Matlab function by A. Forcina, University of Perugia, Italy.

Antonio Forcina, Giovanni M. Marchetti

Bartolucci, F., Colombi, R. and Forcina, A. (2007). An extended class of marginal link functions for modelling contingency tables by equality and inequality constraints. Statist. Sinica 17, 691-711.

mat.mlogit

ggm documentation built on March 26, 2020, 7:49 p.m.