R: Inverts a marginal log-linear parametrization

binve {ggm} | R Documentation

## Inverts a marginal log-linear parametrization

### Description

Inverts a marginal log-linear parametrization.

### Usage

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

### Arguments

`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`.

### Details

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

### Value

A vector of probabilities `p`.

### Note

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

### Author(s)

Antonio Forcina, Giovanni M. Marchetti

### References

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.

### See Also

`mat.mlogit`

[Package ggm version 2.3 Index]