R: Link function of marginal log-linear parameterization

marg.param {ggm} | R Documentation

## Link function of marginal log-linear parameterization

### Description

Provides the contrast and marginalization matrices for the marginal parametrization of a probability vector.

### Usage

    marg.param(lev, type)

### Arguments

`lev` | Integer vector containing the number of levels of each variable.
`type` | A character vector with elements `"l"`, `"g"`, `"c"`, or `"r"` indicating the type of logit. The meaning is as follows: `"g"` for global, `"c"` for continuation, `"r"` for reverse continuation and `"l"` for local.

### Details

See Bartolucci, Colombi and Forcina (2007).

### Value

`C` | Matrix of constrasts (the first `sum(lev)-length(r)` elements are referred to univariate logits)
`M` | Marginalization matrix with elements 0 and 1.
`G` | Corresponding design matrix for the corresponding log-linear model.

### Note

Assumes that the vector of probabilities is in inv lex order. The interactions are returned in order of dimension, like e.g., 1, 2, 3, 12, 13, 23, 123.

### Author(s)

Francesco Bartolucci, 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`

### Examples

    marg.param(c(3,3), c("l", "g"))

[Package ggm version 2.3 Index]