checkEstimable {gnm}

Check Whether One or More Parameter Combinations in a gnm Model are Identified

Description

For each of a specified set of linear combinations of parameters from a gnm model, checks numerically whether the combination's estimate is invariant to re-parameterization of the model.

Usage

checkEstimable(model, combMatrix = diag(length(coef(model))),
               tolerance = NULL)

Arguments

model

a model object of class "gnm"

combMatrix

numeric: either a vector of length the same as length(coef(model)), or a matrix with that number of rows. Coefficients of one or more linear combinations of the model's parameters.

tolerance

numeric: a threshold value for detection of non-estimability. If NULL, the default value of the tol argument to rankMatrix is used.

Value

A logical vector of length equal to the number of parameter combinations tested; NA where a parameter combination is identically zero.

Author(s)

David Firth and Heather Turner

References

Catchpole, E.A. and Morgan, B.J.T. (1997). Detecting parameter redundancy. Biometrika, 84, 187–196.

See Also

gnm, se.gnm, getContrasts

Examples

set.seed(1)

## Fit the "UNIDIFF" mobility model across education levels
unidiff <- gnm(Freq ~ educ*orig + educ*dest +
               Mult(Exp(educ), orig:dest), family = poisson,
               data = yaish, subset = (dest != 7))

## Check whether multiplier contrast educ4 - educ5 is estimable
ofInterest(unidiff) <- pickCoef(unidiff, "[.]educ")
mycontrast <- numeric(length(coef(unidiff)))
mycontrast[ofInterest(unidiff)[4:5]] <- c(1, -1)
checkEstimable(unidiff, mycontrast)
## should be TRUE

## Check whether multiplier educ4 itself is estimable
mycontrast[ofInterest(unidiff)[5]] <- 0
checkEstimable(unidiff, mycontrast)
## should be FALSE -- only *differences* are identified here