checkEstimable {gnm} | R Documentation |
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.
checkEstimable(model, combMatrix = diag(seq(along = coef(model))), tolerance = 1e6 * .Machine$double.eps)
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. |
A logical vector of length equal to the number of parameter combinations
tested; NA
where a parameter combination is identically zero.
David Firth
Catchpole, E.A. and Morgan, B.J.T. (1997). Detecting parameter redundancy. Biometrika, 84, 187–196.
data(yaish) 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