| se {gnm} | R Documentation |
Computes approximate standard errors for (a selection of) individual
parameters or one or more linear combinations of the parameters in a
gnm (generalized nonlinear model) object. By default, a
check is made first on the estimability of each specified combination.
se(model, estimate = ofInterest(model), checkEstimability = TRUE, Vcov = NULL, dispersion = NULL, ...)
model |
a model object of class "gnm". |
estimate |
(optional) specifies parameters or linear
combinations of parameters for which to find standard errors. In the
first case either a character vector of names, a
numeric vector of indices or "[?]" to select from a Tk
dialog. In the second case coefficients given as a vector or the
rows of a matrix, such that NROW(estimate) is equal to
length(coef(model)) or length(coef(model)) -
model$eliminate. If missing, standard errors are returned for all
parameters in the model. |
checkEstimability |
logical: should the estimability of all specified combinations be checked? |
Vcov |
either NULL, or a matrix |
dispersion |
either NULL, or a positive number |
... |
possible further arguments for
checkEstimable. |
A data frame with two columns:
Estimate |
The estimated parameter combinations |
Std. Error |
Their estimated standard errors |
If available, the column names of coefMatrix will be used to name
the rows.
In the case where estimate is a numeric vector, se will
assume that indices have been specified if all the values of
estimate are in seq(length(coef(model)).
Where both Vcov and dispersion are supplied, the
variance-covariance matrix of estimated model coefficients is taken to
be Vcov * dispersion.
David Firth
gnm, getContrasts,
checkEstimable, ofInterest
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),
ofInterest = "[.]educ", family = poisson,
data = yaish, subset = (dest != 7))
## Deviance is 200.3
## Get estimate and se for the contrast between educ4 and educ5 in the
## UNIDIFF multiplier
mycontrast <- numeric(length(coef(unidiff)))
mycontrast[ofInterest(unidiff)[4:5]] <- c(1, -1)
se(unidiff, mycontrast)
## Get all of the contrasts with educ5 in the UNIDIFF multipliers
getContrasts(unidiff, rev(ofInterest(unidiff)))