Computes confidence intervals for one or more parameters in
a fitted model object, resulting from a
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
the confidence level required.
additional argument(s) passed to
Calculates confidence intervals for model parameters assuming
asymptotic normality and using the result from
As such, if the MLE is on the boundary of the parameter space,
object$boundary) the normality assumption
is invalid and
NA is returned.
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1-(1-level)/2 in % (by default 2.5% and 97.5%).
Mark W. Donoghoe email@example.com
## For an example, see example(logbin)
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