Confidence Intervals for Model Parameters
# S3 method for tsgarch.estimate
confint(object, parm, level = 0.95, vcov_type = "H", ...)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%).
an object of class tsgarch.estimate.
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.
valid choices are “H” for using the analytic hessian for the bread, “OP” for the outer product of gradients, “QMLE” for the Quasi-ML sandwich estimator (Huber-White), and “NW” for the Newey-West adjusted sandwich estimator (a HAC estimator).
additional parameters passed to the Newey-West bandwidth function to determine the optimal lags.