predict(type = "response") with
alpha = NULL now returns the conditional mean loss rate
(the effective PD), Phi(qnorm(p) + sum kappa_j u_j),
matching the convention of predict.glm(). Previously it
returned pnorm() of the linear predictor, which is the
conditional median; that quantity is now available via
alpha = 0.5.vcov(), confint(), and
summary() gain a type argument.
type = "HAC" computes heteroskedasticity- and
autocorrelation-consistent standard errors via
sandwich::lrvar(); extra arguments are forwarded to it. The
default type = "iid" is unchanged. sandwich is
a suggested dependency.
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