% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/svp_internal.R
\name{.add_leverage}
\alias{.add_leverage}
\title{Add leverage estimation to a fitted SV(p) model (post-processing)
Works for all error distributions: Gaussian, Student-t, GED.
- Gaussian: closed form (C_F = 1)
- Student-t: closed form with C_t(nu) correction
- GED: exact 1D root-finding via uniroot + Gauss-Hermite quadrature}
\usage{
.add_leverage(out, y, p, rho_type, del, trunc_lev, wDecay, errorType)
}
\arguments{
\item{out}{Model object from .svp_gaussian/.svp_t/.svp_ged (without leverage)}

\item{y}{Numeric vector of observations}

\item{p}{AR order}

\item{rho_type}{"pearson", "kendall", or "both"}

\item{del}{Small constant for log transform}

\item{trunc_lev}{Logical: truncate rho to [-0.999, 0.999]}

\item{wDecay}{Logical: decaying weights (passed from original estimation)}

\item{errorType}{"Gaussian", "Student-t", or "GED"}
}
\value{
Updated model object with leverage fields added
}
\description{
Add leverage estimation to a fitted SV(p) model (post-processing)
Works for all error distributions: Gaussian, Student-t, GED.
- Gaussian: closed form (C_F = 1)
- Student-t: closed form with C_t(nu) correction
- GED: exact 1D root-finding via uniroot + Gauss-Hermite quadrature
}
\keyword{internal}
