% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/invgauss.R
\name{invgauss_lowercase}
\alias{invgauss_lowercase}
\alias{dinvgaussmix}
\alias{pinvgaussmix}
\alias{qinvgaussmix}
\alias{rinvgaussmix}
\alias{dinvgaussmixgpd}
\alias{pinvgaussmixgpd}
\alias{qinvgaussmixgpd}
\alias{rinvgaussmixgpd}
\alias{dinvgaussgpd}
\alias{pinvgaussgpd}
\alias{qinvgaussgpd}
\alias{rinvgaussgpd}
\title{Lowercase vectorized inverse Gaussian distribution functions}
\usage{
dinvgaussmix(x, w, mean, shape, log = FALSE)

pinvgaussmix(q, w, mean, shape, lower.tail = TRUE, log.p = FALSE)

qinvgaussmix(
  p,
  w,
  mean,
  shape,
  lower.tail = TRUE,
  log.p = FALSE,
  tol = 1e-10,
  maxiter = 200
)

rinvgaussmix(n, w, mean, shape)

dinvgaussmixgpd(
  x,
  w,
  mean,
  shape,
  threshold,
  tail_scale,
  tail_shape,
  log = FALSE
)

pinvgaussmixgpd(
  q,
  w,
  mean,
  shape,
  threshold,
  tail_scale,
  tail_shape,
  lower.tail = TRUE,
  log.p = FALSE
)

qinvgaussmixgpd(
  p,
  w,
  mean,
  shape,
  threshold,
  tail_scale,
  tail_shape,
  lower.tail = TRUE,
  log.p = FALSE,
  tol = 1e-10,
  maxiter = 200
)

rinvgaussmixgpd(n, w, mean, shape, threshold, tail_scale, tail_shape)

dinvgaussgpd(x, mean, shape, threshold, tail_scale, tail_shape, log = FALSE)

pinvgaussgpd(
  q,
  mean,
  shape,
  threshold,
  tail_scale,
  tail_shape,
  lower.tail = TRUE,
  log.p = FALSE
)

qinvgaussgpd(
  p,
  mean,
  shape,
  threshold,
  tail_scale,
  tail_shape,
  lower.tail = TRUE,
  log.p = FALSE,
  tol = 1e-10,
  maxiter = 200
)

rinvgaussgpd(n, mean, shape, threshold, tail_scale, tail_shape)
}
\arguments{
\item{x}{Numeric vector of quantiles.}

\item{w}{Numeric vector of mixture weights.}

\item{mean, shape}{Numeric vectors (mix) or scalars (base+gpd) of component parameters.}

\item{log}{Logical; if \code{TRUE}, return log-density.}

\item{q}{Numeric vector of quantiles.}

\item{lower.tail}{Logical; if \code{TRUE} (default), probabilities are \eqn{P(X \le x)}.}

\item{log.p}{Logical; if \code{TRUE}, probabilities are on log scale.}

\item{p}{Numeric vector of probabilities.}

\item{tol, maxiter}{Tolerance and max iterations for numerical inversion.}

\item{n}{Integer number of observations to generate.}

\item{threshold, tail_scale, tail_shape}{GPD tail parameters (scalars).}
}
\value{
Numeric vector of densities, probabilities, quantiles, or random variates.
}
\description{
Vectorized R wrappers for the scalar inverse-Gaussian-kernel topics in this file.
}
\details{
These functions are vectorized R front ends to the scalar inverse-Gaussian
and splice routines. They retain the \eqn{(\mu,\lambda)} parameterization
used everywhere else in the package and apply the scalar evaluator
repeatedly over the supplied input vector or draw index.
}
\section{Functions}{
\itemize{
\item \code{dinvgaussmix()}: Inverse Gaussian mixture density (vectorized)

\item \code{pinvgaussmix()}: Inverse Gaussian mixture distribution function (vectorized)

\item \code{qinvgaussmix()}: Inverse Gaussian mixture quantile function (vectorized)

\item \code{rinvgaussmix()}: Inverse Gaussian mixture random generation (vectorized)

\item \code{dinvgaussmixgpd()}: Inverse Gaussian mixture + GPD density (vectorized)

\item \code{pinvgaussmixgpd()}: Inverse Gaussian mixture + GPD distribution function (vectorized)

\item \code{qinvgaussmixgpd()}: Inverse Gaussian mixture + GPD quantile function (vectorized)

\item \code{rinvgaussmixgpd()}: Inverse Gaussian mixture + GPD random generation (vectorized)

\item \code{dinvgaussgpd()}: Inverse Gaussian + GPD density (vectorized)

\item \code{pinvgaussgpd()}: Inverse Gaussian + GPD distribution function (vectorized)

\item \code{qinvgaussgpd()}: Inverse Gaussian + GPD quantile function (vectorized)

\item \code{rinvgaussgpd()}: Inverse Gaussian + GPD random generation (vectorized)

}}
\examples{
w <- c(0.6, 0.3, 0.1)
mu <- c(1, 1.5, 2)
lam <- c(2, 3, 4)

# Inverse Gaussian mixture
dinvgaussmix(c(1, 2, 3), w = w, mean = mu, shape = lam)
rinvgaussmix(5, w = w, mean = mu, shape = lam)

}
\seealso{
\code{\link[=InvGauss_mix]{InvGauss_mix()}}, \code{\link[=InvGauss_mixgpd]{InvGauss_mixgpd()}}, \code{\link[=InvGauss_gpd]{InvGauss_gpd()}}, \code{\link[=bundle]{bundle()}},
\code{\link[=get_kernel_registry]{get_kernel_registry()}}.

Other vectorized kernel helpers: 
\code{\link{amoroso_lowercase}},
\code{\link{base_lowercase}},
\code{\link{cauchy_mix_lowercase}},
\code{\link{gamma_lowercase}},
\code{\link{laplace_lowercase}},
\code{\link{lognormal_lowercase}},
\code{\link{normal_lowercase}}
}
\concept{vectorized kernel helpers}
