% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/huge.ct.R
\name{huge.ct}
\alias{huge.ct}
\title{Graph estimation via correlation thresholding (ct)}
\usage{
huge.ct(
  x,
  nlambda = NULL,
  lambda.min.ratio = NULL,
  lambda = NULL,
  verbose = TRUE,
  input.type = "auto"
)
}
\arguments{
\item{x}{There are 2 options: (1) \code{x} is an \code{n} by \code{d} data matrix (2) a \code{d} by \code{d} sample covariance matrix. The program automatically identifies the input matrix by checking the symmetry. (\code{n} is the sample size and \code{d} is the dimension).}

\item{nlambda}{The number of regularization/thresholding parameters. The default value is \code{20} for \code{method = "ct"} and \code{10} for \code{method = "mb"}, \code{"glasso"} or \code{"tiger"}.}

\item{lambda.min.ratio}{If \code{method = "mb"}, \code{"glasso"} or \code{"tiger"}, it is the smallest value for \code{lambda}, as a fraction of the upperbound (\code{MAX}) of the regularization/thresholding parameter which makes all estimates equal to \code{0}. The program can automatically generate \code{lambda} as a sequence of length = \code{nlambda} starting from \code{MAX} to \code{lambda.min.ratio*MAX} in log scale. If \code{method = "ct"}, it is the largest sparsity level for estimated graphs. The program can automatically generate \code{lambda} as a sequence of length = \code{nlambda}, which makes the sparsity level of the graph path increases from \code{0} to \code{lambda.min.ratio} evenly.The default value is \code{0.1} when \code{method = "mb"}, \code{"glasso"} or \code{"tiger"}, and 0.05 when \code{method = "ct"}.}

\item{lambda}{A numeric scalar or non-empty one-dimensional numeric input
of finite, non-negative thresholds. Values are applied in the supplied
order, and zero is allowed. Leave
\code{lambda = NULL} to generate a path from \code{nlambda} and
\code{lambda.min.ratio}.}

\item{verbose}{If \code{verbose = FALSE}, tracing information printing is disabled. The default value is \code{TRUE}.}

\item{input.type}{How to interpret \code{x}: \code{"auto"} preserves
symmetry-based detection, \code{"data"} forces an observation matrix,
and \code{"covariance"} requires a square covariance or correlation
matrix.}
}
\description{
See more details in \code{\link{huge}}
}
\details{
The default path targets increasing numbers of undirected edges
  and defines each graph by the strict rule
  \code{abs(correlation) > lambda}. Equal-weight edges are never split, so
  ties can make the realized sparsity smaller than the nominal target.
  Reusing the returned \code{lambda} values therefore reconstructs the
  same path. When \code{lambda = NULL}, \code{nlambda} must be a positive
  integer and \code{lambda.min.ratio} must lie in \code{(0, 1]}. Supplying
  \code{lambda} overrides those two arguments.
}
\seealso{
\code{\link{huge}}, and \code{\link{huge-package}}.
}
