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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/simulate_data.R
+\name{simulate_data}
+\alias{simulate_data}
+\title{Simulate Multivariate Normal Data}
+\usage{
+simulate_data(
+  n,
+  p,
+  rho = 0.8,
+  contamination = 0,
+  block_fraction = 0.5,
+  t_df = Inf,
+  exact_contamination = FALSE
+)
+}
+\arguments{
+\item{n}{Number of observations to generate.}
+
+\item{p}{Number of features to simulate.}
+
+\item{rho}{The AR(1) decay parameter (default 0.8). Setting rho = 0 uses the identity matrix as the true covariance (0 <= rho < 1).}
+
+\item{contamination}{The proportions of rows to contaminate as outlier observations (default 0, 0 <= contamination <= 1).}
+
+\item{block_fraction}{The fraction of the covariance matrix to form as AR(1) structure (default 0.5, 0 < block_fraction <= 1).}
+
+\item{t_df}{The degrees of freedom to use for scaling observations into heavy tails (default Inf, 0 <= t_df < 2).}
+}
+\value{
+A list with X, S and a vector identifying the contaminated rows.
+}
+\description{
+Given a set of parameters controlling the properties
+of the true covariance matrix, simulate data
+with the intention of evaluating the performance
+of covariance or correlation matrix estimators.
+}
+\examples{
+X_obj <- generate_data(n = 10, p = 10)
+X <- X_obj$X
+S_true <- X_obj$S
+
+}