\name{asym.env}
\alias{asym.env}
\title{Asyptotic covariance of vec(beta) for a fitted envelope model}
\description{
  This function compute the asyptotic covariance of vec(beta) and asymptotic standard error for elements in beta for a fiteed envelope model. 
  }
\usage{
       ModelOutput = asym.env(object)
}

\arguments{
  \item{object}{A fitted env object.}
}

\value{
  \item{covMatrix}{The asymptotic covariance of vec(beta). An rp by rp matrix. The covariance matrix returned are asymptotic.  For the actual standard errors, multiply by 1/n.}
  \item{asySE}{The asymptotic standard error for elements in beta under the envelope model.  An r by p matrix.  The standard errors returned are asymptotic, for actual standard errors, multiply by 1/sqrt(n).}
  \item{ratio}{The asymptotic standard error ratio of the standard multivariate linear regression estimator over the envelope estimator, for each element in beta.  An r by p matrix.}
}
  
\references{
Cook, R. Dennis, Bing Li, and Francesca Chiaromonte. "Envelope models for parsimonious and efficient multivariate linear regression." \emph{Statist. Sinica} 20 (2010): 927-1010.
}

\author{Zhihua Su\cr Maintainer: Guangyu Zhu \email{gzhu22@ufl.edu}}

\seealso{\code{choose_env} for choosing the dimension of envelope subspace.}