Nothing

```
#' Calculate metrics corresponding to the Standard Ellipse based on a
#' covariance matrix
#'
#' This function takes a covariance 2x2 matrix Sigma and returns various
#' metrics relating to the corresponding Standard Ellipse. The function is
#' limited to the 2-dimensional case, as many of the ancilliary summary
#' statistics are not defined for higher dimensions (e.g. eccentricity).
#'
#' @section Note: This function is currently based on the eigenvalue and
#' eigenvector approach which is more flexible for higher dimensional problems
#' method for calculating the standard ellipse, and replaces the parametric
#' method used previously in siar and siber.
#'
#' @param sigma a 2x2 covariance ellipse.
#'
#' @return A list comprising the following metrics for summarising the Standard
#' Ellipse
#' #' \itemize{
#' \item {SEA}{ the Standard Ellise Area (not sample size corrected)}
#' \item {eccentricity}{ a measure of the elongation of the ellipse.}
#' \item {a}{ the length of the semi-major axis}
#' \item {b}{ the length of the semi-minor axis}
#' }
#'
#' @examples
#' # A perfect circle
#' sigma <- matrix( c(1, 0, 0, 1), 2, 2)
#' sigmaSEA(sigma)
#'
#' @export
#'
sigmaSEA <- function(sigma){
eig <- eigen(sigma)
a <- sqrt(eig$values[1])
b <- sqrt(eig$values[2])
# As of v2.0.4 I have replaced the asin() line with atan which
# returns the angle of correct sign due to the inclusion of the quotient
# of the vectors.
theta <- atan(eig$vectors[2,1] / eig$vectors[1,1])
SEA <- pi*a*b
out <- list()
out$SEA <- pi*a*b
out$eccentricity <- sqrt(1-((b^2)/(a^2)))
out$a <- a
out$b <- b
out$theta <- theta
return(out)
}
```

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