Nothing
#' Generalized inverse
#'
#' \code{ginv} Computes the Moore-Penrose generalized inverse
#' of a matrix X.
#' @param X Matrix for which the Moore-Penrose inverse is
#' required.
#' @param tol A relative tolerance to detect zero singular
#' values.
#' @return A MP generalized inverse matrix for X.
#' @references Venables, W. N. and Ripley, B. D. (1999) Modern
#' Applied Statistics with S-PLUS. Third Edition. Springer.
#' p.100.
#' @seealso \code{\link{solve}}, \code{\link{svd}},
#' \code{\link{eigen}}
#' @export
ginv <-
function(X, tol = sqrt(.Machine$double.eps))
{
if (length(dim(X)) > 2L || !(is.numeric(X) || is.complex(X)))
stop("'X' must be a numeric or complex matrix")
if (!is.matrix(X))
X <- as.matrix(X)
Xsvd <- svd(X)
if (is.complex(X))
Xsvd$u <- Conj(Xsvd$u)
Positive <- Xsvd$d > max(tol * Xsvd$d[1L], 0)
if (all(Positive))
Xsvd$v %*% (1/Xsvd$d * t(Xsvd$u))
else if (!any(Positive))
array(0, dim(X)[2L:1L])
else Xsvd$v[, Positive, drop = FALSE] %*% ((1/Xsvd$d[Positive]) *
t(Xsvd$u[, Positive, drop = FALSE]))
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.