R/S3-methods.R

In CR2: Compute Cluster Robust Standard Errors with Degrees of Freedom Adjustments

#' @export
#' @importFrom stats printCoefmat
print.CR2 <- function(x, ...){
  cat("\nStandard error type =", x$crtype, '\n')
  cat("Degrees of freedom =", x$df, '\n\n')
  printCoefmat(x$ttable, x$digits)
}

#' Compute the inverse square root of a matrix
#'
#' From Imbens and Kolesar (2016).
#' @param A The matrix object.
#' @export
#' @return Returns a matrix.
MatSqrtInverse <- function(A) {

  ei <- eigen(A, symmetric = TRUE) #obtain eigenvalues and eigenvectors
  d <- pmax(ei$values, 10^-12) #set negatives values to zero
  #or near zero 10^-12
  d2 <- 1/sqrt(d) #get the inverse of the square root
  d2[d == 0] <- 0
  ei$vectors %*% (if (length(d2)==1) d2 else diag(d2)) %*% t(ei$vectors)
}