R/pros.R

In lsm: Estimation of the log Likelihood of the Saturated Model

#' pros
#' 
#' @title pros
#' @name pros
#' @usage pros
#' @format A data frame with 380 observations on the following 9 variables.
#' \describe{
#'  \item{\code{ID}}{a numeric vector}
#'  \item{\code{CAPSULE}}{a numeric vector}
#'  \item{\code{AGE}}{a numeric vector}
#'  \item{\code{RACE}}{a numeric vector}
#'  \item{\code{DPROS}}{a numeric vector}
#'  \item{\code{DCAPS}}{a numeric vector}
#'  \item{\code{PSA}}{a numeric vector}
#'  \item{\code{VOL}}{a numeric vector}
#'  \item{\code{GLEASON}}{a numeric vector}
#'}
#' 
#' @references Hosmer, D. (2013). Wiley Series in Probability and Statistics Ser. : Applied Logistic Regression (3). New York: John Wiley & Sons, Incorporated.
#' @examples 
#'   # data(pros)
#'   # maybe str(pros) ; plot(pros) ...
#' @keywords data
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