R/repair.tsplot.R

In Auburngrads/SMRD: Statistical Methods For Reliability Data

#' Title
#'
#' @param data.rdu 
#' @param my.title 
#' @param xlab 
#' @param ylab 
#' @param ... 
#'
#' @return NULL
#' @export
#'
#' @examples
#' \dontrun{
#' 
#' halfbeak.rdu <- frame.to.rdu(halfbeak,
#'                              ID.column = "unit", 
#'                              time.column = "hours" ,
#'                              event.column = "event", 
#'                              data.title = "Halfbeak Data", 
#'                              time.units = "Thousands of Hours of Operation")
#' 
#' repair.tsplot(halfbeak.rdu)
#' 
#' }
repair.tsplot <-
function (data.rdu, 
          my.title = NULL, 
          xlab = "Failure Number",
          ylab = "Time Between Failure", ...)
{
    par(mar = c(5.1, 6.1, 4.1, 2.1))
    event <- events(data.rdu)
    EndPoints <- is.element(casefold(event), c("end", "mend", "removed"))
    StartPoints <- is.element(casefold(event), c("start", "mstart"))
    CriticalEvent <- !(EndPoints | StartPoints)
    Times <- times(data.rdu)
    UnitID <- as.factor(get.UnitID(data.rdu))
    WindowInfo <- attr(data.rdu, "WindowInfo")
    WindowPoint <- WindowInfo$WindowPoint
    WindowU <- WindowInfo$WindowU
    WindowL <- WindowInfo$WindowL
    EndPoints <- is.element(casefold(event), c("end", "mend"))
    StartPoints <- is.element(casefold(event), c("start", "mstart"))
    CriticalEvent <- !(EndPoints | StartPoints)
    RecurrTimes <- Times[CriticalEvent, ]
    interarrival.times <- diff(c(0, RecurrTimes))
    
    plot(interarrival.times, 
         xlab = "", 
         ylab = "", 
         pch = 20,
         cex = 1.5, 
         type = "b", 
         las = 1, ...)
    
    title(xlab = xlab, cex = 1.5)
    title(ylab = ylab, cex = 1.5, mgp = c(4, 1, 0))
    
    if (is.null(my.title)) my.title <- get.data.title(data.rdu)
    title(my.title)
}