# R/ecdf_fun.R In SwampThingPaul/AnalystHelper: Helper functions developed over the years to extract and format data

#### Documented in ecdf_fun

```#' eCDF with confidence intervals
#'
#' @param x numeric vector of the observations for ecdf; for the methods, an object inheriting from class "ecdf".
#' @param CI If TRUE CDF confidence intervals will be calculated; default is set to TRUE.
#' @param CI.interval Confidence interval; default is set to 0.95
#' @keywords cdf
#' @return Compute an empirical cumulative distribution function, returns a data frame with value and proporiton. Code based on base eCDF function.
#' @export
#' @examples
#' set.seed(12)
#' test<-rnorm(100)
#' ecdf_fun(test)

ecdf_fun=function(x,CI=TRUE,CI.interval=0.95){
#modifed from ecdf() function in stats.
x <- sort(x)
n <- length(x)
vals <- unique(x)
rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n,
method = "constant", yleft = 0, yright = 1, f = 0, ties = "ordered")
class(rval) <- c("ecdf", "stepfun", class(rval))
assign("nobs", n, envir = environment(rval))
attr(rval, "call") <- sys.call()
rval
x.val=environment(rval)\$x
y.val=environment(rval)\$y

if(CI==TRUE){
alpha=1-CI.interval
eps=sqrt(log(2/alpha)/(2*n))
ll=pmax(y.val-eps,0) 		# pmin and pmax do element wise min/max;  min and max would find the min/max of the entire vector
uu=pmin(y.val+eps,1)
return(data.frame(value=x.val,proportion=y.val,lwr.CI=ll,upr.CI=uu))
}else{
return(data.frame(value=x.val,proportion=y.val))
}
}
```
SwampThingPaul/AnalystHelper documentation built on June 19, 2024, 11:30 a.m.