R/cdfStats.R

In samuel-rosa/pedometrics: Miscellaneous Pedometric Tools

# Descriptive statistics of the cumulative distribution function of a
# continuous variable
# 
# This function returns summary statistics of the cumulative distribution
# function of a continuous variable estimated with \pkg{spsurvey}-package.
# 
# The function \code{cont.analysis()} of \pkg{spsurvey}-package estimates the
# population total, mean, variance, and standard deviation of a continuous
# variable. It also estimates the standard error and confidence bounds of
# these population estimates. In some cases it may be interesting to see all
# estimates, for which one uses \code{all = TRUE}. However, in other
# circumstances there might be interest only in taking a look at the estimated
# population mean and standard deviation. Then the argument \code{all} has to
# be set to \code{FALSE}.
# 
# @param obj Object containing the estimated cumulative distribution function
# of the continuous variable. The resulting object of \code{cont.analysis()}
# of \pkg{spsurvey}-package.
# @param ind Indicator variable. The name of the continuous variable as
# displayed in the resulting object of \code{cont.analysis()}.
# @param all Summary statistics to be returned. The default option (\code{all
# = TRUE}) returns all summary statistics available. If \code{all = FALSE},
# then only estimated population mean and standard deviation are returned. See
# \sQuote{Details}.
# @return A \code{data.frame} containing summary statistics of the cumulative
# distribution function of a continuous variable.
# @author Alessandro Samuel-Rosa \email{alessandrosamuelrosa@@gmail.com}
# @references Kincaid, T. M. and Olsen, A. R. (2013). spsurvey: Spatial Survey
# Design and Analysis. R package version 2.6. URL: \url{https://www.epa.gov/}.
# @keywords methods print
# @export
# @examples
# 
# \dontrun{
# if (require(spsurvey)) {
# ## Estimate the CDF
# my.cdf <- spsurvey::cont.analysis(spsurvey.obj = my.spsurvey)
# 
# ## See indicator levels in the resulting object
# levels(my.cdf$Pct$Indicator)
# 
# ## Return all summary statistics of indicator variable 'dx'
# cdfStats(my.cdf, "dx", all = TRUE)
# }
# }
# 
# FUNCTION #########################################################################################
cdfStats <-
  function(obj, ind, all = TRUE) {
    stats <- data.frame(obj$Pct[obj$Pct$Indicator == ind, 4:9][8:10, ], row.names = NULL)
    if(all) {
      res <- stats
    } else {
      res <- stats[1, 3]
    }
    res
  }