SGmisc: Miscellaneous R Convenience Functions

#' SGmisc
#'
#' A collection of small wrappers and convienience functions.
#'
#' @name SGmisc
#' @docType package
#' @author Steve Gutreuter: \email{sgutreuter@@gmail.com}
#' @seealso
#' The exported functions in the \code{SGmisc} package are:
#' \describe{
#' \item{\code{link{BBS_mortality}}}{Estimate probability of mortality
#' among key population members from bio-behavioral surveillance surveys}
#' \item{\code{\link{computeBetaMoments}}}{Compute the mean oand variance of the
#' Beta distribution}
#' \item{\code{\link{computeBetaParms}}}{Compute the shape parameters of the
#' Beta distribution}
#' \item{\code{\link{computeGammaMoments}}}{Compute the mean oand variance of the
#' Gamma distribution}
#' \item{\code{\link{computeGammaParms}}}{Compute the shape, rate and scale
#' parameters of the Gamma distribution}
#' \item{\code{\link{count_NA}}}{Get a count of the numbers of NA, NaN and Inf
#' for each column of a dataframe}
#' \item{\code{\link{empCDF}}}{Compute the empirical cumulative distribution
#' function for a discrete random vector}
#' \item{\code{\link{fp_table}}}{Create one- and two-way tables of frequencies and
#' percentages}
#' \item{\code{\link{icc2deff}}}{Compute the conventional survey design effect
#' from the intraclass correlation}
#' \item{\code{\link{ilogit}}}{Compute the inverse of the logit transformation
#' ("expit" function)}
#' \item{\code{\link{logit}}}{Compute the logit transformation of a vector of
#' elements in (0, 1)}
#' \item{\code{\link{mid_date}}}{Find the midpoint date between two dates}
#' \item{\code{\link{Oz_incidencer}}}{Compute HIV incidence rate using
#' "Osmond's" method}
#' \item{\code{\link{rand_date}}}{Compute a random uniformly distributed date
#' between two dates}
#' \item{\code{\link{recode_if}}}{Conditional recoding of elements of a vector}
#' \item{\code{\link{sampsize_DHS}}}{Compute a sample-size requirement from for
#' a Demographic and Health Survey}
#' \item{\code{\link{sampsize_multinomial}}}{Compute the approximate worst-case
#' sample-size for a vector of multinomially distributed proportions}
#' \item{\code{\link{smooth_extremum}}}{Compute a smooth differentiable approximation
#' to the minimum or maximum of a numeric vector}
#'}
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