MINI MINI MANI MO

%
% Copyright (c) 2012, 2014, Oracle and/or its affiliates. All rights reserved. 
%
\name{ore.rank}
\alias{ore.rank}
\title{Oracle R Enterprise Data Ranking}
\description{
  Enables the investigation of the distribution of values along numeric
  columns in an \code{\link[OREbase:ore.frame-class]{ore.frame}} object.
  Highlights include:
  Allows ranking within groups,
  Partitions observations into groups based on rank tiles,
  Provides options for treatment of ties,
  Calculates cumulative percentages and percentiles,
  Calculates normal scores from ranks.
}
\usage{
  ore.rank(data, var, desc = FALSE, groups = NULL, group.by = NULL,
           ties = c("mean", "high", "low", "dense",
                    "condense"),
           score = c("none", "fraction", "nplus1", "blom", "tukey",
                     "vw", "percent", "savage",
                     "waerden", "fn1", "n1"),
           fraction = FALSE, percent = FALSE, nplus1 = FALSE,
           savage = FALSE, blom = FALSE, tukey = FALSE, vw = FALSE)
}
\arguments{
  \item{data}{An \code{\link[OREbase:ore.frame-class]{ore.frame}} object.}
  \item{var}{A comma-separated character string specifying the names of
    numeric columns within argument \code{data}.}
  \item{desc}{A logical value indicating whether to rank in ascending or
    descending order.}
  \item{groups}{An optional numeric value specifying the number of
    partitions in the data. For percentiles, specify
    \code{groups = 100}. For deciles, specify \code{groups = 10}. For
    quartiles, specify \code{groups = 4}.}
  \item{group.by}{An optional character vector specifying the group by
    column names within argument \code{data}.}
  \item{ties}{A character string specifying how to handle ties; One of

    \code{"low"} (smallest rank within the tied group), 
    
    \code{"high"} (largest rank within the tied group), 

    \code{"mean"} (average rank within the tied group), and 

    \code{"dense"}/\code{"condense"} (arbitrary unique rank within the tied group).}
  \item{score}{A character string specifying a score; One of

    \code{"none"}, \code{"fraction"}, \code{"nplus1"}, \code{"blom"},
    \code{"tukey"}, \code{"vw"}, \code{"percent"}, or \code{"savage"},
    \code{"waerden"}, \code{"fn1"}, or \code{"n1"}.}
  \item{fraction}{A logical value indicating whether to compute the
    ratio of \samp{rank/#non-missing values} for each column in argument
    \code{var}.}
  \item{percent}{A logical value indicating whether to compute the ratio
    \samp{(rank * 100)/#non-missing values} for each column in argument
    \code{var}.}
  \item{nplus1}{A logical value indicating whether to compute the ratio
    \samp{rank/(#non-missing values + 1)} for each column in argument
    \code{var}.}
  \item{savage}{Equivalent to \code{score = "savage"}.}
  \item{blom}{Equivalent to \code{score = "blom"}.}
  \item{tukey}{Equivalent to \code{score = "tukey"}.}
  \item{vw}{Equivalent to \code{score = "vw"}.}
}
\value{
  Returns an \code{\link[OREbase:ore.frame-class]{ore.frame}} object.
}
\references{
  \href{http://www.oracle.com/technetwork/database/database-technologies/r/r-enterprise/documentation/index.html}{Oracle R Enterprise}
}
\author{
  Oracle \email{oracle-r-enterprise@oracle.com}
}
\seealso{
  \code{\link{ore.sort}}
}
\examples{
  IRIS <- ore.push(iris)

  # Rank 2 columns with column aliases and sort them in descending rank order
  ore.rank(data = IRIS,
           var  = "Petal.Length=Col1Rank, Sepal.Length=Col2Rank",
           desc = TRUE)
 
  # Handling of ties
  ore.rank(data = IRIS,
           var  = "Petal.Length=PetalLengthRanks, Sepal.Length=SepalRanks",
           ties = "low")

  # Rank within each Species group
  ore.rank(data = IRIS,
           var  = "Petal.Length=PetalLengthRanks, Sepal.Length=SepalRanks",
           group.by = "Species")

  # Partition rows into 10 groups to get deciles
  ore.rank(data = IRIS,
           var  = "Petal.Length=PetalLengthRanks, Sepal.Length=SepalRanks",
           groups = 10)

  # Estimate the cumulative distribution function
  ore.rank(data = IRIS,
           var  = "Petal.Length=PetalLengthRanks, Sepal.Length=SepalRanks",
           nplus1 = TRUE)

  # Calculate scores
  ore.rank(data = IRIS,
           var = "Petal.Length=PetalLengthRanks, Sepal.Length=SepalRanks",
           score = "savage", groups = 100, group.by = "Species")
}
\keyword{univar}