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\name{rank}
\alias{rank}
\alias{rank,timeSeries-method}
\title{Sample ranks of a time series}
\description{
Compute the sample ranks of the values of a 'timeSeries' object.
}
\usage{
\S4method{rank}{timeSeries}(x, na.last = TRUE, ties.method = )
}
\arguments{
\item{x}{
an univariate object of class \code{timeSeries}.
}
\item{na.last}{
for controlling the treatment of \code{NA}s. If \code{TRUE}, missing
values in the data are put last; if \code{FALSE}, they are put
first; if \code{NA}, they are removed; if \code{"keep"} they are
kept with rank \code{NA}.
}
\item{ties.method}{
a character string specifying how ties are treated; can be
abbreviated.
}
}
\details{
If all components are different (and no \code{NA}s), the ranks are
well defined, with values in \code{seq_len(x)}. With some values equal
(called \sQuote{ties}), argument \code{ties.method} determines the
result at the corresponding indices. The \code{"first"} method results
a permutation with increasing values at each index set of ties. The
\code{"random"} method puts these in random order, whereas the
default, \code{"average"}, replaces them by their mean, and
\code{"max"} and \code{"min"} replace them with their maximum and
minimum respectively, the latter being the typical sports ranking.
\code{NA} values are never considered to be equal: for \code{na.last =
TRUE} and \code{na.last = FALSE} they are given distinct ranks in the
order in which they occur in \code{x}.
}
\value{
a \code{"timeSeries"} object
}
\examples{
## Load Microsoft Data -
X <- 100 * returns(MSFT)
## Compute the Ranks -
head(rank(X[, "Open"]), 10)
## Only Interested in the Vector, then use -
head(rank(series(X[, "Open"])), 10)
}
\keyword{chron}
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