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\name{BasicStatistics}
\alias{BasicStatistics}
\alias{basicStats}
\alias{skewness}
\alias{skewness.default}
\alias{skewness.data.frame}
\alias{skewness.POSIXct}
\alias{skewness.POSIXlt}
\alias{kurtosis}
\alias{kurtosis.default}
\alias{kurtosis.data.frame}
\alias{kurtosis.POSIXct}
\alias{kurtosis.POSIXlt}
\alias{rowStats}
\alias{rowAvgs}
\alias{rowVars}
\alias{rowStdevs}
\alias{rowSkewness}
\alias{rowKurtosis}
\alias{rowCumsums}
\alias{colStats}
\alias{colAvgs}
\alias{colVars}
\alias{colStdevs}
\alias{colSkewness}
\alias{colKurtosis}
\alias{colCumsums}
\title{Basic Statistics Summary}
\description{
A collection and description of functions which compute
basic statistical properties. Missing functions in R to
calculate skewness and kurtosis are added, a function
which creates a summary statistics, and functions to
calculate column statistics.
\cr
The functions are:
\tabular{ll}{
\code{skewness} \tab returns value of skewness, \cr
\code{kurtosis} \tab returns value of kurtosis, \cr
\code{basicStats} \tab computes an overview of basic statistical values, \cr
\code{rowStats}\tab calculates row statistics, \cr
\code{colStats} \tab calculates column statistics, \cr
\code{rowAvgs} \tab calculates row means, \cr
\code{colAvgs} \tab calculates column means, \cr
\code{rowVars} \tab calculates row variances, \cr
\code{colVars} \tab calculates column variances, \cr
\code{rowStdevs} \tab calculates row standard deviations, \cr
\code{colStdevs} \tab calculates column standard deviations, \cr
\code{rowSkewness} \tab calculates row skewness, \cr
\code{colSkewness} \tab calculates column skewness, \cr
\code{rowKurtosis} \tab calculates row kurtosis, \cr
\code{colKurtosis} \tab calculates column kurtosis, \cr
\code{rowCumsums} \tab calculates row cumulated Sums, \cr
\code{colCumsums} \tab calculates column cumulated Sums. }
}
\usage{
skewness(x, \dots)
\method{skewness}{default}(x, na.rm = FALSE, \dots)
\method{skewness}{data.frame}(x, \dots)
\method{skewness}{POSIXct}(x, \dots)
\method{skewness}{POSIXlt}(x, \dots)
kurtosis(x, \dots)
\method{kurtosis}{default}(x, na.rm = FALSE, \dots)
\method{kurtosis}{data.frame}(x, \dots)
\method{kurtosis}{POSIXct}(x, \dots)
\method{kurtosis}{POSIXlt}(x, \dots)
basicStats(x, ci = 0.95)
rowStats(x, FUN, na.rm = FALSE, \dots)
rowAvgs(x, na.rm = FALSE, \dots)
rowVars(x, na.rm = FALSE, \dots)
rowStdevs(x, na.rm = FALSE, \dots)
rowSkewness(x, na.rm = FALSE, \dots)
rowKurtosis(x, na.rm = FALSE, \dots)
rowCumsums(x, na.rm = FALSE, \dots)
colStats(x, FUN, na.rm = FALSE, \dots)
colAvgs(x, na.rm = FALSE, \dots)
colVars(x, na.rm = FALSE, \dots)
colStdevs(x, na.rm = FALSE, \dots)
colSkewness(x, na.rm = FALSE, \dots)
colKurtosis(x, na.rm = FALSE, \dots)
colCumsums(x, na.rm = FALSE, \dots)
}
\arguments{
\item{ci}{
confidence interval, a numeric value, by default 0.95,
i.e. 95 percent.
}
\item{FUN}{
the statistical function to be applied.
}
\item{na.rm}{
a logical. Should missing values be removed?
}
\item{x}{
a numeric vector, or a matrix for column statistics.
}
\item{\dots}{
arguments to be passed.
}
}
\value{
\code{skewness}, \code{kurtosis}
\cr
returns the value of the statistics, a numeric value.
\cr
\code{basicsStats}
\cr
returns data frame with the following entries and row names:
nobs, NAs, Minimum, Maximum , 1. Quartile, 3. Quartile,
Mean, Median, Sum, SE Mean, LCL Mean, UCL Mean, Variance,
Stdev, Skewness, Kurtosis.
\cr
\code{rowStats}, \code{rowAvgs}, \code{rowVars}, \code{rowStdevs},\cr
\code{rowSkewness}, \code{rowKurtosis}, \code{rowCumsum}
\cr
computes sample statistics by column. Missing values can be
handled.
\cr
\code{colStats}, \code{colAvgs}, \code{colVars}, \code{colStdevs},\cr
\code{colSkewness}, \code{colKurtosis}, \code{colCumsum}
\cr
computes sample statistics by column. Missing values can be
handled.
}
\note{
\R's-base package contains a function \code{colMeans} with an
additional argument \code{dim=1}. Therefore, the function used
here to compute column means (averages) is named \code{colAvgs}.
}
\author{
Diethelm Wuertz for the Rmetrics \R-port.
}
\seealso{
\code{\link{colMeans}},
\code{\link{mean}},
\code{\link{median}},
\code{\link{var}}.
}
\examples{
## basicStats -
xmpBasics("\nStart: Basic Statistics of log-Returns > ")
# Data NYSE Composite Index:
data(nyseres)
basicStats(nyseres)
## moments -
xmpBasics("\nNext: Moments, Skewness and Kurtosis > ")
# Mean, Variance:
mean(nyseres)
var(nyseres)
# Skewness, Kurtosis:
# Note, can handele data.frames:
skewness(nyseres)
kurtosis(nyseres)
}
\keyword{univar}
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