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\name{timeSeries-method-stats}
\docType{methods}
\alias{sd-methods}
\alias{var-methods}
\alias{cov-methods}
\alias{cor-methods}
%\alias{dcauchy-methods}
%\alias{dnorm-methods}
%\alias{dt-methods}
%\alias{sd,timeSeries-method}
%\alias{var,timeSeries-method}
%\alias{cov,timeSeries-method}
%\alias{cor,timeSeries-method}
%\alias{dcauchy,timeSeries-method}
%\alias{dnorm,timeSeries-method}
%\alias{dt,timeSeries-method}
\title{Base R functions applied to 'timeSeries' objects}
\description{
Many base R statistical functions work on (the data part of)
\code{timeSeries} objects without the need for special methods, e.g.,
\code{var}, \code{sd}, \code{cov}, \code{cor}, probability densities,
and others. This page gives some examples with such functions.
}
%% 2023-05-29: these S4 methods don't exist! (and the functions are not generic!)
%\usage{
%\S4method{cov}{timeSeries}(x, y = NULL, use = "all.obs",
% method = c("pearson", "kendall", "spearman"))
%
%\S4method{cor}{timeSeries}(x, y = NULL, use = "all.obs",
% method = c("pearson", "kendall", "spearman"))
%}
%
%\arguments{
% \item{x}{
% an univariate object of class \code{timeSeries}.
% }
% \item{y}{
% \code{NULL} (default) or a \code{timeSeries} object with compatible
% dimensions to \code{x}. The default is equivalent to \code{y = x}
% (but more efficient).
% }
% \item{use}{
% an optional character string giving a method for computing
% covariances in the presence of missing values. This must be (an
% abbreviation of) one of the strings \code{"all.obs"},
% \code{"complete.obs"} or \code{"pairwise.complete.obs"}.
% }
% \item{method}{
% a character string indicating which correlation coefficient (or
% covariance) is to be computed. One of \code{"pearson"} (default),
% \code{"kendall"}, or \code{"spearman"}. Can be abbreviated.
% }
%}
%
%\value{
% covariance or correlation matrix
%}
\seealso{
\code{\link{colStats}},
\code{\link{colVars}}, and other \code{colXXX} functions
}
\examples{
## Load Microsoft Data Set -
data(MSFT)
X = MSFT[, 1:4]
X = 100 * returns(X)
## Compute Covariance Matrix -
cov(X[, "Open"], X[, "Close"])
cov(X)
cor(X)
}
\keyword{methods}
\keyword{chron}
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