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\name{DelayedArray-stats}
\alias{DelayedArray-stats}
\alias{dnorm}
\alias{dnorm,DelayedArray-method}
\alias{pnorm}
\alias{pnorm,DelayedArray-method}
\alias{qnorm}
\alias{qnorm,DelayedArray-method}
\alias{dbinom}
\alias{dbinom,DelayedArray-method}
\alias{pbinom}
\alias{pbinom,DelayedArray-method}
\alias{qbinom}
\alias{qbinom,DelayedArray-method}
\alias{dpois}
\alias{dpois,DelayedArray-method}
\alias{ppois}
\alias{ppois,DelayedArray-method}
\alias{qpois}
\alias{qpois,DelayedArray-method}
\alias{dlogis}
\alias{dlogis,DelayedArray-method}
\alias{plogis}
\alias{plogis,DelayedArray-method}
\alias{qlogis}
\alias{qlogis,DelayedArray-method}
\title{Statistical functions on DelayedArray objects}
\description{
Statistical functions on \link{DelayedArray} objects.
All these functions are implemented as delayed operations.
}
\usage{
## --- The Normal Distribution ----- ##
\S4method{dnorm}{DelayedArray}(x, mean=0, sd=1, log=FALSE)
\S4method{pnorm}{DelayedArray}(q, mean=0, sd=1, lower.tail=TRUE, log.p=FALSE)
\S4method{qnorm}{DelayedArray}(p, mean=0, sd=1, lower.tail=TRUE, log.p=FALSE)
## --- The Binomial Distribution --- ##
\S4method{dbinom}{DelayedArray}(x, size, prob, log=FALSE)
\S4method{pbinom}{DelayedArray}(q, size, prob, lower.tail=TRUE, log.p=FALSE)
\S4method{qbinom}{DelayedArray}(p, size, prob, lower.tail=TRUE, log.p=FALSE)
## --- The Poisson Distribution ---- ##
\S4method{dpois}{DelayedArray}(x, lambda, log=FALSE)
\S4method{ppois}{DelayedArray}(q, lambda, lower.tail=TRUE, log.p=FALSE)
\S4method{qpois}{DelayedArray}(p, lambda, lower.tail=TRUE, log.p=FALSE)
## --- The Logistic Distribution --- ##
\S4method{dlogis}{DelayedArray}(x, location=0, scale=1, log=FALSE)
\S4method{plogis}{DelayedArray}(q, location=0, scale=1, lower.tail=TRUE, log.p=FALSE)
\S4method{qlogis}{DelayedArray}(p, location=0, scale=1, lower.tail=TRUE, log.p=FALSE)
}
\arguments{
\item{x, q, p}{
A \link{DelayedArray} object.
}
\item{mean, sd, log, lower.tail, log.p, size, prob, lambda, location, scale}{
See \code{?stats::\link[stats]{dnorm}}, \code{?stats::\link[stats]{dbinom}},
\code{?stats::\link[stats]{dpois}}, and \code{?stats::\link[stats]{dlogis}},
for a description of these arguments.
}
}
\seealso{
\itemize{
\item \code{\link[stats]{dnorm}}, \code{\link[stats]{dbinom}},
\code{\link[stats]{dpois}}, and \code{\link[stats]{dlogis}}
in the \pkg{stats} package for the corresponding operations
on ordinary arrays or matrices.
\item \link{DelayedMatrix-stats} for \link{DelayedMatrix} row/col
summarization.
\item \link{DelayedArray} objects.
\item \link[HDF5Array]{HDF5Array} objects in the \pkg{HDF5Array} package.
\item \link[base]{array} objects in base R.
}
}
\examples{
a <- array(4 * runif(1500000), dim=c(10000, 30, 5))
A <- DelayedArray(a)
A
A2 <- dnorm(A + 1)[ , , -3] # very fast! (operations are delayed)
A2
a2 <- as.array(A2) # "realize" 'A2' in memory (as an ordinary
# array)
DelayedArray(a2) == A2 # DelayedArray object of type "logical"
stopifnot(all(DelayedArray(a2) == A2))
library(HDF5Array)
A3 <- as(A2, "HDF5Array") # "realize" 'A2' on disk (as an HDF5Array
# object)
A3 == A2 # DelayedArray object of type "logical"
stopifnot(all(A3 == A2))
## See '?DelayedArray' for general information about DelayedArray objects
## and their "realization".
}
\keyword{methods}
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