swh:1:snp:c5bf23010a433f55124ad01cf6314106162422e4
Tip revision: 3026c20762a46521a0493b710702d7fba8ea2d60 authored by Björn Böttcher on 23 April 2020, 15:50:03 UTC
version 2.3.0
version 2.3.0
Tip revision: 3026c20
coins.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/multivariance-functions.R
\name{coins}
\alias{coins}
\title{dependence example: k-independent coin sampling}
\usage{
coins(N = 1000, k = 2, type = "even")
}
\arguments{
\item{N}{number of samples}
\item{k}{each k-tuple will be independent}
\item{type}{one of \code{"even"} or \code{"odd"}}
}
\value{
It returns the samples as rows of an \code{N} by \code{k+1} matrix. The columns are dependent but k-independent.
}
\description{
This function creates samples which are dependent but k-independent.
}
\details{
Throw \code{k} independent fair coins. Now consider
the k+1 events: The first shows head, the second shows head,... the \code{k}-th shows head,
there is an \code{even} (or \code{odd} as selected via \code{type}) number of heads. Each row
contains the state of these k+1 events.
}
\examples{
coins(200,4)
}
\references{
For the theoretic background see the reference [3] given on the main help page of this package: \link{multivariance-package}.
}