\name{get.p}
\alias{get.p}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Test if the kernel density estimate given by x and h0 has at most m modes }
\description{
  This function returns the p-value of rejecting the null hypothesis that the kernel density estimate given by x and h0 has at most m modes.
}
\usage{
get.p(x,h0,m=1,num.sim=200)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{x}{ the data vector }
  \item{h0}{ the bandwidth for the gaussian kernel density estimate for the standardized data}
  \item{m}{ the number iof modes we are trying to reject is the maximum }
  \item{num.sim}{ the number of bootstrap simulations to determine this p-value }
}

\value{
  returns the p-value of the test
}
\references{B.W. Silverman (1981),Using Kernel Density Estimates to
  Investigate Multimodatlity. J.R. Statist. Soc. B,43,1,97-99.}
\author{ Kevin Rader }



\seealso{ \code{\link{get.h}}, \code{\link{emp.f}}, \code{\link{get.num.modes}}}
\examples{
 set.seed(12345)
 x1<-matrix(rnorm(50),ncol=1)
 x2<-matrix(c(rnorm(25,mean=-2),rnorm(25,mean=2)),ncol=1)
 h1<-get.h(x1,m=1,prec=0.001)
 h2<-get.h(x2,m=1,prec=0.001)
 p1<-get.p(x1,h1,1,100)
 p2<-get.p(x2,h2,1,100)
 c(p1,p2)
}
\keyword{distribution}