% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.Poisson3_1D.R
\docType{data}
\name{Poisson3_1D}
\alias{Poisson3_1D}
\alias{lambda3_1D}
\alias{E_nc3a}
\alias{E_nc3b}
\alias{pts3}
\alias{countdata3a}
\alias{countdata3b}
\title{1-Dimensional NonHomogeneous Poisson example.}
\format{The data contain the following \code{R} objects:
 \describe{
   \item{\code{lambda3_1D}:}{ A function defining the intensity function of a 
   nonhomogeneous Poisson process. Note that this function is only defined on
   the interval (0,55).}
   \item{\code{E_nc3a}}{ The expected counts of gridded data for the wider bins (10 bins).}
   \item{\code{E_nc3b}}{ The expected counts of gridded data for the wider bins (20 bins).}
   \item{\code{pts3}}{ The locations of the observed points (a data frame with one column, named \code{x}).}
   \item{\code{countdata3a}}{ A data frame with three columns, containing the count data for the 
   10-interval case:}
   \item{\code{countdata3b}}{ A data frame with three columns, containing the count data for the 
   20-interval case:}
   \describe{
     \item{\code{x}}{ The grid cell midpoint.}
     \item{\code{count}}{ The number of detections in the cell.}
     \item{\code{exposure}}{ The width of the cell.}
   }
 }}
\usage{
data(Poisson3_1D)
}
\description{
Point data and count data, together with intensity function and expected counts for 
a multimodal nonhomogeneous 1-dimensional Poisson process example. Counts are given for two 
different gridded data interval widths.
}
\examples{
\donttest{
library(ggplot2)
data(Poisson3_1D)
# first the plots for the 10-bin case:
p1a = ggplot(countdata3a) + 
geom_point(data = countdata3a, aes(x=x,y=count),col="blue") +ylim(0,max(countdata3a$count,E_nc3a)) +
  geom_point(data = countdata3a, aes(x=x), y = 0, shape = "+",col="blue",cex=4) +
  geom_point(data=data.frame(x=countdata3a$x,y=E_nc3a), aes(x=x), y = E_nc3a, shape = "_",cex=5) +
  xlab(expression(bold(s))) +ylab("count")
ss = seq(0,55,length=200)
lambda = lambda3_1D(ss)
p2a = ggplot() + 
  geom_line(data=data.frame(x=ss,y=lambda), aes(x=x,y=y),col="blue") +ylim(0,max(lambda)) +
  geom_point(data = pts3, aes(x=x), y = 0.2, shape = "|",cex=4) +
  xlab(expression(bold(s))) +ylab(expression(lambda(bold(s))))
multiplot(p1a,p2a,cols=1)

# Then the plots for the 20-bin case:
p1a = ggplot(countdata3b) + 
  geom_point(data = countdata3b, aes(x=x,y=count),col="blue") +
  ylim(0,max(countdata3b$count,E_nc3b)) +
  geom_point(data = countdata3b, aes(x=x), y = 0, shape = "+",col="blue",cex=4) +
  geom_point(data=data.frame(x=countdata3b$x,y=E_nc3b), aes(x=x), y = E_nc3b, shape = "_",cex=5) +
  xlab(expression(bold(s))) +ylab("count")
ss = seq(0,55,length=200)
lambda = lambda3_1D(ss)
p2a = ggplot() + 
  geom_line(data=data.frame(x=ss,y=lambda), aes(x=x,y=y),col="blue") +ylim(0,max(lambda)) +
  geom_point(data = pts3, aes(x=x), y = 0.2, shape = "|",cex=4) +
  xlab(expression(bold(s))) +ylab(expression(lambda(bold(s))))
multiplot(p1a,p2a,cols=1)
}
}
