Point data and count data, together with intensity function and expected counts for a homogeneous 1-dimensional Poisson process example.

## Usage

`data(Poisson1_1D)`

## Format

The data contain the following `R`

objects:

`lambda1_1D`

:A function defining the intensity function of a nonhomogeneous Poisson process. Note that this function is only defined on the interval (0,55).

`E_nc1`

The expected counts of the gridded data.

`pts1`

The locations of the observed points (a data frame with one column, named

`x`

).`countdata1`

A data frame with three columns, containing the count data:

## Examples

```
# \donttest{
if (require("ggplot2", quietly = TRUE)) {
data(Poisson1_1D)
ggplot(countdata1) +
geom_point(data = countdata1, aes(x = x, y = count), col = "blue") +
ylim(0, max(countdata1$count)) +
geom_point(data = pts1, aes(x = x), y = 0.2, shape = "|", cex = 4) +
geom_point(
data = countdata1, aes(x = x), y = 0, shape = "+",
col = "blue", cex = 4
) +
xlab(expression(bold(s))) +
ylab("count")
}
# }
```