Poisson1_1D: 1-Dimensional Homogeneous Poisson example.

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

1-Dimensional Homogeneous Poisson example.

Description

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:

x

The grid cell midpoint.

count

The number of detections in the cell.

exposure

The width of the cell.

Examples

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")
}

inlabru documentation built on Nov. 2, 2023, 6:07 p.m.