inlabru (version 2.3.1)

Poisson3_1D: 1-Dimensional NonHomogeneous Poisson example.

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.

Usage

data(Poisson3_1D)

Format

The data contain the following R objects:

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).

E_nc3a

The expected counts of gridded data for the wider bins (10 bins).

E_nc3b

The expected counts of gridded data for the wider bins (20 bins).

pts3

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

countdata3a

A data frame with three columns, containing the count data for the 10-interval case:

countdata3b

A data frame with three columns, containing the count data for the 20-interval case:

x

The grid cell midpoint.

count

The number of detections in the cell.

exposure

The width of the cell.

Examples

# NOT RUN {
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)
# }