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Visualizing EI (tomography plot)

Source: R/plot_tomog.R
plot_tomog.Rd

Tomography plot with various opitons.

Usage

plot_tomog(
  ei.object,
  options = list(color = TRUE, linecolor = "length", category = 0, breaks = "even", CI =
    NULL, points = FALSE, contour_ML = FALSE, contour_posterior = FALSE)
)

Arguments

ei.object

The output of ei()

options

The list of options

  • color: Change the line color by linecolor option.

  • linecolor: Focus of the line color, options are length, betab, and betaw.

  • category: Categorize values to color lines. The default value 0 means that it does not categorize values. When creating categories, it uses the option breaks.

  • breaks: How to create categories. Options are even and quantile.

  • CI: Tomography plot with confidence intervals. The default value is 0.8 (80

  • points: Tomography plot with estimated mean posterior \(\beta_i^b\) and \(\beta_i^w\) points.

  • contour_ML: Tomography plot with ML contours.

  • contour_posterior: Tomography plot with mean posterior contours.

Value

a ggplot object

Examples

data(matproii)
suppressMessages({
  ei_res <- ei(formula = t ~ x, total = "n", data = matproii)
})
plot_tomog(ei_res)

plot_tomog(ei_res, options = list(linecolor = "betab"))

plot_tomog(ei_res, options = list(linecolor = "betaw", category = 5))

plot_tomog(ei_res, options = list(CI = 0.8))

plot_tomog(ei_res, options = list(points = TRUE, contour_ML = TRUE))