rmsb: pdensityContour – R documentation

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pdensityContour

Bivariate Posterior Contour

Description

Computes coordinates of a highest density contour containing a given probability volume given a sample from a continuous bivariate distribution, and optionally plots. The default method assumes an elliptical shape, but one can optionally use a kernel density estimator. Code adapted from embbook::HPDregionplot. See http://www.sumsar.net/blog/2014/11/how-to-summarize-a-2d-posterior-using-a-highest-density-ellipse/.

Usage

pdensityContour(
  x,
  y,
  method = c("ellipse", "kernel"),
  prob = 0.95,
  otherprob = c(0.01, 0.1, 0.25, 0.5, 0.75, 0.9),
  h = c(1.3 * MASS::bandwidth.nrd(x), 1.3 * MASS::bandwidth.nrd(y)),
  n = 70,
  pl = FALSE
)

Arguments

`x`	a numeric vector
`y`	a numeric vector the same length of x
`method`	defaults to `'ellipse'`, can be set to `'kernel'`
`prob`	main probability coverage (the only one for `method='ellipse'`)
`otherprob`	vector of other probability coverages for `method='kernel'`
`h`	vector of bandwidths for x and y. See `MASS::kde2d()`.
`n`	number of grid points in each direction, defaulting to normal reference bandwidth (see `bandwidth.nrd`).
`pl`	set to `TRUE` to plot contours

Value

a 2-column matrix with x and y coordinates unless pl=TRUE in which case a ggplot2 graphic is returned

Author(s)

Ben Bolker and Frank Harrell

rmsb

Bayesian Regression Modeling Strategies

v0.0.2

GPL (>= 3)

Authors

Frank Harrell [aut, cre] (<https://orcid.org/0000-0002-8271-5493>), Ben Goodrich [ctb] (contributed Stan code), Ben Bolker [ctb] (wrote original code that is folded into the pdensityContour function), Doug Bates [ctb] (write original code for highest posterior density interval that is folded into the HPDint function)

Initial release

2021-02-27