Bivariate kernel density HDR estimator — method

Function used to specify bivariate kernel density estimator for get_hdr() and layer functions (e.g. geom_hdr()).

Usage

method_kde(h = NULL, adjust = c(1, 1))

Arguments

h: Bandwidth (vector of length two). If NULL, estimated using MASS::bandwidth.nrd().
adjust: A multiplicative bandwidth adjustment to be used if 'h' is 'NULL'. This makes it possible to adjust the bandwidth while still using the a bandwidth estimator. For example, adjust = 1/2 means use half of the default bandwidth.

Details

For more details on the use and implementation of the method_*() functions, see vignette("method", "ggdensity").

Examples

set.seed(1)
df <- data.frame(x = rnorm(1e3, sd = 3), y = rnorm(1e3, sd = 3))

ggplot(df, aes(x, y)) +
  geom_hdr(method = method_kde()) +
  geom_point(size = 1)


# The defaults of `method_kde()` are the same as the estimator for `ggplot2::geom_density_2d()`
ggplot(df, aes(x, y)) +
  geom_density_2d_filled() +
  geom_hdr_lines(method = method_kde(), probs = seq(.1, .9, by = .1)) +
  theme(legend.position = "none")


# The bandwidth of the estimator can be set directly with `h` or scaled with `adjust`
ggplot(df, aes(x, y)) +
  geom_hdr(method = method_kde(h = 1)) +
  geom_point(size = 1)


ggplot(df, aes(x, y)) +
  geom_hdr(method = method_kde(adjust = 1/2)) +
  geom_point(size = 1)


# Can also be used with `get_hdr()` for numerical summary of HDRs
res <- get_hdr(df, method = method_kde())
str(res)
#> List of 3
#>  $ df_est:'data.frame':	10000 obs. of  5 variables:
#>   ..$ x               : num [1:10000] -9.02 -8.82 -8.61 -8.4 -8.2 ...
#>   ..$ y               : num [1:10000] -9.76 -9.76 -9.76 -9.76 -9.76 ...
#>   ..$ fhat            : num [1:10000] 2.86e-08 6.11e-08 1.24e-07 2.39e-07 4.35e-07 ...
#>   ..$ fhat_discretized: num [1:10000] 1.24e-09 2.65e-09 5.38e-09 1.04e-08 1.88e-08 ...
#>   ..$ hdr             : num [1:10000] 1 1 1 1 1 1 1 1 1 1 ...
#>  $ breaks: Named num [1:5] 0.000226 0.000913 0.003072 0.007748 Inf
#>   ..- attr(*, "names")= chr [1:5] "99%" "95%" "80%" "50%" ...
#>  $ data  :'data.frame':	1000 obs. of  3 variables:
#>   ..$ x             : num [1:1000] -1.879 0.551 -2.507 4.786 0.989 ...
#>   ..$ y             : num [1:1000] 3.405 3.336 -2.612 0.632 0.208 ...
#>   ..$ hdr_membership: num [1:1000] 0.5 0.5 0.5 0.8 0.5 0.8 0.5 0.95 0.8 0.5 ...