Compute the density value at a given point of a distribution (i.e.,
the value of the y
axis of a value x
of a distribution).
Arguments
- posterior
Vector representing a posterior distribution.
- x
The value of which to get the approximate probability.
- precision
Number of points of density data. See the
n
parameter indensity
.- method
Density estimation method. Can be
"kernel"
(default),"logspline"
or"KernSmooth"
.- ...
Currently not used.
Examples
library(bayestestR)
posterior <- distribution_normal(n = 10)
density_at(posterior, 0)
#> [1] 0.3206131
density_at(posterior, c(0, 1))
#> [1] 0.3206131 0.2374056