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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).
y
x
density_at(posterior, x, precision = 2^10, method = "kernel", ...)
Vector representing a posterior distribution.
The value of which to get the approximate probability.
Number of points of density data. See the n parameter in density.
n
density
Density estimation method. Can be "kernel" (default), "logspline" or "KernSmooth".
"kernel"
"logspline"
"KernSmooth"
Currently not used.
# NOT RUN { library(bayestestR) posterior <- distribution_normal(n = 10) density_at(posterior, 0) density_at(posterior, c(0, 1)) # }
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