dtnorm_cpp {oeli} | R Documentation |
Truncated normal distribution
Description
The function dtnorm()
computes the density of a truncated normal
distribution.
The function rtnorm()
samples from a truncated normal distribution.
The function dttnorm()
and rttnorm()
compute the density and sample from
a two-sided truncated normal distribution, respectively.
The functions with suffix _cpp
perform no input checks, hence are faster.
Usage
dtnorm_cpp(x, mean, sd, point, above, log = FALSE)
dttnorm_cpp(x, mean, sd, lower, upper, log = FALSE)
rtnorm_cpp(mean, sd, point, above, log = FALSE)
rttnorm_cpp(mean, sd, lower, upper, log = FALSE)
dtnorm(x, mean, sd, point, above, log = FALSE)
dttnorm(x, mean, sd, lower, upper, log = FALSE)
rtnorm(mean, sd, point, above, log = FALSE)
rttnorm(mean, sd, lower, upper, log = FALSE)
Arguments
x |
[ |
mean |
[ |
sd |
[ |
point , lower , upper |
[ |
above |
[ |
log |
[ |
Value
For dtnorm()
and dttnorm()
: The density value.
For rtnorm()
and rttnorm()
: The random draw
See Also
Other simulation helpers:
Simulator
,
correlated_regressors()
,
ddirichlet_cpp()
,
dmvnorm_cpp()
,
dwishart_cpp()
,
simulate_markov_chain()
Examples
x <- c(0, 0)
mean <- c(0, 0)
Sigma <- diag(2)
# compute density
dmvnorm(x = x, mean = mean, Sigma = Sigma)
dmvnorm(x = x, mean = mean, Sigma = Sigma, log = TRUE)
# sample
rmvnorm(n = 3, mean = mean, Sigma = Sigma)
rmvnorm(mean = mean, Sigma = Sigma, log = TRUE)