dtnorm: Truncated normal distribution

In oeli: Some Utilities for Developing Data Science Software

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	[numeric(1)] A quantile.
mean	[numeric(1)] The mean.
sd	[numeric(1)] The non-negative standard deviation.
point, lower, upper	[numeric(1)] The truncation point.
above	[logical(1)] Truncate from above? Else, from below.
log	[logical(1)] Return the logarithm of the density value?

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(), dmixnorm_cpp(), dmvnorm_cpp(), dwishart_cpp(), gaussian_tv(), 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)

oeli documentation built on Aug. 18, 2025, 5:24 p.m.