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Truncated Normal Density Function

Source: R/core_bayes_estimate.R
dtnorm.Rd

Computes the probability density function for the truncated normal distribution. This version supports both vector and matrix input for x.

Usage

dtnorm(x, mean = 0, sd = 1, lower = -Inf, upper = Inf, log = FALSE)

rtnorm(n, mean = 0, sd = 1, lower = -Inf, upper = Inf)

Arguments

x

A numeric vector or matrix of values where the density should be evaluated.

mean

Mean of the normal distribution. Can be a scalar or vector (recycled if necessary).

sd

Standard deviation of the normal distribution. Can be a scalar or vector (recycled if necessary).

lower

Lower truncation bound. Can be a scalar or vector (recycled if necessary). Default is -Inf.

upper

Upper truncation bound. Can be a scalar or vector (recycled if necessary). Default is Inf.

log

Logical; if TRUE, probabilities p are given as log(p). Default is FALSE.

Value

A numeric vector or matrix of the same shape as x, containing the (possibly log) densities.

Details

The function evaluates the normal density at x and scales it to reflect truncation to the interval (lower, upper). Values outside the truncation bounds are assigned a density of 0 (or -Inf on the log scale). Internally, stats::dnorm and stats::pnorm are used.

If x is a matrix, the result retains the same dimensions. All other arguments are recycled as needed. For example, if x has two rows and 5 columns, then mean might provide 2 values, so that the first/second row is evaluated under the first/second mean value.