trunct: Truncated t distribution

In RTMBdist: Distributions Compatible with Automatic Differentiation by 'RTMB'

Truncated t distribution

Description

Density, distribution function, quantile function, and random generation for the truncated t distribution.

Usage

dtrunct(x, df, min = -Inf, max = Inf, log = FALSE)

ptrunct(q, df, min = -Inf, max = Inf, lower.tail = TRUE, log.p = FALSE)

qtrunct(p, df, min = -Inf, max = Inf, lower.tail = TRUE, log.p = FALSE)

rtrunct(n, df, min = -Inf, max = Inf)

Arguments

x, q	vector of quantiles
df	degrees of freedom parameter, must be positive.
min, max	truncation bounds.
log, log.p	logical; if TRUE, probabilities/densities p are returned as \log(p).
lower.tail	logical; if TRUE, probabilities are P[X \le x], otherwise P[X > x].
p	vector of probabilities
n	number of random values to return.

Details

This implementation of dtrunct allows for automatic differentiation with RTMB.

f(x;\,\nu,a,b) = \frac{f_t(x;\,\nu)}{F_t(b;\,\nu) - F_t(a;\,\nu)}, \quad x \in [a, b],

where f_t(\cdot;\nu) and F_t(\cdot;\nu) are the Student-t PDF and CDF.

Value

dtrunct gives the density, ptrunct gives the distribution function, qtrunct gives the quantile function, and rtrunct generates random deviates.

Examples

x <- rtrunct(1, df = 5, min = -1, max = 5)
d <- dtrunct(x, df = 5, min = -1, max = 5)
p <- ptrunct(x, df = 5, min = -1, max = 5)
q <- qtrunct(p, df = 5, min = -1, max = 5)

RTMBdist documentation built on Oct. 31, 2026, 5:07 p.m.