dist_trunc: Truncated distribution

In reservr: Fit Distributions and Neural Networks to Censored and Truncated Data

Truncated distribution

Description

Truncated distribution

Usage

dist_trunc(dist = NULL, min = NULL, max = NULL, offset = 0, max_retry = 100)

Arguments

dist	An underlying distribution, or NULL as a placeholder.
min	Minimum value to truncate at (exclusive), or NULL as a placeholder.
max	Maxmimum value to truncate at (inclusive), or NULL as a placeholder.
offset	Offset to be added to each observation after truncation, or NULL as a placeholder. Truncation of dist will occur to (min, max]. The offset is then added deterministically.
max_retry	Maximum number of resample attempts when trying to sample with rejection.

Value

A TruncatedDistribution object.

See Also

Other Distributions: Distribution, dist_bdegp(), dist_beta(), dist_binomial(), dist_blended(), dist_dirac(), dist_discrete(), dist_empirical(), dist_erlangmix(), dist_exponential(), dist_gamma(), dist_genpareto(), dist_lognormal(), dist_mixture(), dist_negbinomial(), dist_normal(), dist_pareto(), dist_poisson(), dist_translate(), dist_uniform(), dist_weibull()

Examples

d_norm <- dist_normal(mean = 0, sd = 1)
d_tnorm <- dist_trunc(dist = d_norm, min = -2, max = 2, offset = 1)
plot_distributions(d_norm, d_tnorm, .x = seq(-2, 3, length.out = 100))

reservr documentation built on June 24, 2024, 5:10 p.m.