dtrunc: Probability Density Function

In TruncExpFam: Truncated Exponential Family

Probability Density Function

Description

Calculates the PDF for a given truncated distribution

Usage

dtruncbeta(y, shape1, shape2, eta, a = 0, b = 1, ...)

dtruncbinom(y, size, prob, eta, a = 0, b = attr(y, "parameters")$size, ...)

dtruncchisq(y, df, eta, a = 0, b = Inf, ...)

dtrunccontbern(y, lambda, eta, a = 0, b = 1, ...)

dtrunccontbern(y, lambda, eta, a = 0, b = 1, ...)

dtrunc(y, ...)

dtruncexp(y, rate = 1, eta, a = 0, b = Inf, ...)

dtruncgamma(y, shape, rate = 1, scale = 1/rate, eta, a = 0, b = Inf, ...)

dtruncinvgamma(y, shape, rate = 1, scale = 1/rate, eta, a = 0, b = Inf, ...)

dtruncinvgauss(y, m, s, eta, a = 0, b = Inf, ...)

dtrunclnorm(y, meanlog = 0, sdlog = 1, eta, a = 0, b = Inf, ...)

## S3 method for class 'trunc_nbinom'
dtrunc(y, size, prob, eta, a = 0, b = Inf, ...)

dtruncnbinom(y, size, prob, eta, a = 0, b = Inf, ...)

dtruncnbinom(y, size, prob, eta, a = 0, b = Inf, ...)

dtruncnorm(y, mean = 0, sd = 1, eta, a = -Inf, b = Inf, ...)

dtruncpois(y, lambda, eta, a = 0, b = Inf, ...)

Arguments

y	output from rtrunc or any valid numeric value(s).
shape1	positive shape parameter alpha
shape2	positive shape parameter beta
eta	vector of natural parameters
a	point of left truncation. For discrete distributions, a will be included in the support of the truncated distribution.
b	point of right truncation
...	size
size	target for number of successful trials, or dispersion parameter (the shape parameter of the gamma mixing distribution). Must be strictly positive, need not be integer.
prob	probability of success on each trial
df	degrees of freedom for "parent" distribution
lambda	mean and var of "parent" distribution
rate	inverse gamma rate parameter
shape	inverse gamma shape parameter
scale	inverse gamma scale parameter
m	vector of means
s	vector of dispersion parameters
meanlog	mean of untruncated distribution
sdlog	standard deviation of untruncated distribution
mean	mean of parent distribution
sd	standard deviation is parent distribution

Value

The density of y for the given values of the eta parameter.

Note

Either the common or the natural parameters must be provided.

Examples

# Using the output of rtrunc
y <- rtrunc(50, mean = 5, sd = 2)
dtrunc(y, eta = c(0, -1))

# Directly-inputting values
dtruncnorm(y = c(5, 0, -10), eta = c(0, -0.05))

TruncExpFam documentation built on April 11, 2025, 6:11 p.m.