ptrunc: Cumulative Distribution Function

In TruncExpFam: Truncated Exponential Family

Cumulative Distribution Function

Description

Calculates the cumulative probability for a given truncated distribution

Usage

ptrunc(q, family, ..., lower.tail = TRUE, log.p = FALSE)

ptruncnorm(
  q,
  mean = 0,
  sd = 1,
  a = -Inf,
  b = Inf,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncbeta(
  q,
  shape1,
  shape2,
  a = 0,
  b = 1,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncbinom(
  q,
  size,
  prob,
  a = 0,
  b = size,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncpois(q, lambda, a = 0, b = Inf, ..., lower.tail = TRUE, log.p = FALSE)

ptruncchisq(q, df, a = 0, b = Inf, ..., lower.tail = TRUE, log.p = FALSE)

ptrunccontbern(q, lambda, a = 0, b = 1, ...)

ptruncexp(q, rate = 1, a = 0, b = Inf, ..., lower.tail = TRUE, log.p = FALSE)

ptruncgamma(
  q,
  shape,
  rate = 1,
  scale = 1/rate,
  a = 0,
  b = Inf,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncinvgamma(
  q,
  shape,
  rate = 1,
  scale = 1/rate,
  a = 0,
  b = Inf,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncinvgauss(q, m, s, a = 0, b = Inf, ...)

ptrunclnorm(
  q,
  meanlog = 0,
  sdlog = 1,
  a = 0,
  b = Inf,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

ptruncnbinom(
  q,
  size,
  prob,
  mu,
  a = 0,
  b = Inf,
  ...,
  lower.tail = TRUE,
  log.p = FALSE
)

Arguments

q	vector of quantiles
family	distribution family to use
...	named distribution parameters and/or truncation limits (a, b)
lower.tail	logical; if TRUE, probabilities are P(X <= x) otherwise, P(X > x)
log.p	logical; if TRUE, probabilities p are given as log(p)
mean	mean of parent distribution
sd	standard deviation is parent distribution
a	point of left truncation. For discrete distributions, a will be included in the support of the truncated distribution.
b	point of right truncation
shape1	positive shape parameter alpha
shape2	positive shape parameter beta
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
lambda	mean and var of "parent" distribution
df	degrees of freedom for "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
mu	alternative parametrization via mean

Value

The cumulative probability of y.

Examples

ptrunc(0)
ptrunc(6, family = "gaussian", mean = 5, sd = 10, b = 7)
pnorm(6, mean = 5, sd = 10) # for comparison

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