quantile.PoissonBinomial: Determine quantiles of a PoissonBinomial distribution

In alexpghayes/distributions: Probability Distributions as S3 Objects

Determine quantiles of a PoissonBinomial distribution

Description

quantile() is the inverse of cdf().

Usage

## S3 method for class 'PoissonBinomial'
quantile(
  x,
  probs,
  drop = TRUE,
  elementwise = NULL,
  lower.tail = TRUE,
  log.p = FALSE,
  verbose = TRUE,
  ...
)

Arguments

x	A PoissonBinomial object created by a call to PoissonBinomial().
probs	A vector of probabilities.
drop	logical. Shoul the result be simplified to a vector if possible?
elementwise	logical. Should each distribution in x be evaluated at all elements of probs (elementwise = FALSE, yielding a matrix)? Or, if x and probs have the same length, should the evaluation be done element by element (elementwise = TRUE, yielding a vector)? The default of NULL means that elementwise = TRUE is used if the lengths match and otherwise elementwise = FALSE is used.
lower.tail, log.p, ...	Arguments to be passed to qpbinom or qnorm, respectively.
verbose	logical. Should a warning be issued if the normal approximation is applied because the PoissonBinomial package is not installed?

Value

In case of a single distribution object, either a numeric vector of length probs (if drop = TRUE, default) or a matrix with length(probs) columns (if drop = FALSE). In case of a vectorized distribution object, a matrix with length(probs) columns containing all possible combinations.

Examples

set.seed(27)

X <- PoissonBinomial(0.5, 0.3, 0.8)
X

mean(X)
variance(X)
skewness(X)
kurtosis(X)

random(X, 10)

pdf(X, 2)
log_pdf(X, 2)

cdf(X, 2)
quantile(X, 0.8)

cdf(X, quantile(X, 0.8))
quantile(X, cdf(X, 2))

## equivalent definitions of four Poisson binomial distributions
## each summing up three Bernoulli probabilities
p <- cbind(
  p1 = c(0.1, 0.2, 0.1, 0.2),
  p2 = c(0.5, 0.5, 0.5, 0.5),
  p3 = c(0.8, 0.7, 0.9, 0.8))
PoissonBinomial(p)
PoissonBinomial(p[, 1], p[, 2], p[, 3])
PoissonBinomial(p[, 1:2], p[, 3])

alexpghayes/distributions documentation built on May 18, 2024, 3:44 p.m.