View source: R/PoissonBinomial.R
quantile.PoissonBinomial | R Documentation |
quantile()
is the inverse of cdf()
.
## S3 method for class 'PoissonBinomial'
quantile(
x,
probs,
drop = TRUE,
elementwise = NULL,
lower.tail = TRUE,
log.p = FALSE,
verbose = TRUE,
...
)
x |
A |
probs |
A vector of probabilities. |
drop |
logical. Shoul the result be simplified to a vector if possible? |
elementwise |
logical. Should each distribution in |
lower.tail , log.p , ... |
Arguments to be passed to
|
verbose |
logical. Should a warning be issued if the normal approximation is applied because the PoissonBinomial package is not installed? |
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.
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])
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