Determine quantiles of a NegativeBinomial distribution
Source:R/NegativeBinomial.R
quantile.NegativeBinomial.Rd
Determine quantiles of a NegativeBinomial distribution
Usage
# S3 method for class 'NegativeBinomial'
quantile(x, probs, drop = TRUE, elementwise = NULL, ...)
Arguments
- x
A
NegativeBinomial
object created by a call toNegativeBinomial()
.- probs
A vector of probabilities.
- drop
logical. Should the result be simplified to a vector if possible?
- elementwise
logical. Should each distribution in
x
be evaluated at all elements ofprobs
(elementwise = FALSE
, yielding a matrix)? Or, ifx
andprobs
have the same length, should the evaluation be done element by element (elementwise = TRUE
, yielding a vector)? The default ofNULL
means thatelementwise = TRUE
is used if the lengths match and otherwiseelementwise = FALSE
is used.- ...
Arguments to be passed to
qnbinom
. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.
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.
See also
Other NegativeBinomial distribution:
cdf.NegativeBinomial()
,
pdf.NegativeBinomial()
,
random.NegativeBinomial()
Examples
set.seed(27)
X <- NegativeBinomial(size = 5, p = 0.1)
X
#> [1] "NegativeBinomial(size = 5, p = 0.1)"
random(X, 10)
#> [1] 95 37 48 93 18 16 32 43 27 17
pdf(X, 50)
#> [1] 0.01629887
log_pdf(X, 50)
#> [1] -4.11666
cdf(X, 50)
#> [1] 0.6548517
quantile(X, 0.7)
#> [1] 53
## alternative parameterization of X
Y <- NegativeBinomial(mu = 45, size = 5)
Y
#> [1] "NegativeBinomial(mu = 45, size = 5)"
cdf(Y, 50)
#> [1] 0.6548517
quantile(Y, 0.7)
#> [1] 53