Evaluate the probability mass function of a NegativeBinomial distribution

Evaluate the probability mass function of a NegativeBinomial distribution

Usage

# S3 method for class 'NegativeBinomial'
pdf(d, x, drop = TRUE, elementwise = NULL, ...)

# S3 method for class 'NegativeBinomial'
log_pdf(d, x, drop = TRUE, elementwise = NULL, ...)

Arguments

d

A NegativeBinomial object created by a call to NegativeBinomial().

x

A vector of elements whose probabilities you would like to determine given the distribution d.

drop

logical. Should the result be simplified to a vector if possible?

elementwise

logical. Should each distribution in d be evaluated at all elements of x (elementwise = FALSE, yielding a matrix)? Or, if d and x 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.

...

Arguments to be passed to dnbinom. 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(x) columns (if drop = FALSE). In case of a vectorized distribution object, a matrix with length(x) columns containing all possible combinations.

See also

Other NegativeBinomial distribution: cdf.NegativeBinomial(), quantile.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