pdf.NegativeBinomial {distributions3}

Evaluate the probability mass function of a NegativeBinomial distribution

Description

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

random(X, 10)

pdf(X, 50)
log_pdf(X, 50)

cdf(X, 50)
quantile(X, 0.7)

## alternative parameterization of X
Y <- NegativeBinomial(mu = 45, size = 5)
Y
cdf(Y, 50)
quantile(Y, 0.7)