pdf.HyperGeometric {distributions3} | R Documentation |
Please see the documentation of HyperGeometric()
for some properties
of the HyperGeometric distribution, as well as extensive examples
showing to how calculate p-values and confidence intervals.
## S3 method for class 'HyperGeometric'
pdf(d, x, drop = TRUE, elementwise = NULL, ...)
## S3 method for class 'HyperGeometric'
log_pdf(d, x, drop = TRUE, elementwise = NULL, ...)
d |
A |
x |
A vector of elements whose probabilities you would like to
determine given the distribution |
drop |
logical. Should the result be simplified to a vector if possible? |
elementwise |
logical. Should each distribution in |
... |
Arguments to be passed to |
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.
Other HyperGeometric distribution:
cdf.HyperGeometric()
,
quantile.HyperGeometric()
,
random.HyperGeometric()
set.seed(27)
X <- HyperGeometric(4, 5, 8)
X
random(X, 10)
pdf(X, 2)
log_pdf(X, 2)
cdf(X, 4)
quantile(X, 0.7)