Evaluate the cumulative distribution function of a Binomial distribution

Usage

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

Arguments

d: A Binomial object created by a call to Binomial().
x: A vector of elements whose cumulative 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 pbinom. 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.

Examples


set.seed(27)

X <- Binomial(10, 0.2)
X
#> [1] "Binomial(size = 10, p = 0.2)"

mean(X)
#> [1] 2
variance(X)
#> [1] 1.6
skewness(X)
#> [1] 0.4743416
kurtosis(X)
#> [1] 0.025

random(X, 10)
#>  [1] 5 0 3 1 1 2 0 0 1 1

pdf(X, 2L)
#> [1] 0.3019899
log_pdf(X, 2L)
#> [1] -1.197362

cdf(X, 4L)
#> [1] 0.9672065
quantile(X, 0.7)
#> [1] 3

cdf(X, quantile(X, 0.7))
#> [1] 0.8791261
quantile(X, cdf(X, 7))
#> [1] 7