Evaluate the cumulative distribution function of an RevWeibull distribution

Usage

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

Arguments

d: A RevWeibull object created by a call to RevWeibull().
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 pgev. 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 <- RevWeibull(1, 2)
X
#> [1] "RevWeibull(location = 1, scale = 2, shape = 1)"

random(X, 10)
#>  [1]   0.9426871  -3.9596589   0.7303525  -1.2219891  -2.0076752  -0.8243573
#>  [7]  -4.2483783 -11.0231439  -2.9741769  -2.3014673

pdf(X, 0.7)
#> [1] 0.430354
log_pdf(X, 0.7)
#> [1] -0.8431472

cdf(X, 0.7)
#> [1] 0.860708
quantile(X, 0.7)
#> [1] 0.2866501

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