Evaluate the probability mass function of a Frechet distribution

Evaluate the probability mass function of a Frechet distribution

Usage

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

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

Arguments

d

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

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 dgev. 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 <- Frechet(0, 2)
X
#> [1] "Frechet(location = 0, scale = 2, shape = 1)"

random(X, 10)
#>  [1] 69.7922625  0.8065071 14.8341823  1.8001889  1.3299308  2.1925530
#>  [7]  0.7621402  0.3326917  1.0064977  1.2115825

pdf(X, 0.7)
#> [1] 0.2344189
log_pdf(X, 0.7)
#> [1] -1.450646

cdf(X, 0.7)
#> [1] 0.05743262
quantile(X, 0.7)
#> [1] 5.607347

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