Evaluate the probability mass function of an F distribution

Evaluate the probability mass function of an F distribution

Usage

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

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

Arguments

d

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

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 df. 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 <- FisherF(5, 10, 0.2)
X
#> [1] "FisherF(df1 = 5, df2 = 10, lambda = 0.2)"

random(X, 10)
#>  [1] 3.1450634 0.2781146 0.5846266 0.8103721 0.6263227 2.4989529 0.6281965
#>  [8] 0.3110039 0.5357005 0.4882204

pdf(X, 2)
#> [1] 0.1699603
log_pdf(X, 2)
#> [1] -1.77219

cdf(X, 4)
#> [1] 0.9667464
quantile(X, 0.7)
#> [1] 1.467954

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