quantile() is the inverse of cdf().
Usage
# S3 method for class 'Frechet'
quantile(x, probs, drop = TRUE, elementwise = NULL, ...)Arguments
- x
A
Frechetobject created by a call toFrechet().- probs
A vector of probabilities.
- drop
logical. Should the result be simplified to a vector if possible?
- elementwise
logical. Should each distribution in
xbe evaluated at all elements ofprobs(elementwise = FALSE, yielding a matrix)? Or, ifxandprobshave the same length, should the evaluation be done element by element (elementwise = TRUE, yielding a vector)? The default ofNULLmeans thatelementwise = TRUEis used if the lengths match and otherwiseelementwise = FALSEis used.- ...
Arguments to be passed to
qgev. 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(probs) columns (if drop = FALSE). In case of a vectorized
distribution object, a matrix with length(probs) 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