quantile() is the inverse of cdf().
Usage
# S3 method for class 'Gumbel'
quantile(x, probs, drop = TRUE, elementwise = NULL, ...)Arguments
- x
A
Gumbelobject created by a call toGumbel().- 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 <- Gumbel(1, 2)
X
#> [1] "Gumbel(mu = 1, sigma = 2)"
random(X, 10)
#> [1] 8.104751940 -0.816379582 5.007573903 0.789488808 0.183959497
#> [6] 1.183838833 -0.929543900 -2.587372533 -0.373340977 -0.002439646
pdf(X, 0.7)
#> [1] 0.1817758
log_pdf(X, 0.7)
#> [1] -1.704981
cdf(X, 0.7)
#> [1] 0.3129117
quantile(X, 0.7)
#> [1] 3.061861
cdf(X, quantile(X, 0.7))
#> [1] 0.7
quantile(X, cdf(X, 0.7))
#> [1] 0.7