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quantile() is the inverse of cdf().

Usage

# S3 method for Gamma
quantile(x, probs, drop = TRUE, elementwise = NULL, ...)

Arguments

x

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

probs

A vector of probabilities.

drop

logical. Should the result be simplified to a vector if possible?

elementwise

logical. Should each distribution in x be evaluated at all elements of probs (elementwise = FALSE, yielding a matrix)? Or, if x and probs 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 qgamma. 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 <- Gamma(5, 2)
X
#> [1] "Gamma distribution (shape = 5, rate = 2)"

random(X, 10)
#>  [1] 4.727510 3.628168 1.512156 4.771854 2.257310 3.645070 5.083710 2.509344
#>  [9] 1.093361 2.021506

pdf(X, 2)
#> [1] 0.3907336
log_pdf(X, 2)
#> [1] -0.9397292

cdf(X, 4)
#> [1] 0.9003676
quantile(X, 0.7)
#> [1] 2.945181

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