Evaluate the probability mass function of a continuous Uniform distribution

Usage

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

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

Arguments

d: A Uniform object created by a call to Uniform().
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 dunif. 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 <- Uniform(1, 2)
X
#> [1] "Uniform(a = 1, b = 2)"

random(X, 10)
#>  [1] 1.971750 1.083758 1.873870 1.329231 1.222276 1.401648 1.072499 1.002450
#>  [9] 1.137094 1.191909

pdf(X, 0.7)
#> [1] 0
log_pdf(X, 0.7)
#> [1] -Inf

cdf(X, 0.7)
#> [1] 0
quantile(X, 0.7)
#> [1] 1.7

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