The probability density function (density()), cumulative distribution function (cdf()), and quantile function / inverse CDF (quantile()) of an rvar.

# S3 method for rvar
density(x, at, ...)

# S3 method for rvar_factor
density(x, at, ...)

# S3 method for rvar
cdf(x, q, ...)

# S3 method for rvar_factor
cdf(x, q, ...)

# S3 method for rvar_ordered
cdf(x, q, ...)

# S3 method for rvar
quantile(x, probs, ...)

# S3 method for rvar_factor
quantile(x, probs, ...)

# S3 method for rvar_ordered
quantile(x, probs, ...)

## Arguments

x

(rvar) An rvar object.

...

Additional arguments passed onto underlying methods:

• For density(), these are passed to stats::density().

• For cdf(), these are ignored.

• For quantile(), these are passed to stats::quantile().

q, at

(numeric vector) One or more quantiles.

probs

(numeric vector) One or more probabilities in [0,1].

## Value

If x is a scalar rvar, returns a vector of the same length as the input (q, at, or probs) containing values from the corresponding function of the given rvar.

If x has length greater than 1, returns an array with dimensions c(length(y), dim(x)) where y is q, at, or probs, where each result[i,...] is the value of the corresponding function,f(y[i]), for the corresponding cell in the input array, x[...].

## Examples


set.seed(1234)
x = rvar(rnorm(100))

density(x, seq(-2, 2, length.out = 10))
#>  [1] 0.05268921 0.15669674 0.33325128 0.42911534 0.38825093 0.27760481
#>  [7] 0.20794004 0.14720607 0.10387881 0.07011558
cdf(x, seq(-2, 2, length.out = 10))
#>  [1] 0.02 0.04 0.15 0.34 0.54 0.68 0.81 0.89 0.92 0.96
quantile(x, ppoints(10))
#>  [1] -1.371156446 -1.107797288 -0.877775358 -0.574614497 -0.476119783
#>  [6] -0.187048613 -0.007696628  0.448815321  0.902987295  1.646284259

x2 = c(rvar(rnorm(100, mean = -0.5)), rvar(rnorm(100, mean = 0.5)))
density(x2, seq(-2, 2, length.out = 10))
#>             [,1]        [,2]
#>  [1,] 0.08849633 0.001641837
#>  [2,] 0.20332937 0.024310255
#>  [3,] 0.33447478 0.081654865
#>  [4,] 0.41944017 0.167732070
#>  [5,] 0.40333595 0.241892638
#>  [6,] 0.28289139 0.309987338
#>  [7,] 0.15847776 0.462678904
#>  [8,] 0.12750072 0.466875791
#>  [9,] 0.07751964 0.234727355
#> [10,] 0.02149798 0.109987934
cdf(x2, seq(-2, 2, length.out = 10))
#>       [,1] [,2]
#>  [1,] 0.07 0.01
#>  [2,] 0.11 0.01
#>  [3,] 0.25 0.03
#>  [4,] 0.43 0.08
#>  [5,] 0.63 0.16
#>  [6,] 0.79 0.31
#>  [7,] 0.86 0.43
#>  [8,] 0.91 0.69
#>  [9,] 0.97 0.87
#> [10,] 0.99 0.93
quantile(x2, ppoints(10))
#>             [,1]       [,2]
#>  [1,] -2.0034466 -0.6872996
#>  [2,] -1.3541896 -0.2346473
#>  [3,] -1.0276966  0.1308444
#>  [4,] -0.8207823  0.3500387
#>  [5,] -0.5789329  0.6861700
#>  [6,] -0.3647747  0.8192384
#>  [7,] -0.1451222  0.9367486
#>  [8,]  0.1230689  1.1749908
#>  [9,]  0.4371228  1.4569163
#> [10,]  1.1776442  2.1500961