PDF, CDF, PMF, quantiles and random number generation for <epiparameter> objects

The <epiparameter> object holds a probability distribution which can either be a continuous or discrete distribution. These are the density, cumulative distribution, quantile and random number generation functions. These operate on any distribution that can be included in an <epiparameter> object.

Usage

# S3 method for class 'epiparameter'
density(x, at, ...)

# S3 method for class 'epiparameter'
cdf(x, q, ..., log = FALSE)

# S3 method for class 'epiparameter'
quantile(x, p, ...)

# S3 method for class 'epiparameter'
generate(x, times, ...)

Arguments

x

An <epiparameter> object.

at

The quantiles to evaluate at.

...

dots Extra arguments to be passed to the method.

q

The quantiles to evaluate at.

log

If TRUE, probabilities will be given as log probabilities.

p

The probabilities to evaluate at.

times

The number of random samples.

Value

numeric vector.

Examples

ep <- epiparameter(
  disease = "ebola",
  epi_name = "incubation_period",
  prob_distribution = create_prob_distribution(
    prob_distribution = "gamma",
    prob_distribution_params = c(shape = 1, scale = 1)
  )
)
#> Citation cannot be created as author, year, journal or title is missing

# example of each distribution method for an `epiparameter` object
stats::density(ep, at = 1)
#> [1] 0.3678794
distributional::cdf(ep, q = 1)
#> [1] 0.6321206
stats::quantile(ep, p = 0.2)
#> [1] 0.2231436
distributional::generate(ep, times = 10)
#>  [1] 3.56720380 1.16790186 0.05745463 0.34040705 3.47156091 1.04366207
#>  [7] 3.02627506 0.36756952 0.09970044 0.78957870