Create a distribution object — create_prob

Creates an S3 class holding the distribution and parameters from the probability distribution name, its parameters and distribution truncation and discretisation.

The class holding the distribution depends on whether it is a discretised distribution. For continuous and discrete distributions S3 classes from the distributional package are used, for discretised continuous distributions the an S3 class from the distcrete package is used.

For details on the properties of the distribution classes from each respective package see their documentation (either ?distributional or ?distcrete)

Usage

create_prob_dist(
  prob_dist,
  prob_dist_params,
  discretise = FALSE,
  truncation = NA,
  ...
)

Arguments

prob_dist: A character string specifying the probability distribution. This should match the R naming convention of probability distributions (e.g. lognormal is lnorm, negative binomial is nbinom, and geometric is geom).
prob_dist_params: A named vector of probability distribution parameters.
discretise: A boolean logical whether the distribution is discretised. Default is FALSE which assumes a continuous probability distribution
truncation: A numeric specifying the truncation point if the inferred distribution was truncated, NA if not or unknown.
...: dots Extra arguments to be passed to distributional or distcrete functions that construct the S3 distribution objects. To see which arguments can be adjusted for discretised distributions see distcrete::distcrete(), for other distributions see the ?distributional documentation and find the specific distribution constructor function, e.g. for the Gamma distribution see distributional::dist_gamma().

Value

An S3 class containing the probability distribution.

Details

Truncation is enabled only for continuous distributions as there is no truncation implemented in distcrete.

By default the discretisation of continuous distributions uses a discretisation interval (interval) of 1. If the unit of the distribution is days, then this will be discretised by day. The endpoint weighting (w) for the discretisation is 1. w can be [0,1]. For more information please see distcrete::distcrete().

Examples

# example with continuous distribution without truncation
create_prob_dist(
  prob_dist = "gamma",
  prob_dist_params = c(shape = 1, scale = 1),
  discretise = FALSE,
  truncation = NA
)
#> <distribution[1]>
#> [1] Γ(1, 1)

# example with continuous distribution with truncation
create_prob_dist(
  prob_dist = "gamma",
  prob_dist_params = c(shape = 1, scale = 1),
  discretise = FALSE,
  truncation = 10
)
#> <distribution[1]>
#> [1] Γ(1, 1)[-Inf,10]

# example with discrete distribution
create_prob_dist(
  prob_dist = "gamma",
  prob_dist_params = c(shape = 1, scale = 1),
  discretise = TRUE,
  truncation = NA
)
#> A discrete distribution
#>   name: gamma
#>   parameters:
#>     shape: 1
#>     scale: 1

# example passing extra arguments to distcrete
create_prob_dist(
  prob_dist = "gamma",
  prob_dist_params = c(shape = 1, scale = 1),
  discretise = TRUE,
  truncation = NA,
  w = 0.5
)
#> A discrete distribution
#>   name: gamma
#>   parameters:
#>     shape: 1
#>     scale: 1