This function acts as a skeleton for a truncated distribution defined by model type, maximum value and model parameters.
dist_skel( n, dist =FALSE, cum =TRUE, model, discrete =FALSE, params, max_value =120)
Arguments
n: Numeric vector, number of samples to take (or days for the probability density).
dist: Logical, defaults to FALSE. Should the probability density be returned rather than a number of samples.
cum: Logical, defaults to TRUE. If dist = TRUE should the returned distribution be cumulative.
model: Character string, defining the model to be used. Supported options are exponential ("exp"), gamma ("gamma"), and log normal ("lognormal")
discrete: Logical, defaults to FALSE. Should the probability distribution be discretised. In this case each entry of the probability mass function corresponds to the 2-length interval ending at the entry except for the first interval that covers (0, 1). That is, the probability mass function is a vector where the first entry corresponds to the integral over the (0,1] interval of the continuous distribution, the second entry corresponds to the (0,2] interval, the third entry corresponds to the (1, 3] interval etc.
params: A list of parameters values (by name) required for each model. For the exponential model this is a rate parameter and for the gamma model this is alpha and beta.
max_value: Numeric, the maximum value to allow. Defaults to 120. Samples outside of this range are resampled.
Returns
A vector of samples or a probability distribution.