The function returns its arguments as a named list. The function is used
inside the utility functions. It is transformed to an expression using
parse and evaluated using eval. This ensures
that in the case of an RPL with Bayesian priors, recursion is handled
automatically. This significantly simplifies translating the utility function
to lists of parameters to use when optimizing the designs. It is also less
error prone.
normal(mu, sigma)
normal_p(mu, sigma)
lognormal(mu, sigma)
lognormal_p(mu, sigma)
triangular(mu, sigma)
triangular_p(mu, sigma)
uniform(mu, sigma)
uniform_p(mu, sigma)A parameter indicating the mean or location of the distribution
depending on whether it is a normal, log-normal, triangular or uniform,
or it can be another call to normal, lognormal,
uniform or triangular if the model is an RPL with
a Bayesian prior.
A parameter indicating the SD or spread of the distribution
or it can be another call to normal, lognormal,
uniform or triangular.
A list of parameters
normal(): The normal distribution
normal_p(): The normal distribution when applied to a prior
lognormal(): The log normal distribution
lognormal_p(): The log-normal distribution when applied to a prior
triangular(): The triangular distribution
triangular_p(): The triangular distribution when applied to a prior
uniform(): The uniform distribution
uniform_p(): The uniform distribution when applied to a prior