Univariate prior on model parameter

A Prior object represents a prior distribution on the single model parameter of a DataDistribution class object. Together a prior and data-distribution specify the class of the joint distribution of the test statisic, X, and its parameter, theta. Currently, adoptr only allows simple models with a single parameter. Implementations for PointMassPrior and ContinuousPrior are available.

Details

For an example on working with priors, see here.

See also

For the available methods, see bounds, expectation, condition, predictive_pdf, predictive_cdf, posterior

Examples

disc_prior <- PointMassPrior(c(0.1, 0.25), c(0.4, 0.6))

cont_prior <- ContinuousPrior(
  pdf     = function(x) dnorm(x, mean = 0.3, sd = 0.2),
  support = c(-2, 3)
)