A Beta distribution in which the alpha and beta parameters are provided.
Dirichlet distributions in which the parameters are constants.
Dirichlet distributions in which the parameters are constants. These Dirichlet elements can also serve as parameters for ParameterizedSelect.
An exponential distribution in which the parameter is a constant.
A Gamma distribution in which both the k and theta parameters are constants.
A Gamma distribution in which both the k and theta parameters are constants. Theta defaults to 1.
A Gamma distribution in which both the k and theta parameters are constants.
A Gamma distribution in which both the k and theta parameters are constants. Theta defaults to 1.
A multivariate normal distribution in which the means and variance-covariances are constants.
A normal distribution in which the mean and variance are constants.
A continuous uniform distribution in which the parameters are constants.
A Beta distribution in which the parameters are elements.
Dirichlet distributions in which the parameters are elements.
An exponential distribution in which the parameter is an element.
A Gamma distribution in which k and theta are both elements.
A normal distribution in which the mean and variance are both elements.
A continuous uniform distribution in which the parameters are elements.
A Gamma distribution in which the k parameter is an element and theta is constant.
A Gamma distribution in which the k parameter is an element and theta is constant. Theta defaults to 1.
A normal distribution in which the mean and variance are both elements.
A normal distribution in which the mean is an element and the variance is constant.
A normal distribution in which the mean is an element and the variance is constant.
A normal distribution in which the mean is constant and the variance is an element.
A Beta distribution in which the alpha and beta parameters are provided. This Beta element can be used as the parameter for a ParameterizedFlip.