.. _variables-gamma_uncertain: """"""""""""""" gamma_uncertain """"""""""""""" Aleatory uncertain variable - gamma **Topics** continuous_variables, aleatory_uncertain_variables .. toctree:: :hidden: :maxdepth: 1 variables-gamma_uncertain-alphas variables-gamma_uncertain-betas variables-gamma_uncertain-initial_point variables-gamma_uncertain-descriptors **Specification** - *Alias:* None - *Arguments:* INTEGER - *Default:* no gamma uncertain variables **Child Keywords:** +-------------------------+--------------------+--------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+====================+=============================================+ | Required | `alphas`__ | First parameter of the gamma distribution | +----------------------------------------------+--------------------+---------------------------------------------+ | Required | `betas`__ | Second parameter of the gamma distribution | +----------------------------------------------+--------------------+---------------------------------------------+ | Optional | `initial_point`__ | Initial values for variables | +----------------------------------------------+--------------------+---------------------------------------------+ | Optional | `descriptors`__ | Labels for the variables | +----------------------------------------------+--------------------+---------------------------------------------+ .. __: variables-gamma_uncertain-alphas.html __ variables-gamma_uncertain-betas.html __ variables-gamma_uncertain-initial_point.html __ variables-gamma_uncertain-descriptors.html **Description** The gamma distribution is sometimes used to model time to complete a task, such as a repair or service task. It is a very flexible distribution with its shape governed by alpha and beta. The density function for the gamma distribution is given by: .. math:: f(x) = \frac{ {x}^{\alpha-1} \exp \left( \frac{-x}{\beta} \right) } { \beta^{\alpha}\Gamma(\alpha) }, where :math:`\mu = \alpha\beta,` and :math:`\sigma^2 = \alpha\beta^2` . Note that the exponential distribution is a special case of this distribution for parameter :math:`\alpha = 1` . **Theory** When used with some methods such as design of experiments and multidimensional parameter studies, distribution bounds are inferred to be [0, :math:`\mu + 3 \sigma` ]. For some methods, including vector and centered parameter studies, an initial point is needed for the uncertain variables. When not given explicitly, these variables are initialized to their means.