.. _method-stoch_collocation-quadrature_order: """""""""""""""" quadrature_order """""""""""""""" Order for tensor-products of Gaussian quadrature rules .. toctree:: :hidden: :maxdepth: 1 method-stoch_collocation-quadrature_order-dimension_preference method-stoch_collocation-quadrature_order-nested method-stoch_collocation-quadrature_order-non_nested **Specification** - *Alias:* None - *Arguments:* INTEGER **Child Keywords:** +-------------------------+--------------------+--------------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+==========================+=============================================+ | Optional | `dimension_preference`__ | A set of weights specifying the realtive | | | | importance of each uncertain variable | | | | (dimension) | +-------------------------+--------------------+--------------------------+---------------------------------------------+ | Optional (Choose One) | Quadrature Rule | `nested`__ | Enforce use of nested quadrature rules if | | | Nesting | | available | | | +--------------------------+---------------------------------------------+ | | | `non_nested`__ | Enforce use of non-nested quadrature rules | +-------------------------+--------------------+--------------------------+---------------------------------------------+ .. __: method-stoch_collocation-quadrature_order-dimension_preference.html __ method-stoch_collocation-quadrature_order-nested.html __ method-stoch_collocation-quadrature_order-non_nested.html **Description** Multidimensional integration by a tensor-product of Gaussian quadrature rules (specified with ``quadrature_order``, and, optionally, ``dimension_preference``). The default rule selection is to employ ``non_nested`` Gauss rules including Gauss-Hermite (for normals or transformed normals), Gauss-Legendre (for uniforms or transformed uniforms), Gauss-Jacobi (for betas), Gauss-Laguerre (for exponentials), generalized Gauss-Laguerre (for gammas), and numerically-generated Gauss rules (for other distributions when using an Extended basis). For the case of ``p_refinement`` or the case of an explicit ``nested`` override, Gauss-Hermite rules are replaced with Genz-Keister nested rules and Gauss-Legendre rules are replaced with Gauss-Patterson nested rules, both of which exchange lower integrand precision for greater point reuse. By specifying a ``dimension_preference``, where higher preference leads to higher order polynomial resolution, the tensor grid may be rendered anisotropic. The dimension specified to have highest preference will be set to the specified ``quadrature_order`` and all other dimensions will be reduced in proportion to their reduced preference; any non-integral portion is truncated. To synchronize with tensor-product integration, a tensor-product expansion is used, where the order :math:`p_i` of the expansion in each dimension is selected to be half of the integrand precision available from the rule in use, rounded down. In the case of non-nested Gauss rules with integrand precision :math:`2m_i-1` , :math:`p_i` is one less than the quadrature order :math:`m_i` in each dimension (a one-dimensional expansion contains the same number of terms, :math:`p+1` , as the number of Gauss points). The total number of terms, *N*, in a tensor-product expansion involving *n* uncertain input variables is .. math:: N ~=~ 1 + P ~=~ \prod_{i=1}^{n} (p_i + 1) In some advanced use cases (e.g., multifidelity UQ), multiple grid resolutions can be employed; for this reason, the ``quadrature_order`` specification supports an array input. A corresponding sequence specification is documented at, e.g., :dakkw:`method-multifidelity_polynomial_chaos-quadrature_order_sequence` and :dakkw:`method-multifidelity_stoch_collocation-quadrature_order_sequence`