logjac

values at which to evaluate \(J(x)\)

Character vector specifying link function for which the 
inverse link function should be evaluated. Supports <code>'identity'</code>,
<code>'log'</code>, and <code>'logit'</code>.

link

Optional list of additional parameters for link functions.
For example, the logit function can be extended to allow mappings to any 
closed interval. There should be one list entry for each link function. 
Specify NA if defaults should be used.

linkparams

Wrapper to abstractly evaluate log-Jacobian functions for transforms

Implementation of the 'bisque' strategy for approximate Bayesian posterior inference. See Hewitt and Hoeting (2019) <arXiv:1904.07270> for complete details. 'bisque' combines conditioning with sparse grid quadrature rules to approximate marginal posterior quantities of hierarchical Bayesian models. The resulting approximations are computationally efficient for many hierarchical Bayesian models. The 'bisque' package allows approximate posterior inference for custom models; users only need to specify the conditional densities required for the approximation.

logjac: Wrapper to abstractly evaluate log-Jacobian functions for transforms

Description

Usage

Arguments

See Also

Examples