bisque
1.0.2Approximate Bayesian Inference via Sparse Grid Quadrature Evaluation (BISQuE) for Hierarchical Models
Overview
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.
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- Documented parameters
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- Return-value docs
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- References docs
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3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-09-17email to the maintainer is undeliverable
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.0.22020-02-05 · diff ↗
- 1.0.12019-04-26 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 1.0.02019-04-24
- RR 3.5.0 released · 2018-04-23
Package metadata
- Total releases
- 3
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.0.2
- Bundled data
- 0.2 KB / 1 file
- Download size
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