Package: deconvolveR 1.2-1
Balasubramanian Narasimhan
deconvolveR: Empirical Bayes Estimation Strategies
Empirical Bayes methods for learning prior distributions from data. An unknown prior distribution (g) has yielded (unobservable) parameters, each of which produces a data point from a parametric exponential family (f). The goal is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical Bayes methods. Details and examples are in the paper by Narasimhan and Efron (2020, <doi:10.18637/jss.v094.i11>).
Authors:
deconvolveR_1.2-1.tar.gz
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deconvolveR.pdf |deconvolveR.html✨
deconvolveR/json (API)
NEWS
| # Install 'deconvolveR' in R: |
| install.packages('deconvolveR', repos = c('https://bnaras.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bnaras/deconvolver/issues
- bardWordCount - Shakespeare word counts in the entire canon: 14,376 distinct words appeared exactly once, 4343 words appeared twice etc.
- disjointTheta - A set of Theta values that have a bimodal distribution for testing
- surg - Intestinal surgery data involving 844 cancer patients. The data consists of pairs (n_i, s_i) where n_i is the number of satellites removed and s_i is the number of satellites found to be malignant.
Last updated 4 years agofrom:07e0333075. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 18 2024 |
| R-4.5-win | NOTE | Nov 18 2024 |
| R-4.5-linux | NOTE | Nov 18 2024 |
| R-4.4-win | NOTE | Nov 18 2024 |
| R-4.4-mac | NOTE | Nov 18 2024 |
| R-4.3-win | OK | Nov 18 2024 |
| R-4.3-mac | OK | Nov 18 2024 |
Exports:deconv
Dependencies:
