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README.md
In deconvolveR: Empirical Bayes Estimation Strategies
Empirical Bayes Deconvolution
An unknown prior density $g(\theta)$ has yielded (unobservable)
$\Theta_1, \Theta_2,\ldots,\Theta_N$, and each $\Theta_i$ produces an
observation $X_i$ from an exponential family. deconvolveR is an R
package for estimating prior distribution $g(\theta)$ from the data
using Empirical Bayes deconvolution.
Details and examples may be found in the paper by Narasimhan and Efron,
2020. A vignette with further
examples is also provided.
Try the deconvolveR package in your browser
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deconvolveR documentation built on Aug. 30, 2020, 9:07 a.m.
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Empirical Bayes Deconvolution
An unknown prior density $g(\theta)$ has yielded (unobservable)
$\Theta_1, \Theta_2,\ldots,\Theta_N$, and each $\Theta_i$ produces an
observation $X_i$ from an exponential family. deconvolveR is an R
package for estimating prior distribution $g(\theta)$ from the data
using Empirical Bayes deconvolution.
Details and examples may be found in the paper by Narasimhan and Efron, 2020. A vignette with further examples is also provided.
Try the deconvolveR package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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