The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

smashr: smoothing using Adaptive Shrinkage in R

This R package implements fast, wavelet-based Empirical Bayes shrinkage methods for signal denoising. This includes smoothing Poisson-distributed data and Gaussian-distributed data, with possibly heteroskedastic error. The algorithms implement the methods described in Xing, Carbonetto & Stephens (2021).

If you find a bug, please post an issue.

License

All source code and software in this repository is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.

Citing this work

If you find that this R package useful for your work, please cite our paper:

Zhengrong Xing, Peter Carbonetto and Matthew Stephens (2021). Flexible signal denoising via flexible empirical Bayes shrinkage. Journal of Machine Learning Research 22(93), 1-28.

Quick Start

Follow these steps to quickly get started using smashr.

In R, install the latest version of smashr using devtools:
```
install.packages("devtools")
library(devtools)
install_github("stephenslab/smashr")
```
If you are interested in replicating results from the paper, we recommendg installing smashr 1.2-7:
```
install_github("stephenslab/smashr@v1.2-7")
```
This will build the smashr package without the vignettes. To build with the vignettes, do this instead:
```
install_github("stephenslab/smashr",build_vignettes = TRUE)
```
We caution that some of the simulation examples may take a long time to run (20–30 minutes, or possibly longer). Also note that the install_github call should also install any missing packages that are required for smashr to work.
Load the smashr package, and run the smashr demo:
```
library(smashr)
demo("smashr")
```
To learn more, see the smashr package help and the smashr vignette (which you can also view here):
```
help(package = "smashr")
vignette("smashr")
```

Credits

This R package was developed by Zhengrong Xing and Matthew Stephens at the University of Chicago, with contributions from Peter Carbonetto.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.