LPBkg
Detecting New Signals under Background Mismodelling
Given a postulated model and a set of data, the comparison density is estimated and the deviance test is implemented in order to assess if the data distribution deviates significantly from the postulated model. Finally, the results are summarized in a CD-plot as described in Algeri S. (2019) doi:10.48550/arXiv.1906.06615.
- Version1.2
- R version≥ 2.0.1
- LicenseGPL-3
- Needs compilation?No
- Last release10/04/2019
Team
Sara Algeri
Haoran Liu
Insights
Last 30 days
This package has been downloaded 200 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,933 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 31 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports2 packages
- Reverse Imports1 package