libopenh264-8
OpenH264 Video Codec
OpenH264 is a codec library which supports H.264 encoding and decoding.
It is suitable for use in real time applications such as WebRTC.
python3-pyopenuv
Library to access UV and ozone data from OpenUV
This library allows access to UV and ozone data from the OpenUV API. It
provides functions to retrieve current UV index, forecasted UV information,
and details about safe exposure times for different skin types. Additionally,
it includes features to get the maximum UV index for the day, the current
ozone level, and a protection window indicating when sunblock protection
should be used.
debian-edu-router-fai
FAI config space (et al.) for the Debian Edu Router system
The Debian Edu Router project provides installation routines for
setting up a network router for the Debian Edu system (or for other
school networks).
debian-edu-router-plugin.content-filter
Debian Edu Router Plugin for content filtering
The Debian Edu Router project provides installation routines for
setting up a network router for the Debian Edu system (or for other
school networks).
r-cran-gap.datasets
Datasets for 'gap'
Datasets associated with the 'gap' package. Currently,
it includes an example data for regional association
plot (CDKN), an example data for a genomewide association
meta-analysis (OPG), data in studies of Parkinson's diease (PD),
ALHD2 markers and alcoholism (aldh2), APOE/APOC1 markers
and Schizophrenia (apoeapoc), cystic fibrosis (cf), a
Olink/INF panel (inf1), Manhattan plots with (hr1420, mhtdata)
and without (w4) gene annotations.
r-cran-qgam
Smooth Additive Quantile Regression Models
Smooth additive quantile regression models, fitted using the methods of
Fasiolo et al. (2020) <doi:10.1080/01621459.2020.1725521>. See Fasiolo
at al. (2021) <doi:10.18637/jss.v100.i09> for an introduction to the
package. Differently from 'quantreg', the smoothing parameters are
estimated automatically by marginal loss minimization, while the
regression coefficients are estimated using either PIRLS or Newton
algorithm. The learning rate is determined so that the Bayesian credible
intervals of the estimated effects have approximately the correct
coverage. The main function is qgam() which is similar to gam() in
'mgcv', but fits non-parametric quantile regression models.