libfreecad-python3-0.20

Extensible Open Source CAx program - Python 3 library files

FreeCAD is an Open Source CAx RAD based on OpenCasCade, Qt and Python. It features some key concepts like macro recording, workbenches, ability to run as a server and dynamically loadable application extensions and it is designed to be platform independent.

libweasel-perl

PHP's Mink inspired multi-protocol web-testing library for Perl

Weasel abstracts away the differences between the various web-driver protocols, like the Mink project does for PHP.

librnd4-pixmap

Import and export pixmap images.

Low level support for png/jpeg/gif export plugins, low level import pixmap objects using libgd.

libxcb-cursor0

utility libraries for X C Binding -- cursor

This package contains the library files needed to run software using libxcb-cursor, providing port of Xlib's libXcursor functions.

libcbor0.10

library for parsing and generating CBOR (RFC 7049)

CBOR is a general-purpose schema-less binary data format, defined in RFC 7049. This package provides a C library for parsing and generating CBOR. The main features are:

r-cran-brglm2

GNU R bias reduction in generalized linear models

Estimation and inference from generalized linear models based on various methods for bias reduction and maximum penalized likelihood with powers of the Jeffreys prior as penalty. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias- reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2017) <doi:10.1093/biomet/asx046>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <https://www.jstor.org/stable/2345592>. See Kosmidis et al (2020) <doi:10.1007/s11222-019-09860-6> for more details. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses (both ordinal and nominal), the adjusted score approaches to mean and media bias reduction have been found to return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi- complete separation; see Kosmidis and Firth, 2020 <doi:10.1093/biomet/asaa052>, for a proof for mean bias reduction in logistic regression).