libmrpt-graphslam2.4

Mobile Robot Programming Toolkit - graphslam library

The Mobile Robot Programming Toolkit (MRPT) is an extensive, cross-platform, and open source C++ library aimed to help robotics researchers to design and implement algorithms in the fields of Simultaneous Localization and Mapping (SLAM), computer vision, and motion planning (obstacle avoidance).

python3-kiwi-boxed-plugin

KIWI plugin to provide self contained build support

The KIWI boxed plugin provides support for self contained building of images based on fast booting VM images.

dh-nss

debhelper addon to inject NSS services into /etc/nsswitch.conf

The` dh_installnss` debhelper provides a declarative way for NSS-related packages to express how the NSS services they supply should be installed and in which order.

libjim0.81

small-footprint implementation of Tcl - shared library

Jim is an opensource small-footprint implementation of the Tcl programming language. It implements a large subset of Tcl and adds new features like references with garbage collection, closures, built-in Object Oriented Programming system, Functional Programming commands, first-class arrays and UTF-8 support. All this with a binary size of about 100-200kB (depending upon selected options).

libopencv-core406t64

computer vision core library

This package contains the OpenCV (Open Computer Vision) core runtime libraries.

r-cran-gb2

GNU R generalized beta distribution of the second kind

Properties, Likelihood, Estimation Package GB2 explores the Generalized Beta distribution of the second kind. Density, cumulative distribution function, quantiles and moments of the distributions are given. Functions for the full log-likelihood, the profile log-likelihood and the scores are provided. Formulas for various indicators of inequality and poverty under the GB2 are implemented. The GB2 is fitted by the methods of maximum pseudo-likelihood estimation using the full and profile log-likelihood, and non-linear least squares estimation of the model parameters. Various plots for the visualization and analysis of the results are provided. Variance estimation of the parameters is provided for the method of maximum pseudo-likelihood estimation. A mixture distribution based on the compounding property of the GB2 is presented (denoted as "compound" in the documentation). This mixture distribution is based on the discretization of the distribution of the underlying random scale parameter. The discretization can be left or right tail. Density, cumulative distribution function, moments and quantiles for the mixture distribution are provided. The compound mixture distribution is fitted using the method of maximum pseudo- likelihood estimation. The fit can also incorporate the use of auxiliary information. In this new version of the package, the mixture case is complemented with new functions for variance estimation by linearization and comparative density plots.