|
kubernetes-kind
|
public |
Kubernetes IN Docker - local clusters for testing Kubernetes
|
2025-09-22 |
|
r-neldermead
|
public |
Provides several direct search optimization algorithms based on the simplex method. The provided algorithms are direct search algorithms, i.e. algorithms which do not use the derivative of the cost function. They are based on the update of a simplex. The following algorithms are available: the fixed shape simplex method of Spendley, Hext and Himsworth (unconstrained optimization with a fixed shape simplex), the variable shape simplex method of Nelder and Mead (unconstrained optimization with a variable shape simplex made), and Box's complex method (constrained optimization with a variable shape simplex).
|
2025-09-22 |
|
r-pathdiagram
|
public |
Implementation of simple functions to draw basic path diagrams just for visualization purposes.
|
2025-09-22 |
|
r-admm
|
public |
Provides algorithms to solve popular optimization problems in statistics such as regression or denoising based on Alternating Direction Method of Multipliers (ADMM). See Boyd et al (2010) <doi:10.1561/2200000016> for complete introduction to the method.
|
2025-09-22 |
|
r-rworldxtra
|
public |
High resolution vector country boundaries derived from Natural Earth data, can be plotted in rworldmap.
|
2025-09-22 |
|
r-ggbump
|
public |
A geom for ggplot to create bump plots. Can be good to use for showing rank over time.
|
2025-09-22 |
|
r-clustvarsel
|
public |
Variable selection for Gaussian model-based clustering as implemented in the 'mclust' package. The methodology allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting 'mclust' models. By default the algorithm uses a sequential search, but parallelisation is also available.
|
2025-09-22 |
|
eqcorrscan
|
public |
Detection and analysis of repeating and near-repeating earthquakes
|
2025-09-22 |
|
adaptivecpp
|
public |
The independent, community-driven platform for heterogeneous programming in C++
|
2025-09-22 |
|
py-cid
|
public |
Self-describing content-addressed identifiers for distributed systems
|
2025-09-22 |
|
jaxlib
|
public |
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
|
2025-09-22 |
|
coverage
|
public |
Code coverage measurement for Python
|
2025-09-22 |
|
r-leaflet.minicharts
|
public |
Add and modify small charts on an interactive map created with package 'leaflet'. These charts can be used to represent at same time multiple variables on a single map.
|
2025-09-22 |
|
r-contrast
|
public |
One degree of freedom contrasts for 'lm', 'glm', 'gls', and 'geese' objects.
|
2025-09-22 |
|
r-gpca
|
public |
This package implements guided principal components analysis for the detection of batch effects in high-throughput data.
|
2025-09-22 |
|
stir
|
public |
Software for Tomographic Image Reconstruction
|
2025-09-22 |
|
r-baguette
|
public |
Tree- and rule-based models can be bagged using this package and their predictions equations are stored in an efficient format to reduce the model objects size and speed.
|
2025-09-22 |
|
r-fdboost
|
public |
Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm.
|
2025-09-22 |
|
r-ssc
|
public |
Provides a collection of self-labeled techniques for semi-supervised classification. In semi-supervised classification, both labeled and unlabeled data are used to train a classifier. This learning paradigm has obtained promising results, specifically in the presence of a reduced set of labeled examples. This package implements a collection of self-labeled techniques to construct a classification model. This family of techniques enlarges the original labeled set using the most confident predictions to classify unlabeled data. The techniques implemented can be applied to classification problems in several domains by the specification of a supervised base classifier. At low ratios of labeled data, it can be shown to perform better than classical supervised classifiers.
|
2025-09-22 |
|
flake8-black
|
public |
Extension for flake8 for validating Python code style using black
|
2025-09-22 |
|
r-rslurm
|
public |
Functions that simplify submitting R scripts to a 'Slurm' workload manager, in part by automating the division of embarrassingly parallel calculations across cluster nodes.
|
2025-09-22 |
|
r-snpls
|
public |
Tools for performing variable selection in three-way data using N-PLS in combination with L1 penalization, Selectivity Ratio and VIP scores. The N-PLS model (Rasmus Bro, 1996 <DOI:10.1002/(SICI)1099-128X(199601)10:1%3C47::AID-CEM400%3E3.0.CO;2-C>) is the natural extension of PLS (Partial Least Squares) to N-way structures, and tries to maximize the covariance between X and Y data arrays. The package also adds variable selection through L1 penalization, Selectivity Ratio and VIP scores.
|
2025-09-22 |
|
r-coursekata
|
public |
Easily install and load all packages and functions used in 'CourseKata' courses. Aid teaching with helper functions and augment generic functions to provide cohesion between the network of packages. Learn more about 'CourseKata' at <https://coursekata.org>.
|
2025-09-22 |
|
uproot
|
public |
ROOT I/O in pure Python and NumPy.
|
2025-09-21 |
|
r-openair
|
public |
Tools to analyse, interpret and understand air pollution data. Data are typically hourly time series and both monitoring data and dispersion model output can be analysed. Many functions can also be applied to other data, including meteorological and traffic data.
|
2025-09-21 |
