This package provides functions to export graphics drawn with package grid to SVG format. Extra functions provide access to SVG features that are not available in standard R graphics, such as hyperlinks, animation, filters, masks, clipping paths, and gradient and pattern fills.

KPeg is a simple PEG library for Ruby. It provides an API as well as native grammar to build the grammar. KPeg supports direct left recursion of rules via the OMeta memoization technique.

METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill-reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes.

This package provides probability computation, data generation, and model estimation for fully-visible Boltzmann machines. It follows the methods described in Nguyen and Wood (2016a) <doi:10.1162/NECO_a_00813> and Nguyen and Wood (2016b) <doi:10.1109/TNNLS.2015.2425898>.

This package provides a suite of functions that allow the user to analyze A/B test data in a Bayesian framework. Intended to be a drop-in replacement for common frequentist hypothesis test such as the t-test and chi-sq test.

An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed hydrological model originally proposed by Beven and Freer (2001) <doi:10.1002/hyp.252>. The dynatop package implements code for simulating models which can be created using the dynatopGIS package.

Generate motivational quotes and Shakespearean word combinations (bardâ bits) that a user can consider for their personal projects. Each of the package functions takes two arguments, cat which default to any, and a a numeric or character seed to ensure reproducible results.

Computes shrinkage estimators for regression problems. Selects penalty parameter by minimizing bias and variance in the effect estimate, where bias and variance are estimated from the posterior predictive distribution. See Keller and Rice (2017) <doi:10.1093/aje/kwx225> for more details.

Efficiently impute large scale matrix with missing values via its unbiased low-rank matrix approximation. Our main approach is Hard-Impute algorithm proposed in <https://www.jmlr.org/papers/v11/mazumder10a.html>, which achieves highly computational advantage by truncated singular-value decomposition.

Group Bayesian Networks: This package implements the inference of group Bayesian networks based on hierarchical feature clustering, and the adaptive refinement of the grouping regarding an outcome of interest, as described in Becker et. al (2021) <doi: 10.1371/journal.pcbi.1008735>.

Simulating, visualizing and comparing tumor clonal data by using simple commands. This aims at providing a tool to help researchers to easily simulate tumor data and analyze the results of their approaches for studying the composition and the evolutionary history of tumors.

This package implements the hub graphical lasso and hub covariance graph proposal by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). Learning graphical models with hubs. Journal of Machine Learning Research 15(Oct):3297-3331.

This package implements the vine copula based kernel density estimator of Nagler and Czado (2016) <doi:10.1016/j.jmva.2016.07.003>. The estimator does not suffer from the curse of dimensionality and is therefore well suited for high-dimensional applications.

This package performs extreme value analysis at multiple locations using functions from the evd package. Supports both point-based and gridded input data using the terra package, enabling flexible looping across spatial datasets for batch processing of generalised extreme value, Gumbel fits.

Compute important quantities when we consider stochastic systems that are observed continuously. Such as, Cost model, Limiting distribution, Transition matrix, Transition distribution and Occupancy matrix. The methods are described, for example, Ross S. (2014), Introduction to Probability Models. Eleven Edition. Academic Press.

Various kinds of plots (observations, variables, correlations, weights, regression coefficients and Variable Importance in the Projection) and aids to interpretation (coefficients, Q2, correlations, redundancies) for partial least squares regressions computed with the pls package, following Tenenhaus (1998, ISBN:2-7108-0735-1).

Given a CSV file with titles and abstracts, the package creates a document-term matrix that is lemmatized and stemmed and can directly be used to train machine learning methods for automatic title-abstract screening in the preparation of a meta analysis.

This package provides utility functions for multivariate analysis (factor analysis, discriminant analysis, and others). The package is primary written for the course Multivariate analysis and for the course Computer intensive methods at the masters program of Applied Statistics at University of Ljubljana.

This package provides a programmatic interface to the OpenM++ microsimulation platform (<https://openmpp.org>). The primary goal of this package is to wrap the OpenM++ Web Service (OMS) to provide OpenM++ users a programmatic interface for the R language.

This package provides a shiny application for teaching introductory quantitative genetics and plant breeding through interactive simulations. The application relies on established plant breeding and quantitative genetic theory found in Falconer and Mackay (1996, ISBN:0582243025) and Bernardo (2010, ISBN:978-0972072427).

Estimate morphometric and gonadal size at sexual maturity for organisms, usually fish and invertebrates. It includes methods for classification based on relative growth (using principal components analysis, hierarchical clustering, discriminant analysis), logistic regression (Frequentist or Bayes), parameters estimation and some basic plots.

Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias. The package is based on the paper Solà s, M. (2018) <arXiv:1803.03333>.

This package provides functions that wrap HTML Bootstrap components code to enable the design and layout of informative landing home pages for Shiny applications. This can lead to a better user experience for the users and writing less HTML for the developer.

M-estimators of location and shape following the power family (Frahm, Nordhausen, Oja (2020) <doi:10.1016/j.jmva.2019.104569>) are provided in the case of complete data and also when observations have missing values together with functions aiding their visualization.