This is a meta-package designed to support the installation of Rmosek (>= 6.0) and bring the optimization facilities of MOSEK (>= 6.0) to the R-language. The interface supports large-scale optimization of many kinds: Mixed-integer and continuous linear, second-order cone, exponential cone and power cone optimization, as well as continuous semidefinite optimization. Rmosek and the R-language are open-source projects. MOSEK is a proprietary product, but unrestricted trial and academic licenses are available.

Rserve acts as a socket server (TCP/IP or local sockets) which allows binary requests to be sent to R. Every connection has a separate workspace and working directory. Client-side implementations are available for popular languages such as C/C++ and Java, allowing any application to use facilities of R without the need of linking to R code. Rserve supports remote connection, user authentication and file transfer. A simple R client is included in this package as well.

rg is an Emacs search package based on the ripgrep command line tool. It allows one to interactively search based on the editing context then refine or modify the search results.

Nix seeks to provide friendly bindings to various *nix platform APIs. The goal is to not provide a 100% unified interface, but to unify what can be while still providing platform specific APIs.

R client for Bender Hyperparameters optimizer : <https://bender.dreem.com> The R client allows you to communicate with the Bender API and therefore submit some new trials within your R script itself.

This package provides a way to reduce model objects to necessary parts, making them easier to work with, store, share and simulate multiple values for new responses while allowing for parameter uncertainty.

The Bloom Detecting Algorithm enables the detection of blooms within a time series of species abundance and extracts 22 phenological variables. For details, see Karasiewicz et al. (2022) <doi:10.3390/jmse10020174>.

This package provides a fast and intuitive batch effect removal tool for single-cell data. BBKNN is originally used in the scanpy python package, and now can be used with Seurat seamlessly.

R/C++ implementation of the model proposed by Primiceri ("Time Varying Structural Vector Autoregressions and Monetary Policy", Review of Economic Studies, 2005), with functionality for computing posterior predictive distributions and impulse responses.

The implementation of bias-corrected sandwich variance estimators for the analysis of cluster randomized trials with time-to-event outcomes using the marginal Cox model, proposed by Wang et al. (under review).

Fast and memory-efficient (or cheap') tools to facilitate efficient programming, saving time and memory. It aims to provide cheaper alternatives to common base R functions, as well as some additional functions.

Evaluates the performance of binary classifiers. Computes confusion measures (TP, TN, FP, FN), derived measures (TPR, FDR, accuracy, F1, DOR, ..), and area under the curve. Outputs are well suited for nested dataframes.

Chat with large language models from a range of providers including Claude <https://claude.ai>, OpenAI <https://chatgpt.com>, and more. Supports streaming, asynchronous calls, tool calling, and structured data extraction.

This package implements the most common Gaussian process (GP) models using Laplace and expectation propagation (EP) approximations, maximum marginal likelihood (or posterior) inference for the hyperparameters, and sparse approximations for larger datasets.

To create the multiple polygonal point layer for easily discernible shapes, we developed the package, it is like the geom_point of ggplot2'. It can be used to draw the scatter plot.

This package provides probability functions (cumulative distribution and density functions), simulation function (Gumbel copula multivariate simulation) and estimation functions (Maximum Likelihood Estimation, Inference For Margins, Moment Based Estimation and Canonical Maximum Likelihood).

Command-line and shiny GUI implementation of the GenEst models for estimating bird and bat mortality at wind and solar power facilities, following Dalthorp, et al. (2018) <doi:10.3133/tm7A2>.

This package implements various tools for storing and analyzing hypergraphs. Handles basic undirected, unweighted hypergraphs, and various ways of creating hypergraphs from a number of representations, and converting between graphs and hypergraphs.

Simulate and implement early phase two-stage adaptive dose-finding design for binary and quasi-continuous toxicity endpoints. See Chiuzan et al. (2018) for further reading <DOI:10.1080/19466315.2018.1462727>.

This package provides facilities of general to specific model selection for exogenous regressors in 2SLS models. Furthermore, indicator saturation methods can be used to detect outliers and structural breaks in the sample.

For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.

This package provides a collection of useful functions not found anywhere else, mainly for programming: Pretty intervals, generalized lagged differences, checking containment in an interval, and an alternative interface to assign().

This package provides a function to detect and trim outliers in Gaussian mixture model-based clustering using methods described in Clark and McNicholas (2024) <doi:10.1007/s00357-024-09473-3>.

Genomic and multi-environmental soybean data. Soybean Nested Association Mapping (SoyNAM) project dataset funded by the United Soybean Board (USB). BLUP function formats data for genome-wide prediction and association analysis.