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.

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>.

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 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.

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).

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().

Univariate time series forecasting with STL decomposition based Extreme Learning Machine hybrid model. For method details see Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.

This package performs two-sample comparisons based on average hazard with survival weight (AHSW) or general censoring-free incidence rate (CFIR) proposed by Uno and Horiguchi (2023) <doi:10.1002/sim.9651>.

Fast enrichment analysis for locally correlated statistics via circular permutations. The analysis can be performed at multiple significance thresholds for both primary and auxiliary data sets with efficient correction for multiple testing.

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.

Statistical analysis of spatio-temporal point processes on linear networks. This packages provides tools to visualise and analyse spatio-temporal point patterns on linear networks using first- and second-order summary statistics.

This package provides a set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling.

Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation developed in Salter-Townshend and Murphy (2013) <doi:10.1016/j.csda.2012.08.004>.

This package is designed for visualization of RNA-related genomic features with respect to the landmarks of RNA transcripts, i.e., transcription starting site, start codon, stop codon and transcription ending site.

This package implements infrastructures for ontology analysis by offering efficient data structures, fast ontology traversal methods, and elegant visualizations. It provides a robust toolbox supporting over 70 methods for semantic similarity analysis.

This package extends the ggplot2 plotting system which implements a grammar of graphics. ggtree is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.

This package provides functions to estimate variance-mean dependence in count data from high-throughput nucleotide sequencing assays and test for differential expression based on a model using the negative binomial distribution.

This package conducts batch effects removal from a taxa read count table by a conditional quantile regression method. The distributional attributes of microbiome data - zero-inflation and over-dispersion, are simultaneously considered.