This package provides functions and a graphical user interface for graphical described multiple test procedures.

Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.

This package provides a variety of functions useful for data analysis, selection, manipulation, and graphics.

This package implements likelihood inference based on higher order approximations for linear nonnormal regression models.

An implementation of the pediatric complex chronic conditions (CCC) classification system using R and C++.

Inference and visualize gene regulatory network based on single-cell RNA sequencing pseudo-time information.

This package provides functions and Datasets from Lohr, S. (1999), Sampling: Design and Analysis, Duxbury.

The sparse principal component regression is computed. The regularization parameters are optimized by cross-validation.

Statistical interpretation of forensic glass transfer (Simulation of the probability distribution of recovered glass fragments).

This package implements Python-style zip for R. Is a more flexible version of cbind.

Selects one model with variable selection FDR controlled at a specified level. A q-value for each potential variable is also returned. The input, variable selection counts over many bootstraps for several levels of penalization, is modeled as coming from a beta-binomial mixture distribution.

Conduct simulations of the Response Adaptive Block Randomization (RABR) design to evaluate its type I error rate, power and operating characteristics for binary and continuous endpoints. For more details of the proposed method, please refer to Zhan et al. (2021) <doi:10.1002/sim.9104>.

Rbec is a adapted version of DADA2 for analyzing amplicon sequencing data from synthetic communities (SynComs), where the reference sequences for each strain exists. Rbec can not only accurately profile the microbial compositions in SynComs, but also predict the contaminants in SynCom samples.

Resolve the dependency graph of R packages at a specific time point based on the information from various R-hub web services <https://blog.r-hub.io/>. The dependency graph can then be used to reconstruct the R computational environment with Rocker <https://rocker-project.org>.

Assists in the manipulation and processing of linear features with the help of the sf package. Makes use of linear referencing to extract data from most shape files. Reference for this packages methods: Albeke, S.E. et al. (2010) <doi:10.1007/s10980-010-9528-4>.

Implements an efficient multi-locus mixed-model approach for genome-wide association studies in structured populations.

This package provides tools for large-scale identification and advanced visualization of sets of conserved noncoding elements.

This package provides tools for the computation of the matrix exponential, logarithm, square root, and related quantities.

This package provides tools to fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.

This is an R package for dimension reduction based on finite Gaussian mixture modeling of inverse regression.

This package provides the means to plot ggplot2 graphs in the style of the XKCD web comic.

This package implements an empirical Bayes approach for large-scale hypothesis testing and false discovery rate estimation.

This package provides numerical simulations, and visualizations, of Hubbell's Unified Neutral Theory of Biodiversity (UNTB).

Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.