This package provides density, distribution function, quantile function and random generation for the Generalized Gamma proposed in Stacy, E. W. (1962) <doi:10.1214/aoms/1177704481>.

Camv-rnd is a viewer for PCB supporting gerber, excellon and g-code. It is part of the RiNgDove EDA suite.

For instructions, check <https://github.com/Hzhang-ouce/ARTofR>. This is a wrapper of bannerCommenter', for inserting neat comments, headers and dividers.

Create a hierarchical acoustic event species classifier out of multiple call type detectors as described in Rankin et al (2017) <doi:10.1111/mms.12381>.

This package provides tools for assessing data quality, performing exploratory analysis, and semi-automatic preprocessing of messy data with change tracking for integral dataset cleaning.

Integrated differential expression (DE) and differential co-expression (DC) analysis on gene expression data based on DECODE (DifferEntial CO-expression and Differential Expression) algorithm.

The cointegration based support vector regression model enables researchers to use data obtained from the cointegrating vector as input in the support vector regression model.

Wrapper for the ggplot2 package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.

Four graph-based tests are provided for testing whether two samples are from the same distribution. It works for both continuous data and discrete data.

Design of group sequential trials, including non-binding futility analysis at multiple time points (Gallo, Mao, and Shih, 2014, <doi:10.1080/10543406.2014.932285>).

Automatically choose an appropriate chart type based on the types and values in the data. Apply more accessible default styling and colours to ggplot2 charts.

This package provides a set of fast, chainable image-processing operations which are applicable to images of two, three or four dimensions, particularly medical images.

This package provides datasets for the book "Introduction to Statistical Data Analysis for the Life Sciences, Second edition" by Ekstrøm and Sørensen (2014).

Introduces in-sample, out-of-sample, pseudo out-of-sample, and benchmark model forecast tests and a new class for working with forecast data, Forecast.

Predicts ploidal level from sequence data using site-based heterozygosity and a mixture models approach. See Gaynor et al. (2024) <doi:10.1002/aps3.11606>.

Fast and Accurate Randomized Singular Value Decomposition (RSVD) methods proposed in the PCAone paper by Li (2023) <https://genome.cshlp.org/content/33/9/1599>.

This package provides functions for obtaining the density, random deviates and maximum likelihood estimates of the Poisson lognormal distribution and the bivariate Poisson lognormal distribution.

Performant interactive scatterplot for ~ 1 million points. Zoom, pan, and pick points. Includes tooltips, labels, a grid overlay, legend, and coupled interactions across multiple plots.

Confidence intervals and point estimation for R under various parametric model assumptions; likelihood inference based on classical first-order approximations and higher-order asymptotic procedures.

Create PX-files from scratch or read and modify existing ones. Includes a function for every PX keyword, making metadata manipulation simple and human-readable.

Compare directories flexibly (by date, content, or both) and synchronize files efficiently, with asymmetric and symmetric modes, helper tools, and visualization support for file management.

Probability functions, family for glm() and Stan code for working with the unifed distribution (Quijano Xacur, 2019; <doi:10.1186/s40488-019-0102-6>).

This package provides R functions to draw lines and curves with the width of the curve allowed to vary along the length of the curve.

This package provides a convenience wrapper that uses the rmarkdown package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites or email. reprex also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.