Perform tasks commonly encountered when preparing and analysing demographic data. Some functions are intended for end users, and others for developers. Includes functions for working with life tables.

This package provides methods for spatial predictive modeling, especially for spatial distribution models. This includes algorithms for model fitting and prediction, as well as methods for model evaluation.

An engaging collection of datasets from Portland Parks and Recreation. The city of Portland inventoried every tree in over 170 parks and along the streets in 96 neighborhoods.

In Shiny apps, it is sometimes useful to store information on a particular item in a tooltip. Prompter allows you to easily create such tooltips, using Hint.css'.

Read, process, fit, and analyze photosynthetic gas exchange measurements. Documentation is provided by several vignettes; also see Lochocki, Salesse-Smith, & McGrath (2025) <doi:10.1111/pce.15501>.

Bootstrapped response and correlation functions, seasonal correlations and evaluation of reconstruction skills for use in dendroclimatology and dendroecology, see Zang and Biondi (2015) <doi:10.1111/ecog.01335>.

This package provides numerous functions to fill data. These can be applied either to missing or skewed data. The functions are designed within the scope of Student Analytics.

This package provides tools for interactive data exploration built using shiny'. Includes apps for descriptive statistics, visualizing probability distributions, inferential statistics, linear regression, logistic regression and RFM analysis.

The x3p file format is specified in ISO standard 5436:2000 to describe 3d surface measurements. x3ptools allows reading, writing and basic modifications to the 3D surface measurements.

We provide a number of algorithms to estimate fundamental statistics including Fréchet mean and geometric median for manifold-valued data. Also, C++ header files are contained that implement elementary operations on manifolds such as Sphere, Grassmann, and others. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> if you are interested in statistics on manifolds, and Absil et al (2007, ISBN:9780691132983) on computational aspects of optimization on matrix manifolds.

This package creates a header only package to link to the CGAL (Computational Geometry Algorithms Library) header files in Rcpp'. There are a variety of potential uses for the software such as Hilbert sorting, K-D Tree nearest neighbors, and convex hull algorithms. For more information about how to use the header files, see the CGAL documentation at <https://www.cgal.org>. Currently downloads version 6.1 of the CGAL header files.

The package contains functions to perform normalization of high-throughput qPCR data. Basic functions for processing raw Ct data plus functions to generate diagnostic plots are also available.

This package implements different performance measures for classification and ranking tasks. Area under curve (AUC), precision at a given recall, F-score for single and multiple classes are available.

ChIPComp implements a statistical method for quantitative comparison of multiple ChIP-seq datasets. It detects differentially bound sharp binding sites across multiple conditions considering matching control in ChIP-seq datasets.

This package implements a parametric bootstrap test and a Kenward Roger modification of F-tests for linear mixed effects models and a parametric bootstrap test for generalized linear mixed models.

In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics that are not provided by base R methods related to model fitting.

This package implements general purpose tools, such as functions for sampling and basic manipulation of Brazilian lawsuits identification number. It also implements functions for text cleaning, such as accentuation removal.

MSpec is a specialized framework that is syntax-compatible with RSpec 2 for basic features. MSpec contains additional features that assist in writing specs for Ruby implementations in ruby/spec.

Lemon is a unit testing framework that enforces highly formal case-to-class and unit-to-method test construction. This enforcement can help focus concern on individual units of behavior.

An implementation of the additive polynomial (AP) design matrix. It constructs and appends an AP design matrix to a data frame for use with longitudinal data subject to seasonality.

Plot stacked areas and confidence bands as filled polygons, or add polygons to existing plots. A variety of input formats are supported, including vectors, matrices, data frames, formulas, etc.

This package provides functions streamlining the data analysis workflow: Outsourcing data import, renaming and type casting to a *.csv. Manipulating imputed datasets and fitting models on them. Summarizing models.

Differential Item Functioning (DIF) Analysis with shiny application interfaces. You can run the functions in this package without any arguments and perform your DIF analysis using user-friendly interfaces.

This package provides a grammar of data manipulation with data.table', providing a consistent a series of utility functions that help you solve the most common data manipulation challenges.