Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 1098 packages in 0.01 seconds

nor1mix — by Martin Maechler, 2 years ago

Normal aka Gaussian 1-d Mixture Models

Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics. Fitting to data by efficient ML (Maximum Likelihood) or traditional EM estimation.

polyclip — by Adrian Baddeley, 2 years ago

Polygon Clipping

R port of Angus Johnson's open source library 'Clipper'. Performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. Computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. Computes Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.

clusterGeneration — by Weiliang Qiu, 3 years ago

Random Cluster Generation (with Specified Degree of Separation)

We developed the clusterGeneration package to provide functions for generating random clusters, generating random covariance/correlation matrices, calculating a separation index (data and population version) for pairs of clusters or cluster distributions, and 1-D and 2-D projection plots to visualize clusters. The package also contains a function to generate random clusters based on factorial designs with factors such as degree of separation, number of clusters, number of variables, number of noisy variables.

spam — by Reinhard Furrer, 4 months ago

SPArse Matrix

Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) ; see 'citation("spam")' for details.

bookdown — by Yihui Xie, 5 months ago

Authoring Books and Technical Documents with R Markdown

Output formats and utilities for authoring books and technical documents with R Markdown.

psychometric — by Thomas D. Fletcher, 3 years ago

Applied Psychometric Theory

Contains functions useful for correlation theory, meta-analysis (validity-generalization), reliability, item analysis, inter-rater reliability, and classical utility.

emdbook — by Ben Bolker, 10 months ago

Support Functions and Data for "Ecological Models and Data"

Auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).

BHTSpack — by Ivo D. Shterev, 5 years ago

Bayesian Multi-Plate High-Throughput Screening of Compounds

Can be used for joint identification of candidate compound hits from multiple assays, in drug discovery. This package implements the framework of I. D. Shterev, D. B. Dunson, C. Chan and G. D. Sempowski. "Bayesian Multi-Plate High-Throughput Screening of Compounds", Scientific Reports 8(1):9551, 2018. This project was funded by the Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract No. HHSN272201400054C entitled "Adjuvant Discovery For Vaccines Against West Nile Virus and Influenza", awarded to Duke University and lead by Drs. Herman Staats and Soman Abraham.

palr — by Michael D. Sumner, 3 years ago

Colour Palettes for Data

Colour palettes for data, based on some well known public data sets. Includes helper functions to map absolute values to known palettes, and capture the work of image colour mapping as raster data sets.

topicmodels — by Bettina GrĂ¼n, 2 years ago

Topic Models

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.