This package implements the Differential Evolution algorithm. This algorithm is used for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of DifferentialEvolution in DEoptim interfaces with C code for efficiency.
This package contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off-error-free sum and cumsum, etc.
This package provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. It uses a trans-dimensional Markov Chain Monte Carlo (MCMC) approach based on a continuous-time birth-death process.
This package provides an implementation of multiscale bootstrap resampling for assessing the uncertainty in hierarchical cluster analysis. It provides an AU (approximately unbiased) P-value as well as a BP (bootstrap probability) value for each cluster in a dendrogram.
This package interacts with a suite of web services for chemical information. Sources include: Alan Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver, ChEBI, Chemical Translation Service, ChemSpider, ETOX, Flavornet, NIST Chemistry WebBook, OPSIN, PubChem, SRS, Wikidata.
This is an extension of the testthat package that lets you add parameters to your unit tests. Parameterized unit tests are often easier to read and more reliable, since they follow the DNRY (do not repeat yourself) rule.
Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).
The goal of this package is to generate an attractive and useful website from a source package. pkgdown converts your documentation, vignettes, README file, and more to HTML making it easy to share information about your package online.
The main function biclust() provides several algorithms to find biclusters in two-dimensional data, spectral, plaid model, xmotifs, and bimax. In addition, the package provides methods for data preprocessing (normalization and discretization), visualization, and validation of bicluster solutions.
Common techinical complications such as clogging can result in spurious events and fluorescence intensity shifting, flowCut is designed to detect and remove technical artifacts from your data by removing segments that show statistical differences from other segments.
Bedgraph files generated by Bisulfite pipelines often come in various flavors. Critical downstream step requires summarization of these files into methylation/coverage matrices. This step of data aggregation is done by Methrix, including many other useful downstream functions.
Posterior distribution in the Black-Litterman model is computed from a prior distribution given in the form of a time series of asset returns and a continuous distribution of views provided by the user as an external function.
Data sets of the Spanish National Forest Inventory <https://www.miteco.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible.html> are processed to compute tree metrics and statistics. Function metrics2Vol() controls most of the routines.
This package provides a client for cryptocurrency exchange BitMEX <https://www.bitmex.com/> including the ability to obtain historic trade data and place, edit and cancel orders. BitMEX's Testnet and live API are both supported.
Preprocessing tools and biodiversity measures (species abundance, species richness, population heterogeneity and sensitivity) for analysing marine benthic data. See Van Loon et al. (2015) <doi:10.1016/j.seares.2015.05.002> for an application of these tools.
Extends the Cox model to events with more than one causes. Also supports random and fixed effects, tied events, and time-varying variables. Model details are provided in Peng et al. (2018) <doi:10.1509/jmr.14.0643>.
Utilities to make your clinical collaborations easier if not fun. It contains functions for designing studies such as Simon 2-stage and group sequential designs and for data analysis such as Jonckheere-Terpstra test and estimating survival quantiles.
An investigative tool designed to help users visualize correlations between variables in their datasets. This package aims to provide an easy and effective way to explore and visualize these correlations, making it easier to interpret and communicate results.
This package provides a programmatic interface to the Chromosome Counts Database (<https://ccdb.tau.ac.il/>), Rice et al. (2014) <doi:10.1111/nph.13191>. This package is part of the ROpenSci suite (<https://ropensci.org>).
This package provides a set of functions to solve Erlang-C model. The Erlang C formula was invented by the Danish Mathematician A.K. Erlang and is used to calculate the number of advisors and the service level.
Computes alpha and beta diversity metrics using concurrent C threads. Metrics include UniFrac', Faith's phylogenetic diversity, Bray-Curtis dissimilarity, Shannon diversity index, and many others. Also parses newick trees into phylo objects and rarefies feature tables.
This package provides a collection of small functions useful for epidemics analysis and infectious disease modelling. This includes computation of basic reproduction numbers from growth rates, generation of hashed labels to anonymize data, and fitting discretized Gamma distributions.
Different evidential classifiers, which provide outputs in the form of Dempster-Shafer mass functions. The methods are: the evidential K-nearest neighbor rule, the evidential neural network, radial basis function neural networks, logistic regression, feed-forward neural networks.
This package provides Regional (Brazil, 2020) and Multi-Regional (World, 2000) input-output matrices for R. This package serves as a data-only companion to the fio package, facilitating input-output analysis by providing standardized R6 data objects.