Download and plot education specific demographic data from the Wittgenstein Centre for Demography and Human Capital Data Explorer <http://dataexplorer.wittgensteincentre.org/>.

Helps to fit thermal performance curves (TPCs). rTPC contains 26 model formulations previously used to fit TPCs and has helper functions to set sensible start parameters, upper and lower parameter limits and estimate parameters useful in downstream analyses, such as cardinal temperatures, maximum rate and optimum temperature. See Padfield et al. (2021) <doi:10.1111/2041-210X.13585>.

This package provides functions to deal with binary classification problems in the presence of imbalanced classes. Synthetic balanced samples are generated according to ROSE (Menardi and Torelli, 2013). Functions that implement more traditional remedies to the class imbalance are also provided, as well as different metrics to evaluate a learner accuracy. These are estimated by holdout, bootstrap or cross-validation methods.

R parallel implementation of Local Outlier Factor(LOF) which uses multiple CPUs to significantly speed up the LOF computation for large datasets. (Note: The overall performance depends on the computers especially the number of the cores).It also supports multiple k values to be calculated in parallel, as well as various distance measures in addition to the default Euclidean distance.

RtMidi is a set of C++ classes (RtMidiIn, RtMidiOut, and API specific classes) that provide a common cross-platform API for realtime MIDI input/output.

RtMidi is a set of C++ classes (RtMidiIn, RtMidiOut, and API specific classes) that provide a common cross-platform API for realtime MIDI input/output.

This package provides data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.

This package provides a simple, consistent interface to working with XML files in R. It is built on top of the libxml2 C library.

This package provides an R module for display of maps. Projection code and larger maps are in separate packages (mapproj and mapdata).

This package is desgined to perform statistical analysis to identify statistically significant differentially bound regions between multiple groups of ChIP-seq dataset.

The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI).

This package provides a summarization method to estimate allele-specific copy number signals for Affymetrix SNP microarrays using non-negative matrix factorization (NMF).

Bayesian variable selection methods for analyzing the structure of a Markov random field model for a network of binary and/or ordinal variables.

Fast Bayesian inference of marginal and conditional independence structures from high-dimensional data. Leday and Richardson (2019), Biometrics, <doi:10.1111/biom.13064>.

Retorna detalhes de dados de CEPs brasileiros, bairros, logradouros e tal. (Returns info of Brazilian postal codes, city names, addresses and so on.).

Detect and quantify community assembly processes using trait values of individuals or populations, the T-statistics and other metrics, and dedicated null models.

Statistical tools for environmental and ecological surveys. Simulation-based power and precision analysis; detection probabilities from different survey designs; visual fast count estimation.

API wrapper to download statistical information from the Economic Statistics System (ECOS) of the Bank of Korea <https://ecos.bok.or.kr/api/#/>.

We implement the Fast Covariance Estimation for Sparse Functional Data paper published in Statistics and Computing <doi: 10.1007/s11222-017-9744-8>.

Full descriptive statistics, physical description of sediment, metric or phi sieves. Includes a Shiny web application for interactive grain size analysis and visualization.

Fits latent space models for single networks and hierarchical latent space models for ensembles of networks as described in Sweet, Thomas & Junker (2013).

HAR files are generated and consumed by GEMPACK applications. This package reads/writes HAR files (and SL4 files) directly using basic R functions.

Datasets and code examples that accompany our book Visser & Speekenbrink (2021), "Mixture and Hidden Markov Models with R", <https://depmix.github.io/hmmr/>.

This package provides functions and datasets from Hilbe, J.M., and Robinson, A.P. 2013. Methods of Statistical Model Estimation. Chapman & Hall / CRC.