Tests coefficients with sandwich estimator of variance and with small samples. Regression types supported are gee, linear regression, and conditional logistic regression.

Density, distribution function, quantile function and random generation for the Truncated Generalised Gamma Distribution (also in log10(x) and ln(x) space).

Bindings to system utilities found in most Unix systems such as POSIX functions which are not part of the Standard C Library.

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

This R package is providing functions to perform geneset significance analysis over simple cross-sectional data between 2 and 5 phenotypes of interest.

This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data.

This package provides software for the book Spectral Analysis for Physical Applications, Donald B. Percival and Andrew T. Walden, Cambridge University Press, 1993.

This package provides tools to read, write, create, and manipulate DESCRIPTION files. It is intended for packages that create or manipulate other packages.

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>.

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.

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.

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

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

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

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

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

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

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

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

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

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

This package provides the Arctic Ice Studio's Nord and Group of Seven inspired colour palettes for use with ggplot2 via custom functions.

Fits two-dimensional data by means of orthogonal nonlinear least-squares using Levenberg-Marquardt minimization and provides functionality for fit diagnostics and plotting.

Simultaneous inference procedures for high-dimensional linear models as described by Zhang, X., and Cheng, G. (2017) <doi:10.1080/01621459.2016.1166114>.