This package provides a set of functions for weather and climate data manipulation, and other helper functions, to support dynamic ecological modeling, particularly crop and crop disease modeling.

This package contains several functions for statistical data analysis; e.g. for sample size and power calculations, computation of confidence intervals and tests, and generation of similarity matrices.

An implementation of a Neural Network using the Levenberg-Marquardt optimization from minpack.lm', ideal for small datasets. For more details see Moré (1978) <doi:10.1007/BFb0067700>.

Stacking arrays according to dimension names, subset-aware splitting and mapping of functions, intersecting along arbitrary dimensions, converting to and from data.frames, and many other helper functions.

Represent network or igraph objects whose vertices can be represented by features in an sf object as a network graph surmising a sf plot. Fits into ggplot2 grammar.

Body Shape and related measurements from the US National Health and Nutrition Examination Survey (NHANES, 1999-2004). See <https://www.cdc.gov/nchs/nhanes/index.html> for details.

Presentation of a new goodness-of-fit normality test based on the Lilliefors method. For details on this method see: Sulewski (2019) <doi:10.1080/03610918.2019.1664580>.

Bayesian hierarchical methods for pathway analysis of genomewide association data: Normal/Bayes factors and Sparse Normal/Adaptive lasso. The Frequentist Fisher's product method is included as well.

Games that can be played in the R console. Includes coin flip, hangman, jumble, magic 8 ball, poker, rock paper scissors, shut the box, spelling bee, and 2048.

Gives design points from a sequential full factorial-based Latin hypercube design, as described in Duan, Ankenman, Sanchez, and Sanchez (2015, Technometrics, <doi:10.1080/00401706.2015.1108233>).

This package implements the smooth LASSO estimator for the function-on-function linear regression model described in Centofanti et al. (2022) <doi:10.1016/j.csda.2022.107556>.

Evolutionary reconstruction based on substitutions and insertion-deletion (indels) analyses in a distance-based framework as described in Muñoz-Pajares (2013) <doi:10.1111/2041-210X.12118>.

This package provides functions for interacting directly with the Taiwan Economic Journal API to offer data in R. For more information go to <https://api.tej.com.tw>.

Tree Ring Analysis of Disturbance Events in R (TRADER) package provides functions for disturbance reconstruction from tree-ring data, e.g. boundary line, absolute increase, growth averaging methods.

This package provides a suite of statistics for identifying areas of the genome under selective pressure. See Jacobs, Sluckin and Kivisild (2016) <doi:10.1534/genetics.115.185900>.

Some basic features of MUMPS are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: PORD, METIS, SCOTCH.

An implementation of functionalities to transform directed graphs that are bound to a set of known forbidden paths. There are several transformations, following the rules provided by Villeneuve and Desaulniers (2005) <doi: 10.1016/j.ejor.2004.01.032>, and Hsu et al. (2009) <doi: 10.1007/978-3-642-03095-6_60>. The resulting graph is generated in a data-frame format. See rsppfp website for more information, documentation an examples.

This package implements the t-walk algorithm, a general-purpose, self-adjusting Markov Chain Monte Carlo (MCMC) sampler for continuous distributions as described by Christen & Fox (2010) <doi:10.1214/10-BA603>. The t-walk requires no tuning and is robust for a wide range of target distributions, including high-dimensional and multimodal problems. This implementation includes an option for running multiple chains in parallel to accelerate sampling and facilitate convergence diagnostics.

This package lets you plot model surfaces for a wide variety of models using partial dependence plots and other techniques. Also plot model residuals and other information on the model.

This package provides Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

This package provides methods and algorithms for discrete optimization, e.g. knapsack and subset sum procedures, derivative-free Nelder-Mead and Hooke-Jeeves minimization, and some (evolutionary) global optimization functions.

This package provides an all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

This package provides tools for exploratory data analysis and data visualization of biological sequence (DNA and protein) data. It also includes utilities for sequence data management under the ACNUC system.

Visualisation of peptide isotopic peaks and SIP peptide spectra match (PSM). Filtration of high quality PSM. Accurate isotopic abundance calculation of peptide and metabolites. Visualisation of SIP proteomics results.