All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos <https://OTexts.com/fpp3/>. All packages required to run the examples are also loaded. Additional data sets not used in the book are also included.

Implementation of the Future API <doi:10.32614/RJ-2021-048> on top of the batchtools package. This allows you to process futures, as defined by the future package, in parallel out of the box, not only on your local machine or ad-hoc cluster of machines, but also via high-performance compute ('HPC') job schedulers such as LSF', OpenLava', Slurm', SGE', and TORQUE / PBS', e.g. y <- future.apply::future_lapply(files, FUN = process)'.

Analysis of Fluorescence Recovery After Photobleaching (FRAP) experiments using nonlinear mixed-effects regression models and analysis of the results. FRApp is not limited to the analysis of FRAP experiments only. Any nonlinear mixed-effects models with an asymptotic exponential functional relationship to hierarchical data in various domains can be fitted. The analysis of data available in the package is presented in Di Credico, G., Pelucchi, S., Pauli, F. et al. (2025) <doi:10.1038/s41598-025-87154-w>.

An implementation of revised functional regression models for multiple genetic variation data, such as single nucleotide polymorphism (SNP) data, which provides revised functional linear regression models, partially functional interaction regression analysis with penalty-based techniques and corresponding drawing functions, etc.(Ruzong Fan, Yifan Wang, James L. Mills, Alexander F. Wilson, Joan E. Bailey-Wilson, and Momiao Xiong (2013) <doi:10.1002/gepi.21757>).

Simple key-value database using SQLite as the backend.

This package provides implementation of statistical methods for random objects lying in various metric spaces, which are not necessarily linear spaces. The core of this package is Fréchet regression for random objects with Euclidean predictors, which allows one to perform regression analysis for non-Euclidean responses under some mild conditions. Examples include distributions in 2-Wasserstein space, covariance matrices endowed with power metric (with Frobenius metric as a special case), Cholesky and log-Cholesky metrics, spherical data. References: Petersen, A., & Müller, H.-G. (2019) <doi:10.1214/17-AOS1624>.

Clustering for categorical and mixed-type of data, to preventing classification biases due to race, gender or others sensitive attributes. This algorithm is an extension of the methodology proposed by "Santos & Heras (2020) <doi:10.28945/4643>".

Read and write PNG images with arrays, rasters, native rasters, numeric arrays, integer arrays, raw vectors and indexed values. This PNG encoder exposes configurable internal options enabling the user to select a speed-size tradeoff. For example, disabling compression can speed up writing PNG by a factor of 50. Multiple image formats are supported including raster, native rasters, and integer and numeric arrays at color depths of 1, 2, 3 or 4. 16-bit images are also supported. This implementation uses the libspng C library which is available from <https://github.com/randy408/libspng/>.

Efficient computation of the Liu regression coefficient paths, Liu-related statistics and information criteria for a grid of the regularization parameter. The computations are based on the C++ library Armadillo through the R package Rcpp'.

Allows users to create and deploy the workflow with multiple functions in Function-as-a-Service (FaaS) cloud computing platforms. The FaaSr package makes it simpler for R developers to use FaaS platforms by providing the following functionality: 1) Parsing and validating a JSON-based payload compliant to FaaSr schema supporting multiple FaaS platforms 2) Invoking user functions written in R in a Docker container (derived from rocker), using a list generated from the parser as argument 3) Downloading/uploading of files from/to S3 buckets using simple primitives 4) Logging to files in S3 buckets 5) Triggering downstream actions supporting multiple FaaS platforms 6) Generating FaaS-specific API calls to simplify the registering of a user's workflow with a FaaS platform Supported FaaS platforms: Apache OpenWhisk <https://openwhisk.apache.org/> GitHub Actions <https://github.com/features/actions> Amazon Web Services (AWS) Lambda <https://aws.amazon.com/lambda/> Supported cloud data storage for persistent storage: Amazon Web Services (AWS) Simple Storage Service (S3) <https://aws.amazon.com/s3/>.

Converts vectors of numbers into character vectors of numerals, including cardinals (one, two, three) and ordinals (first, second, third). Supports negative numbers, fractions, and arbitrary-precision integer and high-precision floating-point vectors provided by the bignum package.

Dataset of 302 measurements of 11 fish species to accompany the manuscript "Length-weight relationships of six freshwater fish species from lake Kirkkojarvi, Finland".

R companion to Tsay (2005) Analysis of Financial Time Series, second edition (Wiley). Includes data sets, functions and script files required to work some of the examples. Version 0.3-x includes R objects for all data files used in the text and script files to recreate most of the analyses in chapters 1-3 and 9 plus parts of chapters 4 and 11.

This package provides a collection of methods for modeling time-to-event data using both functional and scalar predictors. It implements functional data analysis techniques for estimation and inference, allowing researchers to assess the impact of functional covariates on survival outcomes, including time-to-single event and recurrent event outcomes.

Helps you imagine your data before you collect it. Hierarchical data structures and correlated data can be easily simulated, either from random number generators or by resampling from existing data sources. This package is faster with data.table and mvnfast installed.

Fits Weibull or sigmoidal models to percent loss conductivity (plc) curves as a function of plant water potential, computes confidence intervals of parameter estimates and predictions with bootstrap or parametric methods, and provides convenient plotting methods.

Lognormal models have broad applications in various research areas such as economics, actuarial science, biology, environmental science and psychology. The estimation problem in lognormal models has been extensively studied. This R package fuel implements thirty-nine existing and newly proposed estimators. See Zhang, F., and Gou, J. (2020), A unified framework for estimation in lognormal models, Technical report.

This is a method for Allele-specific DNA Copy Number Profiling using Next-Generation Sequencing. Given the allele-specific coverage at the variant loci, this program segments the genome into regions of homogeneous allele-specific copy number. It requires, as input, the read counts for each variant allele in a pair of case and control samples. For detection of somatic mutations, the case and control samples can be the tumor and normal sample from the same individual.

Calculate numerical asymptotic distribution functions of likelihood ratio statistics for fractional unit root tests and tests of cointegration rank. For these distributions, the included functions calculate critical values and P-values used in unit root tests, cointegration tests, and rank tests in the Fractionally Cointegrated Vector Autoregression (FCVAR) model. The functions implement procedures for tests described in the following articles: Johansen, S. and M. Ã . Nielsen (2012) <doi:10.3982/ECTA9299>, MacKinnon, J. G. and M. Ã . Nielsen (2014) <doi:10.1002/jae.2295>.

This package provides a shiny design of experiments (DOE) app that aids in the creation of traditional, un-replicated, augmented and partially-replicated designs applied to agriculture, plant breeding, forestry, animal and biological sciences.

Interval estimation of the population allele frequency from qPCR analysis based on the restriction enzyme digestion (RED)-DeltaDeltaCq method (Osakabe et al. 2017, <doi:10.1016/j.pestbp.2017.04.003>), as well as general DeltaDeltaCq analysis. Compatible with the Cq measurement of DNA extracted from multiple individuals at once, so called "group-testing", this model assumes that the quantity of DNA extracted from an individual organism follows a gamma distribution. Therefore, the point estimate is robust regarding the uncertainty of the DNA yield.

R shiny app to perform data analysis and visualization for the Fully Automated Senescence Test (FAST) workflow.

Use R as a minimal build system. This might come in handy if you are developing R packages and can not use a proper build system. Stay away if you can (use a proper build system).

Computes unidimensional and multidimensional Reciprocity and Inaccuracy indices. These indices are applicable to common heterostylous populations and to any other type of stylar dimorphic and trimorphic populations, such as in enantiostylous and three-dimensional heterostylous plants. Simón-Porcar, V., A. J. Muñoz-Pajares, J. Arroyo, and S. D. Johnson. (in press) "FlowerMate: multidimensional reciprocity and inaccuracy indices for style-polymorphic plant populations.".