This package provides quick and easy access to official spatial data from Germanyâ s Federal Agency for Cartography and Geodesy (BKG) <https://gdz.bkg.bund.de/>. Interfaces various web feature services (WFS) and download servers. Allows retrieval, caching and filtering with a wide range of open geodata products, including administrative or non-administrative boundaries, land cover, elevation models, geographic names, and points of interest covering Germany. Can be particularly useful for linking regional statistics to their spatial representations and streamlining workflows that involve spatial data of Germany.

Transform output files of some tools to the microtable object of microtable class in microeco package. The microtable class is the basic class in microeco package and is necessary for the downstream microbial community data analysis.

Easy installation, loading and management, of high-performance packages for statistical computing and data manipulation in R. The core fastverse consists of 4 packages: data.table', collapse', kit and magrittr', that jointly only depend on Rcpp'. The fastverse can be freely and permanently extended with additional packages, both globally or for individual projects. Separate package verses can also be created. Fast packages for many common tasks such as time series, dates and times, strings, spatial data, statistics, data serialization, larger-than-memory processing, and compilation of R code are listed in the README file: <https://github.com/fastverse/fastverse#suggested-extensions>.

FDR functions for permutation-based estimators, including pi0 as well as FDR confidence intervals. The confidence intervals account for dependencies between tests by the incorporation of an overdispersion parameter, which is estimated from the permuted data. Also included are options for an analog parametric approach.

Fast reverse complement of DNA and RNA sequences using a C++ lookup table for O(1) per-base complement mapping. Supports full IUPAC ambiguity codes, DNA and RNA modes, case preservation, and NA handling. Much faster than other packages for computing reverse complements of many short sequences such as primers, probes, and, k-mers.

Download Data from the FAOSTAT Database of the Food and Agricultural Organization (FAO) of the United Nations. A list of functions to download statistics from FAOSTAT (database of the FAO <https://www.fao.org/faostat/>) and WDI (database of the World Bank <https://data.worldbank.org/>), and to perform some harmonization operations.

Parses financial condition and performance data (Call Reports) for institutions in the United States Farm Credit System. Contains functions for downloading files from the Farm Credit Administration (FCA) Call Report archive website and reading the files into tidy data frame format. The archive website can be found at <https://www.fca.gov/bank-oversight/call-report-data-for-download>.

Basic analysis of all penalties taken in the German men's Bundesliga between the start of its inaugural season and May 2017. The main functions are suitable printing and plotting functions. Flexible selection of a player is supported via grep. Missed penalties can easily be included or excluded, depending on the user's wishes.

Processes tracked points on a fish's body and uses them to estimate standard kinematic parameters such as tail beat amplitude and frequency, body wavelength and wavespeed. As part of this, it also estimates the location of the center of mass and the principal swimming axis. The techniques are described in detail in the main vignette and are published in the book chapter Hawkins, O.H., Di Santo, V., Tytell, Eric.D., 2025. "Biomechanics and energetics of swimming", in: Higham, T.E., Lauder, G.V. (Eds.), Integrative Fish Biomechanics, Fish Physiology. Academic Press. <doi:10.1016/bs.fp.2025.06.003>.

Fatty acid metabolic analysis aimed to the estimation of FA import (I), de novo synthesis (S), fractional contribution of the 13C-tracers (D0, D1, D2), elongation (E) and desaturation (Des) based on mass isotopologue data.

This package provides functions for calculating various measures of foreign policy similarity or association commonly used in the study of international relations. These include Signorino and Ritter's S statistic (weighted and unweighted), Benati and Capurri's chance-corrected S statistic (A), Cohen's weighted kappa, Scott's pi, and Kendall's tau-b. The package facilitates the generation of dyadic similarity scores for empirical analyses and can also serve as an educational resource for understanding how such measures are calculated.

Maps individual tree stem locations on field plots of the Forest Inventory and Analysis Program of USDA Forest Service (<https://research.fs.usda.gov/programs/nfi>). Stem locations are mapped in cartesian coordinate space based on field-measured distance and azimuth from subplot and microplot centers. Per-tree crown widths are estimated using a curated set of allometric equations with coverage for the conterminous US. Spatial descriptors of tree point pattern are computed at the whole plot level. Several stand height metrics are also computed and provided in the output. The spatial representation of modeled tree crowns is used to generate estimates of fractional tree canopy cover at the microplot, subplot and whole plot levels. Convenience functions are provided for efficient data processing. Exploratory data analysis is also facilitated via integration with the spatstat packages.

Gives a Stan'-based R package one interface for fitting its models through either rstan or cmdstanr', neither of which is required to install this package (install whichever you use). Collects and validates sampler options, guarding against mixing one backend's argument vocabulary into the other, dispatches the fit to the chosen backend, and exposes backend-agnostic accessors for reading posterior draws, extracting parameters, and running generated quantities. The host package supplies its own compiled models; flexstanr resolves them from the calling package at run time, so the same code works whichever backend is installed.

This package implements shape-based clustering algorithms for multidimensional longitudinal data based on the Fréchet distance. It implements two main methods: MFKmL (Multidimensional Fréchet distance-based K-means for Longitudinal data), an extension of the K-means algorithm using the Fréchet distance originally developed in the kmlShape package, adapted for multidimensional trajectories; and SFKmL (Sparse multidimensional Fréchet distance-based K-medoids for Longitudinal data), a K-medoids-based clustering algorithm that incorporates variable selection. These tools are designed to enhance clustering performance in high-dimensional longitudinal data settings, particularly those with time delays, variations in trajectory speed, irregular sampling intervals, and noise. This package implements methods derived from Kang et al. (2023) <doi:10.1007/s11222-023-10237-z>.

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).

Average rating and number of votes reported by IMDb for films and shorts with over 100 votes in 2022. The data are analysed in Chapter 3 of the Book Getting (more out of) Graphics (Antony Unwin, CRC Press 2024).

This package provides routines for the estimation and specification analysis of fractional response models. Includes univariate one-part, two-part, and double-inflated three-part fractional models. Further incorporates estimators for panel data settings and addresses unobserved heterogeneity and endogeneity via correlated random effects and control function approaches. Extends fractional methodology to multivariate data via fractional multinomial logit models and handles high-dimensional multicollinear data via fractional ridge regression. Calculates analytical partial effects across all model types and includes generalised goodness-of-functional-form (GGOFF) and Regression Equation Specification Error Test (RESET) hypothesis tests. Methods are described in Papke and Wooldridge (1996) <doi:10.1002/(SICI)1099-1255(199611)11:6%3C619::AID-JAE418%3E3.0.CO;2-1>, Papke and Wooldridge (2008) <doi:10.1016/j.jeconom.2008.05.009>, Buis (2008) <http://maartenbuis.nl/software/likelihoodFmlogit.pdf>, Ramalho, Ramalho and Murteira (2011) <doi:10.1111/j.1467-6419.2009.00602.x>, Fang and Ma (2013) <doi:10.1080/02664763.2012.758246>, Mullahy (2015) <doi:10.1515/jem-2012-0006>, Murteira and Ramalho (2016) <doi:10.1080/07474938.2013.806849>, and Rokem and Kay (2020) <doi:10.1093/gigascience/giaa133>.

This package provides tools to work with the Flexible Dirichlet distribution. The main features are an E-M algorithm for computing the maximum likelihood estimate of the parameter vector and a function based on conditional bootstrap to estimate its asymptotic variance-covariance matrix. It contains also functions to plot graphs, to generate random observations and to handle compositional data.

Allows generating heatmap-like visualisations for data frames. Funky heatmaps can be fine-tuned by providing annotations of the columns and rows, which allows assigning multiple palettes or geometries or grouping rows and columns together in categories. Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.

Computes chlorophyll a fluorescence transient parameters from fluorescence summary data, including minimum and maximum fluorescence, selected transient steps, and area. Provides standard photosynthetic performance indices and fluxes per reaction center and per cross section. Includes helpers to read exported trace tables in supported csv formats and validation workflows based on bundled example files, as well as visualization tools and an interactive shiny interface. The implemented calculations are based on Strasser et al. (2004) <doi:10.1007/978-1-4020-3218-9_12> and Stirbet and Govindjee (2011) <doi:10.1016/j.jphotobiol.2010.12.010>.

Frequentist assisted by Bayes (FAB) p-values and confidence interval construction. See Hoff (2019) <arXiv:1907.12589> "Smaller p-values via indirect information", Hoff and Yu (2019) <doi:10.1214/18-EJS1517> "Exact adaptive confidence intervals for linear regression coefficients", and Yu and Hoff (2018) <doi:10.1093/biomet/asy009> "Adaptive multigroup confidence intervals with constant coverage".

Compute energy fluxes in trophic networks, from resources to their consumers, and can be applied to systems ranging from simple two-species interactions to highly complex food webs. It implements the approach described in Gauzens et al. (2017) <doi:10.1101/229450> to calculate energy fluxes, which are also used to calculate equilibrium stability.

This package provides a simple method to select the best model or best subset of variables using different types of data (binary, Gaussian or Poisson) and applying it in different contexts (parametric or non-parametric). Implemented methodology described in: M. Sestelo, N. M. Villanueva, L. Meira-Machado and J. Roca-Pardiñas (2016). FWDselect: an R package for variable selection in regression models. The R Journal, 8 (1), 132-148. <doi:10.32614/RJ-2016-009>.

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.