Fast implementations of functional enrichment analysis methods using C++ via Rcpp'. Currently provides Over-Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). The multilevel GSEA algorithm is derived from the fgsea package. Methods are described in Subramanian et al. (2005) <doi:10.1073/pnas.0506580102> and Korotkevich et al. (2021) <doi:10.1101/060012>.

Reads water network simulation data in Epanet text-based .inp and .rpt formats into R. Also reads results from Epanet-msx'. Provides basic summary information and plots. The README file has a quick introduction. See <https://www.epa.gov/water-research/epanet> for more information on the Epanet software for modeling hydraulic and water quality behavior of water piping systems.

Randomized multiple-select and single-select question generation for the MyLearn teaching and learning platform. Question templates in the form of the R/exams package (see <http://www.r-exams.org/>) are transformed into XML format required by MyLearn'.

Computes alpha and beta diversity metrics using concurrent C threads. Metrics include UniFrac', Faith's phylogenetic diversity, Bray-Curtis dissimilarity, Shannon diversity index, and many others. Also parses newick trees into phylo objects and rarefies feature tables.

This package provides a rich toolkit of using the whole building simulation program EnergyPlus'(<https://energyplus.net>), which enables programmatic navigation, modification of EnergyPlus models and makes it less painful to do parametric simulations and analysis.

Rolling and expanding window approaches to assessing abundance based early warning signals, non-equilibrium resilience measures, and machine learning. See Dakos et al. (2012) <doi:10.1371/journal.pone.0041010>, Deb et al. (2022) <doi:10.1098/rsos.211475>, Drake and Griffen (2010) <doi:10.1038/nature09389>, Ushio et al. (2018) <doi:10.1038/nature25504> and Weinans et al. (2021) <doi:10.1038/s41598-021-87839-y> for methodological details. Graphical presentation of the outputs are also provided for clear and publishable figures. Visit the EWSmethods website for more information, and tutorials.

The equality of a large number k of densities is tested by measuring the L2 distance between the corresponding kernel density estimators and the one based on the pooled sample. The test even works for sample sizes as small as 2.

This package provides a consistent representation of year-based time scales as a numeric vector with an associated era'. There are built-in era definitions for many year numbering systems used in contemporary and historic calendars (e.g. Common Era, Islamic Hijri years); year-based time scales used in archaeology, astronomy, geology, and other palaeosciences (e.g. Before Present, SI-prefixed annus'); and support for arbitrary user-defined eras. Years can converted from any one era to another using a generalised transformation function. Methods are also provided for robust casting and coercion between years and other numeric types, type-stable arithmetic with years, and pretty-printing in tables.

Density, distribution function, quantile function and random generation for the Kumaraswamy Complementary Weibull Geometric (Kw-CWG) lifetime probability distribution proposed in Afify, A.Z. et al (2017) <doi:10.1214/16-BJPS322>.

Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies in an image. The image is first transformed into the wavelet domain in order to decorrelate any noise components, following which the coefficients at each resolution are standardised. Statistical tests (in a multiple hypothesis testing setting) are then carried out to find the anomalies. The power of EFDR exceeds that of standard FDR, which would carry out tests on every wavelet coefficient: EFDR choose which wavelets to test based on a criterion described in Shen et al. (2002). The package also provides elementary tools to interpolate spatially irregular data onto a grid of the required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. Nonparametric hypothesis testing for a spatial signal. Journal of the American Statistical Association 97.460 (2002): 1122-1140.

Several web services are available that provide access to elevation data. This package provides access to many of those services and returns elevation data either as an sf simple features object from point elevation services or as a raster object from raster elevation services. In future versions, elevatr will drop support for raster and will instead return terra objects. Currently, the package supports access to the Amazon Web Services Terrain Tiles <https://registry.opendata.aws/terrain-tiles/>, the Open Topography Global Datasets API <https://opentopography.org/developers/>, and the USGS Elevation Point Query Service <https://apps.nationalmap.gov/epqs/>.

This package provides methods for fitting various extreme value distributions with parameters of generalised additive model (GAM) form are provided. For details of distributions see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GAMs see Wood, S.N. (2017) <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>. Details of how evgam works and various examples are given in Youngman, B.D. (2022) <doi:10.18637/jss.v103.i03>.

Easy and rapid quantitative estimation of small terrestrial ectotherm temperature regulation effectiveness in R. ectotemp is built on classical formulas that evaluate temperature regulation by means of various indices, inaugurated by Hertz et al. (1993) <doi: 10.1086/285573>. Options for bootstrapping and permutation testing are included to test hypotheses about divergence between organisms, species or populations.

This package provides tools to fit Mixture Cure Rate models via the Expectation-Maximization (EM) algorithm, allowing for flexible link functions in the cure component and various survival distributions in the latency part. The package supports user-specified link functions, includes methods for parameter estimation and model diagnostics, and provides residual analysis tailored for cure models. The classical theory methods used are described in Berkson, J. and Gage, R. P. (1952) <doi:10.2307/2281318>, Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977) <https://www.jstor.org/stable/2984875>, Bazán, J., Torres-Avilés, F., Suzuki, A. and Louzada, F. (2017)<doi:10.1002/asmb.2215>.

This package provides a client for the Environmental Data Initiative repository REST API. The EDI data repository <https://portal.edirepository.org/nis/home.jsp> is for publication and reuse of ecological data with emphasis on metadata accuracy and completeness. It is built upon the PASTA+ software stack <https://pastaplus-core.readthedocs.io/en/latest/index.html#> and was developed in collaboration with the US LTER Network <https://lternet.edu/>. EDIutils includes functions to search and access existing data, evaluate and upload new data, and assist other data management tasks common to repository users.

This software downloads and manages air quality data from the European Environmental Agency (EEA) dataflow (<https://www.eea.europa.eu/data-and-maps/data/aqereporting-9>). See the web page <https://eeadmz1-downloads-webapp.azurewebsites.net/> for details on the EEA's Air Quality Download Service. The package allows dynamically mapping the stations, summarising and time aggregating the measurements and building spatial interpolation maps. See the web page <https://www.eea.europa.eu/en> for further information on EEA activities and history. Further details, as well as, an extended vignette of the main functions included in the package, are available at the GitHub web page dedicated to the project.

This package provides functions for estimating catalytic constant and Michaelis-Menten constant for enzyme kinetics model using Metropolis-Hasting algorithm within Gibbs sampler based on the Bayesian framework.

Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data using the model described in Forcina et al. (2012), as extension of the model proposed in Brown and Payne (1986). Allows incorporation of covariates. References: Brown, P. and Payne, C. (1986). Aggregate data, ecological regression and voting transitions''. Journal of the American Statistical Association, 81, 453â 460. <DOI:10.1080/01621459.1986.10478290>. Forcina, A., Gnaldi, M. and Bracalente, B. (2012). A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy''. Statistical Methods & Applications, 21, 109â 119. <DOI:10.1007/s10260-011-0184-x>.

Wrapper for the ggplot2 package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.

This package provides a system for calculating the optimal sampling effort, based on the ideas of "Ecological cost-benefit optimization" as developed by A. Underwood (1997, ISBN 0 521 55696 1). Data is obtained from simulated ecological communities with prep_data() which formats and arranges the initial data, and then the optimization follows the following procedure of four functions: (1) prep_data() takes the original dataset and creates simulated sets that can be used as a basis for estimating statistical power and type II error. (2) sim_beta() is used to estimate the statistical power for the different sampling efforts specified by the user. (3) sim_cbo() calculates then the optimal sampling effort, based on the statistical power and the sampling costs. Additionally, (4) scompvar() calculates the variation components necessary for (5) Underwood_cbo() to calculate the optimal combination of number of sites and samples depending on either an economic budget or on a desired statistical accuracy. Lastly, (6) plot_power() helps the user visualize the results of sim_beta().

This package provides a consistent set of functions for enriching and analyzing sovereign-level economic data. Economists, data scientists, and financial professionals can use the package to add standardized identifiers, demographic and macroeconomic indicators, and derived metrics such as gross domestic product per capita or government expenditure shares.

This package provides R access to election results data. Wraps elex (https://github.com/newsdev/elex/), a Python package and command line tool for fetching and parsing Associated Press election results.

Expert Algorithm Verbal Autopsy assigns causes of death to 2016 WHO Verbal Autopsy Questionnaire data. odk2EAVA() converts data to a standard input format for cause of death determination building on the work of Thomas (2021) <https://cran.r-project.org/src/contrib/Archive/CrossVA/>. codEAVA() uses the presence and absence of signs and symptoms reported in the Verbal Autopsy interview to diagnose common causes of death. A deterministic algorithm assigns a single cause of death to each Verbal Autopsy interview record using a hierarchy of all common causes for neonates or children 1 to 59 months of age.

Elastic net regression models are controlled by two parameters, lambda, a measure of shrinkage, and alpha, a metric defining the model's location on the spectrum between ridge and lasso regression. glmnet provides tools for selecting lambda via cross validation but no automated methods for selection of alpha. Elastic Net SearcheR automates the simultaneous selection of both lambda and alpha. Developed, in part, with support by NICHD R03 HD094912.