S3 functions for management, analysis, interpolation and plotting of time series used in hydrology and related environmental sciences. In particular, this package is highly oriented to hydrological modelling tasks. The focus of this package has been put in providing a collection of tools useful for the daily work of hydrologists (although an effort was made to optimise each function as much as possible, functionality has had priority over speed). Bugs / comments / questions / collaboration of any kind are very welcomed, and in particular, datasets that can be included in this package for academic purposes.

The hydReng package provides a set of functions for hydraulic engineering tasks and natural hazard assessments. It includes basic hydraulics (wetted area, wetted perimeter, flow, flow velocity, flow depth, and maximum flow) for open channels with arbitrary geometry under uniform flow conditions. For structures such as circular pipes, weirs, and gates, the package includes calculations for pressure flow, backwater depth, and overflow over a weir crest. Additionally, it provides formulas for calculating bedload transport. The formulas used can be found in standard literature on hydraulics, such as Bollrich (2019, ISBN:978-3-410-29169-5) or Hager (2011, ISBN:978-3-642-77430-0).

We use the Alternating Direction Method of Multipliers (ADMM) for parameter estimation in high-dimensional, single-modality mediation models. To improve the sensitivity and specificity of estimated mediation effects, we offer the sure independence screening (SIS) function for dimension reduction. The available penalty options include Lasso, Elastic Net, Pathway Lasso, and Network-constrained Penalty. The methods employed in the package are based on Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011). <doi:10.1561/2200000016>, Fan, J., & Lv, J. (2008) <doi:10.1111/j.1467-9868.2008.00674.x>, Li, C., & Li, H. (2008) <doi:10.1093/bioinformatics/btn081>, Tibshirani, R. (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, Zhao, Y., & Luo, X. (2022) <doi:10.4310/21-sii673>, and Zou, H., & Hastie, T. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.

Read hierarchical fixed width files like those commonly used by many census data providers. Also allows for reading of data in chunks, and reading gzipped files without storing the full file in memory.

This package provides a multiple-testing procedure for high-dimensional mediation hypotheses. Mediation analysis is of rising interest in epidemiology and clinical trials. Among existing methods for mediation analyses, the popular joint significance (JS) test yields an overly conservative type I error rate and therefore low power. In the R package HDMT we implement a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when using JS for testing high-dimensional mediation hypotheses. The core of our procedure is based on estimating the proportions of three component null hypotheses and deriving the corresponding mixture distribution of null p-values. Results of the data examples include better-behaved quantile-quantile plots and improved detection of novel mediation relationships on the role of DNA methylation in genetic regulation of gene expression. With increasing interest in mediation by molecular intermediaries such as gene expression, the proposed method addresses an unmet methodological challenge. Methods used in the package refer to James Y. Dai, Janet L. Stanford & Michael LeBlanc (2020) <doi:10.1080/01621459.2020.1765785>.

Hypergeometric Intersection distributions are a broad group of distributions that describe the probability of picking intersections when drawing independently from two (or more) urns containing variable numbers of balls belonging to the same n categories. <arXiv:1305.0717>.

This package provides a set of routines to quickly download and import the HUGO Gene Nomenclature Committee (HGNC) data set on mapping of gene symbols to gene entries in other genomic databases or resources.

Facilitates estimation of full univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and nonparametric correlation (bivariate) using Hermite series based estimators. These estimators are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) <doi:10.1016/j.jmva.2021.104783>.

This package provides methods for closed testing using Simes local tests. In particular, calculates adjusted p-values for Hommel's multiple testing method, and provides lower confidence bounds for true discovery proportions. A robust but more conservative variant of the closed testing procedure that does not require the assumption of Simes inequality is also implemented. The methods have been described in detail in Goeman et al (Biometrika 106, 841-856, 2019).

Read, plot, manipulate and process hydro-meteorological data records (with special features for Argentina and Chile data-sets).

Programmatic interface to the Harmonized World Soil Database HWSD web services (<https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1247>). Allows for easy downloads of HWSD soil data directly to your R workspace or your computer. Routines for both single pixel data downloads and gridded data are provided.

Estimates survey indicators using complex survey designs. Supports mean, proportion, and ratio estimation with multi-stage stratified sampling, weights, and finite population correction. The output is designed to be comparable to results from SPSS (Statistical Package for the Social Sciences) Complex Samples procedures.

Function to identify haplotypes within QTL (Quantitative Trait Loci). One haplotype is a combination of SNP (Single Nucleotide Polymorphisms) within the QTL. This function groups together all individuals of a population with the same haplotype. Each group contains individual with the same allele in each SNP, whether or not missing data. Thus, haplotyper groups individuals, that to be imputed, have a non-zero probability of having the same alleles in the entire sequence of SNP's. Moreover, haplotyper calculates such probability from relative frequencies.

It provides functions to design historical controlled trials with survival outcome by group sequential method. The options for interim look boundaries are efficacy only, efficacy & futility or futility only. It also provides the function to monitor the trial for any unplanned look. The package is based on Jianrong Wu, Xiaoping Xiong (2016) <doi:10.1002/pst.1756> and Jianrong Wu, Yimei Li (2020) <doi:10.1080/10543406.2019.1684305>.

An interactive Shiny dashboard for visualizing and exploring key metrics related to HIV/AIDS, including prevalence, incidence, mortality, and treatment coverage. The dashboard is designed to work with a dataset containing specific columns with standardized names. These columns must be present in the input data for the app to function properly: year: Numeric year of the data (e.g. 2010, 2021); sex: Gender classification (e.g. Male, Female); age_group: Age bracket (e.g. 15â 24, 25â 34); hiv_prevalence: Estimated HIV prevalence percentage; hiv_incidence: Number of new HIV cases per year; aids_deaths: Total AIDS-related deaths; plhiv: Estimated number of people living with HIV; art_coverage: Percentage receiving antiretroviral therapy (ART); testing_coverage: HIV testing services coverage; causes: Description of likely HIV transmission cause (e.g. unprotected sex, drug use). The dataset structure must strictly follow this column naming convention for the dashboard to render correctly.

This package provides a scalable implementation of the highly adaptive lasso algorithm, including routines for constructing sparse matrices of basis functions of the observed data, as well as a custom implementation of Lasso regression tailored to enhance efficiency when the matrix of predictors is composed exclusively of indicator functions. For ease of use and increased flexibility, the Lasso fitting routines invoke code from the glmnet package by default. The highly adaptive lasso was first formulated and described by MJ van der Laan (2017) <doi:10.1515/ijb-2015-0097>, with practical demonstrations of its performance given by Benkeser and van der Laan (2016) <doi:10.1109/DSAA.2016.93>. This implementation of the highly adaptive lasso algorithm was described by Hejazi, Coyle, and van der Laan (2020) <doi:10.21105/joss.02526>.

This package provides access to Uber's H3 library for geospatial indexing via its JavaScript transpile h3-js <https://github.com/uber/h3-js> and V8 <https://github.com/jeroen/v8>.

This package provides a set of tools to create georeferenced hillshade relief raster maps using ray-tracing and other advanced hill-shading techniques. It includes a wrapper function to create a georeferenced, ray-traced hillshade map from a digital elevation model, and other functions that can be used in a rayshader pipeline.

Fit, summarize and plot sinusoidal hysteretic processes using: two-step simple harmonic least squares, ellipse-specific non-linear least squares, the direct method, geometric least squares or linear least squares. See Yang, F and A. Parkhurst, "Efficient Estimation of Elliptical Hysteresis with Application to the Characterization of Heat Stress" <DOI:10.1007/s13253-015-0213-6>.

This package provides a unified, extensible interface to discover hydrologic stations and download daily time series (e.g., water discharge, water level, water temperature, and several other water quality parameter) from national and regional public APIs. Includes a provider registry, S3 generics stations and timeseries', licensing metadata, date-range and complete history modes, rate limiting and retries, optional authentication via environment variables, tidy outputs, UTF-8 to ASCII transliteration, and WGS84 coordinates. Designed for reproducible workflows and straightforward addition of new providers. Background and use cases are described in Farber et al. (2025) <doi:10.5194/essd-17-4613-2025> and Farber et al. (2023) <doi:10.57757/IUGG23-2838>.

Shiny-App that allows to annotate vectors of texts to predefined categories by hand.

This package provides datasets used for analysis and visualizations in the open-access Hello Data Science book.

Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) <https://www.jstor.org/stable/2346105?seq=1>. We provide an implementation (Ronnegard, Alam and Shen 2010) <https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf> following Lee, Nelder and Pawitan (2006) <ISBN: 9781420011340> with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) <https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf>.

It is used to construct run sequences with minimum changes for half replicate of two level factorial run order. Experimenter can save time and resources by minimizing the number of changes in levels of individual factor and therefore the total number of changes. It consists of the function minimal_hrtlf(). This technique can be employed to any half replicate of two level factorial run order where the number of factors are greater than two. In Design of Experiments (DOE) theory, two level of a factor can be represented as integers e.g. - 1 for low and 1 for high. User is expected to enter total number of factors to be considered in the experiment. minimal_hrtlf() provides the required run sequences for the input number of factors. The output also gives the number of changes of each factor along with total number of changes in the run sequence. Due to restricted randomization the minimally changed run sequences of half replicate of two level factorial run order will be affected by trend effect. The output also provides the Trend Factor value of the run order. Trend factor value will lies between 0 to 1. Higher the values, lesser the influence of trend effects on the run order.