Hadoop InteractiVE facilitates distributed computing via the MapReduce paradigm through R and Hadoop. An easy to use interface to Hadoop, the Hadoop Distributed File System (HDFS), and Hadoop Streaming is provided.

Facilitates the analysis and evaluation of hydrologic model output and time-series data with functions focused on comparison of modeled (simulated) and observed data, period-of-record statistics, and trends.

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.

Enhance package testthat by allowing tests to be attached to the function/object they test. This allows to keep functional and unit test code together.

Processing of CSV files generated by HOBO weather stations and data loggers. The package automatically imports multiple HOBO data records, removes duplicate records, identifies impossible values, subsets user-defined time ranges, and summarizes environmental data.

Aimed at applying the Harvest classification tree algorithm, modified algorithm of classic classification tree.The harvested tree has advantage of deleting redundant rules in trees, leading to a simplify and more efficient tree model.It was firstly used in drug discovery field, but it also performs well in other kinds of data, especially when the region of a class is disconnected. This package also improves the basic harvest classification tree algorithm by extending the field of data of algorithm to both continuous and categorical variables. To learn more about the harvest classification tree algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf for more information.

This package provides functions for the estimation, plotting, predicting and cross-validation of hierarchical feature regression models as described in Pfitzinger (2024). Cluster Regularization via a Hierarchical Feature Regression. Econometrics and Statistics (in press). <doi:10.1016/j.ecosta.2024.01.003>.

Code Syntax Highlighting made easy for code snippets or complete files. Whether you're documenting your data analysis or creating interactive shiny apps.

Several procedures for the hierarchical kernel extreme value process of Reich and Shaby (2012) <DOI:10.1214/12-AOAS591>, including simulation, estimation and spatial extrapolation. The spatial latent variable model <DOI:10.1214/11-STS376> is also included.

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.

This package provides an example HiC dataset and two examples of HiCociety outputs from a function named hic2community(). The data are intended for demonstration purposes only and kept small enough to be distributed via CRAN.

This package provides a comprehensive suite of spatial functions created to analyze and assess data heterogeneity and climate variability in spatial datasets. This package is specifically designed to address the challenges associated with characterizing and understanding complex spatial patterns in environmental and climate-related data.

This package provides a wrapper around a CSS library called Hover.css', intended for use in shiny applications.

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

This package provides a suite of routines for the hyperdirichlet distribution and reified Bradley-Terry; supersedes the hyperdirichlet package; uses disordR discipline <doi:10.48550/ARXIV.2210.03856>. To cite in publications please use Hankin 2017 <doi:10.32614/rj-2017-061>, and for Generalized Plackett-Luce likelihoods use Hankin 2024 <doi:10.18637/jss.v109.i08>.

This package implements the Hatemi-J (2008) cointegration test which allows for two unknown structural breaks (regime shifts) in the cointegrating relationship. The test provides three test statistics: ADF* (Augmented Dickey-Fuller), Zt* (Phillips-Perron Z_t), and Za* (Phillips-Perron Z_alpha), along with endogenously determined break dates. Critical values are based on simulations from Hatemi-J (2008) <doi:10.1007/s00181-007-0175-9>. The long-run variance in the Phillips statistics is estimated by default with a prewhitened quadratic spectral kernel and the automatic bandwidth of Andrews (1991) <doi:10.2307/2938229>, following Andrews and Monahan (1992) <doi:10.2307/2951574>.

This package provides functions to build and use hexagonal discrete global grids using the Icosahedral Snyder Equal Area ('ISEA') projection (Snyder 1992 <doi:10.3138/27H7-8K88-4882-1752>) and the H3 hierarchical hexagonal system (Uber Technologies). Implements the ISEA discrete global grid system (Sahr, White and Kimerling 2003 <doi:10.1559/152304003100011090>). Includes a fast C++ core for ISEA projection and aperture quantization, an included H3 v4.4.1 C library for native H3 grid operations, and sf'/'terra'-compatible R wrappers for grid generation and coordinate assignment. Output is compatible with dggridR for interoperability.

This package provides functions to assess and test for heterogeneity in the utility of a surrogate marker with respect to a baseline covariate using censored (survival data), and to test for heterogeneity across multiple time points. More details are available in Parast et al (2024) <doi:10.1002/sim.10122>.

This package contains various functions for data analysis, notably helpers and diagnostics for Bayesian modelling using Stan.

By analyzing time series, it is possible to observe significant changes in the behavior of observations that frequently characterize events. Events present themselves as anomalies, change points, or motifs. In the literature, there are several methods for detecting events. However, searching for a suitable time series method is a complex task, especially considering that the nature of events is often unknown. This work presents Harbinger, a framework for integrating and analyzing event detection methods. Harbinger contains several state-of-the-art methods described in Salles et al. (2020) <doi:10.5753/sbbd.2020.13626>.

Probability functions and other utilities for the generalized Hermite distribution.

Enables high dimensional statistical modeling using Bayesian inference and provides a probabilistic programming language for high dimensional problems. See Kleinsasser (2026) <doi:10.5281/zenodo.22309216>.

Facilitates hierarchical clustering analysis with functions to read data in txt', xlsx', and xls formats, apply normalization techniques to the dataset, perform hierarchical clustering and construct scatter plot from principal component analysis to evaluate the groups obtained.

Estimates parameters in Mixture Transition Distribution (MTD) models, a class of high-order Markov chains. The set of relevant pasts (lags) is selected using either the Bayesian Information Criterion or the Forward Stepwise and Cut algorithms. Other model parameters (e.g. transition probabilities and oscillations) can be estimated via maximum likelihood estimation or the Expectation-Maximization algorithm. Additionally, hdMTD includes a perfect sampling algorithm that generates samples of an MTD model from its invariant distribution. For theory, see Ost & Takahashi (2023) <http://jmlr.org/papers/v24/22-0266.html>.