Fit a predictive model using iteratively reweighted boosting (IRBoost) to minimize robust loss functions within the CC-family (concave-convex). This constitutes an application of iteratively reweighted convex optimization (IRCO), where convex optimization is performed using the functional descent boosting algorithm. IRBoost assigns weights to facilitate outlier identification. Applications include robust generalized linear models and robust accelerated failure time models. Wang (2025) <doi:10.6339/24-JDS1138>.

This package provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class incidence is used to store computed incidence and can be easily manipulated, subsetted, and plotted. In addition, log-linear models can be fitted to incidence objects using fit'. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.

This package provides access to low-level operating system mechanisms for performing atomic operations on shared data structures. Mutexes provide shared and exclusive locks. Semaphores act as counters. Message queues move text strings from one process to another. All these interprocess communication (IPC) tools can optionally block with or without a timeout. Implemented using the cross-platform boost C++ library <https://www.boost.org/doc/libs/release/libs/interprocess/>.

This package provides functions to fetch market data, search historical prices, execute trades, and get account details from the IG Trading REST API <https://labs.ig.com>. Returns tidy tibbles for easy analysis. Trading contracts for difference (CFDs), options and spread bets carries a high risk of losing money. This package is not financial or trading advice.

For environmental chemists, ecologists, researchers and agricultural scientists to understand the dissipation kinetics, calculate the half-life periods and rate constants of compounds, pesticides, contaminants in different matrices.

An implementation of the iterative bootstrap procedure of Kuk (1995) <doi:10.1111/j.2517-6161.1995.tb02035.x> to correct the estimation bias of a fitted model object. This procedure has better bias correction properties than the bootstrap bias correction technique.

Query for enriched data such as country, region, city, latitude & longitude, ZIP code, time zone, Autonomous System, Internet Service Provider, domain, net speed, International direct dialing (IDD) code, area code, weather station data, mobile data, elevation, usage type, address type, advertisement category, fraud score, and proxy data with an IP address. You can also query a list of hosted domain names for the IP address too. This package uses the IP2Location.io API to query this data. To get started with a free API key, sign up here <https://www.ip2location.io/sign-up?ref=1>.

An implementation of the Canny Edge Detector for detecting edges in images. The package provides an interface to the algorithm available at <https://github.com/Neseb/canny>.

This package provides datasets for the book "Introduction to Statistical Data Analysis for the Life Sciences, Second edition" by Ekstrøm and Sørensen (2014).

Functionality required to efficiently use R with IBM(R) Db2(R) Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2 for z/OS(R) in conjunction with IBM Db2 Analytics Accelerator for z/OS. Many basic and complex R operations are pushed down into the database, which removes the main memory boundary of R and allows to make full use of parallel processing in the underlying database. For executing R-functions in a multi-node environment in parallel the idaTApply() function requires the SparkR package (<https://spark.apache.org/docs/latest/sparkr.html>). The optional ggplot2 package is needed for the plot.idaLm() function only.

The ISA is a biclustering algorithm that finds modules in an input matrix. A module or bicluster is a block of the reordered input matrix.

Takes in vivo toxicokinetic concentration-time data and fits parameters of 1-compartment and 2-compartment models for each chemical. These methods are described in detail in "Informatics for Toxicokinetics" (2025).

Develops stochastic models based on the Theory of Island Biogeography (TIB) of MacArthur and Wilson (1967) <doi:10.1023/A:1016393430551> and extensions. It implements methods to estimate colonization and extinction rates (including environmental variables) given presence-absence data, simulates community assembly, and performs model selection.

This package implements the Interval-Censored Sequence Kernel Association (ICSKAT) test for testing the association between interval-censored time-to-event outcomes and groups of single nucleotide polymorphisms (SNPs). Interval-censored time-to-event data occur when the event time is not known exactly but can be deduced to fall within a given interval. For example, some medical conditions like bone mineral density deficiency are generally only diagnosed at clinical visits. If a patient goes for clinical checkups yearly and is diagnosed at, say, age 30, then the onset of the deficiency is only known to fall between the date of their age 29 checkup and the date of the age 30 checkup. Interval-censored data include right- and left-censored data as special cases. This package also implements the interval-censored Burden test and the ICSKATO test, which is the optimal combination of the ICSKAT and Burden tests. Please see the vignette for a quickstart guide. The paper describing these methods is " Inference for Set-Based Effects in Genetic Association Studies with Interval-Censored Outcomes" by Sun R, Zhu L, Li Y, Yasui Y, & Robison L (Biometrics 2023, <doi:10.1111/biom.13636>).

Interpreting the differences between mean scale scores across various forms of an assessment can be challenging. This difficulty arises from different mappings between raw scores and scale scores, complex mathematical relationships, adjustments based on judgmental procedures, and diverse equating functions applied to different assessment forms. An alternative method involves running simulations to explore the effect of incrementing raw scores on mean scale scores. The idmact package provides an implementation of this approach based on the algorithm detailed in Schiel (1998) <https://www.act.org/content/dam/act/unsecured/documents/ACT_RR98-01.pdf> which was developed to help interpret differences between mean scale scores on the American College Testing (ACT) assessment. The function idmact_subj() within the package offers a framework for running simulations on subject-level scores. In contrast, the idmact_comp() function provides a framework for conducting simulations on composite scores.

Fit parametric models for time-to-event data that show an initial incubation period', i.e., a variable delay phase where the hazard is zero. The delayed Weibull distribution serves as foundational data model. The specific method of MPSE (maximum product of spacings estimation) and MLE-based methods are used for parameter estimation. Bootstrap confidence intervals for parameters and significance tests in a two group setting are provided.

This package provides a personalized dynamic latent factor model (Zhang et al. (2024) <doi:10.1093/biomet/asae015>) for irregular multi-resolution time series data, to interpolate unsampled measurements from low-resolution time series.

When added to an existing shiny app, users may subset any developer-chosen R data.frame on the fly. That is, users are empowered to slice & dice data by applying multiple (order specific) filters using the AND (&) operator between each, and getting real-time updates on the number of rows effected/available along the way. Thus, any downstream processes that leverage this data source (like tables, plots, or statistical procedures) will re-render after new filters are applied. The shiny moduleâ s user interface has a minimalist aesthetic so that the focus can be on the data & other visuals. In addition to returning a reactive (filtered) data.frame, IDEAFilter as also returns dplyr filter statements used to actually slice the data.

This package provides a method that estimates an IV-optimal individualized treatment rule. An individualized treatment rule is said to be IV-optimal if it minimizes the maximum risk with respect to the putative IV and the set of IV identification assumptions. Please refer to <arXiv:2002.02579> for more details on the methodology and some theory underpinning the method. Function IV-PILE() uses functions in the package locClass'. Package locClass can be accessed and installed from the R-Forge repository via the following link: <https://r-forge.r-project.org/projects/locclass/>. Alternatively, one can install the package by entering the following in R: install.packages("locClass", repos="<http://R-Forge.R-project.org>")'.

This is the central location for data and tools for the development, maintenance, analysis, and deployment of the International Soil Radiocarbon Database (ISRaD). ISRaD was developed as a collaboration between the U.S. Geological Survey Powell Center and the Max Planck Institute for Biogeochemistry. This R package provides tools for accessing and manipulating ISRaD data, compiling local data using the ISRaD data structure, and simple query and reporting functions for ISRaD. For more detailed information visit the ISRaD website at: <https://soilradiocarbon.org/>.

Most existing approaches for network reconstruction can only infer an overall network and, also, fail to capture a complete set of network properties. To address these issues, a new model has been developed, which converts static data into their dynamic form. idopNetwork is an R interface to this model, it can inferring informative, dynamic, omnidirectional and personalized networks. For more information on functional clustering part, see Kim et al. (2008) <doi:10.1534/genetics.108.093690>, Wang et al. (2011) <doi:10.1093/bib/bbr032>. For more information on our model, see Chen et al. (2019) <doi:10.1038/s41540-019-0116-1>, and Cao et al. (2022) <doi:10.1080/19490976.2022.2106103>.

An R client for the iplookupapi.com IP Lookup API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://iplookupapi.com/docs> .

An R interface to the InfluxDB time series database <https://www.influxdata.com>. This package allows you to fetch and write time series data from/to an InfluxDB server. Additionally, handy wrappers for the Influx Query Language (IQL) to manage and explore a remote database are provided.

This package provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.