Data sets for statistical inference modeling related to People Analytics. Contains various data sets from the book Handbook of Regression Modeling in People Analytics by Keith McNulty (2020).

uniform_notifier is extracted from bullet, it gives you the ability to send notification through rails logger, customized logger, javascript alert, javascript console, growl, xmpp, airbrake and honeybadger.

Estimates weights to make a continuous-valued exposure statistically independent of a vector of pre-treatment covariates using the method proposed in Huling, Greifer, and Chen (2021) <arxiv:2107.07086>.

CL-random-forest is an implementation of Random Forest for multiclass classification and univariate regression written in Common Lisp. It also includes an implementation of Global Refinement of Random Forest.

This package provides tools for NanoString Technologies GeoMx Technology. Package to easily graph on top of an OME-TIFF image. Plotting annotations can range from tissue segment to gene expression.

Enable seamless interaction with Consibio Cloud <https://consibio.cloud> API <https://api.v2.consibio.com/api-docs/>. This package provides tools to query data from resources like projects, elements, devices, and datalogs.

Utility functions for discovering and managing metadata associated with spatially unique "known locations". Applications include all fields of environmental monitoring (e.g. air and water quality) where data are collected at stationary sites.

AnnotationHub package containing datasets for use in the TENET package. Includes GenomicRanges objects representing putative enhancer, promoter, and open chromatin regions. All included datasets are aligned to the hg38 human genome.

Package cors is net/http handler to handle Cross-origin resource sharing related requests as defined by http://www.w3.org/TR/cors/.

The package provides support for use of Babel in documents written in Russian (in both traditional and modern forms). The support is adapted for use both under traditional TeX engines, and under XeTeX and LuaTeX.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was HT\_HG-U133\_Plus\_PM\_probe\_tab.

Calculate incidence and prevalence using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence can be estimated for the total population in a database or for a stratification cohort.

Fits temperature response models to rate measurements taken at different temperatures. Etienne Low-Decarie,Tobias G. Boatman, Noah Bennett,Will Passfield,Antonio Gavalas-Olea,Philipp Siegel, Richard J. Geider (2017) <doi:10.1002/ece3.3576> .

Implementation of conceptual properties norming studies, including estimates of CPNs parameters with their corresponding variances and estimates for the sampling process, and a sampling property function based on a modified empirical distribution from the original data.

Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). The package makes use of a free service provided by <https://stellarapi.io>.

The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways via a rich API. This API was preceded by an earlier version which has been deprecated since 2010 (but is still supported to provide backwards compatibility in the package RcppClassic'). This package RcppClassicExamples provides usage examples for the older, deprecated API. There is also a corresponding package RcppExamples with examples for the newer, current API which we strongly recommend as the basis for all new development.

This package provides a drop-in replacement for requests.Session with caching offload to SQLite, Redis, MongoDB and AWS DynamoDB or save responses as planin JSON/YAML file or save responses as plain JSON/YAML files.

This data package contains chimp and human brain data extracted from the ArrayExpress accession E-AFMX-2. Both human and chimp RNAs were run on human hgu95av2 Affymetrix arrays. It is a useful dataset for tutorials.

This package provides a set of predicates and assertions for checking the properties of dates and times. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides a sample size calculator for micro-randomized trials (MRTs) with binary outcomes based on Cohn et al. (2023) <doi:10.1002/sim.9748>. Also provides a power calculator when the sample size is input by the user.

The package provides a comprehensive mapping table of nine different Metabolite ID formats and their common name. The data has been collected and merged from four publicly available source, including HMDB, Comptox Dashboard, ChEBI, and the graphite Bioconductor R package.

This package provides a datetime range picker widget for usage in Shiny'. It creates a calendar allowing to select a start date and an end date as well as two fields allowing to select a start time and an end time.

Allows to install the R languageserver with all dependencies into a separate library and use that independent installation automatically when R is instantiated as a language server process. Useful for making language server seamless to use without running into package version conflicts.

Ensemble model, for classification, regression and unsupervised learning, based on a forest of unpruned and randomized binary decision trees. Each tree is grown by sampling, with replacement, a set of variables at each node. Each cut-point is generated randomly, according to the continuous Uniform distribution. For each tree, data are either bootstrapped or subsampled. The unsupervised mode introduces clustering, dimension reduction and variable importance, using a three-layer engine. Random Uniform Forests are mainly aimed to lower correlation between trees (or trees residuals), to provide a deep analysis of variable importance and to allow native distributed and incremental learning.