This package supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward.

Simple SendGrid Email API client for creating and sending emails. For more information, visit the official SendGrid Email API documentation: <https://sendgrid.com/en-us/solutions/email-api>.

This is software accompanying the book 'Applied Smoothing Techniques for Data Analysis---The Kernel Approach with S-Plus Illustrations', Oxford University Press. It provides smoothing methods for nonparametric regression and density estimation

This library was designed to make it easier to access web services that claim to be "RESTful". It includes convenience wrappers for libsoup and libxml to ease remote use of the RESTful API.

This library was designed to make it easier to access web services that claim to be "RESTful". It includes convenience wrappers for libsoup and libxml to ease remote use of the RESTful API.

This package provides functions for calculating the conditional power for different models in survival time analysis within randomized clinical trials with two different treatments to be compared and survival as an endpoint.

This package provides functions for metabolomics data analysis: data preprocessing, orthogonal signal correction, PCA analysis, PCA-DA analysis, PLS-DA analysis, classification, feature selection, correlation analysis, data visualisation and re-sampling strategies.

An interface for data processing, building models, predicting values and analysing outcomes. Fitting Linear Models, Robust Fitting of Linear Models, k-Nearest Neighbor Classification, 1-Nearest Neighbor Classification, and Conditional Inference Trees are available.

This package provides functions to import and handle infrared spectra (import from .csv and Thermo Galactic's .spc', baseline correction, binning, clipping, interpolating, smoothing, averaging, adding, subtracting, dividing, multiplying, atmospheric correction, tidyverse methods, plotting).

RTTR stands for Run Time Type Reflection. It describes the ability of a computer program to introspect and modify an object at runtime. It is also the name of the library itself, which is written in C++.

Duplicated music data (pre-processed and formatted) for entity resolution. The total size of the data set is 9763. There are respective gold standard records that are labeled and can be considered as a unique identifier.

This package allows for data objects in R to be rendered as HTML tables using the JavaScript library DataTables (typically via R Markdown or Shiny). The DataTables library has been included in this R package.

Multivariate modeling of data after deflation of interfering effects. EF Mosleth et al. (2021) <doi:10.1038/s41598-021-82388-w> and EF Mosleth et al. (2020) <doi:10.1016/B978-0-12-409547-2.14882-6>.

Computes different multidimensional FD indices. Implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. Also contains other useful tools for functional ecology.

This package provides support for simple features, a standardized way to encode spatial vector data. It binds to GDAL for reading and writing data, to GEOS for geometrical operations, and to PROJ for projection conversions and datum transformations.

Enables researchers to conduct multivariate statistical analyses of survey data with randomized response technique items from several designs, including mirrored question, forced question, and unrelated question. This includes regression with the randomized response as the outcome and logistic regression with the randomized response item as a predictor. In addition, tools for conducting power analysis for designing randomized response items are included. The package implements methods described in Blair, Imai, and Zhou (2015) Design and Analysis of the Randomized Response Technique, Journal of the American Statistical Association <https://graemeblair.com/papers/randresp.pdf>.

An implementation of locally Gaussian distributions. It provides methods for implementing locally Gaussian multivariate density estimation, conditional density estimation, various independence tests for iid and time series data, a test for conditional independence and a test for financial contagion.

Support for interfaces from R to other languages, built around a class for evaluators and a combination of functions, classes and methods for communication. Will be used through a specific language interface package. Described in the book "Extending R".

runc is a command line client for running applications packaged according to the Open Container Initiative (OCI) format and is a compliant implementation of the Open Container Initiative specification.

ROOT is a data analysis framework developed by CERN for tasks such as data storage, processing, and visualization. It provides tools for histograms, statistical tests, fitting, simulations, and machine learning. It can handle large datasets and uses a specialized file format.

This package provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.

This package provides functionalities to build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t family, and provides related statistical methods for data fitting and diagnostics, in the univariate and the multivariate case.

An iterative process that optimizes a function by alternately performing restricted optimization over parameter subsets. Instead of joint optimization, it breaks the optimization problem down into simpler sub-problems. This approach can make optimization feasible when joint optimization is too difficult.

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.